Zahid Farooq Khan¹, Muhammad Ramzan^1,*, Mudassar Raza¹, Muhammad Attique Khan^2,3, Khalid Iqbal⁴, Taerang Kim⁵, Jae-Hyuk Cha⁵

CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 1207-1225, 2024, DOI:10.32604/cmc.2023.045491

Abstract Accurate detection and classification of artifacts within the gastrointestinal (GI) tract frames remain a significant challenge in medical image processing. Medical science combined with artificial intelligence is advancing to automate the diagnosis and treatment of numerous diseases. Key to this is the development of robust algorithms for image classification and detection, crucial in designing sophisticated systems for diagnosis and treatment. This study makes a small contribution to endoscopic image classification. The proposed approach involves multiple operations, including extracting deep features from endoscopy images using pre-trained neural networks such as Darknet-53 and Xception. Additionally, feature optimization utilizes the binary dragonfly algorithm… More >

Sangeeta Yadav¹, Preeti Gulia^1,*, Nasib Singh Gill^1,*, Piyush Kumar Shukla², Arfat Ahmad Khan³, Sultan Alharby⁴, Ahmed Alhussen⁴, Mohd Anul Haq⁵

CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 1253-1274, 2024, DOI:10.32604/cmc.2023.042869

Abstract Inpatient falls from beds in hospitals are a common problem. Such falls may result in severe injuries. This problem can be addressed by continuous monitoring of patients using cameras. Recent advancements in deep learning-based video analytics have made this task of fall detection more effective and efficient. Along with fall detection, monitoring of different activities of the patients is also of significant concern to assess the improvement in their health. High computation-intensive models are required to monitor every action of the patient precisely. This requirement limits the applicability of such networks. Hence, to keep the model lightweight, the already designed… More >

Zhou Ji¹, Mengmeng Zhou², Qiang Wang², Jiandong Huang^3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.2, pp. 1557-1582, 2024, DOI:10.32604/cmes.2023.046025

Abstract To improve the prediction accuracy of the International Roughness Index (IRI) of Jointed Plain Concrete Pavements (JPCP) and Continuously Reinforced Concrete Pavements (CRCP), a machine learning approach is developed in this study for the modelling, combining an improved Beetle Antennae Search (MBAS) algorithm and Random Forest (RF) model. The 10-fold cross-validation was applied to verify the reliability and accuracy of the model proposed in this study. The importance scores of all input variables on the IRI of JPCP and CRCP were analysed as well. The results by the comparative analysis showed the prediction accuracy of the IRI of the newly… More > Graphic Abstract

Xuechuan Wang¹, Wei He^1,*, Haoyang Feng¹, Satya N. Atluri²

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.2, pp. 1263-1294, 2024, DOI:10.32604/cmes.2023.043068

Abstract Although predictor-corrector methods have been extensively applied, they might not meet the requirements of practical applications and engineering tasks, particularly when high accuracy and efficiency are necessary. A novel class of correctors based on feedback-accelerated Picard iteration (FAPI) is proposed to further enhance computational performance. With optimal feedback terms that do not require inversion of matrices, significantly faster convergence speed and higher numerical accuracy are achieved by these correctors compared with their counterparts; however, the computational complexities are comparably low. These advantages enable nonlinear engineering problems to be solved quickly and accurately, even with rough initial guesses from elementary predictors.… More > Graphic Abstract

Chein-Shan Liu¹, Jian-Hung Shen², Chung-Lun Kuo¹, Yung-Wei Chen^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.2, pp. 1317-1335, 2024, DOI:10.32604/cmes.2023.030618

Abstract This study sets up two new merit functions, which are minimized for the detection of real eigenvalue and complex eigenvalue to address nonlinear eigenvalue problems. For each eigen-parameter the vector variable is solved from a nonhomogeneous linear system obtained by reducing the number of eigen-equation one less, where one of the nonzero components of the eigenvector is normalized to the unit and moves the column containing that component to the right-hand side as a nonzero input vector. 1D and 2D golden section search algorithms are employed to minimize the merit functions to locate real and complex eigenvalues. Simultaneously, the real… More >

Yong Qin^1,2, Xiaoyu Li^1,2, Yanhong Wu^1,2, Hai Wang³, Guiqi Han^1,2,3, Zhuyun Yan^1,2,*

Phyton-International Journal of Experimental Botany, Vol.93, No.1, pp. 119-135, 2024, DOI:10.32604/phyton.2023.046075

Abstract Root exudates serve as crucial mediators for information exchange between plants and soil, and are an important evolutionary mechanism for plants’ adaptation to environmental changes. In this study, 15 different abiotic stress models were established using various stress factors, including drought (D), high temperature (T), nitrogen deficiency (N), phosphorus deficiency (P), and their combinations. We investigated their effects on the seedling growth of Salvia miltiorrhiza Bunge and the activities of Solid-Urease (S-UE), Solid-Nitrite Reductase (S-NiR), Solid-Nitrate Reductase (S-NR), Solid-Phosphotransferase (S-PT), and Solid-Catalase (S-CAT), as well as the contents of polysaccharides in the culture medium. The results showed that the growth… More >

Bo Chen¹, Mingjun Wang², Bo Liu^3,*, Chunping Lu⁴, Guohai Jia¹, Yong Chao⁵, Chao Zhong¹

Journal of Renewable Materials, Vol.12, No.1, pp. 119-129, 2024, DOI:10.32604/jrm.2023.031521

Abstract In order to study the combustion characteristics of tar in biomass gasifier inner wall and gasification gas, “tobacco stem semi-tar inside furnace”, “tobacco stem tar inside furnace” and “tobacco stem tar out-of-furnace” were subjected to thermogravimetric experiments, and the combustion characteristics and kinetic characteristics were analyzed. The result shows that “tobacco stem semi-tar inside furnace” has the highest value and “tobacco stem tar out-of-furnace” is has the lowest value on ignition characteristics, combustion characteristics and combustible stability; “tobacco stem semi-tar inside furnace” has the lowest value and “tobacco stem tar outside furnace” has the highest value on burnout characteristics; “tobacco… More > Graphic Abstract

Yujing Ma^1,*, Leilei Chen^2,3, Haojie Lian^3,4, Zhongwang Wang^2,3

The International Conference on Computational & Experimental Engineering and Sciences, Vol.28, No.1, pp. 1-1, 2023, DOI:10.32604/icces.2023.010585

Abstract An efficient method of moments (MoM) based on polynomial chaos expansion(PCE) is applied to quickly calculate the electromagnetic scattering problems. The triangle basic functions are used to discretize the surface integral equations. The PCE is utilized to accelerate the MoM by constructing a surrogate model for univariate and bivariate analysis[1]. The mathematical expressions of the surrogate model for the radar cross-section (RCS) are established by considering uncertain parameters such as bistatic angle, incident frequency, and dielectric constant[2,3]. By using the example of a scattering cylinder with analytical solution, it is verified that the MoM accelerated by PCE presents a considerable… More >

Jiajie He^1,2, Fuzheng Liu³, Xiangyi Geng³, Xifeng Liang¹, Faye Zhang^3,*, Mingshun Jiang³

Structural Durability & Health Monitoring, Vol.18, No.1, pp. 37-54, 2024, DOI:10.32604/sdhm.2023.029428

Abstract Incomplete fault signal characteristics and ease of noise contamination are issues with the current rolling bearing early fault diagnostic methods, making it challenging to ensure the fault diagnosis accuracy and reliability. A novel approach integrating enhanced Symplectic geometry mode decomposition with cosine difference limitation and calculus operator (ESGMD-CC) and artificial fish swarm algorithm (AFSA) optimized extreme learning machine (ELM) is proposed in this paper to enhance the extraction capability of fault features and thus improve the accuracy of fault diagnosis. Firstly, SGMD decomposes the raw vibration signal into multiple Symplectic geometry components (SGCs). Secondly, the iterations are reset by the… More >

Hongzhi Xu^1,2, Jian Wang^1,3, Shuxia Li^1,*, Fengrui Zhao¹, Chengwen Wang¹, Yang Guo¹

FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.3, pp. 505-523, 2024, DOI:10.32604/fdmp.2023.030604

Abstract Natural gas hydrate (NGH) is generally produced and accumulated together with the underlying conventional gas. Therefore, optimizing the production technology of these two gases should be seen as a relevant way to effectively reduce the exploitation cost of the gas hydrate. In this study, three types of models accounting for the coexistence of these gases are considered. Type A considers the upper hydrate-bearing layer (HBL) adjacent to the lower conventional gas layer (CGL); with the Type B a permeable interlayer exists between the upper HBL and the lower CGL; with the type C there is an impermeable interlayer between the… More >