Wenbo Zhu¹, Neng Liu¹, Zhengjun Zhu^2,*, Haibing Li¹, Weijie Fu¹, Zhongbo Zhang¹, Xinghao Zhang¹

Intelligent Automation & Soft Computing, Vol.38, No.3, pp. 259-273, 2023, DOI:10.32604/iasc.2023.041860

Abstract The detection of ash content in coal slime flotation tailings using deep learning can be hindered by various factors such as foam, impurities, and changing lighting conditions that disrupt the collection of tailings images. To address this challenge, we present a method for ash content detection in coal slime flotation tailings. This method utilizes chromatographic filter paper sampling and a multi-scale residual network, which we refer to as MRCN. Initially, tailings are sampled using chromatographic filter paper to obtain static tailings images, effectively isolating interference factors at the flotation site. Subsequently, the MRCN, consisting of a multi-scale residual network, is… More >

Shulan Lei^1,2, Shujuan Wang¹, Zhuohong Zhu^1,2, Min Lu^1,2, Xinying Li^1,2, Yiming Shen³, Jing Chen^1,2,*

International Journal of Mental Health Promotion, Vol.26, No.1, pp. 61-67, 2024, DOI:10.32604/ijmhp.2023.045478

Abstract The purpose of this study was to explore the reliability and validity of the Warwick-Edinburgh Mental Well-being Scale (WEMWBS) among Chinese civil servants, thus establishing a useful tool for assessing the mental health of individuals in this occupation. The WEMWBS, Satisfaction with Life Scale (SWLS), and Depression Anxiety and Stress Scale-21 (DASS-21) were administered to a sample of 2,624 civil servants (42.860 ± 9.690 years) in a city located within Shandong Province, China. The findings revealed significant differences between groups with high and low scores on each item of the WEMWBS (t = 48.127–78.308, all p < 0.01). The item-total… More >

Siyuan Bi¹, Junfeng Yuan^1,2, Lin Luo^1,2,3,*

International Journal of Mental Health Promotion, Vol.26, No.1, pp. 51-60, 2024, DOI:10.32604/ijmhp.2023.041614

Abstract Purpose: The core component theory of addiction behavior provides a multidimensional theoretical model for measuring social networking addiction. Based on this theoretical model, the Social Networking Addiction Scale (SNAS) was developed. The aim of this study was to test the psychometric properties of the Chinese version of the SNAS (SNAS-C). Methods: This study used a sample of 3383 Chinese university students to conduct confirmatory factor analysis (CFA) to explore the structural validity of the SNAS-C. This study examined the Pearson correlations between the six subscales of the SNAS-C (i.e., salience, mood modification, tolerance, withdrawal symptoms, conflict, and relapse) and “social… More >

Zhihua Liu, Shengquan Liu^*, Jian Zhang

CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 411-433, 2024, DOI:10.32604/cmc.2023.046237

Abstract Network intrusion detection systems (NIDS) based on deep learning have continued to make significant advances. However, the following challenges remain: on the one hand, simply applying only Temporal Convolutional Networks (TCNs) can lead to models that ignore the impact of network traffic features at different scales on the detection performance. On the other hand, some intrusion detection methods consider multi-scale information of traffic data, but considering only forward network traffic information can lead to deficiencies in capturing multi-scale temporal features. To address both of these issues, we propose a hybrid Convolutional Neural Network that supports a multi-output strategy (BONUS) for… More >

Jinxian Bai, Yao Fan^*, Zhiwei Zhao, Lizhi Zheng

CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 999-1025, 2024, DOI:10.32604/cmc.2023.044612

Abstract Recently, deep learning-based image inpainting methods have made great strides in reconstructing damaged regions. However, these methods often struggle to produce satisfactory results when dealing with missing images with large holes, leading to distortions in the structure and blurring of textures. To address these problems, we combine the advantages of transformers and convolutions to propose an image inpainting method that incorporates edge priors and attention mechanisms. The proposed method aims to improve the results of inpainting large holes in images by enhancing the accuracy of structure restoration and the ability to recover texture details. This method divides the inpainting task… More >

Shigeki Kaneko¹, Naoto Mitsume², Shinobu Yoshimura^1,*

Digital Engineering and Digital Twin, Vol.2, pp. 33-48, 2024, DOI:10.32604/dedt.2023.044279

Abstract In an integrated coal gasification combined cycle plant, cooling pipes are installed in the gasifier reactor and water cooling is executed to avoid reaching an excessively high temperature. To accelerate the design, it is necessary to develop an analysis system that can simulate the cooling operation within the practical computational time. In the present study, we assumed the temperature fields of the cooled object and the cooling water to be governed by the three-dimensional (3D) heat equation and the one-dimensional (1D) convection-diffusion equation, respectively. Although some existing studies have employed similar modeling, the applications have been limited to simple-shaped structures.… More >

Yanhui Zhang¹, Lianhua Ma¹, Hailiang Su^1,2,3,*, Jirong Qin², Zhining Chen², Kaibiao Deng¹

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.2, pp. 1961-1980, 2024, DOI:10.32604/cmes.2023.045570

Abstract In this paper, to present a lightweight-developed front underrun protection device (FUPD) for heavy-duty trucks, plain weave carbon fiber reinforced plastic (CFRP) is used instead of the original high-strength steel. First, the mechanical and structural properties of plain carbon fiber composite anti-collision beams are comparatively analyzed from a multi-scale perspective. For studying the design capability of carbon fiber composite materials, we investigate the effects of TC-33 carbon fiber diameter (D), fiber yarn width (W) and height (H), and fiber yarn density (N) on the front underrun protective beam of carbon fiber composite materials. Based on the investigation, a material-structure matching… More >

Qifa Lang, Yuqiao Zheng^*, Tiancai Cui, Chenglong Shi, Heyu Zhang

Energy Engineering, Vol.121, No.2, pp. 483-498, 2024, DOI:10.32604/ee.2023.042437

Abstract This work presents a novel approach to achieve nonlinear vibration response based on the Hamilton principle. We chose the 5-MW reference wind turbine which was established by the National Renewable Energy Laboratory (NREL), to research the effects of the nonlinear flap-wise vibration characteristics. The turbine wheel is simplified by treating the blade of a wind turbine as an Euler-Bernoulli beam, and the nonlinear flap-wise vibration characteristics of the wind turbine blades are discussed based on the simplification first. Then, the blade’s large-deflection flap-wise vibration governing equation is established by considering the nonlinear term involving the centrifugal force. Lastly, it is… More >

Junhui Li¹, Haotian Zhang¹, Cuiping Li^1,*, Xingxu Zhu¹, Ruitong Liu², Fangwei Duan², Yongming Peng³

Energy Engineering, Vol.121, No.2, pp. 291-313, 2024, DOI:10.32604/ee.2023.027593

Abstract In the existing power system with a large-scale hydrogen storage system, there are problems such as low efficiency of electric-hydrogen-electricity conversion and single modeling of the hydrogen storage system. In order to improve the hydrogen utilization rate of hydrogen storage system in the process of participating in the power grid operation, and speed up the process of electric-hydrogen-electricity conversion. This article provides a detailed introduction to the mathematical and electrical models of various components of the hydrogen storage unit, and also establishes a charging and discharging efficiency model that considers the temperature and internal gas partial pressure of the hydrogen… More >

Zihao Yang¹, Shaoqi Zheng¹, Fei Han^2,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.27, No.4, pp. 1-1, 2023, DOI:10.32604/icces.2023.09250

Abstract This paper proposes a peridynamics-based statistical multiscale (PSM) framework to simulate the macroscopic structure fracture with high efficiency. The heterogeneities of composites, including the shape, spatial distribution and volume fraction of particles, are characterized within the representative volume elements (RVEs), and their impact on structure failure are extracted as two types of peridynamic parameters, namely, statistical critical stretch and equivalent micromodulus. At the microscale level, a bondbased peridynamic (BPD) model with energy-based micromodulus correction technique is introduced to simulate the fracture in RVEs, and then the computational model of statistical critical stretch is established through micromechanical analysis. Moreover, based on… More >