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Machine Learning and Deep Learning Techniques for Internet of Things Network Anomaly Detection—Current Research Trends
(Multidisciplinary Digital Publishing Institute (MDPI), 2024-03)With its exponential growth, the Internet of Things (IoT) has produced unprecedented levels of connectivity and data. Anomaly detection is a security feature that identifies instances in which system behavior deviates from ... -
Wireless Charging for Electric Vehicles: A Survey and Comprehensive Guide
(Multidisciplinary Digital Publishing Institute (MDPI), 2024-03)This study compiles, reviews, and discusses the relevant history, present status, and growing trends in wireless electric vehicle charging. Various reported concepts, technologies, and available literature are discussed ... -
CP_DeepNet: a novel automated system for COVID-19 and pneumonia detection through lung X-rays
(Springer, 2024)In recent years, the COVID-19 outbreak has affected humanity across the globe. The frequent symptoms of COVID-19 are identical to the normal flu, such as fever and cough. COVID-19 disseminates rapidly, and it has become a ... -
Smart home energy management systems: Research challenges and survey
(Elsevier B.V., 2024-04)Electricity is establishing ground as a means of energy, and its proportion will continue to rise in the next generations. Home energy usage is expected to increase by more than 40% in the next 20 years. Therefore, to ... -
A Meta-Heuristic Sustainable Intelligent Internet of Things Framework for Bearing Fault Diagnosis of Electric Motor under Variable Load Conditions
(Multidisciplinary Digital Publishing Institute (MDPI), 2023-12)The study introduces an Intelligent Diagnosis Framework (IDF) optimized using the Grasshopper Optimization Algorithm (GOA), an advanced swarm intelligence method, to enhance the precision of bearing defect diagnosis in ... -
Battery State-of-Health Estimation: A Step towards Battery Digital Twins
(Multidisciplinary Digital Publishing Institute (MDPI), 2024-02)For a lithium-ion (Li-ion) battery to operate safely and reliably, an accurate state of health (SOH) estimation is crucial. Data-driven models with manual feature extraction are commonly used for battery SOH estimation, ... -
An adaptive power smoothing approach based on artificial potential field for PV plant with hybrid energy storage system
(Elsevier Ltd, 2024-03-01)The increasing quantity of PV installation has brought great challenges to the grid owing to power fluctuations. Hybrid energy storage systems have been an effective solution to smooth out PV output power variations. In ... -
That's how the preform crumples: Wrinkle creation during forming of thick binder-stabilised stacks of non-crimp fabrics
(Elsevier Ltd, 2024-03-15)The simultaneous forming of multiple layers of fabric is being used in industry to increase the throughput of composite parts. A polymeric binder may be used to stabilise the fabric layers to make it easier to handle, ... -
Deep learning based simulators for the phosphorus removal process control in wastewater treatment via deep reinforcement learning algorithms
(Elsevier Ltd, 2024-07)Phosphorus removal is vital in wastewater treatment to reduce reliance on limited resources. Deep reinforcement learning (DRL) can be used to optimize the processes in wastewater treatment plants by learning control policies ... -
Multiobjective and Coordinated Reconfiguration and Allocation of Photovoltaic Energy Resources in Distribution Networks Using Improved Clouded Leopard Optimization Algorithm
(Wiley-Hindawi, 2024)In this paper, a multiobjective framework for simultaneous reconfiguration and allocation of photovoltaic (PV) energy resources in radial distribution networks is performed for minimizing the power losses, lowering network ... -
Improving Robot-Assisted Virtual Teaching Using Transformers, GANs, and Computer Vision
(IGI Global, 2024-01-17)This study aims to enhance the efficacy of personalized learning paths by amalgamating transformer models, generative adversarial networks (GANs), and reinforcement learning techniques. To refine personalized learning ... -
Hybrid Climate Forecasting: Variational Mode Decomposition and Convolutional Neural Network with Long-Term Short Memory
(HARD Publishing Company, 2024)Ozone (O3) pollution has surfaced as a significant threat to urban air quality in contemporary years. The precise and efficient forecast of ozone levels is fundamental in the mitigation and management of ozone pollution. ... -
Direct numerical simulation of the drag, lift, and torque coefficients of high aspect ratio biomass cylindrical particles
(American Institute of Physics Inc., 2024-01)Biomass straw fuel has the advantage of low-carbon sustainability, and therefore, it has been widely used in recent years in coupled blending combustion with coal-fired utility boilers for power generation. At present, the ... -
Advanced series decomposition with a gated recurrent unit and graph convolutional neural network for non-stationary data patterns
(Springer Science and Business Media Deutschland GmbH, 2024-12)In this study, we present the EEG-GCN, a novel hybrid model for the prediction of time series data, adept at addressing the inherent challenges posed by the data's complex, non-linear, and periodic nature, as well as the ... -
Characterisation of the transverse shear behaviour of binder-stabilised preforms for wind turbine blade manufacturing
(Elsevier Ltd, 2024-01-15)Binder-stabilised preforms are being used increasingly in the production of large composite structures, such as wind turbine blades, to increase the throughput. The transverse shear behaviour of the preform is one of the ... -
4E analysis and optimization of a novel hybrid biomass-solar system: Focusing on peak load management and environmental emissions
(Institution of Chemical Engineers, 2024-01)Renewable energies are available as clean sources to replace fossil fuels. Providing continuous power without compromising the environment through hybridizing solar and biomass source is one of the promising solutions. ... -
Usage of radial basis function neural network for dual-energy radiative detection system for measuring the oil pipelines scale layer
(Elsevier Ltd, 2024-02)Scaling oil pipelines over time leads to issues including diminished flow rates, wasted energy, and decreased efficiency. In order to take preventative measures in a timely manner and avoid the aforementioned issues, it ... -
Setting time, sulfuric acid resistance, and strength development of alkali-activated mortar with slag & fly ash binders
(Elsevier B.V., 2024-03)This study evaluated the effect of initial molar ratios SiO2/Al2O3 and (CaO + SiO2)/Al2O3, on the setting time of mortar with alkali-activated Ground Granulated Blast Furnace Slag (GBS) and fly ash (FA) binders. The study ... -
Multi-stage planning of integrated electricity-gas-heating system in the context of carbon emission reduction
(Elsevier Ltd, 2024-03)In order to facilitate the carbon emission reduction to mitigate climate change, this paper proposes a coordinated multi-stage planning strategy for the transmission-level integrated electricity-gas-heating system. The ... -
Towards explainability for AI-based edge wireless signal automatic modulation classification
(Springer Science and Business Media Deutschland GmbH, 2024-12)With the development of artificial intelligence technology and edge computing technology, deep learning-based automatic modulation classification (AI-based AMC) deployed at edge devices using centralised or distributed ...