Abstract
This article is devoted to the problem of training cyclists from a system approach. Technologies were used to monitor and evaluate in an integrated way the physical form, load parameters and level of functional capabilities of the athlete's body. For correlation between the physiological indices and performance, data from cardiac activity (ECG), muscle activity (EMG and temperature), respiratory processes (oximetry), as well as data from the environment where this athlete is inserted (ambient temperature, pressure, humidity).

Abstract
Kinematic analysis of human movement is very important in several areas, such as in sports (e.g., for athletic performance analysis), health (e.g., rehabilitation of people with motor disabilities) and others. The study of the kinematics of the human body involves several methods that resort to the analysis of several parameters that come from the movement. Important parameters to take into account are the acceleration, velocity and position (linear or angular) of the various articulations of the human body, which can be measured by sensors or through the analysis of repeated images obtained by camera. In this paper will be presented a suit that acquire the different position of human joints that will be useful in rehabilitation, FatoXtract. It is through the analysis of human movement that we can analyze whether the movement in rehabilitation is adequate or not.

Abstract
The study explores the technical optimization of an athlete through the use of intelligent system performance metrics that produce information obtained from inertial sensors associated to the coach's technical qualifications in real time, using Mixed Methods and Machine Learning. The purpose of this study is to illustrate, from the confusion matrices, the different performance metrics that provide information of high pertinence for the sports training in context. 2000 technical fencing actions with two levels of complexity were performed, captured through a single sensor applied in the armed hand and, simultaneously, the gesture’s qualification through a dichotomous way by the coach. The signals were divided into segments through Dynamic Time Warping, with the resulting extracted characteristics and qualitative assessments being fed to a Neural Network to learn the patterns inherent to a good or poor execution. The performance analysis of the resulting models returned a prediction accuracy of 76.6% and 72.7% for each exercise, but other metrics indicate the existence of high bias in the data. The study demonstrates the potential of intelligent algorithms to uncover trends not captured by other statistical methods. © Edições Desafio Singular.

Abstract
This paper describes the implementation of a simulated bioinspired 3D model, which was moved through segmented gestures using fractional calculation segmentation methods. It was observed that for the increase in the detection of such gestures from this segmentation an improvement in the recognition and standardization of gesture images using the FODPSO method would be obtained. We used the AlexNet neural network for training and recognition of the processed gestures, which resulted in a simulated 3D model of a spider moved by gestures recognized through a webcam, which had an accuracy of approximately 98% recognition through the neural network.

Abstract
This article describes part of the development cycle of an educational robotic platform to be used as an interdisciplinary teaching tool integrated in the curriculum. We focus on the creation of the alpha and beta versions of our prototype and it’s evaluation by representative users. The SUS score of 92.5 points, Best Imaginable, show a very stable and satisfactory robotic platform, with almost no usability problems detected.

Abstract
Aging of Tawny Port wine is a multifactorial process critical for attaining the desired quality. Real time monitoring of important intrinsic and extrinsic factors that are known to affect the time and quality of the aging process are important to optimize and to manage the natural variability between wines aged in different long used wood barrels. For this study, a distributed monitoring system was installed in sixteen oak barrels, placed in two adjacent wineries - one of them with controlled temperature in the Douro Demarcated Region, Portugal. The monitoring process was performed using a RS-485 industrial network, which interconnects sensors that continuously measure wine temperature, pH, redox potential and wine's dissolved oxygen, as well as other sensors that measure parameters related to the barrels' environmental context, such as room temperature and relative humidity. This work presents the design, development and implementation of a remote distributed system to monitor such parameters, aiming to determine the existence of behaviour models for Port Tawny wine during aging in long-used oak barrels, depending on their storage history and to understand the evolution of wine pH, dissolved oxygen and redox potential in real winery conditions as well as their dependence on the wine's storage temperature. This approach is based on easy-to-use embedded systems, with the aim of giving a relevant contribution to other projects in the area of precision enology.