Neural network pruning based on channel attention mechanism by Jianqiang Hu, Yang Liu, Keshou Wu

“…Furthermore, it effectively balances pruning efficiency and prediction accuracy.…”
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Research on multi-objective control of PPCI diesel engine combustion process based on data driven modelling by Ziqiang Chen, Peng Ju, Zhe Wang, Du Huang, Lei Shi, Kangyao Deng

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Data-Driven Robust Optimization for Solving the Heterogeneous Vehicle Routing Problem with Customer Demand Uncertainty by Jingling Zhang, Mengfan Yu, Qinbing Feng, Longlong Leng, Yanwei Zhao

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Distribution of age at natural menopause, age at menarche, menstrual cycle length, height and BMI in BRCA1 and BRCA2 pathogenic variant carriers and non-carriers: results from EMBR... by Nasim Mavaddat, Debra Frost, Emily Zhao, Daniel R. Barnes, Munaza Ahmed, Julian Barwell, Angela F. Brady, Paul Brennan, Hector Conti, Jackie Cook, Harriet Copeland, Rosemarie Davidson, Alan Donaldson, Emma Douglas, David Gallagher, Rachel Hart, Louise Izatt, Zoe Kemp, Fiona Lalloo, Zosia Miedzybrodzka, Patrick J. Morrison, Jennie E. Murray, Alex Murray, Hannah Musgrave, Claire Searle, Lucy Side, Katie Snape, Vishakha Tripathi, Lisa Walker, Stephanie Archer, D. Gareth Evans, Marc Tischkowitz, Antonis C. Antoniou, Douglas F. Easton

“…Conclusion Information on the distribution of cancer risk factors in PV carriers is needed for incorporating these factors into multifactorial cancer risk prediction algorithms. Contrary to previous reports, we found no evidence that BRCA1 or BRCA2 PV are associated with hormonal or anthropometric factors, except for a weak association with height. …”
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Active Disturbance Rejection Attitude Control for Hypersonic Vehicle Based on Intelligent Stochastic Robust Optimization Method by Bo Wang, Wei Liu, Zhongtao Cheng, Lei Liu, Yongji Wang

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Projections of single-level indirect lumbar interbody fusion volume and associated costs for Medicare patients to 2050 by Kyle A. Mani, BS, Samuel N. Goldman, BS, Noel Akioyamen, MD, Emily Kleinbart, BS, Yaroslav Gelfand, MD, Saikiran Murthy, DO, Jonathan Krystal, MD, Ananth Eleswarapu, MD, Reza Yassari, MD, Mitchell S. Fourman, MD, MPhil

“…Predictive performance was evaluated by splitting the data into training (75%) and validation (25%) sets, and calculating normalized root mean square error (NRMSE). …”
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Ginkgetin Alleviates Inflammation and Senescence by Targeting STING by Yadan Liu, Jialin Ye, Zisheng Fan, Xiaolong Wu, Yinghui Zhang, Ruirui Yang, Bing Jiang, Yajie Wang, Min Wu, Jingyi Zhou, Jingyi Meng, Zhiming Ge, Guizhen Zhou, Yuan Zhu, Yichuan Xiao, Mingyue Zheng, Sulin Zhang

“…To reveal the molecular mechanism of Ginkgetin's anti‐aging effect, a graph convolutional network‐based drug “on‐target” pathway prediction algorithm for prediction is employed. The results indicate that the cGAS‐STING pathway may be a potential target for Ginkgetin. …”
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Short time solar power forecasting using P-ELM approach by Shuqi Shi, Boyang Liu, Long Ren, Yu Liu

“…The results indicate that the P-ELM algorithm achieves higher accuracy in short-term prediction, demonstrating its suitability for ensuring accuracy and reliability in real-time solar power forecasting.…”
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Metabolic network segmentation: A probabilistic graphical modeling approach to identify the sites and sequential order of metabolic regulation from non-targeted metabolomics data. by Andreas Kuehne, Urs Mayr, Daniel C Sévin, Manfred Claassen, Nicola Zamboni

“…We present the metabolic network segmentation (MNS) algorithm, a probabilistic graphical modeling approach that enables genome-scale, automated prediction of regulated metabolic reactions from differential or serial metabolomics data. …”
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Deep Reinforcement Learning Method for Wireless Video Transmission Based on Large Deviations by Yongxiao Xie, Shian Song

“…To further optimize resources in wireless energy transmission and tackle the challenge of balancing exploration and exploitation in the DRL algorithm, this paper develops an adaptive DRL algorithm that extends classical DRL frameworks by integrating dropout techniques during both the training and prediction processes. …”
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Hybrid Reactive Power Compensator with Adaptation of the Operation of the Control System to the Parameters of the Mains Voltage by Goolak S., Tkachenko V., Kyrychenko M., Kozlov S.

“…The most important result is the development of a block diagram of the control system for the active part of the reactive power compensator based on the implementation of the Levinson-Durbin linear prediction algorithm. The significance of the results obtained lies in the possibility of the proposed control scheme for the active part of the compensator to adapt the operation of the compensator to the voltage parameters of the catenary, that is, to the actual operating conditions of the electric locomotive.…”
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Мethodology for calculation of phase behavior of a natural hydrocarbon system with account of formation water mineralization by L. T. Abdrazakova, A. Gilmanov, A. P. Shevelev

“…The development of gas condensate fields requires the prediction of phase behavior. The existing models do not consider the presence of several roots of material balance equation and water mineralization. …”
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Mutual-Energy Inner Product Optimization Method for Constructing Feature Coordinates and Image Classification in Machine Learning by Yuanxiu Wang

“…Finally, the mutual-energy inner product optimization method is used to construct feature coordinates, and multi-class Gaussian classifiers are trained on the MINST training set. Good prediction results of the Gaussian classifiers are achieved on the MINST test set.…”
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Authorship identification methods in student plagiarism detection by A. I. Paramonov, I. A. Trukhanovich

“…In the modern educational context the problem of plagiarism is urgent and requires the development of effective methods of detection and prevention of this phenomenon. …”
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From LMS to adaptive training systems by Y. B. Popova

“…The use of information technology and, in particular, learning management systems, increases the ability of both the teacher and the learner to achieve their goals in the educational process. Such systems provide educational content, help organize and monitor training, collect progress statistics, and can also take into account the individual characteristics of each user of the system. …”
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Disagreement in Detected Heatwave Trends Resulting From Diagnostic Methods by Boyuan Zhang, Yongli He, Zhanbo Wang, Bo Huang, Yongkun Xie, Xiaodan Guan, Jianping Huang

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Quantum ensemble learning with a programmable superconducting processor by Jiachen Chen, Yaozu Wu, Zhen Yang, Shibo Xu, Xuan Ye, Daili Li, Ke Wang, Chuanyu Zhang, Feitong Jin, Xuhao Zhu, Yu Gao, Ziqi Tan, Zhengyi Cui, Aosai Zhang, Ning Wang, Yiren Zou, Tingting Li, Fanhao Shen, Jiarun Zhong, Zehang Bao, Zitian Zhu, Zixuan Song, Jinfeng Deng, Hang Dong, Pengfei Zhang, Wei Zhang, Hekang Li, Qiujiang Guo, Zhen Wang, Ying Li, Xiaoting Wang, Chao Song, H. Wang

“…Based on the probabilistic nature of quantum measurement, the algorithm improves the prediction accuracy by refining the attention mechanism during the adaptive training and combination of quantum classifiers. …”
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Localizing axial dense emitters based on single-helix point spread function and compressed sensing by Wu Hanzhe, Chen Danni, Ji Yihong, Xiang Gan, Ni Yanxiang, Li Heng, Yu Bin, Qu Junle

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Validation Indicator Identification and Customer Ranking in Microloans: A Study at Middle East Bank in Iran by Azadeh Ahmadi Kousha, Faegh Ahmadi, Mohammad Hossein Ranjbar, Hamidreza Kordlouie

“…Naive Bayes, Meta, Attribute Selected Classifier, and j48 algorithms were implemented and WEKA software was used to classify criteria and create patterns. …”
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Reducing the Effects of City Heat Islands Through Cool Pavement Materials (Case Study: District 8 of Tabriz Metropolis) by Asghar Abedini, Mojtaba Azmoun, Kiarash Azarkish, Sina Moshtaghi

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