Tianyi Li^1,2, Xin Gu², Qing Zhang^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 339-361, 2024, DOI:10.32604/cmes.2024.047566 - 16 April 2024

Abstract This study proposes a comprehensive, coupled thermomechanical model that replaces local spatial derivatives in classical differential thermomechanical equations with nonlocal integral forms derived from the peridynamic differential operator (PDDO), eliminating the need for calibration procedures. The model employs a multi-rate explicit time integration scheme to handle varying time scales in multi-physics systems. Through simulations conducted on granite and ceramic materials, this model demonstrates its effectiveness. It successfully simulates thermal damage behavior in granite arising from incompatible mineral expansion and accurately calculates thermal crack propagation in ceramic slabs during quenching. To account for material heterogeneity, the More >

Chengkan Xu^1,2,4, Xiaofei Wang³, Yixuan Li², Guannan Wang^2,*, He Zhang^2,4,*

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 957-974, 2024, DOI:10.32604/cmes.2024.047327 - 16 April 2024

Abstract Structural damage in heterogeneous materials typically originates from microstructures where stress concentration occurs. Therefore, evaluating the magnitude and location of localized stress distributions within microstructures under external loading is crucial. Repeating unit cells (RUCs) are commonly used to represent microstructural details and homogenize the effective response of composites. This work develops a machine learning-based micromechanics tool to accurately predict the stress distributions of extracted RUCs. The locally exact homogenization theory efficiently generates the microstructural stresses of RUCs with a wide range of parameters, including volume fraction, fiber/matrix property ratio, fiber shapes, and loading direction. Subsequently, More > Graphic Abstract

Inga Zotova^1,*, Edgars Kirilovs¹, Laura Ziemele²

Journal of Renewable Materials, Vol.12, No.3, pp. 603-613, 2024, DOI:10.32604/jrm.2024.047607 - 11 April 2024

Abstract Nowadays buildings contain innovative materials, materials from local resources, production surpluses and rapidly renewable natural resources. Phase Change Materials (PCM) are one such group of novel materials which reduce building energy consumption. With the wider availability of microencapsulated PCM, there is an opportunity to develop a new type of insulating materials, combinate PCM with traditional insulation materials for latent heat energy storage. These materials are typically flammable and are located on the interior wall finishing yet there has been no detailed assessment of their fire performance. In this research work prototypes of low-density insulating boards… More > Graphic Abstract

Verônica Távilla Ferreira Silva, Adriane Maria Ferreira Milagres^*

Journal of Renewable Materials, Vol.12, No.3, pp. 539-551, 2024, DOI:10.32604/jrm.2023.045726 - 11 April 2024

Abstract This study was conducted to evaluate the effectiveness of enzymes in purifying and reducing the degree of polymerization of cellulose for the production of dissolving pulp. Our goal was to determine the contributions of xylanase (X) and endoglucanase (EG) in the treatment of pulp, specifically by quantifying the formation of soluble and insoluble reducing sugars using the dinitrosalycilic acid (DNS) test. Predominantly, the release of soluble reducing sugars (RSSol) was enhanced after xylanase treatment, while endoglucanase (EG) treatment led to changes in insoluble reducing sugars (RSIns). The maximum synergism was observed for RSIns when a… More > Graphic Abstract

Moumouni Sidibé^1,2,*, Augustin K. N. Aoudji¹, Yaya Issifou Moumouni^3,*, Issa Sacko⁴, Idelphonse Saliou¹, Bourema Koné², Achille Ephrem Assogbadjo⁵, Afio Zannou¹

Revue Internationale de Géomatique, Vol.33, pp. 51-76, 2024, DOI:10.32604/rig.2024.045505 - 05 April 2024

Abstract La dynamique d’occupation des terres constitue un préalable pour l’identification des contraintes de gestion des ressources naturelles, l’évolution de pratiques agraires et la croissance démographique. L’objectif de cette recherche est d’améliorer les connaissances sur la dynamique d’occupation des terres agricoles dans les zones de cultures sèches (Cinzana) et cotonnière (Kléla) au Mali. La méthodologie utilisée a consisté à la collecte des données planimétriques et à l’analyse diachronique à travers des images satellitaires Landsat TM (Thematic Mapper) de 2000 et OLI (Operational Land Image) de 2020. Les taux de dégradation et de déforestation des formations naturelles… More > Graphic Abstract

He Wang^1,*, Ying He²

FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.4, pp. 889-899, 2024, DOI:10.32604/fdmp.2023.042728 - 28 March 2024

Abstract Magnetohydrodynamic (MHD) induction pumps are contactless pumps able to withstand harsh environments. The rate of fluid flow through the pump directly affects the efficiency and stability of the device. To explore the influence of induction pump settings on the related delivery speed, in this study, a numerical model for coupled electromagnetic and flow field effects is introduced and used to simulate liquid metal lithium flow in the induction pump. The effects of current intensity, frequency, coil turns and coil winding size on the velocity of the working fluid are analyzed. It is shown that the More >

Teng Wang, Yao Zhang, Jiangguo Liang, Shuai Wang, Shuanggen Liu^*

CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 3891-3907, 2024, DOI:10.32604/cmc.2024.048115 - 26 March 2024

Abstract With the widespread data collection and processing, privacy-preserving machine learning has become increasingly important in addressing privacy risks related to individuals. Support vector machine (SVM) is one of the most elementary learning models of machine learning. Privacy issues surrounding SVM classifier training have attracted increasing attention. In this paper, we investigate Differential Privacy-compliant Federated Machine Learning with Dimensionality Reduction, called Fed_DPDR-DPML, which greatly improves data utility while providing strong privacy guarantees. Considering in distributed learning scenarios, multiple participants usually hold unbalanced or small amounts of data. Therefore, Fed_DPDR-DPML enables multiple participants to collaboratively learn a global… More >

Xiaohui Cui^1,2,#, Chao Song^1,2,#, Dongmei Li^1,2,*, Xiaolong Qu^1,2, Jiao Long^1,2, Yu Yang^1,2, Hanchao Zhang³

CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 3603-3618, 2024, DOI:10.32604/cmc.2024.047321 - 26 March 2024

Abstract Named Entity Recognition (NER) stands as a fundamental task within the field of biomedical text mining, aiming to extract specific types of entities such as genes, proteins, and diseases from complex biomedical texts and categorize them into predefined entity types. This process can provide basic support for the automatic construction of knowledge bases. In contrast to general texts, biomedical texts frequently contain numerous nested entities and local dependencies among these entities, presenting significant challenges to prevailing NER models. To address these issues, we propose a novel Chinese nested biomedical NER model based on RoBERTa and Global Pointer… More >

Muhammad Saad¹, Muhammad Raheel Bhutta², Jongik Kim^3,*, Tae-Sun Chung¹

CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 4263-4282, 2024, DOI:10.32604/cmc.2024.047132 - 26 March 2024

Abstract With the increase in IoT (Internet of Things) devices comes an inherent challenge of security. In the world today, privacy is the prime concern of every individual. Preserving one’s privacy and keeping anonymity throughout the system is a desired functionality that does not come without inevitable trade-offs like scalability and increased complexity and is always exceedingly difficult to manage. The challenge is keeping confidentiality and continuing to make the person innominate throughout the system. To address this, we present our proposed architecture where we manage IoT devices using blockchain technology. Our proposed architecture works on… More >

Pengjun Li¹, Qixin Zhao¹, Yingmin Liu¹, Chao Zhong¹, Jinlong Wang^1,*, Zhihan Lyu²

CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 3825-3865, 2024, DOI:10.32604/cmc.2024.046851 - 26 March 2024

Abstract Enterprise risk management holds significant importance in fostering sustainable growth of businesses and in serving as a critical element for regulatory bodies to uphold market order. Amidst the challenges posed by intricate and unpredictable risk factors, knowledge graph technology is effectively driving risk management, leveraging its ability to associate and infer knowledge from diverse sources. This review aims to comprehensively summarize the construction techniques of enterprise risk knowledge graphs and their prominent applications across various business scenarios. Firstly, employing bibliometric methods, the aim is to uncover the developmental trends and current research hotspots within the… More >