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1.
Ciênc. cogn ; 26(2): 266-276, 31 dez. 2021. ilus
Article in Portuguese | LILACS | ID: biblio-1353869

ABSTRACT

O fenômeno de aceleração social, intimamente ligado a nossa modernização tecnológica e os sistemas políticos e sociais que adotamos, vem sendo alvo de questionamentos por parte da teoria crítica por diversos filósofos e sociólogos, principalmente em relação a se tal "aceleração" seja algo que, possa ser justificável pelo bem comum da sociedade. De fato, as rápidas mudanças que ocorreram no último século causaram uma tremenda mudança em nossos estilos-de-vida, e na maneira como experienciamos o mundo. Que a nossa sociedade mudou e continua a mudar é um fato evidente quando olhamos criticamente para o passado e presente, e comparamos diferentes épocas da história humana. Neste ensaio tentaremos explorar algumas possíveis hipóteses que fundamentem o comportamento aceleracionista em certos fatores e mecanismo biológicos que caracterizam os sistemas de motivação e saciação humanos. Também tentaremos mostrar como certos fenômenos sociais podem auxiliar em fortalecer este tipo de comportamento, e suas possíveis origens evolutivas. Este estudo tem como objetivo principal fundamentar a Tese Aceleracionista em evidências neurofisiológicas, cognitivo-comportamentais, evolutivas e sociais.


The phenomenon of social acceleration is closely linked to our technological modernization and the political and social systems we have adopted, and it has been questioned by several philosophers and sociologists, especially in relation to whether such acceleration is something that can be justified for the common good of society. In fact, the rapid changes that have occurred in the last century have caused a tremendous change in our lifestyles, and in the way we experience the world. That society have changed and continues to change is an evident fact when we look critically to the past and our present and compare different times in human history. In this essay we will try to explore some possible hypotheses that underpin accelerated behavior, in certain biological factors and mechanisms that characterize human motivation and satiation systems. We will also try to show how certain social phenomena can help to strengthen this type of behavior, and its possible evolutionary origins. The main objective of this study is to base the Accelerationist Thesis on neurophysiological, cognitive-behavioral, evolutionary and also social evidence.


Subject(s)
Humans , Reward , Satiation/physiology , Social Change , Cognition/physiology , Neurotransmitter Agents/physiology , Motivation/physiology
2.
Res. Biomed. Eng. (Online) ; 33(4): 362-369, Oct.-Dec. 2017. tab, graf
Article in English | LILACS | ID: biblio-896196

ABSTRACT

Abstract Introduction Skateboarding is one of the most popular cultures in Brazil, with more than 8.5 million skateboarders. Nowadays, the discipline of street skating has gained recognition among other more classical sports and awaits its debut at the Tokyo 2020 Summer Olympic Games. This study aimed to explore the state-of-the-art for inertial measurement unit (IMU) use in skateboarding trick detection, and to develop new classification methods using supervised machine learning and artificial neural networks (ANN). Methods State-of-the-art knowledge regarding motion detection in skateboarding was used to generate 543 artificial acceleration signals through signal modeling, corresponding to 181 flat ground tricks divided into five classes (NOLLIE, NSHOV, FLIP, SHOV, OLLIE). The classifier consisted of a multilayer feed-forward neural network created with three layers and a supervised learning algorithm (backpropagation). Results The use of ANNs trained specifically for each measured axis of acceleration resulted in error percentages inferior to 0.05%, with a computational efficiency that makes real-time application possible. Conclusion Machine learning can be a useful technique for classifying skateboarding flat ground tricks, assuming that the classifiers are properly constructed and trained, and the acceleration signals are preprocessed correctly.

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