Rapid screening and optimization of CO2 enhanced oil recovery operations in unconventional reservoirs: A case study by Shuqin Wen, Bing Wei, Junyu You, Yujiao He, Qihang Ye, Jun Lu

“…The proposed framework was validated by comparing the GA-RF predictions with simulation results under different reservoir conditions, which yielded a minimum relative error of 0.34% and an average relative error of 5.3%. …”
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Use of stepwise m5 model tree to forecast the P24max based on teleconnection indices by Golnar Ghanbarzadeh, Khalil Ghorbani, Meysam Salarijazi, Chooghi Bairam Komaki, Laleh Rezaei Ghaleh

“…The stepwise execution of the M5 model tree showed that the algorithm follows a greedy approach, and it is not necessary to use all variables to predict P24max. …”
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Method of Construction of pareto set At a dynamic initial data reception by S. V. Chebakov, L. V. Serebryanaya

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Amygdala activity for the modulation of goal-directed behavior in emotional contexts. by Kazutaka Maeda, Jun Kunimatsu, Okihide Hikosaka

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A qualitative process evaluation within a clinical trial that used healthcare technologies for children with asthma-insights and implications. by Louisa Lawrie, Stephen Turner, Seonaidh C Cotton, Jessica Wood, Heather M Morgan

“…<h4>Conclusion</h4>The use of technology and individual data within appointments was considered useful to both staff and families: closer monitoring and the educational impacts were especially highlighted. Utilising an algorithm was broadly acceptable, with caveats around clinicians using the recommendations as a guide only and wariness around extreme step-ups/downs considering contextual factors not taken into account.…”
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The Integration Of Artificial Intelligence In English Language Teaching And Machine Translation: A Bridge Between Theory And Practice In Language Teaching For Specific Purposes. by Hafida Slimani, Rachid Saim

“…However, it also raises challenges, such as the reliability of machine translations, algorithmic biases, and excessive dependence on technology. …”
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Peptide inhibitors of the anaphase promoting-complex that cause sensitivity to microtubule poison. by Scott C Schuyler, Yueh-Fu Olivia Wu, Hsin-Yu Chen, Yi-Shan Ding, Chia-Jung Lin, Yu-Ting Chu, Ting-Chun Chen, Louis Liao, Wei-Wei Tsai, Anna Huang, Lin-Ing Wang, Ting-Wei Liao, Jia-Hua Jhuo, Vivien Cheng

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rhBNN+ Comprehensive Detections and Analyses of the Human Body Temperatures and Sounds by the Same Smart Mask by Bingcan Liao, Pin Sun, Shuyi Chen, Rihong Huang, Junyu Yang, Guofeng Li, Chengzhi Lv, Nan Zhu, Shui Guan, Hailong Liu, Rong Liu, Ali Mansouri, Changkai Sun

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DECISION OF THE OPEN ASSIGNMENT PROBLEM BY STANDARD SIMPLEX METHOD by V. S. Mukha

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Analysis of effectiveness of the program of joined air traffic controlles and pilotes training by A. I. Stepnova, S. M. Stepanov, V. V. Borsoeva, V. A. Borsoev

“…Optimization of the educational process is currently an urgent task. The program of joint training can act as an optimization tool. …”
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Identification of copper metabolism-related subtypes, the development of a prognosis model, and characterization of the immune landscape in colorectal cancer by Geng Peng, Lin Zhong, Nan Lai, Lina Luo, Fu Cheng, Manzhao Ouyang

“…CMGs are effective biomarkers for predicting the prognosis of CRC patient and guiding immunotherapy.…”
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CD79A and GADD45A as novel immune-related biomarkers for respiratory syncytial virus severity in children: an integrated machine learning analysis and clinical validation by Juan Juan Chen, Zhang Ze Lu, Yu Xin Jing, Xing Mei Nong, Yi Qin, Jin Yang Huang, Na Lin, Jie Wei

“…Potential drug interactions for hug genes were predicted using the Drug-Gene Interaction Database (DGIdb). …”
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Data processing of non-stationary capillary viscometer for blood by V. G. Leshchenko, M. V. Goltsev, D. V. Mansurov, V. A. Mansurov

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Assessing the Risk of Natural and Socioeconomic Hazards Caused by Rainfall in the Middle Yellow River Basin by Yufeng Zhao, Shun Xiao, Xinshuang Wu, Shuitao Guo, Yingying Yao

“…In this study, we propose a comprehensive quantification framework and apply it to the Loess Plateau of northern China based on 40 years of climate data, streamflow measurements, and multiple spatial and geographical attribute datasets. A deep learning algorithm of long short-term memory (LSTM) was used to predict runoff, and the analytic hierarchy index was utilized to evaluate the comprehensive spatial risk considering natural and socioeconomic factors. …”
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Development of intelligent controller for high performance electric drives with hybrid CSA and RERNN technique by J. Prabhakaran, P. Thirumoorthi, M. Mathankumar, S. P. Mangaiyarkarasi

“…The CSA optimizes the voltage source inverter’s control signal, while RERNN predicts the optimal control signal. The system considered the variables of inertia, load torque, and rotor shaft angle. …”
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Integrative omics analysis reveals the genetic basis of fatty acid composition in Brassica napus seeds by Yuting Zhang, Yunhao Liu, Zhanxiang Zong, Liang Guo, Wenhao Shen, Hu Zhao

“…To elucidate the genetic underpinnings governing fatty acid composition, we then employ a combination of GWAS, TWAS, and dynamic transcriptomic analysis during seed development, along with the POCKET algorithm. We predict six candidate genes that are associated with fatty acid composition. …”
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Automatic identification and characteristics analysis of crack tips in rocks with prefabricated defects based on deep learning methods. by Mingtao Gao, Minhui Li, Lu Chen, Zihao Guo, Chengyang Guo, Liping Li, Changsen Bu

“…Especially in the rock specimen analysis of prefabricated multi-angle cracks, image quality and algorithm adaptability have emerged as the critical bottlenecks restricting the identification accuracy. …”
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Robust Adaptive Multiple Backtracking VBKF for In-Motion Alignment of Low-Cost SINS/GNSS by Weiwei Lyu, Yingli Wang, Shuanggen Jin, Haocai Huang, Xiaojuan Tian, Jinling Wang

“…Furthermore, the modified variational Bayesian Kalman filter (VBKF) that accurately adjusts the measurement noise covariance matrix is proposed, and the Expectation–Maximization (EM) algorithm is employed to refine the prior parameter of the predicted error covariance matrix. …”
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Development of a New Correlation Model for Heat Transfer in Solar Air Heater with Corrugated Absorber Plates Using Swarm Optimization by Abdulkadir Kocer, Uğur Ercan, Zeki Yetgin, Filiz Karaomerlioglu

“…As the main contribution, two different model equations, namely M1 and M2, for the correlation model of the solar heat transfer were proposed to predict the Nusselt number, where M2 is an original model and M1 is newly established with the fine-tuned coefficients. …”
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Investigating lightweight and interpretable machine learning models for efficient and explainable stress detection by Debasish Ghose, Ayan Chatterjee, Indika A. M. Balapuwaduge, Yuan Lin, Soumya P. Dash

“…Furthermore, our study has incorporated local interpretable model-agnostic explanations to provide comprehensive insights into the predictions made by the k-NN-based architecture.…”
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