Dose prediction of CyberKnife Monte Carlo plan for lung cancer patients based on deep learning: robust learning of variable beam configurations by Yuchao Miao, Jiwei Li, Ruigang Ge, Chuanbin Xie, Yaoying Liu, Gaolong Zhang, Mingchang Miao, Shouping Xu

“…Abstract Background Accurate calculation of lung cancer dose using the Monte Carlo (MC) algorithm in CyberKnife (CK) is essential for precise planning. …”
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Deep Reinforcement Learning Based Transferable EMS for Hybrid Electric Trains by Yogesh Wankhede, Sheetal Rana, Faruk Kazi

“…To enhance the performance of the EMS, proposes to use of a deep reinforcement learning (DRL) algorithm specifically the deep deterministic policy gradient (DDPG) combined with transfer learning (TL) which can improve the system's efficiency when driving cycles are changed. …”
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Initialization Methods for FPGA-Based EMT Simulations by Xin Ma, Xiao-Ping Zhang

“…The performance of these four methods are also compared, and Method 4 can initialize instantly with the simplest code. To improve hardware adaptability, optimized strategies are developed for address sequence, interface, update modes and dataflow. …”
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Integration of Hash Encoding Technique with Machine Learning for Employee Turnover Prediction by Ahya Radiatul Kamila, Johanes Fernandes Andry, Francka Sakti Lee, Felliks F. Tampinongkol

“…It is part of the preprocessing stage, aiming to reduce memory usage, speed up data preprocessing, and improve model performance. After preprocessing is completed, the prediction model is trained using the Random Forest algorithm to predict employee turnover. …”
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On Flood Detection Using Dual-Polarimetric SAR Observation by Su-Young Kim, Yeji Lee, Sang-Eun Park

“…This study aims to elucidate the optimal exploitation of polarimetric scattering information in dual-pol SAR data. …”
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Refined Assessment Method of Offshore Wind Resources Based on Interpolation Method by Wenchuan Meng, Zaimin Yang, Zhi Rao, Shuang Li, Xin Lin, Jingkang Peng, Yuwei Cao, Yingquan Chen

“…To enhance the prediction accuracy of offshore wind speed, this study employs an interpolation algorithm to improve spatial resolution based on the ERA5 reanalysis dataset. …”
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Leveraging artificial intelligence to strengthen surgical systems in sub-Saharan Africa by Osedebamen Ralph-Okhiria, Ikhide Alonge

“…However, the review highlighted several crucial challenges and concerns, including data availability and quality, infrastructure gaps, ethical implications (such as data protection and algorithmic bias), costs and affordability, and the need for robust regulatory frameworks. …”
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Deep Q-Networks for Minimizing Total Tardiness on a Single Machine by Kuan Wei Huang, Bertrand M. T. Lin

“…Due to its computational intractability, exact approaches such as dynamic programming algorithms and branch-and-bound algorithms struggle to produce optimal solutions for large-scale instances in a reasonable time. …”
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Prediction of porosity, hardness and surface roughness in additive manufactured AlSi10Mg samples. by Fatma Alamri, Imad Barsoum, Shrinivas Bojanampati, Maher Maalouf

“…The results presented in this study provide significant advantages for additive manufacturing, potentially reducing experimentation costs by identifying the process parameters that optimize the quality of the fabricated parts.…”
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Static Voltage Stability Evaluation and Correction Strategy Based on Stage Solving Strategy and SIFT by Yan Wen, Xiaoming Liu, Yongzhi Zhou, Huiwen Zhang, Donglei Sun

“…Aiming at the static voltage instability problem of the power grid caused by large-scale access of renewable energy sources, the study adopts the scale invariant feature transform algorithm for boundary feature extraction, while optimizing the traditional generalized resilience index of the power grid. …”
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Guaranteed efficient energy estimation of quantum many-body Hamiltonians using ShadowGrouping by Alexander Gresch, Martin Kliesch

“…They are helpful for identifying measurement settings that improve the energy estimate the most. This task constitutes an NP-hard problem. …”
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Approach to knowledge management and the development of a multi-agent knowledge representation and processing system by E. I. Zaytsev, E. V. Nurmatova

“…Methods for distribution of intelligent software agents on the MKRPS nodes are proposed along with algorithms for optimizing the logical structure of the distributed knowledge base (DKB) to improve the performance of the MKRPS in terms of volume, cost and time criteria.Conclusions. …”
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Joint source–channel rate allocation with unequal error protection for space image transmission by Dan Dong, Shaohua Wu, Dongqing Li, Jian Jiao, Chanjuan Ding, Qinyu Zhang

“…This separate design, although simple to be implemented, cannot explore the transmission performance to the most. In this article, we propose a joint source–channel rate allocation framework to improve the space image transmission performance. …”
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Effects of the lavage through fistula in treatment of spontaneous esophageal rupture by combined thoracoscopic and gastroscopic management by Zhao Huang, Penglong Zhao, Bingmei Qiu, Chuan Gao, Zhao Chen, Nan Yang, Yang Xu, Zhiqiang Zou, Yi Shen, Liwen Hu

“…Conclusions The Lavage-Drainage approach enhanced the drainage efficiency, reduced the inflammation level, and improved the prognosis of SER. However, this study has some limitations, and further multi-center prospective studies are needed to optimize the treatment and reduce costs.…”
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Electric Submersible Pump Fault Diagnosis Based on Laplacian Eigenmaps and Weighted Extreme Learning Machine by XU Zekun, FU Jun, GAO Xiaoyong, ZHANG Yu, LI Qiang, TAN Chaodong

“…In response to the serious imbalance in the data collected by ESP, firstly, a fault diagnosis model is established using a weighted extreme learning machine; Then, to solve the problems of insufficient algorithm learning, high computational costs caused by weighted strategies, and poor performance in applying to high-dimensional feature spaces, the Laplacian eigenmaps method is introduced to further optimize the model; finally, the effectiveness of the proposed method was validated on the TE chemical process dataset, and the practicality of the algorithm was experimentally validated on the real-time fault dataset of electric submersible pump. …”
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Scalable reinforcement learning for large-scale coordination of electric vehicles using graph neural networks by Stavros Orfanoudakis, Valentin Robu, E. Mauricio Salazar, Peter Palensky, Pedro P. Vergara

“…We further demonstrate that the proposed architecture’s flexibility allows it to be combined with most state-of-the-art deep RL algorithms to solve a wide range of problems, including those with continuous, multi-discrete, and discrete action spaces. …”
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Interpretable model based on MRI radiomics to predict the expression of Ki-67 in breast cancer by Li Zhang, Qinglin Du, Mengyi Shen, Xin He, Dingyi Zhang, Xiaohua Huang

“…The Shapley Additive Explanation (SHAP) algorithm was employed to explain the optimal model, and the AUC was used to assess the model’s performance. …”
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High-Dimensional Projected Clustering for Learner Competency Analysis in Medical Training Programs by Sandhya Harikumar, C. S. Jayamohan Pillai, V. Vani Chithra, Raghu Raman, Mr Kaimal, Kai-Yu Tang, Prema Nedungadi

“…The key contribution of this work is the process of forming a team of the most qualified medical professionals for a critical care case. …”
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Research and Analysis of Out-of-Tolerance Problem in Mold Processing Based on Intelligence by Juxian Wang

“…According to the numerical simulation results, the reasoning mechanism of an intelligent design system including instance and rule knowledge is designed, and an uncertain knowledge reasoning algorithm based on the reliability factor is proposed to improve the accuracy of mold size and reduce the overtolerance of the mold.…”
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Adaptive Feedforward Vibration Control of Helicopter Cabin Floor Driven by Piezoelectric Stack Actuators: Modeling, Simulation and Experiments by Laishou Song, Yingquan Wang, Xiaoyu Shen

“…Active control of structural response is the most practical and effective approach to mitigate helicopter vibration and enhance ride quality. …”
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