a b s t r a c tFootball is the team sport that mostly attracts great mass audience. Because of the detailed information about all football matches of championships over almost a century, matches build a huge and valuable database to test prediction of matches results. The problem of modeling football data has become increasingly popular in the last years and learning machine have been used to predict football matches results in many studies. Our present work brings a new approach to predict matches results of championships. This approach investigates data of matches in order to predict the results, which are win, draw and defeat. The investigated groups were different type of combinations of two by two pairs, win-draw, windefeat and draw-defeat, of the possible matches results of each championship. In this study we employed the features obtained by scouts during a football match. The proposed system applies a polynomial algorithm to analyse and define matches results. Some machine-learning algorithms were compared with our approach, which includes experiments with information obtained from the football championships. The association between polynomial algorithm and machine learning techniques allowed a significant increase of the accuracy values. Our polynomial algorithm provided an accuracy superior to 96%, selecting the relevant features from the training and testing set.
Introduction: Due to the increasing popularization of computers and the internet expansion, Alternative and Augmentative Communication technologies have been employed to restore the ability to communicate of people with aphasia and tetraplegia. Virtual keyboards are one of the most primitive mechanisms for alternatively entering text and play a very important role in accomplishing this task. However, the text entry for this kind of keyboard is much slower than entering information through their physical counterparts. Many techniques and layouts have been proposed to improve the typing performance of virtual keyboards, each one concerning a different issue or solving a specific problem. However, not all of them are suitable to assist seriously people with motor impairment. Methods: In order to develop an assistive virtual keyboard with improved typing performance, we performed a systematic review on scientific databases. Results: We found 250 related papers and 52 of them were selected to compose. After that, we identified eight essentials virtual keyboard features, five methods to optimize data entry performance and five metrics to assess typing performance. Conclusion: Based on this review, we introduce a concept of an assistive, optimized, compact and adaptive virtual keyboard that gathers a set of suitable techniques such as: a new ambiguous keyboard layout, disambiguation algorithms, dynamic scan techniques, static text prediction of letters and words and, finally, the use of phonetic and similarity algorithms to reduce the user's typing error rate.
This work deals with object tracki through the boundary detection by Hough tra detection through color maps transform. It experiment where the trace of human iris variations of texture and contour measureme the tracking, presented and discussed. Furthe a breakdown of techniques used and the meth
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