Abstract
Particle swarm optimization (PSO) is a search algorithm inspired by the collective behavior of flocking birds and fishes. This algorithm is widely adopted for solving optimization problems involving one objective. The evaluation of the PSO progress is usually measured by the fitness of the best particle and the average fitness of the particles. When several objectives are considered, the PSO may incorporate distinct strategies to preserve nondominated solutions along the iterations. The performance of the multiobjective PSO (MOPSO) is usually evaluated by considering the resulting swarm at the end of the algorithm. In this paper, two indices based on the Shannon entropy are presented, to study the swarm dynamic evolution during the MOPSO execution. The results show that both indices are useful for analyzing the diversity and convergence of multiobjective algorithms.

Abstract
Students born in a digital era require adjusted teaching and learning methodologies incorporating new technologies. A common difficulty found by students is how to test their controller designs in a real system. Thus, the development of affordable, portable and easy to use feedback control kits is highly desirable. The idea is that both lecturers and students can perform simple practical experiments anytime and anywhere. The APMonitor temperature control lab is an Arduino based control kit which fulfils these requirements. Proportional, integrative and derivative control is in operation in the vast majority of industrial process control loops. Thus, it is a mandatory topic in most undergraduate introductory feedback control courses. A teaching/learning PID control experiment for undergraduate Biomedical Engineering student's based on the temperature control lab is reported here. Results received from students are presented.

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The challenge of noise attenuation in images has led to extensive research on improved noise reduction techniques, preserving important image characteristics, improving not only visual perception, but also enabling the use for special purposes, such as in medicine to increase clarity of medical images. In this paper, a technique for noise attenuation in medical images is proposed. Its operation takes place through the application of an adapted genetic algorithm. The results of experiments show that the proposed approach works best in suppressing artifacts and the preservation of the structure compared with several existing methods.