Concrete is one of the most widely used building materials, being composed of different components with different properties, which makes the task of dosing and strength determination complex. Artificial Neural Networks is a tool that has the ability to generalize and learn from previous experiences that are provided by a previously built database. This work aims the implementation of RNA in determining the compressive strength of concrete of various ages. The input data is the material quantities and the output is the compressive strength. The results obtained are promising and advantageous from the point of civil engineering, since the average correlation coefficient obtained was 0.96559, with the neural network showing agility and a low error rate in the inserted context, with an efficiency of approximately 95%.
The present work focuses on the modeling of the thermal system composed of several modules, in which the general model of the system is built, which includes all its components in operation. The environment collected data in real time of the growth and decrease (temperature) curve of a soldering iron tool, under aspects of PWM variation - Pulse Width Modulation - of the signal. It is used as a representative model of device in industrial welding, in which it has similarities in key aspects of behavior. Through analysis and software assistance, the function of transferring the general plan was obtained, which showed an acceptable level of correspondence (86.04%) in non-linear systems. Based on the model discovered, a PItype controller - Proportional Integral - was designed, paying attention to the need for a low-level overshoot signal (6.08%) in order to obtain a response to the rapid stabilization step, rare in thermal systems. The PI was developed in order to generate an output in DC format (Duty Cycle format), since the raw data of the system were collected by varying this indicator at regular intervals of time. After the tests carried out in simulation, results were obtained that confirm that the developed control system is applicable and responds appropriately, being able to be optimized for applications.,
Concrete is one of the most widely used building materials, being composed of different components with different properties, which makes the task of dosing and strength determination complex. Artificial Neural Networks is a tool that has the ability to generalize and learn from previous experiences that are provided by a previously built database. This work aims the implementation of RNA in determining the compressive strength of concrete of various ages. The input data is the material quantities and the output is the compressive strength. The results obtained are satisfactory and promising from the point of view of civil engineering.
Nos serviços de comunicação, a qualidade e integridade do sinal de voz no receptor é um fator relevante que as operadoras de telefonia devem considerar. Neste artigo, estudamos o impacto da degradação que ocorre no canal de transmissão no sinal de voz transmitido. Para tanto, são utilizados parâmetros-chave, como a pontuação média de opiniões (MOS) relacionada ao sinal de voz e a taxa de erro de bit (BER), a fim de avaliar qualitativa e quantitativamente o sinal de fala em cada cenário. É usado um cenário de simulação de modulação, que considera os canais de desvanecimento AWGN, Rician e Rayleigh, e duas modulações: BPSK e QAM. Esses canais têm diferentes parâmetros de configuração. Os resultados experimentais mostram que existem certos valores de índice de qualidade MOS para cada tipo de canal com uma configuração específica, mostrando que para cada cenário de transmissão há a necessidade de adaptações na combinação modulação-canal-ganho para obter melhor desempenho.
O amortecimento é uma propriedade dos materiais que pode ocorrer em aspecto de escala micro e macroscópica. Há um crescimento no conceito da análise de marcadores de trincas internas estruturais que causam danos em materiais diversos, devido sua ampla aplicabilidade na resolução de problemas. No processo de amortecimento ocorre a perda de energia do material quando este entra em contato físico com outro material, no qual o fenômeno pode ser observado por meio de equipamentos modernos de alta sensibilidade sob ambiente controlado. Há poucos institutos de pesquisa com capacidade de análises em ensaios de amortecimento precisos com corpos de prova. O uso de dispositivo acelerômetro contorna a problemática do alto custo laboratorial envolvidos e permite maior acessíbilidade. Objetiva-se apresentar uma metodologia de análise de parâmetros associados ao fenômeno de amortecimento, fazendo-se uso de algotítmos para acesso aberto e que permita sua replicação em modelos físicos. O trabalho apresentou efciência em determinar a frequência e parâmetros associados de sinais de corpos de prova.
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