Dynamic group formation in mobile computer supported collaborative learning environment

Forming suitable learning groups is one of the factors that determine the efficiency of collaborative learning activities. However, only a few studies were carried out to address this problem in the mobile learning environments. In this paper, we propose a new approach for an automatic, customized, and dynamic group formation in Mobile Computer Supported Collaborative Learning (MCSCL) contexts. The proposed solution is based on the combination of three types of grouping criteria: learner’s personal characteristics, learner’s behaviours, and context information. The instructors can freely select the type, the number, and the weight of grouping criteria, together with other settings such as the number, the size, and the type of learning groups (homogeneous or heterogeneous). Apart from a grouping mechanism, the proposed approach represents a flexible tool to control each learner, and to manage the learning processes from the beginning to the end of collaborative learning activities. In order to evaluate the quality of the implemented group formation algorithm, we compare its Average Intra-cluster Distance (AID) with the one of a random group formation method. The results show a higher effectiveness of the proposed algorithm in forming homogenous and heterogeneous groups compared to the random method.

Implementation and comparison of different switching techniques for shunt active power filters

This paper presents a comparison between three switching techniques that can be used in three-phase four-wire Shunt Active Power Filters (SAPFs). The implemented switching techniques are: Periodic-Sampling (PS), Triangular Carrier Pulse-Width Modulation (TC-PWM) and Space Vector PWM (SVPWM). The comparison between them is made in terms of the compensated currents THD%, implementation complexity, necessary CPU time and SAPF efficiency. To perform this comparison are presented and analyzed several experimental results, obtained with a 20 kVA Shunt Active Power Filter prototype, specially developed for this purpose. The control system of the developed SAPF is based in the p-q Theory with a grid synchronization algorithm p-PLL.

Biomass accumulation, photochemical efficiency of photosystem II, nutrient contents and nitrate reductase activity in young rosewood plants (Aniba rosaeodora Ducke) submitted to different NO3-:NH4+ ratios

The rosewood (Aniba rosaeodora Ducke) is a native tree species of Amazon rainforest growing naturally in acidic forest soils with reduced redox potential. However, this species can also been found growing in forest gaps containing oxide soils. Variations in the forms of mineral nitrogen (NO3- or NH4+) may be predicted in these different edaphic conditions. Considering that possibility, an experiment was carried out to analyze the effects of different NO3-:NH4+ ratios on the growth performance, mineral composition, chloroplastid pigment contents, photochemical efficiency photosystem II (PSII), and nitrate redutase activity (RN, E.C.1.6.6.1) on A. rosaeodora seedlings. Nine-month-old seedlings were grown in pots with a washed sand capacity of 7.5 kg and submitted to different NO3-:NH4+ ratios (T1 = 0:100%, T2 = 25:75%, T3 = 50:50%, T4 = 75:25%, and T5 = 100:0%). The lowest relative growth rate was observed when the NO3-:NH4+ ratio was equal to 0:100%. In general, high concentrations of NO3- rather than NH4+ favored a greater nutrient accumulation in different parts of the plant. For the chloroplastid pigment, the highest Chl a, Chl b, Chl tot, Chl a/b and Chl tot/Cx+c contents were found in the treatment with 75:25% of NO3-:NH4+, and for Chl b and Cx+c it was observed no difference. In addition, there was a higher photochemical efficiency of PSII (Fv/Fm) when high NO3- concentrations were used. A linear and positive response for the nitrate reductase activity was recorded when the nitrate content increased on the culture substrate. Our results suggest that A. rosaeodora seedlings have a better growth performance when the NO3- concentrations in the culture substrate were higher than the NH4+ concentrations.

The importance of the category of consciousness and education for sustainability in methodologies for eco‐efficiency in school buildings

This document reports the importance of the category of consciousness and education for sustainability in the school environment. Education in school has a potential to make the benefits of the building construction visible for society and media, showing to the students, parents and communities how sustainability in built environment could improve the people life in economic, social and environment aspects. Thus, this paper addresses the main events related to sustainability, such as the Stockholm Conference, the Brundtland report, United Nations Conference on Environment and Development (UNCED) and Agenda 21, until reaching the necessity of the elaboration of Methodologies for environmental assessment of building, and later, the development of the specific methodologies according to the buildings. It is also described some examples of sustainability in schools in Germany, Finland and Italy and what kind of sustainable systems those countries are currently using.

Testing Nelder-Mead based repulsion algorithms for multiple roots of nonlinear systems via a two-level factorial design of experiments

This paper addresses the challenging task of computing multiple roots of a system of nonlinear equations. A repulsion algorithm that invokes the Nelder-Mead (N-M) local search method and uses a penalty-type merit function based on the error function, known as 'erf', is presented. In the N-M algorithm context, different strategies are proposed to enhance the quality of the solutions and improve the overall efficiency. The main goal of this paper is to use a two-level factorial design of experiments to analyze the statistical significance of the observed differences in selected performance criteria produced when testing different strategies in the N-M based repulsion algorithm. The main goal of this paper is to use a two-level factorial design of experiments to analyze the statistical significance of the observed differences in selected performance criteria produced when testing different strategies in the N-M based repulsion algorithm.

Solving large 0–1 multidimensional knapsack problems by a new simplified binary artificial fish swarm algorithm

The artificial fish swarm algorithm has recently been emerged in continuous global optimization. It uses points of a population in space to identify the position of fish in the school. Many real-world optimization problems are described by 0-1 multidimensional knapsack problems that are NP-hard. In the last decades several exact as well as heuristic methods have been proposed for solving these problems. In this paper, a new simpli ed binary version of the artificial fish swarm algorithm is presented, where a point/ fish is represented by a binary string of 0/1 bits. Trial points are created by using crossover and mutation in the different fi sh behavior that are randomly selected by using two user de ned probability values. In order to make the points feasible the presented algorithm uses a random heuristic drop item procedure followed by an add item procedure aiming to increase the profit throughout the adding of more items in the knapsack. A cyclic reinitialization of 50% of the population, and a simple local search that allows the progress of a small percentage of points towards optimality and after that refines the best point in the population greatly improve the quality of the solutions. The presented method is tested on a set of benchmark instances and a comparison with other methods available in literature is shown. The comparison shows that the proposed method can be an alternative method for solving these problems.

A new competitive implementation of the electromagnetism-like algorithm for global optimization

The Electromagnetism-like (EM) algorithm is a population- based stochastic global optimization algorithm that uses an attraction- repulsion mechanism to move sample points towards the optimal. In this paper, an implementation of the EM algorithm in the Matlab en- vironment as a useful function for practitioners and for those who want to experiment a new global optimization solver is proposed. A set of benchmark problems are solved in order to evaluate the performance of the implemented method when compared with other stochastic methods available in the Matlab environment. The results con rm that our imple- mentation is a competitive alternative both in term of numerical results and performance. Finally, a case study based on a parameter estimation problem of a biology system shows that the EM implementation could be applied with promising results in the control optimization area.

Combining non-dominance, objective-order and spread metric to extend firefly algorithm to multi-objective optimization

In this paper, we propose an extension of the firefly algorithm (FA) to multi-objective optimization. FA is a swarm intelligence optimization algorithm inspired by the flashing behavior of fireflies at night that is capable of computing global solutions to continuous optimization problems. Our proposal relies on a fitness assignment scheme that gives lower fitness values to the positions of fireflies that correspond to non-dominated points with smaller aggregation of objective function distances to the minimum values. Furthermore, FA randomness is based on the spread metric to reduce the gaps between consecutive non-dominated solutions. The obtained results from the preliminary computational experiments show that our proposal gives a dense and well distributed approximated Pareto front with a large number of points.

New control algorithm for single-phase series active power filter

This paper presents a single-phase Series Active Power Filter (Series APF) for mitigation of the load voltage harmonic content, while maintaining the voltage on the DC side regulated without the support of a voltage source. The proposed series active power filter control algorithm eliminates the additional voltage source to regulate the DC voltage, and with the adopted topology it is not used a coupling transformer to interface the series active power filter with the electrical power grid. The paper describes the control strategy which encapsulates the grid synchronization scheme, the compensation voltage calculation, the damping algorithm and the dead-time compensation. The topology and control strategy of the series active power filter have been evaluated in simulation software and simulations results are presented. Experimental results, obtained with a developed laboratorial prototype, validate the theoretical assumptions, and are within the harmonic spectrum limits imposed by the international recommendations of the IEEE-519 Standard.

MOEA/VAN: Multiobjective Evolutionary Algorithm based on Vector Angle Neighborhood

Natural selection favors the survival and reproduction of organisms that are best adapted to their environment. Selection mechanism in evolutionary algorithms mimics this process, aiming to create environmental conditions in which artificial organisms could evolve solving the problem at hand. This paper proposes a new selection scheme for evolutionary multiobjective optimization. The similarity measure that defines the concept of the neighborhood is a key feature of the proposed selection. Contrary to commonly used approaches, usually defined on the basis of distances between either individuals or weight vectors, it is suggested to consider the similarity and neighborhood based on the angle between individuals in the objective space. The smaller the angle, the more similar individuals. This notion is exploited during the mating and environmental selections. The convergence is ensured by minimizing distances from individuals to a reference point, whereas the diversity is preserved by maximizing angles between neighboring individuals. Experimental results reveal a highly competitive performance and useful characteristics of the proposed selection. Its strong diversity preserving ability allows to produce a significantly better performance on some problems when compared with stat-of-the-art algorithms.

Discussing Chevalier’s data on the efficiency of tariffs for american and french canals in the 1830s

This article revisits Michel Chevalier’s work and discussions of tariffs. Chevalier shifted from Saint-Simonism to economic liberalism during his life in the 19th century. His influence was soon perceived in the political world and economic debates, mainly because of his discussion of tariffs as instruments of efficient transport policies. This work discusses Chevalier’s thoughts on tariffs by revisiting his masterpiece, Le Cours d’Économie Politique. Data Envelopment Analysis (DEA) was conducted to test Chevalier’s hypothesis on the inefficiency of French tariffs. This work showed that Chevalier’s claims on French tariffs are not validated by DEA.

Implementação de um sistema MPPT em circuito integrado CMOS

Dissertação de mestrado integrado em Engenharia Eletrónica Industrial e Computadores

Otimização das características de um chassis tubular de automóvel de competição com tração a duas rodas motrizes

Dissertação de mestrado integrado em Engenharia Mecânica

Trap efficiency evaluation for small mammals in the southern Amazon

The effectiveness of ecological researches on small mammals strongly depends on trapping techniques to survey communities and populations accurately. The main goal of this study was to assess the efficiency of three types of traps (Sherman, Tomahawk and Pitfall) to capture non-volant small mammals. We installed traps in 22 forest fragments in the southern Brazilian Amazonia. We captured 873 individuals belonging to 21 species; most of the individuals (N = 369) and species (N = 19) were trapped using Pitfalls, followed by Shermans (N = 271 individuals; N = 15 species) and Tomahawks (N = 233 individuals; N = 15 species). Pitfalls trapped a richer community subset of small mammals than the two other types of traps, and a more abundant community subset than Tomahawks. Proechimys sp. was the most abundant species trapped (N = 125) and Tomahawk was the most efficient type of trap to capture this species (N = 97 individuals). Neacomys spinosus and Marmosops bishopi were more trapped in Pitfalls (N = 92 and 100 individuals, respectively) than Shermans and Tomahawks. Monodelphis glirina was more trapped in Shermans and Pitfalls than Tomahawks. Species composition trapped using the three types of traps were distinct. Pitfalls captured a more distinct subset of the small mammal community than the two other live traps. We recommend the association of the three types of traps to reach a more comprehensive sampling of the community of small mammals. Thus, as stated by previous studies, we also recommend the complementary use of Shermans, Tomahawks and Pitfalls to account for a thorough sampling of the whole small mammal community in researches conducted in the tropical forests of Amazonia.