The Deaf have been denied their natural language for over a hundred years, with dire consequences for their health, citizenship and culture. Sign Language is the natural language of the Deaf, used for intellectual development and other human traits that are language related. Writing Systems (sequence of characters to represent a language) store and retrieve information for literature, science, knowledge creation, information dissemination, communication over time and space etc. SignWriting is a writing system deemed adequate to the spatial-visual nature of Sign Languages. However, current computational technologies fail to provide the Deaf with effective tools for their writing needs (they lack usability, and/or are one-to-one translation from the oral language etc.). This article proposes a new, more natural approach: that of using screen and stylus for online handwritten recognition of SignWriting. This research makes available a database to be used by computer vision/character recognition to inform design of SignWriting editors.
Este trabalho apresenta um jogo educacional para auxiliar no ensino da educação financeira contemplando o conteúdo sobre identificação de cédulas e moedas do Sistema Monetário Brasileiro. O jogo, denominado de Dominó Monetário, é fundamentado na ideia do Dominó tradicional e foi desenvolvido para plataforma web. Possui dois níveis de dificuldades (fácil e difícil) em que o jogador é desafiado a jogar contra o computador, que é um agente implementado com os algoritmos de busca heurística. Como o jogo aborda o valor monetário nas peças de dominós, foi adicionado o item poupança par a guardar esse valor. Assim, quando termina o jogo, o valor monetário da poupança é adicionado da poupança do vencedor e debitado da poupança do jogador que perdeu a jogada.
Transmission lines are fundamental components of the electric power system, demanding special attention from the protection system due to the vulnerability of these lines. This paper presents a method for fault location in transmission lines using data for a single terminal without requiring explicit feature engineering by a domain expert. The fault location task provides an approximate position of the point of the line where the failure occurred, serving as information to the operators to dispatch a maintenance staff to this location to reclose the transmission line with better reliability and safety. In our method, we extract two post-fault cycles of the three-phase current and voltage signals to serve as input to a model based on the LSTM algorithm. We defined the model's architecture with empirical experiments searching for the best structure to estimate the fault distance. For this purpose, we used a dataset with diversified failure events, also available to the scientific community. The results demonstrate the effectiveness of the proposed method with a mean error of 0.1309 km +- 0.4897 km, representing 0.0316% +- 0.1183% of the transmission line extension.
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