DEEP LEARNING BASED EARLY DETECTION FRAMEWORK FOR PRELIMINARY DIAGNOSIS OF COVID-19 VIA ONBOARD SMARTPHONE SENSORS

Deep Learning Based Early Detection Framework for Preliminary Diagnosis of COVID-19 via Onboard Smartphone Sensors

The COVID-19 pandemic has affected almost every country causing devastating economic and social disruption and stretching healthcare systems to the limit.Furthermore, while being the current gold standard, existing test methods including NAAT (Nucleic Acid Amplification Tests), clinical analysis of chest CT (Computer Tomography) scan images, and bl

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An Approach Based on the Use of Commercial Codes and Engineering Judgement for the Battle of Water Demand Forecasting

WILD OIL OF OREGANO This paper demonstrates the synergistic use of engineering judgment and statistical/deep learning models, implemented through a four-step process using the software SAS Viya 4.Initial data filtering, input variable determination, and simultaneous application Body Brush of RNN, LSTM, and GRU forecasting algorithms are conducted.R

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Assessment of a New GC-MS/MS System for the Confirmatory Measurement of PCDD/Fs and (N)DL-PCBs in Food under EU Regulation

Polychlorodibenzo-p-dioxins (PCDDs), polychloro-dibenzofurans (PCDFs), dioxin-like (DL), and non dioxin-like (NDL) polychlorinated biphenyls (PCBs) are currently regulated in food and feed within the European territory (EU 2017/644-771).The confirmatory methods of analysis for checking compliance with maximum levels (MLs) for these involve either t

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Dynamic coordinated control strategy of a dual-motor hybrid electric vehicle based on clutch friction torque observer

The hybrid power system with dual motors and multiple clutches experiences significant torque fluctuation during mode switching process due to the different torque response characteristics of Console the motor and engine.To address this issue, this paper focuses on the estimation of clutch friction torque and the development of dynamic coordinated

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