Community articles — University

The usage of software has grown as computers become popular. There have emerged, both in academia and in the market, technological solutions for several areas, among them education. On the other hand, classroom teaching and learning continues to suffer from classical educational problems such as lack of student and teacher motivation and lack of clear educational goals. And although software supports learning across a range of disciplines and ages, children's audiences, especially in mathematics, have been little contemplated with the benefits that technological solutions can bring. Therefore, the use of pedagogical approaches, such as Bloom's Taxonomy and Formative Assessments, together with gamification techniques, such as Octalysis, can be used to develop a technological solution that contemplates this public. The present work aims to propose the development of a software to assist the teaching and learning of mathematics for children in the classroom.

Research about recommendation systems has increased due to the amount of information that it is available to individuals. In the music context these systems help the individual to filter and discover new songs according the individual's taste. Most of the business music companies use a recommendation system, based on the characteristics of a song listened by an individual, but a group recommendation system is still underexplored. For a shared environment when there is music, the songs selection will be more efficient if a group recommendation system is used. The goal of this project is to develop a music recommendation for a group that, is sharing the same environment, taking into consideration the context. For this reason, in this work we will employ the Spotify API to recover the data of playlists that were listened by an individual, collecting its preferences and adding them to the others individuals playlists.

Neural Networks for Engineering Students Read the top first. Elon Musk thinks this is more dangerous than nukes. Show a little respect, but don't be afraid.

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There are several voice communication systems that are used nowadays which are capable of maintain voice calls between two users in real time. Telephones are widely used all around the world in an unlimited kind of situations. All of these situations expose the microphone (or microphones) of the phones to different and unpredictable noises, as street noise, sea noise, rain noise, wind noise, unwanted voices, car motors, etc. As microphones capture all the sounds around it, including the wanted voice and the unwanted noises, it is necessary to implement digital real time filters capable of attenuate as much as possible all the surrounding noises. It exists a large quantity of noise reduction methods that have been used in the calling algorithms of phones. Even if these methods have had, in general, a good performance, there is still a research being done in this area in order to improve the current results. Because of this, the multichannel methods were created (using multiple microphones) as well as new algorithms that pretend to have a better noise reduction than the single channel methods. Most of these methods require a speech presence probability (SPP) method to achieve the noise reduction. The following document presents a research about different SPP methods as well as a comparison between these. This includes an explanation on how theses algorithm work, a Matlab implementation using real voice and noise recordings and objective tests of the filter.

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Este trabalho apresenta o estudo da performance de algoritmos de criptografia em plataformas de Internet das Coisas. O presente trabalho tem como objetivo estudar o funcionamento de algoritmo de criptografia simétrico AES e assimétrico RSA e aplicá-los a ambientes de Internet das Coisas, para que se possa avaliar o impacto na performance dos mesmos. Assim como, aplicar algoritmos de criptografia na camada de rede, na tentativa de garantir a segurança dos dados trocados em um ambiente de Internet das Coisas. Através do estudo, foi verificado que algoritmos assimétricos possuem maior impacto na performance do dispositivo, pois se baseam em cálculos complexos. Com isso, foram escolhidas plataformas utilizadas em prototipagem para mensurar o impacto no processamento. Ao realizar os testes, foi possível provar o impacto na rede e ajudar, através dos dados coletados, a escolher o algoritmo que melhor se adequa ao ambiente de Internet das Coisas, assim como, às necessidades de segurança dos mesmos. Created with the UNIFOR dissertation template

Introduction to quantum mechanical effects and an implementation example of quantum key distribution

Ejemplo de una tesis de la Escuela Politécnica Nacional