Search
Now showing items 811-820 of 997
PCovNet: A presymptomatic COVID-19 detection framework using deep learning model using wearables data
(
Elsevier
, 2022 , Article)
While the advanced diagnostic tools and healthcare management protocols have been struggling to contain the COVID-19 pandemic, the spread of the contagious viral pathogen before the symptom onset acted as the Achilles' ...
Machine learning-based classification of healthy and impaired gaits using 3D-GRF signals
(
Elsevier
, 2023 , Article)
Gait analysis is helpful for rehabilitation, clinical diagnoses, and sporting activities. Among the gathered signals, ground reaction forces (GRF) may be used for assisting doctors in recognizing and categorizing gait ...
Smart fusion of sensor data and human feedback for personalized energy-saving recommendations
(
Elsevier
, 2022 , Article)
Despite the variety of sensors that can be used in a smart home or office setup, for monitoring energy consumption and assisting users to save energy, their usefulness is limited when they are not properly integrated into ...
Global dissipativity of high-order Hopfield bidirectional associative memory neural networks with mixed delays
(
Springer
, 2020 , Article)
In this paper, the problem of the global dissipativity of high-order Hopfield bidirectional associative memory neural networks with time-varying coefficients and distributed delays is discussed. By using Lyapunov?Krasovskii ...
A Deep Learning Model for LoRa Signals Classification Using Cyclostationay Features
(
IEEE Computer Society
, 2021 , Conference Paper)
With the witnessed exponential growth of Internet of Things (IoT) nodes deployment following the emerging applications, multiple variants of technologies have been proposed to handle the IoT requirements. Among the proposed ...
Simple PWM technique for a three-to-five phase matrix converter
(
John Wiley and Sons Ltd
, 2021 , Article)
Multi-phase converters for more than three-phase applications have become increasingly important topics due to their distinct advantages compared with the conventional three-phase converters. This paper proposes a modified ...
Data-Driven Load Frequency Control Based on Multi-Agent Reinforcement Learning With Attention Mechanism
(
Institute of Electrical and Electronics Engineers Inc.
, 2022 , Article)
With the massive penetration of renewable energy, traditional reinforcement learning algorithms suffer from slow convergence and area control error (ACE) in interconnected power systems. This paper proposes data-driven ...
A pilot protection algorithm for TCSC compensated transmission line with accurate fault location capability
(
Elsevier
, 2020 , Article)
This paper introduces a communication-aided scheme to enhance the fault detection, and fault location calculation for a thyristor-controlled series capacitor (TCSC) compensated transmission lines. In the proposed method ...
A nomogram-based diabetic sensorimotor polyneuropathy severity prediction using Michigan neuropathy screening instrumentations
(
Elsevier
, 2021 , Article)
Background: Diabetic Sensorimotor polyneuropathy (DSPN) is one of the major indelible complications in diabetic patients. Michigan neuropathy screening instrumentation (MNSI) is one of the most common screening techniques ...
Integration of machine learning with economic energy scheduling
(
Elsevier Ltd
, 2022 , Article)
The aim of economic load dispatch (ELD) is to deliver required electrical power for a specified period at the lowest possible generation cost using available generating units (GUs). It is imperative to lower the generation ...