Knowledge-Based Deep Learning for Time-Efficient Inverse Dynamics by Shuhao Ma, Yu Cao, Ian D. Robertson, Chaoyang Shi, Jindong Liu, Zhi-Qiang Zhang

“…Computational musculoskeletal modeling has been widely used as a powerful non-invasive tool to estimate them through inverse dynamics using static optimization, but the inherent computational complexity results in time-consuming analysis. In this paper, we propose a knowledge-based deep learning framework for time-efficient inverse dynamic analysis, which can predict muscle activation and muscle forces from joint kinematic data directly while not requiring any label information during model training. …”
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An efficient algorithmic framework to minimize the summand matrix in binary multiplication by Amit Verma, Manish Prateek, Shiv Naresh Shivhare, Thipendra P. Singh, Anuj Kumar, Rakesh Ranjan, Rahul Priyadarshi

“…Binary multiplication is a key operation in digital systems, often limited by the complexity of generating and summing numerous partial products. …”
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The Partner Selection Modes for Knowledge-Based Innovation Networks: A Multiagent Simulation by Lvcheng Li, Jialong Xie, Ruyi Wang, Jiafu Su, Stavros Sindakis

“…Proper partner selection can increase the efficiency of the entire innovation system. …”
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CSA-Net: Complex Scenarios Adaptive Network for Building Extraction for Remote Sensing Images by Dongjie Yang, Xianjun Gao, Yuanwei Yang, Minghan Jiang, Kangliang Guo, Bo Liu, Shaohua Li, Shengyan Yu

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Intelligent Feature Selection Ensemble Model for Price Prediction in Real Estate Markets by Daniel Cristóbal Andrade-Girón, William Joel Marin-Rodriguez, Marcelo Gumercindo Zuñiga-Rojas

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Estimating Performance Efficiency of Mining and Extracting Sectors Using DEA Models: The Case of Jordan by Jamil J. Jaber, Fatiha Beldjilali, Ali A. Shehadeh, Nawaf N. Hamadneh, Mohammad Saleh, Muhammad Tahir, S. Al Wadi

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Dynamic feature selection for silicon content prediction in blast furnace using BOSVRRFE by Junyi Duan

“…Abstract Accurate prediction of silicon content in blast furnace ironmaking is essential for optimizing furnace temperature control and production efficiency. However, large-scale industrial datasets exhibit complexity, dynamism, and nonlinear relationships, posing challenges for feature selection. …”
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Applications of randomly selected sets of exact Voight's solutions for vibration of thin plates by Ігор Ориняк, Юлія Бай, Ірина Костюшко

“… The principally new method of selected exact solutions, SES, for plate vibration based on fundamental solutions of Voigt is suggested. …”
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Modeling Porosity Surface of 3D Selective Laser Melting Metal Materials by Matej Babič, Roman Šturm, Teofil-Florin Gălățanu, Ildikó-Renáta Száva, Ioan Száva

“…We used fractal dimensions to determine the complexity of the microstructure of selective laser melting specimens. …”
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Two-Stage Unsupervised Hyperspectral Band Selection Based on Deep Reinforcement Learning by Yi Guo, Qianqian Wang, Bingliang Hu, Xueming Qian, Haibo Ye

“…In the design of the reward function, the Optimal Index Factor (OIF) was introduced as the evaluation metric to encourage the agent to select bands with high information content and low redundancy, and thereby improve the efficiency and quality of the selection process. …”
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Optimizing mouse metatranscriptome profiling by selective removal of redundant nucleic acid sequences by Morgan Roos, Samuel Bunga, Asako Tan, Erica Maissy, Dylan Skola, Alexander Richter, Daniel S. Whittaker, Paula Desplats, Amir Zarrinpar, Rick Conrad, Scott Kuersten

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Single-port robotic retroperitoneoscopic nephroureterectomy: Technical approach and recommendations for patient selection by Benjamin Yu, Richard E. Link

“…We focus on patient selection, advantages of regionalized SP surgery, and technical tips for operative efficiency and safety. …”
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Electrochemical Characteristics and Supercapacitance of the Self-Assembled Catocene Complex on Carbon Microfiber Electrode by sajjad Damiri, Zahra Samiei, Hamid reza Pouretedal

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Modulating selectivity and stability of the direct seawater electrolysis for sustainable green hydrogen production by Dazhi Yao, Chun Liu, Yanzhao Zhang, Shuhao Wang, Yan Nie, Man Qiao, Dongdong Zhu

“…However, the inherently complex composition of seawater—laden with halide ions, multivalent cations (Mg2+, Ca2+), and organic/biological impurities—presents formidable challenges in maintaining both selectivity and durability. …”
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LLMAGENTNET: A COLLABORATIVE NETWORK OF AUTONOMOUS AI AGENTS FOR COMPLEX TASK EXECUTION by А. Р. Бідочко, Я. І. Виклюк

“… Recent advancements in Large Language Models (LLMs) have opened new horizons for building autonomous AI agents capable of executing complex, multi-step tasks across a wide range of domains. …”
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Selective evolution of methanogenic communities by β-lactam antibiotics promotes methane production by Yuting Zhe, Huaigang Cheng, Danjing Ding, Yueyue He, Zhuohui Ma, Jing Shen

“…By utilizing amoxicillin, the research promotes the selective growth of methane-producing microbes while suppressing harmful ones, resulting in faster and more efficient methane production with enhanced process control. …”
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Switchable electrochemical pathways for the selective C(sp3)-Ge bond formation by Haifeng Chen, Cai Zhai, Huabing Zhang, Chen Zhu, Magnus Rueping

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INVESTMENT PROGRAM OF POWER GRID COM PANIES: CHECK ALL CAN NOT BE SELECTED by V. A. Karle, LYU. Zolotova, S. A. Kechin

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Outage probability based power allocation and relay selection algorithm in cooperative communication by Li-yue SUN, Xiao-hui ZHAO, Ming GUO

“…The relay selection and power optimization of multi-relay cooperative communication network under a joint sum power constraint was considered.A low complexity lay selection and power allocation algorithm was also pro-posed in amplify-and-forward cooperative network aiming at minimizing the probability of system outage.In this scheme,optimal power allocation among source and relay nodes was conducted.According to the SNR,an optimal relay node set was selected and a power allocation factor leading to lower system outage probability was obtained by steepest descent method.This algorithm did not need large quantity of l statistical information and equal power condition.It can obtain the best set of relay nodes under optimal power allocation only by solving the arranged matrix on the basis of Sig-nal to Noise Ratio.Simulation results show that the proposed relay select and power allocation algorithm,under the same conditions,compared in the outage probability in erent relay node set among several algorithms,achieves better performance in outage probability and power efficiency.…”
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A Generalized Multi-Layer Framework for Video Coding to Select Prediction Parameters by Muhammad Asif, Maaz Bin Ahmad, Imtiaz A. Taj, Muhammad Tahir

“…The exploitation of the RDO technique contributes significantly to increase the computational complexity of the coding process. In this paper, a generalized multi-layer framework is presented, which provides a hierarchical optimized way to select MB prediction parameters. …”
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