Signal Processing
It is the key problem of machine condition monitoring to judge whether the rolling bearing has a fault or not and judge the fault location according to the noise signal. Aiming at this problem, a rolling bearing fault identification method is proposed based on Wavelet Frequency Band Subdivision (WFBS), Principal Component Analysis (PCA) and Multi-Level Clustering (MLC).
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This is the First Arabic voice Commands Dataset to provide personalized control of devices at smart homes for elder persons and persons with disabilities. The dataset contains 12 speakers, each saying 36 different phrases or words in Arabic language. The goal of this dataset is to use it in an Arabic smart home system to control home devices through voice. Participants were asked to say each phrase multiple times. The phrases to record were presented in a random order.
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The proliferation of efficient edge computing has enabled a paradigm shift of how we monitor and interpret urban air quality. Coupled with the dense spatiotemporal resolution realized from large-scale wireless sensor networks, we can achieve highly accurate realtime local inference of airborne pollutants. In this paper, we introduce a novel Deep Neural Network architecture targeted at latent time-series regression tasks from continuous, exogenous sensor measurements, based on the Transformer encoder scheme and designed for deployment on low-cost power-efficient edge processors.
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Demo script and data for infocom 2022 paper titled "Don’t Miss Weak Packets: Boosting LoRa Reception with Antenna Diversities"
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A Frequency-Dependent & Per-Port (FDPP) channel termination & renormalization method is presented as
a more accurate substitute for the traditional method which
uses frequency-independent, uniform impedance as the serialization/deserialization (SerDes) transmit (TX)/receive (RX)
termination impedances. Although the traditional method is
employed in practically all the existing high-speed interface
standards, the assumption of the constant, uniform termination
impedance at TX and RX is not exact and will lead to inaccuracy.
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The performances of ENRZ (Ensemble NRZ) under
the interferences of crosstalk, in conjunction with NRZ (NonReturn-to-Zero), PAM4 (Pulse Amplitude Modulation of 4-level),
and PAM3 are investigated. One-side and two-side crosstalk scenarios with varying levels of crosstalk are studied. The simulated
eye-diagram obtained with the four signaling techniques under
a range of crosstalk levels are compared and the reasons that
lead to the prominent advantages of ENRZ are analyzed. As
an alternative approach of validating the performances of the
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This dataset has been employed in the following articles:
https://ieeexplore.ieee.org/document/9682692
https://ieeexplore.ieee.org/document/9871051
https://content.iospress.com/articles/technology-and-health-care/thc202198
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The measurement and diagnosis of the severity of failures in rotating machines allow the execution of predictive maintenance actions on equipment. These actions make it possible to monitor the operating parameters of the machine and to perform the prediction of failures, thus avoiding production losses, severe damage to the equipment, and safeguarding the integrity of the equipment operators. This paper describes the construction of a dataset composed of vibration signals of a rotating machine.
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This paper introduces a compact Multiple input Multiple output (MIMO) antenna system for vehicular application in the sub-6GHz 5G systems that operates in the middle and high frequency bands from 1.71GHz to 5GHz. The proposed design consists of two symmetrical raised printed monopoles on Flame Retardant 4 (FR4) dielectric material with Electromagnetic Band Gap shape (EBG) to provide defected ground to improve bandwidth impedance and higher isolation across the operating frequency range.
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