91 resultados para Programming tasks
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11th IEEE World Conference on Factory Communication Systems (WFCS 2015). 27 to 29, May, 2015, TII-SS-2: Scheduling and Performance Analysis. Palma de Mallorca, Spain.
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International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP 2015). 7 to 9, Apr, 2015. Singapure, Singapore.
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Demo presented in 12th Workshop on Models and Algorithms for Planning and Scheduling Problems (MAPSP 2015). 8 to 12, Jun, 2015. La Roche-en-Ardenne, Belgium. Extended abstract.
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Poster presented in 12th European Conference on Wireless Sensor Network (EWSN 2015). 9 to 11, Feb, 2015. Porto, Portugal.
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13th IEEE/IFIP International Conference on Embedded and Ubiquitous Computing (EUC 2015). 21 to 23, Oct, 2015, Session W1-A: Multiprocessing and Multicore Architectures. Porto, Portugal.
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Paper/Poster presented in Work in Progress Session, 28th GI/ITG International Conference on Architecture of Computing Systems (ARCS 2015). 24 to 26, Mar, 2015. Porto, Portugal.
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Poster presented in Work in Progress Session, 28th GI/ITG International Conference on Architecture of Computing Systems (ARCS 2015). 24 to 26, Mar, 2015. Porto, Portugal.
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It is well-known that ROVs require human intervention to guarantee the success of their assignment, as well as the equipment safety. However, as its teleoperation is quite complex to perform, there is a need for assisted teleoperation. This study aims to take on this challenge by developing vision-based assisted teleoperation maneuvers, since a standard camera is present in any ROV. The proposed approach is a visual servoing solution, that allows the user to select between several standard image processing methods and is applied to a 3-DOF ROV. The most interesting characteristic of the presented system is the exclusive use of the camera data to improve the teleoperation of an underactuated ROV. It is demonstrated through the comparison and evaluation of standard implementations of different vision methods and the execution of simple maneuvers to acquire experimental results, that the teleoperation of a small ROV can be drastically improved without the need to install additional sensors.
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Currently, the teaching-learning process in domains, such as computer programming, is characterized by an extensive curricula and a high enrolment of students. This poses a great workload for faculty and teaching assistants responsible for the creation, delivery, and assessment of student exercises. The main goal of this chapter is to foster practice-based learning in complex domains. This objective is attained with an e-learning framework—called Ensemble—as a conceptual tool to organize and facilitate technical interoperability among services. The Ensemble framework is used on a specific domain: computer programming. Content issues are tacked with a standard format to describe programming exercises as learning objects. Communication is achieved with the extension of existing specifications for the interoperation with several systems typically found in an e-learning environment. In order to evaluate the acceptability of the proposed solution, an Ensemble instance was validated on a classroom experiment with encouraging results.
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Teaching and learning computer programming is as challenging as difficult. Assessing the work of students and providing individualised feedback to all is time-consuming and error prone for teachers and frequently involves a time delay. The existent tools and specifications prove to be insufficient in complex evaluation domains where there is a greater need to practice. At the same time Massive Open Online Courses (MOOC) are appearing revealing a new way of learning, more dynamic and more accessible. However this new paradigm raises serious questions regarding the monitoring of student progress and its timely feedback. This paper provides a conceptual design model for a computer programming learning environment. This environment uses the portal interface design model gathering information from a network of services such as repositories and program evaluators. The design model includes also the integration with learning management systems, a central piece in the MOOC realm, endowing the model with characteristics such as scalability, collaboration and interoperability. This model is not limited to the domain of computer programming and can be adapted to any complex area that requires systematic evaluation with immediate feedback.
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Massive Open Online Courses (MOOC) are gaining prominence in transversal teaching-learning strategies. However, there are many issues still debated, namely assessment, recognized largely as a cornerstone in Education. The large number of students involved requires a redefinition of strategies that often use approaches based on tasks or challenging projects. In these conditions and due to this approach, assessment is made through peer-reviewed assignments and quizzes online. The peer-reviewed assignments are often based upon sample answers or topics, which guide the student in the task of evaluating peers. This chapter analyzes the grading and evaluation in MOOCs, especially in science and engineering courses, within the context of education and grading methodologies and discusses possible perspectives to pursue grading quality in massive e-learning courses.
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A new iterative algorithm based on the inexact-restoration (IR) approach combined with the filter strategy to solve nonlinear constrained optimization problems is presented. The high level algorithm is suggested by Gonzaga et al. (SIAM J. Optim. 14:646–669, 2003) but not yet implement—the internal algorithms are not proposed. The filter, a new concept introduced by Fletcher and Leyffer (Math. Program. Ser. A 91:239–269, 2002), replaces the merit function avoiding the penalty parameter estimation and the difficulties related to the nondifferentiability. In the IR approach two independent phases are performed in each iteration, the feasibility and the optimality phases. The line search filter is combined with the first one phase to generate a “more feasible” point, and then it is used in the optimality phase to reach an “optimal” point. Numerical experiences with a collection of AMPL problems and a performance comparison with IPOPT are provided.
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O veículo guiado automaticamente (AGV) adquirido pelo Departamento de Engenharia Mecânica (DEM) tem vindo a ficar obsoleto devido ao hardware, que nos dias de hoje começa a dar sinais de falhas bem como falta de peças de substituição, e ao software, sendo o PLC (Programmable Logic Controller) usado muito limitado quanto às suas funções de controlo, ficando as principais tarefas de controlo do AGV a cargo de placas eletrónicas de controlo. Para promover o controlo autónomo do AGV, foi decidido retirar toda a parte de hardware que detinha o controlo do mesmo e passou a ser um novo PLC, com maior capacidade de processamento, a executar todo o tipo de controlo necessário ao funcionamento do mesmo. O hardware considerado apenas incluí, de forma resumida, os motores responsáveis pelo movimento e direção, placa de controlo de potência dos motores, placa de interface entre as saídas digitais do PLC e as entradas da placa de controlo de potência dos motores e os demais sensores necessários à deteção de obstáculos, fins de curso da direção, sensores dos postos de trabalho e avisadores de emergência. Todo o controlo de movimento e direção bem como a seleção das ações a executar passou a ficar a cargo do software programado no PLC assim como a interação entre o sistema de supervisão instalado num posto de controlo e o PLC através de comunicação via rádio. O uso do PLC permitiu a flexibilidade de mudar facilmente a forma como as saídas digitais são usadas, ao contrário de um circuito eletrónico que necessita de uma completa remodelação, tempo de testes e implementação para efetuar a mesma função. O uso de um microcontrolador seria igualmente viável para a aplicação em causa, no entanto o uso do PLC tem a vantagem de ser robusto, mais rápido na velocidade de processamento, existência de software de interface de programação bastante intuitivo e de livre acesso, facilidade de alterar a programação localmente ou remotamente, via rádio, acesso a vários protocolos de comunicação robustos como Modbus, Canbus, Profinet, Modnet, etc., e acesso integrado de uma consola gráfica totalmente programável. iv É ainda possível a sua expansão com adição de módulos de entradas e saídas digitais e/ou analógicas permitindo expandir largamente o uso do AGV para outros fins. A solução está a ser amplamente testada e validada no Laboratório de Automação (LabA) do Departamento de Engenharia Mecânica do ISEP (Instituto Superior de Engenharia do Porto), permitindo a otimização dos sistemas de controlo de direção bem como a interatividade entre o PLC e o programa de interface/supervisão do posto de trabalho.