Min Yao^1,*, Guangjie Hu¹, Yaozu Zhang²

CMC-Computers, Materials & Continua, Vol.83, No.2, pp. 2751-2771, 2025, DOI:10.32604/cmc.2025.060860 - 16 April 2025

Abstract Semantic segmentation of remote sensing images is a critical research area in the field of remote sensing. Despite the success of Convolutional Neural Networks (CNNs), they often fail to capture inter-layer feature relationships and fully leverage contextual information, leading to the loss of important details. Additionally, due to significant intra-class variation and small inter-class differences in remote sensing images, CNNs may experience class confusion. To address these issues, we propose a novel Category-Guided Feature Collaborative Learning Network (CG-FCLNet), which enables fine-grained feature extraction and adaptive fusion. Specifically, we design a Feature Collaborative Learning Module (FCLM)… More >

Wanqing Yuan¹, Huiying Xie¹, Can Huang², Xiaoliang Wang^1,3,*, Qingquan Liu^1,*

CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.2, pp. 2045-2066, 2025, DOI:10.32604/cmes.2025.058977 - 27 January 2025

Abstract Landing spacecraft experience significant impact forces during landing, resulting in large deformation and failure in the soil surface, which severely affects landing safety and stability. This paper establishes a smoothed particle hydrodynamics (SPH) model based on the theory of soil elastoplastic constitutive relations to describe the process of a lander’s footpad impacting lunar regolith vertically. The model can provide engineering indices such as impact load and penetration depth, and illustrate the large deformation and crater characteristics of the regolith. A detailed analysis of the response of the footpad and lunar regolith during landing reveals that… More > Graphic Abstract

Ghaliah Alhamzi¹, Badr Saad T. Alkahtani², Ravi Shanker Dubey³, Mati ur Rahman^4,5,*

CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.1, pp. 609-633, 2025, DOI:10.32604/cmes.2024.056604 - 17 December 2024

Abstract This study directs the discussion of HIV disease with a novel kind of complex dynamical generalized and piecewise operator in the sense of classical and Atangana Baleanu (AB) derivatives having arbitrary order. The HIV infection model has a susceptible class, a recovered class, along with a case of infection divided into three sub-different levels or categories and the recovered class. The total time interval is converted into two, which are further investigated for ordinary and fractional order operators of the AB derivative, respectively. The proposed model is tested separately for unique solutions and existence on… More >

Tianfei Yang¹, Xianyi Long^2,*

International Journal of Mental Health Promotion, Vol.26, No.9, pp. 719-730, 2024, DOI:10.32604/ijmhp.2024.053705 - 20 September 2024

Abstract Background: Though the COVID-19 pandemic recedes, and our society gradually returns to normal, Chinese people’s work and lifestyles are still influenced by the “pandemic aftermath”. In the post-pandemic era, employees may feel uncertainty at work due to the changed organizational operations and management and perceive the external environment to be more dynamic. Both these perceptions may increase employees’ negative emotions and contribute to conflicts between work and life. Drawing from the ego depletion theory, this study aimed to examine the impact of job insecurity during the post-pandemic era on employees’ work-life conflicts, and the mediating… More >

Redžo Hasanagić^1,*, Umejr Šljivo¹, Leila Fathi², Pallavi Gautam³, Mohsen Bahmani^2,*, Miha Humar⁴

Journal of Renewable Materials, Vol.12, No.8, pp. 1417-1431, 2024, DOI:10.32604/jrm.2024.052826 - 06 September 2024

Abstract This study investigated the mechanical properties of beech (Fagus sylvatica L.) and fir (Abies alba) wood from Bosnia and Herzegovina under outdoor exposure. Samples were exposed for 3-month exposure to assess bending strength, color changes, and surface quality. Results showed outdoor exposure negatively affected mechanical properties, particularly in samples with extended finger joints, causing significant surface cracks in uncoated samples. Beech wood exhibited notable color changes under exposure, with approximately 50% darkening without coating compared to 25% under covered conditions. Coated samples displayed minimal color changes, affirming the efficacy of surface treatment. Fir wood exhibited a roughness More > Graphic Abstract

Cassandra Patinet^*

Psycho-Oncologie, Vol.18, No.2, pp. 87-93, 2024, DOI:10.32604/po.2024.049526 - 06 August 2024

Abstract Cet article vise à éclairer les enjeux de continuité et de reprise du dialogue interdisciplinaire entre médecins et psychologues d’orientation psychanalytique sur le terrain de la recherche, après que cette collaboration se soit institutionnalisée et pérennisée sur le plan institutionnel. A partir de la mise en regard de deux dispositifs de recherche se situant dans le prolongement l’un de l’autre sur un même terrain de recherche, nous questionnerons les modalités de négociation du dialogue interdisciplinaire et les voies par lesquelles il se manifeste sur le terrain de la recherche, médié par la rencontre entre soignants More >

G. Sunil Santhosh Kumar^1,2,*, M. Rudra Kumar³

CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 695-713, 2024, DOI:10.32604/cmc.2024.050143 - 18 July 2024

Abstract This article presents an innovative approach to automatic rule discovery for data transformation tasks leveraging XGBoost, a machine learning algorithm renowned for its efficiency and performance. The framework proposed herein utilizes the fusion of diversified feature formats, specifically, metadata, textual, and pattern features. The goal is to enhance the system’s ability to discern and generalize transformation rules from source to destination formats in varied contexts. Firstly, the article delves into the methodology for extracting these distinct features from raw data and the pre-processing steps undertaken to prepare the data for the model. Subsequent sections expound… More >

Aigerim Baimakhanova^1,*, Ainur Zhumadillayeva², Bigul Mukhametzhanova³, Natalya Glazyrina², Rozamgul Niyazova², Nurseit Zhunissov¹, Aizhan Sambetbayeva⁴

Computer Systems Science and Engineering, Vol.48, No.3, pp. 793-811, 2024, DOI:10.32604/csse.2024.043273 - 20 May 2024

Abstract As digital technologies have advanced more rapidly, the number of paper documents recently converted into a digital format has exponentially increased. To respond to the urgent need to categorize the growing number of digitized documents, the classification of digitized documents in real time has been identified as the primary goal of our study. A paper classification is the first stage in automating document control and efficient knowledge discovery with no or little human involvement. Artificial intelligence methods such as Deep Learning are now combined with segmentation to study and interpret those traits, which were not… More >

Cyril Enault^*

Revue Internationale de Géomatique, Vol.33, pp. 77-92, 2024, DOI:10.32604/rig.2024.046591 - 18 April 2024

Abstract La théorie égocentrée est aujourd’hui bien connue des éthologues et des psychologues mais moins diffusée chez les géographes car elle reste encore à l’état de théorie abstraite. Ce papier se propose dans un premier temps de rendre opérationnel cette approche dans le cadre de travaux géographiques à l’échelle de l’individu. Puis, elle envisage d’établir le lien entre l’échelle individu et l’échelle de la ville avec comme objectif de produire des cartes déformées de la ville. More > Graphic Abstract

Yuming Tang^1,#, Yitian Zhang^2,#, Tao Niu¹, Zhen Li^2,3,*, Zijian Zhang^1,3, Huaping Chen⁴, Long Zhang⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 2451-2477, 2024, DOI:10.32604/cmes.2024.030084 - 11 March 2024

Abstract Federated Learning (FL), as an emergent paradigm in privacy-preserving machine learning, has garnered significant interest from scholars and engineers across both academic and industrial spheres. Despite its innovative approach to model training across distributed networks, FL has its vulnerabilities; the centralized server-client architecture introduces risks of single-point failures. Moreover, the integrity of the global model—a cornerstone of FL—is susceptible to compromise through poisoning attacks by malicious actors. Such attacks and the potential for privacy leakage via inference starkly undermine FL’s foundational privacy and security goals. For these reasons, some participants unwilling use their private data… More >