Salesian Journal on Information Systems

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Authors: LINDEN, R.

This is a book review about "Ciência: da filosofia à publicação", from Gilson Volpato

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Authors: TELLES, G.P., ALMEIDA, N.F., ALVAREZ,P. et al.

In this work we propose a simple method to obtain groups of homologous genes across multiple (k) organisms, called kGC. Our method takes as input all-against-all Blastp comparisons and produces groups of homologous sequences. First, homologies among groups of paralogs of all the k compared genomes are found, followed by homologies of groups among k - 1 genomes and so on, until groups belonging exclusively to only one genome, that is, groups of one genome not presenting strong similarities with any group of any other genome, are identified. We have used our method to determine homologous groups across six Actinobacterial complete genomes. To validate kGC, we first investigate the Pfam classification of the homologous groups, and after compare our results with those produced by OrthoMCL. Although kGC is much simpler than OrthoMCL it presented similar results with respect to Pfam classification.

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Authors: FALCAO, H. S.; LOVATO, A. V.; SANTOS A. F. DOS; OLIVEIRA, L. S. et al.

This project intends to develop a prototype for the identification of free spots in open air parking area where there is a good aerial view without obstacles, allowing for the identification of occupied and free spots. We used image processing techniques and pattern recognition using Artificial Neural Networks (ANN). In order to help implement the prototype, we used Matlab. In order to simulate the parking area, we created a model so that we could acquire the images using a webcam, process them, train the neural network, classify the spots and finally, show the results. The results show that it is viable to apply pattern recognition through image capture to classify parking spots.

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Authors: AFFONSO, F. J., CARNEIRO, M. C. V. S., RODRIGUES, E. L. L. et al.

This paper presents a reference model as an automated process to assist the adaptive software development at runtime, also known as Self-adaptive Systems (SaS) at runtime. This type of software has specific characteristics in comparison to traditional one, since it allows that changes (structural or behavioral) to be incorporated at runtime. Automated processes have been used as a feasible solution to conduct software adaptation at runtime by minimizing human involvement (developers) and speeding up the execution of tasks. In parallel, reference models have been used to aggregate knowledge and architectural artifacts, since they capture the systems essence in specific domains. However, presently no there is reference model based on reflection for the automation of software adaptation at runtime. In this scenario, this paper presents a reference model based on reflection, as an automated process, for the development of software systems that require adaptation at runtime. To show the applicability of the model, a case study was conducted and a good perspective to efficiently contribute to the area of SaS has been obtained.