A. MADHAN KUMAR¹, K. JAYAKUMAR^2,*, M. SHALINI³

Journal of Polymer Materials, Vol.39, No.3-4, pp. 269-281, 2022, DOI:10.32381/JPM.2022.39.3-4.7

Abstract Polylactic acid (PLA) is the most popular thermoplastic biopolymer providing a stiffness and strength alternative to fossil-based plastics. It is also the most promising biodegradable polymer on the market right now, thus gaining a substitute for conservative artificial polymers. Therefore, the current research focuses on synthesizing and mechanical characterization of particlereinforced PLA composites. The hot compression molding technique was used to fabricate PLA-based composites with 0, 2.5, 5, and 7.5 weight % of sawdust, rice husk, and bagasse particle reinforcements to enhance the performance of the PLA. The pellets of PLA matrix were taken with… More >

XINGMIN XU¹, QINGQING SUN², AIRONG XU², XINBAO GUO²

Journal of Polymer Materials, Vol.39, No.1-2, pp. 167-181, 2022, DOI:10.32381/JPM.2022.39.1-2.11

Abstract Silk fibroin (SF) with renewability, biocompatibility and biodegradability shows potential application in various fields including biomedicine, tissue engineering, and wearable electronic devices. Herein, SF is used to exert effective reinforcement of polyvinyl alcohol (PVA) composite film to further improve its practicability. As such, PVA/SF composite films were prepared for the first time using a facile approach. The films were characterized to investigate possible interaction of PVA with SF. Meanwhile, systematic investigations have also been completed to explore the influences of PVA/SF mass ratio on the mechanical properties (tensile strength, elongation at break), biodegradability and biocompatibility, More >

Jiangang Lu, Ruifeng Zhao^*, Zhiwen Yu, Yue Dai, Kaiwen Zeng

CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 4453-4469, 2024, DOI:10.32604/cmc.2024.048020

Abstract Time synchronization (TS) is crucial for ensuring the secure and reliable functioning of the distribution power Internet of Things (IoT). Multi-clock source time synchronization (MTS) has significant advantages of high reliability and accuracy but still faces challenges such as optimization of the multi-clock source selection and the clock source weight calculation at different timescales, and the coupling of synchronization latency jitter and pulse phase difference. In this paper, the multi-timescale MTS model is conducted, and the reinforcement learning (RL) and analytic hierarchy process (AHP)-based multi-timescale MTS algorithm is designed to improve the weighted summation of More >

Sepehr Soltani¹, Ehsan Ghafourian², Reza Salehi³, Diego Martín^3,*, Milad Vahidi⁴

Intelligent Automation & Soft Computing, Vol.39, No.1, pp. 93-108, 2024, DOI:10.32604/iasc.2024.042693

Abstract For many years, researchers have explored power allocation (PA) algorithms driven by models in wireless networks where multiple-user communications with interference are present. Nowadays, data-driven machine learning methods have become quite popular in analyzing wireless communication systems, which among them deep reinforcement learning (DRL) has a significant role in solving optimization issues under certain constraints. To this purpose, in this paper, we investigate the PA problem in a -user multiple access channels (MAC), where transmitters (e.g., mobile users) aim to send an independent message to a common receiver (e.g., base station) through wireless channels. To… More >

Gang Niu^1,2, Zhaoyang Jin², Wei Zhang^3,*, Yiqun Huang³

Structural Durability & Health Monitoring, Vol.18, No.2, pp. 161-179, 2024, DOI:10.32604/sdhm.2023.044580

Abstract Amid urbanization and the continuous expansion of transportation networks, the necessity for tunnel construction and maintenance has become paramount. Addressing this need requires the investigation of efficient, economical, and robust tunnel reinforcement techniques. This paper explores fiber reinforced polymer (FRP) and steel fiber reinforced concrete (SFRC) technologies, which have emerged as viable solutions for enhancing tunnel structures. FRP is celebrated for its lightweight and high-strength attributes, effectively augmenting load-bearing capacity and seismic resistance, while SFRC’s notable crack resistance and longevity potentially enhance the performance of tunnel segments. Nonetheless, current research predominantly focuses on experimental analysis,… More > Graphic Abstract

Yan Li, Qiyuan Wang^*, Kaidi Jia

CMC-Computers, Materials & Continua, Vol.78, No.2, pp. 2469-2489, 2024, DOI:10.32604/cmc.2024.047822

Abstract Image description task is the intersection of computer vision and natural language processing, and it has important prospects, including helping computers understand images and obtaining information for the visually impaired. This study presents an innovative approach employing deep reinforcement learning to enhance the accuracy of natural language descriptions of images. Our method focuses on refining the reward function in deep reinforcement learning, facilitating the generation of precise descriptions by aligning visual and textual features more closely. Our approach comprises three key architectures. Firstly, it utilizes Residual Network 101 (ResNet-101) and Faster Region-based Convolutional Neural Network… More >

Xiaozhou Xia¹, Changsheng Qin¹, Guangda Lu², Xin Gu^1,*, Qing Zhang¹

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2257-2276, 2024, DOI:10.32604/cmes.2023.031238

Abstract Accurate simulation of the cracking process caused by rust expansion of reinforced concrete (RC) structures plays an intuitive role in revealing the corrosion-induced failure mechanism. Considering the quasi-brittle fracture of concrete, the fracture phase field driven by the compressive-shear term is constructed and added to the traditional brittle fracture phase field model. The rationality of the proposed model is verified by a mixed fracture example under a shear displacement load. Then, the extended fracture phase model is applied to simulate the corrosion-induced cracking process of RC. The cracking patterns caused by non-uniform corrosion expansion are… More >

Duan Zhu^1,2, Zhende Zhu^1,2, Cong Zhang^1,2,*, Lun Dai^1,2, Baotian Wang^1,2

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2445-2470, 2024, DOI:10.32604/cmes.2023.030847

Abstract Tunnel construction is susceptible to accidents such as loosening, deformation, collapse, and water inrush, especially under complex geological conditions like dense fault areas. These accidents can cause instability and damage to the tunnel. As a result, it is essential to conduct research on tunnel construction and grouting reinforcement technology in fault fracture zones to address these issues and ensure the safety of tunnel excavation projects. This study utilized the Xianglushan cross-fault tunnel to conduct a comprehensive analysis on the construction, support, and reinforcement of a tunnel crossing a fault fracture zone using the three-dimensional finite… More >

Fei Xue^*

Journal on Artificial Intelligence, Vol.5, pp. 131-143, 2023, DOI:10.32604/jai.2023.046293

Abstract Vocational education can effectively improve the vocational skills of employees, improve people’s traditional concept of vocational education, and focus on the training of vocational skills for students by using new educational methods and concepts, so that they can master key vocational skills and develop key abilities. In this paper, three different learning models, Deep Knowledge Tracing (DKT), Dynamic Key-Value Memory Networks (DKVMN) and Double Deep Q-network (DDQN), are used to evaluate the indicators in the vocational education system. On the one hand, the influence of learning degree on the performance of the model is compared, More >

Mesfer Al Duhayyim^1,*, Badriyya B. Al-onazi², Jaber S. Alzahrani³, Hussain Alshahrani⁴, Mohamed Ahmed Elfaki⁴, Abdullah Mohamed⁵, Ishfaq Yaseen⁶, Gouse Pasha Mohammed⁶, Mohammed Rizwanullah⁶, Abu Sarwar Zamani⁶

Computer Systems Science and Engineering, Vol.47, No.3, pp. 3049-3065, 2023, DOI:10.32604/csse.2023.033836

Abstract Sentiment analysis (SA) of the Arabic language becomes important despite scarce annotated corpora and confined sources. Arabic affect Analysis has become an active research zone nowadays. But still, the Arabic language lags behind adequate language sources for enabling the SA tasks. Thus, Arabic still faces challenges in natural language processing (NLP) tasks because of its structure complexities, history, and distinct cultures. It has gained lesser effort than the other languages. This paper developed a Multi-versus Optimization with Deep Reinforcement Learning Enabled Affect Analysis (MVODRL-AA) on Arabic Corpus. The presented MVODRL-AA model majorly concentrates on identifying… More >