Salesian Journal on Information Systems

2-13

Authors: Ferreira, M. S., Dos Santos, K.C., Salgado, V. C. S.

Statistic are commonly used in football to analyze a players performance. Their application is done through the scout, a method of data collection that is seen as the actions of the athletes regarding the technical and/or tactical aspects. After reviewing the literature, we realized even though there are several softwares for scouting applications, they do not perform a thorough avaluation of a goalkeeper actions. The goal of this work is to develop a scout system with support to the evaluation of goalkeepers, called Goalkeeper. The purpose of the system is to assist physical education professionals and goalkeeping instructors in conducting their instructor's training by analyzing statistical statutes on a player's performance. The software was developed for the Android platform in order to allow the mobility of the user and use an application, since an evaluation can be performed through a videos, training camps or games. In order to evaluate the application, a questionnaire was applied to specialists. The results obtained were considered promising and allowed to observe the users' interest in the system.

26-34

Authors: SERPA, P; WEITZEL, L; CALADO, L.

Operational Oceanography is a reality nowadays, making it necessary for computer systems to improv the numerical models and the feasibility of numerical oceanographic systems. The main goal of this research is to study and design a system that uses Web Services paradigm in order to integrate oceanographic numerical modeling systems and autonomous computational systems. The system aims to provide an abstraction layer between applications such as Matlab, Fortran, Python, Java Script and the underlying network infrastructure. It is based on the REST architecture and the JavaScript Object Notation (JSON) protocol. Thus, both internal modules and external systems can communicate in a distributed, low-coupling and transparent manner, regardless of their location, development language and hardware platform. For Operational Oceanography, these characteristics bring some advantages including, for instance, the fact that it provides greater processing power for the execution of numerical models using specific hardware and it makes it possible to integrate new numerical models. Hence, the proposed system enables the evolution of the Numerical Oceanographic Prediction System, specially core operations of the Almirante Paulo Moreira Institute of Sea Studies (Brazilian Navy), as well as other oceanographic researches in general.

49-59

Authors: EBERMAM, E.; KROHLING, R.

Convolutional neural networks have been attracted great attention in the realm of complex tasks, mainly in image recognition. They were specifically designed to process images as inputs, as they act in local receptive fields, performing a convolution process. However, understanding the work principle of this network may not be an easy task, especially for beginners in the area of computational intelligence. Therefore, the objective of this work is to present in a didactic and intuitive way the convolutional neural networks. A case study involving alphabet character recognition is presented in order to ilustrate the feasibility of the approach.

2-10

Authors: FERREIRA, M. V. G.; VIEIRA, F. H. T.

In this paper, we propose a wireless networks resource allocation scheme whose goal is to maximize the total data rate using the Evolutionary Programming (EP) heuristic. The resource allocation algorithm performance is verified and compared to others in the literature and, in these computational simulations, we proved the superior performance of the proposal in terms of throughput. We also consider in simulated scenarios the current and candidate techniques for next generation networks such as f-OFDM (Filtered-Orthogonal Frequency Division Multiplexing) and carrier aggregation and we show that using f-OFDM it is possible to provide 10% higher transmission rate in relation to the 4G networks.

20-34

Authors: CARVALHO, M. N. L., SILVA, M. R. P., VIEIRA, F. H. T., ROCHA, F. G. C.

In this article, it is proposed the use of a multiobjective genetic algorithm NSGA-II (Nondominated Sorting Genetic Algorithm) for dimensioning the mesh optical network that connects the reclosers of a smart grid which has the self-healing capacity. Considering only link distances (cost), this dimensioning can be done considering the solution to the Traveling Salesman Problem. Thus, we first present in this work a performance comparison of the following algorithms used to solve the Traveling Salesman Problem (TSP): Brute Force, Cross Entropy, Genetic Algorithm, and Nondominated SortingGenetic Algorithm (NSGAII). Next, we propose the NSGA-II to dimension the mesh optical network, considering factors such as cost and throughput.

51-58

Authors: LOPES FILHO, G.; FRANCO, R. A. P.; VIEIRA, F. H. T.

The photovoltaic energy is an interesting option for clean energy generation in the entire world, since it has a high potential for electricity generation worldwide. The equipment responsible for transforming the solar rays into electrical energy is the photovoltaic panel. The computational simulation of photovoltaic panels is essential to design photovoltaic systems. However, the datasheets of the panels does not provide the necessary information for the computational simulation. Therefore, it becomes necessary to develop methods to estimate some parameters of the panels. This work proposes the application of Genetic Algorithm to estimate parameters of photovoltaic systems. The objective function of the Genetic Algorithm corresponds to the minimization of the root mean square error between the I-V experimental curve and the I-V curve generated by the estimated parameters. The results obtained with the Genetic algorithm are compared to those of some methods present in the literature.