Abstract
The paper presents the comparison of accuracy in the Speech Emotion Recognition task using the Hamming and Hanning windows for framing the speech and determining the spectrogram to be used as input of a convolutional neural network. The detection of between 4 and 10 emotional states was tested for both windows. The results show significant differences in accuracy between the two window types and provide valuable insights for the development of more efficient emotional state detection systems. The best accuracy between 4 and 10 emotions was 64.1% (4 emotions), 57.8% (5 emotions), 59.8% (6 emotions), 48.4% (7 emotions), 47.8% (8 emotions), 51.4% (9 emotions), and 45.9% (10 emotions). These accuracy is at the state-of-the art level.

Abstract

Abstract
Ventricular tachyarrhythmia (VTA), mainly ventricular tachycardia (VT) and ventricular fibrillation (VF) are the major causes of sudden cardiac death in the world. This work uses deep learning, more precisely, LSTM and biLSTM networks to predict VTA events. The Spontaneous Ventricular Tachyarrhythmia Database from PhysioNET was chosen, which contains 78 patients, 135 VTA signals, and 135 control rhythms. After the pre-processing of these signals and feature extraction, the classifiers were able to predict whether a patient was going to suffer a VTA event or not. A better result using a biLSTM was obtained, with a 5-fold-cross-validation, reaching an accuracy of 96.30%, 94.07% of precision, 98.45% of sensibility, and 96.17% of F1-Score.

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Abstract
Despite the ubiquitous term climate neutral cities, there is a distinct lack of quantifiable and meaningful municipal decarbonization goals in terms of the targeted energy balance and composition that collectively connect to national scenarios. In this paper we present a simple but useful allocation approach to derive municipal targets for energy demand reduction and renewable expansion based on national energy transition strategies in combination with local potential estimators. The allocation uses local and regional potential estimates for demand reduction and the expansion of renewables and differentiates resulting municipal needs of action accordingly. The resulting targets are visualized and opened as a decision support system (DSS) on a web-platform to facilitate the discussion on effort sharing and potential realization in the decarbonization of society. With the proposed framework, different national scenarios, and their implications for municipal needs for action can be compared and their implications made explicit.

Abstract
This paper deliberates some of the motivations for contemplating Kits in the theoretical-practical class of a Curricular Unit of Process Control to first year students of a Master Degree in Mechanical Engineering, alongside their purpose. Also, the perceptions of these students about the use of these kits in their learning process are discussed based on an online questionnaire developed for that purpose. According to students' feedback, gathered by an anonymous online questionnaire, it was possible to investigate the effectiveness of the use of didactics kits in the learning of Process Control topics. The obtained results from the students perception are clearly positive and motivating to further uses of this type kit as portable laboratories. © 2023 IEEE.