BIT: Biosignal Igniter Toolkit

The study of biosignals has had a transforming role in multiple aspects of our society, which go well beyond the health sciences domains to which they were traditionally associated with. While biomedical engineering is a classical discipline where the topic is amply covered, today biosignals are a matter of interest for students, researchers and hobbyists in areas including computer science, informatics, electrical engineering, among others. Regardless of the context, the use of biosignals in experimental activities and practical projects is heavily bounded by the cost, and limited access to adequate support materials. In this paper we present an accessible, albeit versatile toolkit, composed of low-cost hardware and software, which was created to reinforce the engagement of different people in the field of biosignals. The hardware consists of a modular wireless biosignal acquisition system that can be used to support classroom activities, interface with other devices, or perform rapid prototyping of end-user applications. The software comprehends a set of programming APIs, a biosignal processing toolbox, and a framework for real time data acquisition and postprocessing. (C) 2014 Elsevier Ireland Ltd. All rights reserved.

Ensemble: an e-learning framework

E-Learning frameworks are conceptual tools to organize networks of elearning services. Most frameworks cover areas that go beyond the scope of e-learning, from course to financial management, and neglects the typical activities in everyday life of teachers and students at schools such as the creation, delivery, resolution and evaluation of assignments. This paper presents the Ensemble framework - an e-learning framework exclusively focused on the teaching-learning process through the coordination of pedagogical services. The framework presents an abstract data, integration and evaluation model based on content and communications specifications. These specifications must base the implementation of networks in specialized domains with complex evaluations. In this paper we specialize the framework for two domains with complex evaluation: computer programming and computer-aided design (CAD). For each domain we highlight two Ensemble hotspots: data and evaluations procedures. In the former we formally describe the exercise and present possible extensions. In the latter, we describe the automatic evaluation procedures.

From task scheduling in single processor environments to message scheduling in a PROFIBUS fieldbus network

In this paper we survey the most relevant results for the prioritybased schedulability analysis of real-time tasks, both for the fixed and dynamic priority assignment schemes. We give emphasis to the worst-case response time analysis in non-preemptive contexts, which is fundamental for the communication schedulability analysis. We define an architecture to support priority-based scheduling of messages at the application process level of a specific fieldbus communication network, the PROFIBUS. The proposed architecture improves the worst-case messages��� response time, overcoming the limitation of the first-come-first-served (FCFS) PROFIBUS queue implementations.

Server-based scheduling of parallel real-time tasks

Multicore platforms have transformed parallelism into a main concern. Parallel programming models are being put forward to provide a better approach for application programmers to expose the opportunities for parallelism by pointing out potentially parallel regions within tasks, leaving the actual and dynamic scheduling of these regions onto processors to be performed at runtime, exploiting the maximum amount of parallelism. It is in this context that this paper proposes a scheduling approach that combines the constant-bandwidth server abstraction with a priority-aware work-stealing load balancing scheme which, while ensuring isolation among tasks, enables parallel tasks to be executed on more than one processor at a given time instant.

Application of computational intelligence to engineering

Computational Intelligence (CI) includes four main areas: Evolutionary Computation (genetic algorithms and genetic programming), Swarm Intelligence, Fuzzy Systems and Neural Networks. This article shows how CI techniques overpass the strict limits of Artificial Intelligence field and can help solving real problems from distinct engineering areas: Mechanical, Computer Science and Electrical Engineering.

Suporte �� computa����o paralela e distribu��da em Java: distribui����o e execu����o de trabalho

Nos ��ltimos anos come��aram a ser vulgares os computadores dotados de multiprocessadores e multi-cores. De modo a aproveitar eficientemente as novas caracter��sticas desse hardware come��aram a surgir ferramentas para facilitar o desenvolvimento de software paralelo, atrav��s de linguagens e frameworks, adaptadas a diferentes linguagens. Com a grande difus��o de redes de alta velocidade, tal como Gigabit Ethernet e a ��ltima gera����o de redes Wi-Fi, abre-se a oportunidade de, al��m de paralelizar o processamento entre processadores e cores, poder em simult��neo paraleliz��-lo entre m��quinas diferentes. Ao modelo que permite paralelizar processamento localmente e em simult��neo distribu��-lo para m��quinas que tamb��m t��m capacidade de o paralelizar, chamou-se ���modelo paralelo distribu��do���. Nesta disserta����o foram analisadas t��cnicas e ferramentas utilizadas para fazer programa����o paralela e o trabalho que est�� feito dentro da ��rea de programa����o paralela e distribu��da. Tendo estes dois factores em considera����o foi proposta uma framework que tenta aplicar a simplicidade da programa����o paralela ao conceito paralelo distribu��do. A proposta baseia-se na disponibiliza����o de uma framework em Java com uma interface de programa����o simples, de f��cil aprendizagem e legibilidade que, de forma transparente, �� capaz de paralelizar e distribuir o processamento. Apesar de simples, existiu um esfor��o para a tornar configur��vel de forma a adaptar-se ao m��ximo de situa����es poss��vel. Nesta disserta����o ser��o exploradas especialmente as quest��es relativas �� execu����o e distribui����o de trabalho, e a forma como o c��digo �� enviado de forma autom��tica pela rede, para outros n��s cooperantes, evitando assim a instala����o manual das aplica����es em todos os n��s da rede. Para confirmar a validade deste conceito e das ideias defendidas nesta disserta����o foi implementada esta framework �� qual se chamou DPF4j (Distributed Parallel Framework for JAVA) e foram feitos testes e retiradas m��tricas para verificar a exist��ncia de ganhos de performance em rela����o ��s solu����es j�� existentes.

Integrated Management of IaaS Resources

This paper proposes and reports the development of an open source solution for the integrated management of Infrastructure as a Service (IaaS) cloud computing resources, through the use of a common API taxonomy, to incorporate open source and proprietary platforms. This research included two surveys on open source IaaS platforms (OpenNebula, OpenStack and CloudStack) and a proprietary platform (Parallels Automation for Cloud Infrastructure - PACI) as well as on IaaS abstraction solutions (jClouds, Libcloud and Deltacloud), followed by a thorough comparison to determine the best approach. The adopted implementation reuses the Apache Deltacloud open source abstraction framework, which relies on the development of software driver modules to interface with different IaaS platforms, and involved the development of a new Deltacloud driver for PACI. The resulting interoperable solution successfully incorporates OpenNebula, OpenStack (reuses pre-existing drivers) and PACI (includes the developed Deltacloud PACI driver) nodes and provides a Web dashboard and a Representational State Transfer (REST) interface library. The results of the exchanged data payload and time response tests performed are presented and discussed. The conclusions show that open source abstraction tools like Deltacloud allow the modular and integrated management of IaaS platforms (open source and proprietary), introduce relevant time and negligible data overheads and, as a result, can be adopted by Small and Medium-sized Enterprise (SME) cloud providers to circumvent the vendor lock-in problem whenever service response time is not critical.

Criador autom��tico de aplica����es nativas Android e iOS

Nos ��ltimos anos tem-se verificado um acentuado aumento na utiliza����o de dispositivos moveis a n��vel internacional, pelo que as aplica����es desenvolvidas para este tipo espec��fico de dispositivos, conhecidas por apps, tem vindo a ganhar uma enorme popularidade. S��o cada vez mais as empresas que procuram estar presentes nos mais diversos sistemas operativos m��veis, com o objectivo de suportar e desenvolver o seu neg��cio, alargando o seu leque de poss��veis consumidores. Neste sentido surgiram diversas ferramentas com a fun����o de facilitar o desenvolvimento de aplica����es m��veis, denominadas frameworks multi-plataforma. Estas frameworks conduziram ao aparecimento de plataformas web, que permitem criar aplica����es multi-plataforma sem ser obrigat��rio ter conhecimentos em programa����o. Assim, e a partir da an��lise de v��rios criadores online de aplica����es m��veis identificados e das diferentes estrat��gias de desenvolvimento de aplica����es m��veis existentes, foi proposta a implementa����o de uma plataforma web capaz de criar aplica����es nativas Android e iOS, dois dos sistemas operativos mais utilizados na actualidade. Apos desenvolvida a plataforma web, designada MobileAppBuilder, foi avaliada a sua Qualidade e as aplica����es criadas pela mesma, atrav��s do preenchimento de um question��rio por parte de 10 indiv��duos com forma����o em Engenharia Inform��tica, resultando numa classifica����o geral de ���excelente���. De modo a analisar o desempenho das aplica����es produzidas pela plataforma desenvolvida, foram realizados testes comparativos entre uma aplica����o da MobileAppBuilder e duas homologas de dois dos criadores online estudados, nomeadamente Andromo e Como. Os resultados destes testes revelaram que a MobileAppBuilder gera aplica����es menos pesadas, mais r��pidas e mais eficientes em alguns aspetos, nomeadamente no arranque.

Estado da Arte da Computa����o Evolutiva Aplicada �� Eletr��nica

A Computa����o Evolutiva enquadra-se na ��rea da Intelig��ncia Artificial e �� um ramo das ci��ncias da computa����o que tem vindo a ser aplicado na resolu����o de problemas em diversas ��reas da Engenharia. Este trabalho apresenta o estado da arte da Computa����o Evolutiva, assim como algumas das suas aplica����es no ramo da eletr��nica, denominada Eletr��nica Evolutiva (ou Hardware Evolutivo), enfatizando a s��ntese de circuitos digitais combinat��rios. Em primeiro lugar apresenta-se a Intelig��ncia Artificial, passando �� Computa����o Evolutiva, nas suas principais vertentes: os Algoritmos Evolutivos baseados no processo da evolu����o das esp��cies de Charles Darwin e a Intelig��ncia dos Enxames baseada no comportamento coletivo de alguns animais. No que diz respeito aos Algoritmos Evolutivos, descrevem-se as estrat��gias evolutivas, a programa����o gen��tica, a programa����o evolutiva e com maior ��nfase, os Algoritmos Gen��ticos. Em rela����o �� Intelig��ncia dos Enxames, descreve-se a otimiza����o por col��nia de formigas e a otimiza����o por enxame de part��culas. Em simult��neo realizou-se tamb��m um estudo da Eletr��nica Evolutiva, explicando sucintamente algumas das ��reas de aplica����o, entre elas: a rob��tica, as FPGA, o roteamento de placas de circuito impresso, a s��ntese de circuitos digitais e anal��gicos, as telecomunica����es e os controladores. A t��tulo de concretizar o estudo efetuado, apresenta-se um caso de estudo da aplica����o dos algoritmos gen��ticos na s��ntese de circuitos digitais combinat��rios, com base na an��lise e compara����o de tr��s refer��ncias de autores distintos. Com este estudo foi poss��vel comparar, n��o s�� os resultados obtidos por cada um dos autores, mas tamb��m a forma como os algoritmos gen��ticos foram implementados, nomeadamente no que diz respeito aos par��metros, operadores gen��ticos utilizados, fun����o de avalia����o, implementa����o em hardware e tipo de codifica����o do circuito.

Parallel run-time for CO-OPN

Disserta����o para obten����o do Grau de Mestre em Engenharia Inform��tica

Distributed processing of large remote sensing images using MapReduce - A case of Edge Detection

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

Optimization of breast tomosynthesis image reconstruction using parallel computing

Breast cancer is the most common cancer among women, being a major public health problem. Worldwide, X-ray mammography is the current gold-standard for medical imaging of breast cancer. However, it has associated some well-known limitations. The false-negative rates, up to 66% in symptomatic women, and the false-positive rates, up to 60%, are a continued source of concern and debate. These drawbacks prompt the development of other imaging techniques for breast cancer detection, in which Digital Breast Tomosynthesis (DBT) is included. DBT is a 3D radiographic technique that reduces the obscuring effect of tissue overlap and appears to address both issues of false-negative and false-positive rates. The 3D images in DBT are only achieved through image reconstruction methods. These methods play an important role in a clinical setting since there is a need to implement a reconstruction process that is both accurate and fast. This dissertation deals with the optimization of iterative algorithms, with parallel computing through an implementation on Graphics Processing Units (GPUs) to make the 3D reconstruction faster using Compute Unified Device Architecture (CUDA). Iterative algorithms have shown to produce the highest quality DBT images, but since they are computationally intensive, their clinical use is currently rejected. These algorithms have the potential to reduce patient dose in DBT scans. A method of integrating CUDA in Interactive Data Language (IDL) is proposed in order to accelerate the DBT image reconstructions. This method has never been attempted before for DBT. In this work the system matrix calculation, the most computationally expensive part of iterative algorithms, is accelerated. A speedup of 1.6 is achieved proving the fact that GPUs can accelerate the IDL implementation.

Towards an algorithmic skeleton framework for programming the Intel R Xeon PhiTM processor

The Intel R Xeon PhiTM is the first processor based on Intel���s MIC (Many Integrated Cores) architecture. It is a co-processor specially tailored for data-parallel computations, whose basic architectural design is similar to the ones of GPUs (Graphics Processing Units), leveraging the use of many integrated low computational cores to perform parallel computations. The main novelty of the MIC architecture, relatively to GPUs, is its compatibility with the Intel x86 architecture. This enables the use of many of the tools commonly available for the parallel programming of x86-based architectures, which may lead to a smaller learning curve. However, programming the Xeon Phi still entails aspects intrinsic to accelerator-based computing, in general, and to the MIC architecture, in particular. In this thesis we advocate the use of algorithmic skeletons for programming the Xeon Phi. Algorithmic skeletons abstract the complexity inherent to parallel programming, hiding details such as resource management, parallel decomposition, inter-execution flow communication, thus removing these concerns from the programmer���s mind. In this context, the goal of the thesis is to lay the foundations for the development of a simple but powerful and efficient skeleton framework for the programming of the Xeon Phi processor. For this purpose we build upon Marrow, an existing framework for the orchestration of OpenCLTM computations in multi-GPU and CPU environments. We extend Marrow to execute both OpenCL and C++ parallel computations on the Xeon Phi. We evaluate the newly developed framework, several well-known benchmarks, like Saxpy and N-Body, will be used to compare, not only its performance to the existing framework when executing on the co-processor, but also to assess the performance on the Xeon Phi versus a multi-GPU environment.

Augmenting spaces and creating interactive experiences using video camera networks

This research addresses the problem of creating interactive experiences to encourage people to explore spaces. Besides the obvious spaces to visit, such as museums or art galleries, spaces that people visit can be, for example, a supermarket or a restaurant. As technology evolves, people become more demanding in the way they use it and expect better forms of interaction with the space that surrounds them. Interaction with the space allows information to be transmitted to the visitors in a friendly way, leading visitors to explore it and gain knowledge. Systems to provide better experiences while exploring spaces demand hardware and software that is not in the reach of every space owner either because of the cost or inconvenience of the installation, that can damage artefacts or the space environment. We propose a system adaptable to the spaces, that uses a video camera network and a wi-fi network present at the space (or that can be installed) to provide means to support interactive experiences using the visitor���s mobile device. The system is composed of an infrastructure (called vuSpot), a language grammar used to describe interactions at a space (called XploreDescription), a visual tool used to design interactive experiences (called XploreBuilder) and a tool used to create interactive experiences (called urSpace). By using XploreBuilder, a tool built of top of vuSpot, a user with little or no experience in programming can define a space and design interactive experiences. This tool generates a description of the space and of the interactions at that space (that complies with the XploreDescription grammar). These descriptions can be given to urSpace, another tool built of top of vuSpot, that creates the interactive experience application. With this system we explore new forms of interaction and use mobile devices and pico projectors to deliver additional information to the users leading to the creation of interactive experiences. The several components are presented as well as the results of the respective user tests, which were positive. The design and implementation becomes cheaper, faster, more flexible and, since it does not depend on the knowledge of a programming language, accessible for the general public.

Artificial neural networks in diagnosis of liver diseases

Liver diseases have severe patients��� consequences, being one of the main causes of premature death. These facts reveal the centrality of one`s daily habits, and how important it is the early diagnosis of these kind of illnesses, not only to the patients themselves, but also to the society in general. Therefore, this work will focus on the development of a diagnosis support system to these kind of maladies, built under a formal framework based on Logic Programming, in terms of its knowledge representation and reasoning procedures, complemented with an approach to computing grounded on Artificial Neural Networks.