A5062826520- Metaheuristic Optimization Algorithms Research
- EEG and Brain-Computer Interfaces
- ECG Monitoring and Analysis
- Network Security and Intrusion Detection
- Smart Grid Energy Management
- Evolutionary Algorithms and Applications
- Blind Source Separation Techniques
- Microgrid Control and Optimization
- Text and Document Classification Technologies
- Internet Traffic Analysis and Secure E-voting
- Gaze Tracking and Assistive Technology
- Advanced Malware Detection Techniques
- Corneal surgery and disorders
- Neuroscience and Neural Engineering
- Advanced Multi-Objective Optimization Algorithms
- Image Enhancement Techniques
- Network Packet Processing and Optimization
- Advanced Clustering Algorithms Research
- Image and Signal Denoising Methods
- Glaucoma and retinal disorders
- Vehicle License Plate Recognition
- Parallel Computing and Optimization Techniques
- Handwritten Text Recognition Techniques
- Advanced Image Processing Techniques
- Artificial Immune Systems Applications
University of Kufa
2016-2025
University of Kerbala
2022-2024
University of Warith Al-Anbiyaa
2022-2024
Universiti Tenaga Nasional
2022-2024
Imam Ja’afar Al-Sadiq University
2022-2024
Nawroz University
2023
National University of Malaysia
2020-2022
Universiti Sains Malaysia
2016-2020
American University of Kuwait
2020
Al-Balqa Applied University
2020
In this paper, a new nature-inspired human-based optimization algorithm is proposed which called coronavirus herd immunity optimizer (CHIO). The inspiration of CHIO originated from the concept as way to tackle pandemic (COVID-19). speed spreading infection depends on how infected individuals directly contact with other society members. order protect members disease, social distancing suggested by health experts. Herd state population reaches when most immune results in prevention disease...
COVID-19 is the disease evoked by a new breed of coronavirus called severe acute respiratory syndrome 2 (SARS-CoV-2). Recently, has become pandemic infecting more than 152 million people in over 216 countries and territories. The exponential increase number infections rendered traditional diagnosis techniques inefficient. Therefore, many researchers have developed several intelligent techniques, such as deep learning (DL) machine (ML), which can assist healthcare sector providing quick...
Malware is one of the most frequent cyberattacks, with its prevalence growing daily across network. traffic always asymmetrical compared to benign traffic, which symmetrical. Fortunately, there are many artificial intelligence techniques that can be used detect malware and distinguish it from normal activities. However, problem dealing large high-dimensional data has not been addressed enough. In this paper, a high-performance detection system using deep learning feature selection...
Skin cancer is one of the major types with an increasing incidence in recent decades. The source skin arises various dermatologic disorders. classified into based on texture, color, morphological features, and structure. conventional approach for identification needs time money predicted results. Currently, medical science utilizing tools digital technology classification cancer. machine learning-based robust dominant automatic methods classifying existing proposed deep neural network,...
Background. The most common and successful technique for signal denoising with nonstationary signals, such as electroencephalogram (EEG) electrocardiogram (ECG) is the wavelet transform (WT). success of WT depends on optimal configuration its control parameters which are often experimentally set. Fortunately, optimality combination these can be measured in advance by using mean squared error (MSE) function. Method. In this paper, five powerful metaheuristic algorithms proposed to find EEG...
The power scheduling problem in a smart home (PSPSH) refers to the timely operations of appliances under set restrictions and dynamic pricing scheme(s) produced by supplier company (PSC). primary objectives PSPSH are: (I) minimizing cost consumed appliances, which electricity bills, (II) balance during time horizon, particularly at peak periods, is known as peak-to-average ratio, (III) maximizing satisfaction level users. Several approaches have been proposed address optimally, including...
The Lemur Optimizer (LO) is a novel nature-inspired algorithm we propose in this paper. This algorithm’s primary inspirations are based on two pillars of lemur behavior: leap up and dance hub. These principles mathematically modeled the optimization context to handle local search, exploitation, exploration search concepts. LO first benchmarked twenty-three standard functions. Additionally, used solve three real-world problems evaluate its performance effectiveness. In direction, compared six...
Power Scheduling Problem (PSP) is a problem of schedule the smart home appliances at appropriate time period according to an electricity pricing scheme. The can be scheduled by shifting their operations from another. significant objective scheduling process reduce bill and Peak-to-average ratio (PAR) improve user comfort level. In this paper, particle swarm optimization (PSO) algorithm adapted in order handle PSP obtain optimal schedule. Smart battery (SB) formulated used work enhance...
Electroencephalogram signals (EEG) have provided biometric identification systems with great capabilities. Several studies shown that EEG introduces unique and universal features besides specific strength against spoofing attacks. Essentially, is a graphic recording of the brain's electrical activity calculated by sensors (electrodes) on scalp at different spots, but their best locations are uncertain. In this paper, channel selection problem formulated as binary optimization problem, where...
The Coronavirus herd immunity optimizer (CHIO) is a new human-based optimization algorithm that imitates the strategy to eliminate of COVID-19 disease. In this paper, coronavirus modified tackle discrete power scheduling problem in smart home (PSPSH). PSPSH combinatorial with NP-hard features. It highly constrained concerned assigning operation time for appliances based on dynamic pricing scheme(s) and several other constraints. primary objective when solving maintain stability system by...