Qixiang Tong, Zhipeng Zhu, Min Zhang, Kerui Cao, Haihua Xing^*

CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 1353-1375, 2024, DOI:10.32604/cmc.2024.049187

Abstract High-resolution remote sensing image segmentation is a challenging task. In urban remote sensing, the presence of occlusions and shadows often results in blurred or invisible object boundaries, thereby increasing the difficulty of segmentation. In this paper, an improved network with a cross-region self-attention mechanism for multi-scale features based on DeepLabv3+ is designed to address the difficulties of small object segmentation and blurred target edge segmentation. First, we use CrossFormer as the backbone feature extraction network to achieve the interaction between large- and small-scale features, and establish self-attention associations between features at both large and small scales to capture global contextual… More >

Yakui Liu^1,2,3,*, Xing Jiang¹, Ruikang Xu¹, Yihao Cui¹, Chenhui Yu¹, Jingqi Yang¹, Jishuai Zhou¹

CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 1263-1279, 2024, DOI:10.32604/cmc.2024.048864

Abstract The rapid pace of urban development has resulted in the widespread presence of construction equipment and increasingly complex conditions in transmission corridors. These conditions pose a serious threat to the safe operation of the power grid. Machine vision technology, particularly object recognition technology, has been widely employed to identify foreign objects in transmission line images. Despite its wide application, the technique faces limitations due to the complex environmental background and other auxiliary factors. To address these challenges, this study introduces an improved YOLOv8n. The traditional stepwise convolution and pooling layers are replaced with a spatial-depth convolution (SPD-Conv) module, aiming to… More >

Jingyi Mao, Yuchen Zhou, Yifan Wang, Junyu Li, Ziqing Liu, Fanliang Bu^*

CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 837-855, 2024, DOI:10.32604/cmc.2024.048703

Abstract Voice portrait technology has explored and established the relationship between speakers’ voices and their facial features, aiming to generate corresponding facial characteristics by providing the voice of an unknown speaker. Due to its powerful advantages in image generation, Generative Adversarial Networks (GANs) have now been widely applied across various fields. The existing Voice2Face methods for voice portraits are primarily based on GANs trained on voice-face paired datasets. However, voice portrait models solely constructed on GANs face limitations in image generation quality and struggle to maintain facial similarity. Additionally, the training process is relatively unstable, thereby affecting the overall generative performance… More >

Chengzhang Zhu^1,2, Renmao Zhang¹, Yalong Xiao^1,2,*, Beiji Zou¹, Xian Chai¹, Zhangzheng Yang¹, Rong Hu³, Xuanchu Duan⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 1103-1128, 2024, DOI:10.32604/cmes.2024.048453

Abstract Automatic segmentation of medical images provides a reliable scientific basis for disease diagnosis and analysis. Notably, most existing methods that combine the strengths of convolutional neural networks (CNNs) and Transformers have made significant progress. However, there are some limitations in the current integration of CNN and Transformer technology in two key aspects. Firstly, most methods either overlook or fail to fully incorporate the complementary nature between local and global features. Secondly, the significance of integrating the multi-scale encoder features from the dual-branch network to enhance the decoding features is often disregarded in methods that combine CNN and Transformer. To address… More >

Zhong Qu^1,*, Guoqing Mu¹, Bin Yuan²

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 255-273, 2024, DOI:10.32604/cmes.2024.048175

Abstract Automatic crack detection of cement pavement chiefly benefits from the rapid development of deep learning, with convolutional neural networks (CNN) playing an important role in this field. However, as the performance of crack detection in cement pavement improves, the depth and width of the network structure are significantly increased, which necessitates more computing power and storage space. This limitation hampers the practical implementation of crack detection models on various platforms, particularly portable devices like small mobile devices. To solve these problems, we propose a dual-encoder-based network architecture that focuses on extracting more comprehensive fracture feature information and combines cross-fusion modules… More > Graphic Abstract

Zun-Di Huang¹, Zhen-Bin Zhou^1,2,3, Ning Chang¹, Zheng-Wei Chen^2,3,*, Su-Mei Wang^2,3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 975-996, 2024, DOI:10.32604/cmes.2024.047664

Abstract The safety and stability of high-speed maglev trains traveling on viaducts in crosswinds critically depend on their aerodynamic characteristics. Therefore, this paper uses an improved delayed detached eddy simulation (IDDES) method to investigate the aerodynamic features of high-speed maglev trains with different marshaling lengths under crosswinds. The effects of marshaling lengths (varying from 3-car to 8-car groups) on the train’s aerodynamic performance, surface pressure, and the flow field surrounding the train were investigated using the three-dimensional unsteady compressible Navier-Stokes (N-S) equations. The results showed that the marshaling lengths had minimal influence on the aerodynamic performance of the head and middle… More > Graphic Abstract

Zhuo Huang, Ye Tian, Yifan Zhang, Tielin Shi, Qi Xia^*

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 711-733, 2024, DOI:10.32604/cmes.2024.045411

Abstract Stiffened structures have great potential for improving mechanical performance, and the study of their stability is of great interest. In this paper, the optimization of the critical buckling load factor for curved grid stiffeners is solved by using the level set based density method, where the shape and cross section (including thickness and width) of the stiffeners can be optimized simultaneously. The grid stiffeners are a combination of many single stiffeners which are projected by the corresponding level set functions. The thickness and width of each stiffener are designed to be independent variables in the projection applied to each level… More >

Liting Jia¹, Xiao Han¹, Cuixia Qiao², Gang Zhao², Yanzhi Xia¹, Zhixin Xue^1,*

Journal of Renewable Materials, Vol.12, No.3, pp. 427-441, 2024, DOI:10.32604/jrm.2023.044310

Abstract Ba²⁺ pre-crosslinked carrageenan fiber (Ba/CAF) was prepared by adding a small amount of Ba²⁺ to the carrageenan (CA) solution as the spinning solution. Ba/CAF-n/A, Ba/CAF-n/B and Ba/CAF-n/C were prepared with ethanol solution (combine A), high concentration BaCl₂ solution (combine B) and low concentration BaCl₂ solution (combine C), as coagulation bath and stretch bath, respectively. The combination of coagulation bath and stretch bath suitable for Ba²⁺ pre-crosslinking wet spinning was screened. The results showed that Ba²⁺ can induce the birefringence of the CA molecular chain, and the Ba²⁺ pre-crosslinking effect is the best when the CA mass fraction is 8.0 wt%.… More > Graphic Abstract

Feng Sheng^1,*, Chen Kong², Chao Li³

International Journal of Mental Health Promotion, Vol.26, No.3, pp. 221-228, 2024, DOI:10.32604/ijmhp.2024.030209

Abstract Objective: This study was conducted to explore the relationships among sedentary behavior (SB), electronic product addiction (EPA), and depression (D) in adolescents during the COVID-19 epidemic. Methods: A total of 604 adolescents (including 309 girls and 295 boys aged 12–18) were selected from Qufu City, Shandong Province, China for three rounds of investigation. The model was constructed using AMOS 23.0 software, and cross-lagged analysis was conducted. Results: SB at T1 can significantly positively predict SB and EPA at T2 (p < 0.05). EPA at T1 can significantly positively predict SB and D at T2 (p < 0.05). Physical activity level… More >

R. VENKATESAN^*, S. R. DARSON IMMANUEL JOHN, N. RAJESWARI

Journal of Polymer Materials, Vol.36, No.3, pp. 261-273, 2019, DOI:10.32381/JPM.2019.36.03.6

Abstract Nanocomposite films of chitosan (CH) incorporated with different wt. % of the polyoligomericsilsesquioxane (POSS) were prepared by solution casting. The thermal, mechanical, morphological and antimicrobial properties of the nanocomposites were examined. TGA analyses of the nanocomposites indicate that the filler enables the enhancement of thermal stability of chitosan. The tensile strength of the nanocomposite films is enhanced (10.9 MPa for neat chitosan to 24.0MPa for 5wt. % filled chitosan) by the addition of POSS while the elongation at break is reduced. The nanocomposite films exhibited excellent antimicrobial activity against both gram positive and gram negative bacteria. This activity increases with… More >