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  • Open Access

    ARTICLE

    Contrast Normalization Strategies in Brain Tumor Imaging: From Preprocessing to Classification

    Samar M. Alqhtani1, Toufique A. Soomro2,*, Faisal Bin Ubaid3, Ahmed Ali4, Muhammad Irfan5, Abdullah A. Asiri6

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.2, pp. 1539-1562, 2024, DOI:10.32604/cmes.2024.051475

    Abstract Cancer-related to the nervous system and brain tumors is a leading cause of mortality in various countries. Magnetic resonance imaging (MRI) and computed tomography (CT) are utilized to capture brain images. MRI plays a crucial role in the diagnosis of brain tumors and the examination of other brain disorders. Typically, manual assessment of MRI images by radiologists or experts is performed to identify brain tumors and abnormalities in the early stages for timely intervention. However, early diagnosis of brain tumors is intricate, necessitating the use of computerized methods. This research introduces an innovative approach for… More > Graphic Abstract

    Contrast Normalization Strategies in Brain Tumor Imaging: From Preprocessing to Classification

  • Open Access

    ARTICLE

    A Multiscale Reliability-Based Design Optimization Method for Carbon-Fiber-Reinforced Composite Drive Shafts

    Huile Zhang1,2,*, Shikang Li2, Yurui Wu3, Pengpeng Zhi1, Wei Wang1,4, Zhonglai Wang1,4,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.2, pp. 1975-1996, 2024, DOI:10.32604/cmes.2024.050185

    Abstract Carbon fiber composites, characterized by their high specific strength and low weight, are becoming increasingly crucial in automotive lightweighting. However, current research primarily emphasizes layer count and orientation, often neglecting the potential of microstructural design, constraints in the layup process, and performance reliability. This study, therefore, introduces a multiscale reliability-based design optimization method for carbon fiber-reinforced plastic (CFRP) drive shafts. Initially, parametric modeling of the microscale cell was performed, and its elastic performance parameters were predicted using two homogenization methods, examining the impact of fluctuations in microscale cell parameters on composite material performance. A finite… More >

  • Open Access

    ARTICLE

    Highly Differentiated Target Detection under Extremely Low-Light Conditions Based on Improved YOLOX Model

    Haijian Shao1,2,*, Suqin Lei1, Chenxu Yan3, Xing Deng1, Yunsong Qi1

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.2, pp. 1507-1537, 2024, DOI:10.32604/cmes.2024.050140

    Abstract This paper expounds upon a novel target detection methodology distinguished by its elevated discriminatory efficacy, specifically tailored for environments characterized by markedly low luminance levels. Conventional methodologies struggle with the challenges posed by luminosity fluctuations, especially in settings characterized by diminished radiance, further exacerbated by the utilization of suboptimal imaging instrumentation. The envisioned approach mandates a departure from the conventional YOLOX model, which exhibits inadequacies in mitigating these challenges. To enhance the efficacy of this approach in low-light conditions, the dehazing algorithm undergoes refinement, effecting a discerning regulation of the transmission rate at the pixel… More > Graphic Abstract

    Highly Differentiated Target Detection under Extremely Low-Light Conditions Based on Improved YOLOX Model

  • Open Access

    ARTICLE

    Numerical Analysis of Perforation during Hydraulic Fracture Initiation Based on Continuous–Discontinuous Element Method

    Rui Zhang1, Lixiang Wang2,*, Jing Li1,4, Chun Feng2, Yiming Zhang1,3,4,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.2, pp. 2103-2129, 2024, DOI:10.32604/cmes.2024.049885

    Abstract Perforation is a pivotal technique employed to establish main flow channels within the reservoir formation at the outset of hydraulic fracturing operations. Optimizing perforation designs is critical for augmenting the efficacy of hydraulic fracturing and boosting oil or gas production. In this study, we employ a hybrid finite-discrete element method, known as the continuous–discontinuous element method (CDEM), to simulate the initiation of post-perforation hydraulic fractures and to derive enhanced design parameters. The model incorporates the four most prevalent perforation geometries, as delineated in an engineering technical report. Real-world perforations deviate from the ideal cylindrical shape, More >

  • Open Access

    ARTICLE

    Design and Performance Analysis of HMDV Dynamic Inertial Suspension Based on Active Disturbance Rejection Control

    Xiaofeng Yang1,3,4, Wei Wang1,3,4,*, Yujie Shen2,4, Changning Liu1,3,4, Tianyi Zhang1,4

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.2, pp. 1485-1506, 2024, DOI:10.32604/cmes.2024.049837

    Abstract This paper addresses the impact of vertical vibration negative effects, unbalanced radial forces generated by the static eccentricity of the hub motor, and road excitation on the suspension performance of Hub Motor Driven Vehicle (HMDV). A dynamic inertial suspension based on Active Disturbance Rejection Control (ADRC) is proposed, combining the vertical dynamic characteristics of dynamic inertial suspension with the features of ADRC, which distinguishes between internal and external disturbances and arranges the transition process. Firstly, a simulation model of the static eccentricity of the hub motor is established to simulate the unbalanced radial electromagnetic force… More > Graphic Abstract

    Design and Performance Analysis of HMDV Dynamic Inertial Suspension Based on Active Disturbance Rejection Control

  • Open Access

    ARTICLE

    A Planning Method for Operational Test of UAV Swarm Based on Mission Reliability

    Jingyu Wang1, Ping Jiang1,*, Jianjun Qi2

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.2, pp. 1889-1918, 2024, DOI:10.32604/cmes.2024.049813

    Abstract The unmanned aerial vehicle (UAV) swarm plays an increasingly important role in the modern battlefield, and the UAV swarm operational test is a vital means to validate the combat effectiveness of the UAV swarm. Due to the high cost and long duration of operational tests, it is essential to plan the test in advance. To solve the problem of planning UAV swarm operational test, this study considers the multi-stage feature of a UAV swarm mission, composed of launch, flight and combat stages, and proposes a method to find test plans that can maximize mission reliability.… More >

  • Open Access

    ARTICLE

    Energy-Saving Distributed Flexible Job Shop Scheduling Optimization with Dual Resource Constraints Based on Integrated Q-Learning Multi-Objective Grey Wolf Optimizer

    Hongliang Zhang1,2, Yi Chen1, Yuteng Zhang1, Gongjie Xu3,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.2, pp. 1459-1483, 2024, DOI:10.32604/cmes.2024.049756

    Abstract The distributed flexible job shop scheduling problem (DFJSP) has attracted great attention with the growth of the global manufacturing industry. General DFJSP research only considers machine constraints and ignores worker constraints. As one critical factor of production, effective utilization of worker resources can increase productivity. Meanwhile, energy consumption is a growing concern due to the increasingly serious environmental issues. Therefore, the distributed flexible job shop scheduling problem with dual resource constraints (DFJSP-DRC) for minimizing makespan and total energy consumption is studied in this paper. To solve the problem, we present a multi-objective mathematical model for… More >

  • Open Access

    ARTICLE

    Hybrid Strategy of Partitioned and Monolithic Methods for Solving Strongly Coupled Analysis of Inverse and Direct Piezoelectric and Circuit Coupling

    Daisuke Ishihara*, Syunnosuke Nozaki, Tomoya Niho, Naoto Takayama

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.2, pp. 1371-1386, 2024, DOI:10.32604/cmes.2024.049694

    Abstract The inverse and direct piezoelectric and circuit coupling are widely observed in advanced electro-mechanical systems such as piezoelectric energy harvesters. Existing strongly coupled analysis methods based on direct numerical modeling for this phenomenon can be classified into partitioned or monolithic formulations. Each formulation has its advantages and disadvantages, and the choice depends on the characteristics of each coupled problem. This study proposes a new option: a coupled analysis strategy that combines the best features of the existing formulations, namely, the hybrid partitioned-monolithic method. The analysis of inverse piezoelectricity and the monolithic analysis of direct piezoelectric More >

  • Open Access

    ARTICLE

    Sleep Posture Classification Using RGB and Thermal Cameras Based on Deep Learning Model

    Awais Khan1, Chomyong Kim2, Jung-Yeon Kim2, Ahsan Aziz1, Yunyoung Nam3,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.2, pp. 1729-1755, 2024, DOI:10.32604/cmes.2024.049618

    Abstract Sleep posture surveillance is crucial for patient comfort, yet current systems face difficulties in providing comprehensive studies due to the obstruction caused by blankets. Precise posture assessment remains challenging because of the complex nature of the human body and variations in sleep patterns. Consequently, this study introduces an innovative method utilizing RGB and thermal cameras for comprehensive posture classification, thereby enhancing the analysis of body position and comfort. This method begins by capturing a dataset of sleep postures in the form of videos using RGB and thermal cameras, which depict six commonly adopted postures: supine,… More > Graphic Abstract

    Sleep Posture Classification Using RGB and Thermal Cameras Based on Deep Learning Model

  • Open Access

    ARTICLE

    Predicting the Mechanical Behavior of a Bioinspired Nanocomposite through Machine Learning

    Xingzi Yang1, Wei Gao2, Xiaodu Wang1, Xiaowei Zeng1,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.2, pp. 1299-1313, 2024, DOI:10.32604/cmes.2024.049371

    Abstract The bioinspired nacre or bone structure represents a remarkable example of tough, strong, lightweight, and multifunctional structures in biological materials that can be an inspiration to design bioinspired high-performance materials. The bioinspired structure consists of hard grains and soft material interfaces. While the material interface has a very low volume percentage, its property has the ability to determine the bulk material response. Machine learning technology nowadays is widely used in material science. A machine learning model was utilized to predict the material response based on the material interface properties in a bioinspired nanocomposite. This model More >

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