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  • Open Access

    ARTICLE

    A New Method for Diagnosis of Leukemia Utilizing a Hybrid DL-ML Approach for Binary and Multi-Class Classification on a Limited-Sized Database

    Nilkanth Mukund Deshpande1,2, Shilpa Gite3,4,*, Biswajeet Pradhan5,6, Abdullah Alamri7, Chang-Wook Lee8,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.1, pp. 593-631, 2024, DOI:10.32604/cmes.2023.030704

    Abstract Infection of leukemia in humans causes many complications in its later stages. It impairs bone marrow’s ability to produce blood. Morphological diagnosis of human blood cells is a well-known and well-proven technique for diagnosis in this case. The binary classification is employed to distinguish between normal and leukemia-infected cells. In addition, various subtypes of leukemia require different treatments. These sub-classes must also be detected to obtain an accurate diagnosis of the type of leukemia. This entails using multi-class classification to determine the leukemia subtype. This is usually done using a microscopic examination of these blood cells. Due to the requirement… More > Graphic Abstract

    A New Method for Diagnosis of Leukemia Utilizing a Hybrid DL-ML Approach for Binary and Multi-Class Classification on a Limited-Sized Database

  • Open Access

    ARTICLE

    Integration of Digital Twins and Artificial Intelligence for Classifying Cardiac Ischemia

    Mohamed Ammar1,*, Hamed Al-Raweshidy2,*

    Journal on Artificial Intelligence, Vol.5, pp. 195-218, 2023, DOI:10.32604/jai.2023.045199

    Abstract Despite advances in intelligent medical care, difficulties remain. Due to its complicated governance, designing, planning, improving, and managing the cardiac system remains difficult. Oversight, including intelligent monitoring, feedback systems, and management practises, is unsuccessful. Current platforms cannot deliver lifelong personal health management services. Insufficient accuracy in patient crisis warning programmes. No frequent, direct interaction between healthcare workers and patients is visible. Physical medical systems and intelligent information systems are not integrated. This study introduces the Advanced Cardiac Twin (ACT) model integrated with Artificial Neural Network (ANN) to handle real-time monitoring, decision-making, and crisis prediction. THINGSPEAK is used to create an… More >

  • Open Access

    ARTICLE

    Hybrid Algorithm-Driven Smart Logistics Optimization in IoT-Based Cyber-Physical Systems

    Abdulwahab Ali Almazroi1,*, Nasir Ayub2

    CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 3921-3942, 2023, DOI:10.32604/cmc.2023.046602

    Abstract Effectively managing complex logistics data is essential for development sustainability and growth, especially in optimizing distribution routes. This article addresses the limitations of current logistics path optimization methods, such as inefficiencies and high operational costs. To overcome these drawbacks, we introduce the Hybrid Firefly-Spotted Hyena Optimization (HFSHO) algorithm, a novel approach that combines the rapid exploration and global search abilities of the Firefly Algorithm (FO) with the localized search and region-exploitation skills of the Spotted Hyena Optimization Algorithm (SHO). HFSHO aims to improve logistics path optimization and reduce operational costs. The algorithm’s effectiveness is systematically assessed through rigorous comparative analyses… More >

  • Open Access

    ARTICLE

    An Improved Multi-Objective Hybrid Genetic-Simulated Annealing Algorithm for AGV Scheduling under Composite Operation Mode

    Jiamin Xiang1, Ying Zhang1, Xiaohua Cao1,*, Zhigang Zhou2

    CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 3443-3466, 2023, DOI:10.32604/cmc.2023.045120

    Abstract This paper presents an improved hybrid algorithm and a multi-objective model to tackle the scheduling problem of multiple Automated Guided Vehicles (AGVs) under the composite operation mode. The multi-objective model aims to minimize the maximum completion time, the total distance covered by AGVs, and the distance traveled while empty-loaded. The improved hybrid algorithm combines the improved genetic algorithm (GA) and the simulated annealing algorithm (SA) to strengthen the local search ability of the algorithm and improve the stability of the calculation results. Based on the characteristics of the composite operation mode, the authors introduce the combined coding and parallel decoding… More >

  • Open Access

    ARTICLE

    SCChOA: Hybrid Sine-Cosine Chimp Optimization Algorithm for Feature Selection

    Shanshan Wang1,2,3, Quan Yuan1, Weiwei Tan1, Tengfei Yang1, Liang Zeng1,2,3,*

    CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 3057-3075, 2023, DOI:10.32604/cmc.2023.044807

    Abstract Feature Selection (FS) is an important problem that involves selecting the most informative subset of features from a dataset to improve classification accuracy. However, due to the high dimensionality and complexity of the dataset, most optimization algorithms for feature selection suffer from a balance issue during the search process. Therefore, the present paper proposes a hybrid Sine-Cosine Chimp Optimization Algorithm (SCChOA) to address the feature selection problem. In this approach, firstly, a multi-cycle iterative strategy is designed to better combine the Sine-Cosine Algorithm (SCA) and the Chimp Optimization Algorithm (ChOA), enabling a more effective search in the objective space. Secondly,… More >

  • Open Access

    ARTICLE

    Blockchain-Based Cognitive Computing Model for Data Security on a Cloud Platform

    Xiangmin Guo1,2, Guangjun Liang1,2,*, Jiayin Liu1,2, Xianyi Chen3,*

    CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 3305-3323, 2023, DOI:10.32604/cmc.2023.044529

    Abstract Cloud storage is widely used by large companies to store vast amounts of data and files, offering flexibility, financial savings, and security. However, information shoplifting poses significant threats, potentially leading to poor performance and privacy breaches. Blockchain-based cognitive computing can help protect and maintain information security and privacy in cloud platforms, ensuring businesses can focus on business development. To ensure data security in cloud platforms, this research proposed a blockchain-based Hybridized Data Driven Cognitive Computing (HD2C) model. However, the proposed HD2C framework addresses breaches of the privacy information of mixed participants of the Internet of Things (IoT) in the cloud.… More >

  • Open Access

    ARTICLE

    Reliability-Based Model for Incomplete Preventive Replacement Maintenance of Photovoltaic Power Systems

    Wei Chen, Ming Li*, Tingting Pei, Cunyu Sun, Huan Lei

    Energy Engineering, Vol.121, No.1, pp. 125-144, 2024, DOI:10.32604/ee.2023.042812

    Abstract At present, the operation and maintenance of photovoltaic power generation systems mainly comprise regular maintenance, breakdown maintenance, and condition-based maintenance, which is very likely to lead to over- or under-repair of equipment. Therefore, a preventive maintenance and replacement strategy for PV power generation systems based on reliability as a constraint is proposed. First, a hybrid failure function with a decreasing service age factor and an increasing failure rate factor is introduced to describe the deterioration of PV power generation equipment, and the equipment is replaced when its reliability drops to the replacement threshold in the last cycle. Then, based on… More >

  • Open Access

    ARTICLE

    A Hybrid Classification and Identification of Pneumonia Using African Buffalo Optimization and CNN from Chest X-Ray Images

    Nasser Alalwan1,*, Ahmed I. Taloba2, Amr Abozeid3, Ahmed Ibrahim Alzahrani1, Ali H. Al-Bayatti4

    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2497-2517, 2024, DOI:10.32604/cmes.2023.029910

    Abstract An illness known as pneumonia causes inflammation in the lungs. Since there is so much information available from various X-ray images, diagnosing pneumonia has typically proven challenging. To improve image quality and speed up the diagnosis of pneumonia, numerous approaches have been devised. To date, several methods have been employed to identify pneumonia. The Convolutional Neural Network (CNN) has achieved outstanding success in identifying and diagnosing diseases in the fields of medicine and radiology. However, these methods are complex, inefficient, and imprecise to analyze a big number of datasets. In this paper, a new hybrid method for the automatic classification… More >

  • Open Access

    ARTICLE

    New Antenna Array Beamforming Techniques Based on Hybrid Convolution/Genetic Algorithm for 5G and Beyond Communications

    Shimaa M. Amer1, Ashraf A. M. Khalaf2, Amr H. Hussein3,4, Salman A. Alqahtani5, Mostafa H. Dahshan6, Hossam M. Kassem3,4,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2749-2767, 2024, DOI:10.32604/cmes.2023.029138

    Abstract Side lobe level reduction (SLL) of antenna arrays significantly enhances the signal-to-interference ratio and improves the quality of service (QOS) in recent and future wireless communication systems starting from 5G up to 7G. Furthermore, it improves the array gain and directivity, increasing the detection range and angular resolution of radar systems. This study proposes two highly efficient SLL reduction techniques. These techniques are based on the hybridization between either the single convolution or the double convolution algorithms and the genetic algorithm (GA) to develop the Conv/GA and DConv/GA, respectively. The convolution process determines the element’s excitations while the GA optimizes… More >

  • Open Access

    ARTICLE

    MHD (SWCNTS + MWCNTS)/H2O-Based Williamson Hybrid Nanouids Flow Past Exponential Shrinking Sheet in Porous Medium

    Hamzeh Taha Alkasasbeh1,*, Muhammad Khairul Anuar Mohamed2

    Frontiers in Heat and Mass Transfer, Vol.21, pp. 265-279, 2023, DOI:10.32604/fhmt.2023.041539

    Abstract The present study numerically investigates the flow and heat transfer of porous Williamson hybrid nanofluid on an exponentially shrinking sheet with magnetohydrodynamic (MHD) effects. The nonlinear partial differential equations which governed the model are first reduced to a set of ordinary differential equations by using the similarity transformation. Next, the BVP4C solver is applied to solve the equations by considering the pertinent fluid parameters such as the permeability parameter, the magnetic parameter, the Williamson parameter, the nanoparticle volume fractions and the wall mass transfer parameter. The single (SWCNTs) and multi-walled carbon nanotubes (MWCNTs) nanoparticles are taken as the hybrid nanoparticles.… More >

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