Salesian Journal on Information Systems

11-19

Authors: E SILVA, G. M.; DA SILVA, N. F. F.; DIAS, M. S.

Abstract: Machine learning techniques can be used to automatically infer information that is not available from large volumes of data. Social networks have been gaining popularity and turning into an important sources of data for an application of computer techniques. The goal of this work is to study how well preprocessing techniques, feature sets and classifiers work on the task of automatic bullying trace detection, as well as the role of the author of the text on the reported episode.We focused on social networks texts written in Brazilian Portuguese. Several different classifiers and attribute sets were studied and compared, in order to identify which one is the most appropriate for this task. Among all tested configurations, the best results was found when using the largest trainning set transformed into a feature set made of unigrams and bigrams in conjunction with SVM with an RBF kernel

35-50

Authors: RIBEIRO, M. R. C., SANTOS, J. C., OLIVEIRA-JR, A. C.

There are some curves, namely, the Cycloid, the Conchoid of Nicomedes, the Pascal limaçon, the trisectrix of Hippias and the cissoid of Diocles, which have been studied over many centuries because of heir properties. In this work, we report some properties of those curves which are fundamental to the discussion of antiquity problems. We also analyzed, implemented and simulated the main properties of the cycloid curve and the three classical problems of Greek geometry in dynamic geometric open source software.

59-73

Authors: SOUZA, D.F., ABRAHÃO, D.C., VIEIRA, F.H.T, BORGES, V.C.M.

With the development of the next generation of mobile communications systems for 5G, several technologies are being studied in order to reach the new requirements in new application scenarios. Among them, is the use of new modulations with higher spectral eficiency in substitution of OFDM, such as F-OFDM and UFMC, and also the scheduling algorithms which are in charge of sharing resources between users. In this article, we evaluated the application of F-OFDM and UFMC, 5G modulations candidates, on LTE downlink as compared to OFDM and evaluated the Round Robin, QoS Guaranteed and PSO schedulers dealing with additional resources provided by the tested modulations. To reach this, we compared performance considering parameters like fairness, latency, throughput and spectral eficiency. The results showed that the downlink LTE improved performance in all evaluated parameters with UFMC modulation. In fact, there was a performance improvement in all the schedulers evaluated. For example, PSO based scheduler improved latency and throughput while QoS Guaranteed reached the lowest loss, and the highest fairness were reached by QoS Guaranteed and Round Robin.