Browsing Electrical Engineering by Subject "Machine learning"
Now showing items 1-20 of 30
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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 ... -
An investigation to study the effects of Tai Chi on human gait dynamics using classical machine learning
( Elsevier , 2022 , Article)Tai Chi has been proven effective in preventing falls in older adults, improving the joint function of knee osteoarthritis patients, and improving the balance of stroke survivors. However, the effect of Tai Chi on human ... -
Artificial intelligence based anomaly detection of energy consumption in buildings: A review, current trends and new perspectives
( Elsevier , 2021 , Article Review)Enormous amounts of data are being produced everyday by sub-meters and smart sensors installed in residential buildings. If leveraged properly, that data could assist end-users, energy producers and utility companies in ... -
Auto-nahl: A neural network approach for condition-based maintenance of complex industrial systems
( Institute of Electrical and Electronics Engineers Inc. , 2021 , Article)Nowadays, machine learning has emerged as a promising alternative for condition monitoring of industrial processes, making it indispensable for maintenance planning. Such a learning model is able to assess health states ... -
Automated liver tissues delineation techniques: A systematic survey on machine learning current trends and future orientations
( Elsevier , 2023 , Short Survey)Machine learning and computer vision techniques have grown rapidly in recent years due to their automation, suitability, and ability to generate astounding results. Hence, in this paper, we survey the key studies that are ... -
A battery health monitoring method using machine learning: A data-driven approach
( MDPI , 2020 , Article)Batteries are combinations of electrochemical cells that generate electricity to power electrical devices. Batteries are continuously converting chemical energy to electrical energy, and require appropriate maintenance to ... -
Cybersecurity for industrial control systems: A survey
( Elsevier Ltd , 2020 , Article Review)Industrial Control System (ICS) is a general term that includes supervisory control & data acquisition (SCADA) systems, distributed control systems (DCS), and other control system configurations such as programmable logic ... -
Data fusion strategies for energy efficiency in buildings: Overview, challenges and novel orientations
( Elsevier , 2020 , Article)Recently, tremendous interest has been devoted to develop data fusion strategies for energy efficiency in buildings, where various kinds of information can be processed. However, applying the appropriate data fusion strategy ... -
Data-Driven Intelligent Model for Sale Price Prediction and Monitoring of a Building
( Springer , 2020 , Book chapter)The construction cost forecasting and monitoring plays an important role in a building condition assessment. The construction cost of a building (CCB) not only depends on the method of construction, equipment, labor, and ... -
Design and implementation of programmable multi-parametric 4-degrees of freedom seismic waves ground motion simulation IoT platform
( Institute of Electrical and Electronics Engineers Inc. , 2019 , Conference Paper)The early warning and disaster management agencies spend billions of dollars to counter and cater earthquakes but it has always been unique accident. In this work, a programmable four degrees of freedom electromechanical ... -
Development of a stacked machine learning model to compute the capability of ZnO-based sensors for hydrogen detection
( Elsevier , 2024 , Article)Zinc oxide (ZnO) nanocomposite sensors decorated with various dopants are popular tools for detecting even low hydrogen (H2) concentrations. The nanocomposite's chemistry, temperature, and H2 concentration impact the success ... -
Editorial: Machine Learning, Advances in Computing, Renewable Energy and Communication (MARC)
( Springer Science and Business Media Deutschland GmbH , 2022 , Conference Paper)Machine learning (ML) is the subcategory of artificial intelligence (AI), which has the capability to imitate human behavior intelligently as per the task performed by the human. In the modern time, any organization ... -
Estimating blood pressure from the photoplethysmogram signal and demographic features using machine learning techniques
( MDPI AG , 2020 , Article)Hypertension is a potentially unsafe health ailment, which can be indicated directly from the blood pressure (BP). Hypertension always leads to other health complications. Continuous monitoring of BP is very important; ... -
Generative Adversarial Network Approach to Future Sermonizing of Housing Dispersal in Emerging Cities
( American Society of Civil Engineers (ASCE) , 2022 , Article)This study aims to visualize the future housing dispersal of expatriates, based on the predicted urban growth in emerging cities. Generalized adversarial networks (GANs) will be utilized to predict the future urban growth ... -
Machine learning and discriminant function analysis in the formulation of generic models for sex prediction using patella measurements
( Springer Nature , 2022 , Article)Sex prediction from bone measurements that display sexual dimorphism is one of the most important aspects of forensic anthropology. Some bones like the skull and pelvis display distinct morphological traits that are based ... -
Machine learning for cybersecurity in smart grids: A comprehensive review-based study on methods, solutions, and prospects
( Elsevier B.V. , 2022 , Article Review)In modern Smart Grids (SGs) ruled by advanced computing and networking technologies, condition monitoring relies on secure cyberphysical connectivity. Due to this connection, a portion of transported data, containing ... -
ML-Based Handover Prediction and AP Selection in Cognitive Wi-Fi Networks
( Springer , 2022 , Article)Device mobility in dense Wi-Fi networks offers several challenges. Two well-known problems related to device mobility are handover prediction and access point selection. Due to the complex nature of the radio environment, ... -
Multimodal EEG and Keystroke Dynamics Based Biometric System Using Machine Learning Algorithms
( Institute of Electrical and Electronics Engineers Inc. , 2021 , Article)Electroencephalography (EEG) based biometric systems are gaining attention for their anti-spoofing capability but lack accuracy due to signal variability at different psychological and physiological conditions. On the other ... -
Performance analysis of conventional machine learning algorithms for diabetic sensorimotor polyneuropathy severity classification
( MDPI , 2021 , Article)Background: Diabetic peripheral neuropathy (DSPN), a major form of diabetic neuropathy, is a complication that arises in long-term diabetic patients. Even though the application of machine learning (ML) in disease diagnosis ... -
Performance evaluation of time-frequency image feature sets for improved classification and analysis of non-stationary signals: Application to newborn EEG seizure detection
( Elsevier B.V. , 2017 , Article)This study demonstrates that a time-frequency (TF) image pattern recognition approach offers significant advantages over standard signal classification methods that use t-domain only or f-domain only features. Two approaches ...