A Blockchain-Based Architecture of Web3.0: A Comprehensive Decentralized Model With Relay Nodes, Unique IDs and P2P by Hyunjoo Yang, Sejin Park

“…When faced with malicious requests, the system significantly reduces verification latency to an average of 0.0106 ms, ensuring rapid rejection and preserving network stability, while legitimate requests are processed efficiently with an average latency of 0.4125 ms.Experiments comparing latency-based and random-based relay selection methods across various network configurations (public-public, public-private, private-private) demonstrate that latency-based selection optimizes connection setup times in low-latency environments, while random-based selection provides robust performance in complex network scenarios. …”
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An Improved DHA Star and ADA-DWA Fusion Algorithm for Robot Path Planning by Yizhe Jia, Yong Cai, Jun Zhou, Hui Hu, Xuesheng Ouyang, Jinlong Mo, Hao Dai

“…This method successfully resolves the inherent trade-off between efficiency and reliability in complex robot navigation scenarios, providing enhanced operational robustness for practical applications ranging from industrial logistics to field robots.…”
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Research Progress of Abrasive Groups Ordered Grinding Wheels by Ye Guo, Bing Chen, Zihao Liu, Shiwei Sun, Guoyue Liu, Bing Guo

“…This could pave the way for the development of machining processes that are more environmentally friendly, energy-efficient, and precise.…”
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Space-air-ground integrated networks:review and prospect by Xuemin(Sherman) SHEN, Nan CHENG, Haibo ZHOU, Feng LYU, Wei QUAN, Weisen SHI, Huaqing WU, Conghao ZHOU

“…With the advance of the information technologies,the scale of the information services gradually expands,from ground services,to aerial,maritime,and spatial services,with the soaring requirements on multi-dimensional comprehensive information resources.The space-air-ground integrated networks (SAGINs) are envisioned to provide seamless network services to spatial,aerial,maritime,and ground users,satisfying the future network requirements on all-time,all-domain,and all-space communications and interconnected networking.Firstly,we reviewed the current research development of SAGINs,discussing the research trends on the low-earth orbiting (LEO) satellite constellation and space-ground network integration.Then,the reinforcement learning (RL) framework was proposed in SAGINs to address the problems of complex architecture,high dynamics,and resource constraints in SAGINs,which facilitated efficient and fast network design,analysis,optimization,and management.As a case study,the method of applying deep RL (DRL) was showed for the intelligent access network selection in SAGINs.To improve the RL training efficiency,a comprehensive SAGINs simulation platform was established,through which the agent-environments interaction was accelerated and training samples could be obtained more cost-effectively.Finally,some open research directions were presented.…”
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Space-air-ground integrated networks:review and prospect by Xuemin(Sherman) SHEN, Nan CHENG, Haibo ZHOU, Feng LYU, Wei QUAN, Weisen SHI, Huaqing WU, Conghao ZHOU

“…With the advance of the information technologies,the scale of the information services gradually expands,from ground services,to aerial,maritime,and spatial services,with the soaring requirements on multi-dimensional comprehensive information resources.The space-air-ground integrated networks (SAGINs) are envisioned to provide seamless network services to spatial,aerial,maritime,and ground users,satisfying the future network requirements on all-time,all-domain,and all-space communications and interconnected networking.Firstly,we reviewed the current research development of SAGINs,discussing the research trends on the low-earth orbiting (LEO) satellite constellation and space-ground network integration.Then,the reinforcement learning (RL) framework was proposed in SAGINs to address the problems of complex architecture,high dynamics,and resource constraints in SAGINs,which facilitated efficient and fast network design,analysis,optimization,and management.As a case study,the method of applying deep RL (DRL) was showed for the intelligent access network selection in SAGINs.To improve the RL training efficiency,a comprehensive SAGINs simulation platform was established,through which the agent-environments interaction was accelerated and training samples could be obtained more cost-effectively.Finally,some open research directions were presented.…”
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Multi-element synergy in photocatalytic materials integrated mechanism-design-preparation strategies by Qi Zhanfeng, Li Guancheng, Guo Xiuli

“…It is emphasized that the precise regulation of elemental species, ratios and distributions, combined with the synergistic optimization of photocatalytic mechanism and preparation process, is the key path to achieve efficient photocatalytic performance. Finally, it is proposed that future research should focus on the quantitative analysis of the complex interactions between elements and the integrated design of low-cost materials, in order to promote the practical application of photocatalytic technology in the fields of environmental treatment and energy conversion.…”
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Selección de proveedores con el método PSI by Ángel Rodríguez Rodriguez, Raquel Irene Laguado Ramírez, Belisario Peña Rodríguez, Lida Yaneth Maldonado Mateus

“…This makes it an ideal option for complex processes such as supplier selection, where decision criteria are often multiple and diverse, such as cost, quality, reliability, or delivery time, among others. …”
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The Development of Building Materials Recommendation System Based on Feature Crosses by Hui-Ping Tserng, Chung-Cho Chang, Shu-Hsien Tai

“…Relying solely on traditional data often limits architects’ understanding, especially during early design, where material choices impact overall performance. This complexity highlights the need for an efficient recommendation system. …”
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Multi-feature stock price prediction by LSTM networks based on VMD and TMFG by Zhixin Zhang, Qingyang Liu, Yanrong Hu, Hongjiu Liu

“…This paper proposes a novel stock price forecasting model—the Variational Mode Decomposition—Triangulated Maximally Filtered Graph—Long Short-Term Memory (VMD–TMFG–LSTM) combined model—aimed at improving prediction accuracy, stability, and computational efficiency. The proposed model first employs Variational Mode Decomposition (VMD) to decompose the stock price time series into multiple smooth intrinsic mode functions (IMFs), reducing data complexity and mitigating noise interference. …”
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A machine learning framework for predicting healthcare utilization and risk factors by Yead Rahman, Prerna Dua

“…A rigorous preprocessing pipeline ensured data integrity, while exploratory data analysis (EDA) guided feature selection, ultimately retaining 20 key variables to capture complex interactions. …”
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Improving battery safety and sustainability through testing material advances and industry developments by Zoltan Weltsch, Tibor Cseke, Robert Kun

“…By examining the interrelationships between material selection (cathode, anode), cell design, testing protocols and regulatory environment, the study highlights the complex challenges and development directions for battery energy storage. …”
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Vigorous technique for augmented lifetime in WSNs by Sardar Jaffar Ali, Javed Iqbal, Faheem Khan, Yeon-Kug Moon

“…Existing solutions often address energy efficiency in isolation, failing to consider the complex interplay of factors affecting WSN performance. …”
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The analysis of strategic management decisions and corporate competitiveness based on artificial intelligence by Yang Pu, Hao Li, Wenjia Hou, Xingchen Pan

“…This work provides enterprises with an efficient and reliable decision-support tool, facilitating the maintenance of competitive advantages in complex and dynamic market environments.…”
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Colonial bacterial memetic algorithm and its application on a darts playing robot by Szilárd Kovács, Csaba Budai, János Botzheim

“…CBMA incorporates features like multi-level clustering, dynamic gene selection, hierarchical population clustering, and adaptive co-evolutionary mechanisms, enabling efficient management of task-specific parameters and optimizing solution quality while minimizing resource consumption. …”
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Simple and robust in vivo engineering of plasmid DNA at any copy number in Escherichia coli by Ana G. V. Sepulchro, Hendrikje C. J. Kozlowski, Morten H. H. Nørholm

“…Here, we present a robust methodology for plasmid recombineering in E. coli using a triple-selection system customized for efficient performance at any copy number. …”
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FORMALIZATION OF THE PROBLEM OF TRANSPORT LOGISTICS OPTIMIZATION NETWORKS AT THE STAGE OF REENGINEERING by Vladimir Beskorovainyi, Lyudmyla Kolesnyk, Dmytro Yevstrat

“…The practical use of the proposed complex of mathematical models will reduce the time and capacity complexity of project decision-making support technologies, and due to the use of the proposed options selection procedures, increase their quality based on a number of functional and cost indicators. …”
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Medical-psychological rehabilitation of the military men who have received wounds during carrying out of counterterrorist operation in Dagestan in 1999 by A. S. Ibragimova, A. M. Amirov

“…The preferable criteria during the selection of rehabilitative methods depending on the efficiency of the differentiated approach to their use, sequence and duration of the influence, combinability have been defined. …”
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Mobile Robot Path Planning Based on Enhanced Dynamic Window Approach and Improved A∗ Algorithm by Hongxia Yang, Xingqiang Teng

“…In the improved A∗ algorithm, in order to improve the algorithm efficiency, so that a single planning path can pass through multiple target points, the search point selection strategy and evaluation function are optimized. …”
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Comparing Nanofiltration and Ion Exchange for Reverse Osmosis Pretreatment in Industrial Water Treatment: A Techno-Economic Analysis by Harwin Harwin

“…Water softening is a crucial process in various industrial applications, and the selection of an appropriate system involves balancing technical efficiency, environmental impact, and economic considerations. …”
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Comparative Study of Algorithms for the Conversion From Surface Mesh Models to Volume Mesh Models by Youxi Wang, Qi Pang, Meng Li, Yang Liu

“…The results showed that the Frontal algorithm performed the best in the conversion of simple models with a CPU runtime of 0.001 s, while the Delaunay algorithm took relatively longer. For complex models, the Initial mesh, Delaunay, and Frontal algorithms were all successful in completing the conversion, but the HXT algorithm failed, highlighting the importance of algorithm selection. …”
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