Continuous-time signal processing

Особенный интеллектуализированная система (информационно-вычислительная система мониторинга с участием человека участие и интеллектуальная поддержка в решении определенных задач)

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GesHome dataset consists of 18 hand gestures from 20 non-professional subjects with various ages and occupation. The participant performed 50 times for each gesture in 5 days. Thus, GesHome consists of 18000 gesture samples in total. Using embedded accelerometer and gyroscope, we take 3-axial linear acceleration and 3-axial angular velocity with frequency equals to 25Hz. The experiments have been video-recorded to label the data manually using ELan tool.

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The data set contains electrical and mechanical signals from experiments on three-phase induction motors. The experimental tests were carried out for different mechanical loads on the induction motor axis and different severities of broken bar defects in the motor rotor, including data regarding the rotor without defects. Ten repetitions were performed for each experimental condition.

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The sensitivity of an ultrasonic transducer is an important parameter for evaluating its effective frequency band, electroacoustic conversion efficiency, and the measurement capability of the system. Determining the sensitivity of a traditional immersion or contact piezoelectric transducer has been well investigated. However, due to the high attenuation of wave propagation in air and the large acoustic impedance mismatch between the active piezoceramic material and the load medium, there are few reports on the calibration of an air-coupled piezoelectric transducer.

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Recognition of human activities is one of the most promising research areas in artificial intelligence. This has come along with the technological advancement in sensing technologies as well as the high demand for applications that are mobile, context-aware, and real-time. We have used a smart watch (Apple iWatch) to collect sensory data for 14 ADL activities (Activities of Daily Living). 

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