Prediction method of TBM excavation axis deviation for small turning tunnels based on LSTM neural network by Lijie DU, Hongda HAO, Qingwei LI, Yalei YANG, Weidong ZHANG, Jiayi LIU, Hongchao FENG

“…Then, the different structures of the model are analyzed. Different LSTM layers and different number of neurons are selected to form a new model structure, and the optimal model structure and optimal input time periods of different prediction time are determined. …”
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Study on the influence of light environment on brain fatigue of support workers in fully mechanized excavation face by Shuicheng TIAN, Peng TU, Hongxia LI

“…The evaluation indexes of brain fatigue were extracted by single factor analysis of variance and paired sample T-test. Support vector machine, K-nearest neighbor algorithm and random forest algorithm were used to construct the brain fatigue recognition model of the support worker in fully mechanized excavation face, and the confusion matrix was established to comprehensively compare the recognition effect of each model, and the optimal recognition model was selected. …”
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Distinguishing novel coronavirus influenza A virus pneumonia with CT radiomics and clinical features by Lianyu Sui, Huan Meng, Jianing Wang, Wei Yang, Lulu Yang, Xudan Chen, Liyong Zhuo, Lihong Xing, Yu Zhang, Jingjing Cui, Xiaoping Yin

“…Finally, constructing the radiomics model and clinical model using support vector machines and logistic regression methods, respectively. …”
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Precision diagnosis of tomato diseases for sustainable agriculture through deep learning approach with hybrid data augmentation by Kamaldeep Joshi, Sahil Hooda, Archana Sharma, Humira Sonah, Rupesh Deshmukh, Narendra Tuteja, Sarvajeet Singh Gill, Ritu Gill

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Efficient Edge AI for Next Generation Smart Mirror Applications by Nils Kucza, Florian Porrmann, Christian Stollenwerk, Jens Hagemeyer

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Effect of short basalt fibers on energy-dissipating properties of lightweight rubberized concrete shear wall by Artem Zaitsev, Evgenii Matiushin, Victoria Shvetsova, Alexander Burukhin, Stepan Konev, Radmir Karamov, Skolkovo Institute of Science and Technology, Moscow – 121205, Russia.

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Two Stages of Arrival Aircraft: Influencing Factors and Prediction of Integrated Arrival Time by Xiaowei Tang, Mengfan Ye, Jiaqi Wu, Shengrun Zhang

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Driving-Cycle-Adaptive Energy Management Strategy for Hybrid Energy Storage Electric Vehicles by Zhaocheng Lu, Tiezhu Zhang, Rui Li, Xinyu Ni

“…This study addresses the challenges of limited adaptability to driving cycles and significant battery capacity degradation in lithium battery–supercapacitor hybrid energy storage systems by proposing an adaptive EMS based on Dynamic Programming-Optimized Control Rules (DP-OCR). Dynamic programming is employed to optimize the rule-based control strategy, while the grey wolf optimizer (GWO) is utilized to enhance the least squares support vector machine (LSSVM) driving cycle recognition model. …”
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Improved performance of single sided axial flux for reduction in cogging torque (IMPACT) by Ahmed Dawood, Junaid Ikram, Muhammad Bilal Riaz, Khurram Saleem Alimgeer, Shumaila Javeed

“…Latin Hypercube Sampling (LHS) is used to create samples, kriging method is applied to approximate the model and optimized model is obtained by using Genetic Algorithm (GA).…”
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Research on Flexible Job Shop Scheduling Method for Agricultural Equipment Considering Multi-Resource Constraints by Zhangliang Wei, Zipeng Yu, Renzhong Niu, Qilong Zhao, Zhigang Li

“…The agricultural equipment market has the characteristics of rapid demand changes and high demand for machine models, etc., so multi-variety, small-batch, and customized production methods have become the mainstream of agricultural machinery enterprises. …”
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Multisensor Remote Sensing and AI-Driven Analysis for Coastal and Urban Resilience Classification by Sumei Ren, Bushra Ghaffar, Muhammad Mubbin, Muhammad Haseeb, Zainab Tahir, Sher Shah Hassan, Dmitry E. Kucher, Olga D. Kucher, M. Abdullah-Al-Wadud

“…The methodology includes a multistep deep learning pipeline, incorporating data preprocessing, feature extraction, class balancing with SMOTE, and LSTM-based classification. The proposed LSTM model is optimized to enhance performance with dropout regularization (0.3), an Adam optimizer (learning rate = 0.0003), and class weighting strategies. …”
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Research on Dynamic Energy Consumption of Front Warehouse Assembly Cold Storage and Analysis of Influencing Factors by Gu Han, Zhang Hua, Chen Xi, Zhao Ju

“…MATLAB was used to establish a mathematical model of factors related to cold storage load. The results show that when the pressure difference between the inside and outside of the cold storage exceeded the optimal operating range of the air curtain machine, the load of the cold storage caused by personnel entry and exit increased with the increase in internal and external environmental differential pressure, outside relative humidity, outside temperature, and frequency of personnel entry and exit. …”
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The PANEN nomogram: clinical decision support for patients with metastatic pancreatic neuroendocrine neoplasm referred for peptide receptor radionuclide therapy by Aviral Singh, Aviral Singh, Aviral Singh, Sebastian Sanduleanu, Harshad R. Kulkarni, Thomas Langbein, Philippe Lambin, Richard P. Baum

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Mortality Prediction Performance Under Geographical, Temporal, and COVID-19 Pandemic Dataset Shift: External Validation of the Global Open-Source Severity of Illness Score Model by Takeshi Tohyama, MD, PhD, Liam G. McCoy, MD, MSc, Euma Ishii, MD, PhD, Sahil Sood, Jesse Raffa, PhD, Takahiro Kinoshita, MD, MPH, Leo Anthony Celi, MD, MPH, MSc, Satoru Hashimoto, MD, PhD

“…While established models have long been used for risk prediction, healthcare has evolved significantly, and the optimal model must be selected for evaluation in line with contemporary healthcare settings and regional considerations. …”
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Autonomous International Classification of Diseases Coding Using Pretrained Language Models and Advanced Prompt Learning Techniques: Evaluation of an Automated Analysis System Usin... by Yan Zhuang, Junyan Zhang, Xiuxing Li, Chao Liu, Yue Yu, Wei Dong, Kunlun He

“… BackgroundMachine learning models can reduce the burden on doctors by converting medical records into International Classification of Diseases (ICD) codes in real time, thereby enhancing the efficiency of diagnosis and treatment. …”
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Seed purity assessment by means of spectral imaging by G.V. Nesterov, A.V. Guryleva, A.A. Zolotukhina, D.S. Fomin, D.S. Fomin, Y.K. Shashko, A.S. Machikhin

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Analytic Evaluation of the Statistical Power of Accelerated Reliability Demonstration Tests by Philipp Mell, Martin Dazer

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Genome-wide profiling of circulating microRNAs in adolescent idiopathic scoliosis and their relation to spinal deformity severity, and disease pathophysiology by Nasrin Khatami, Iurie Caraus, Mahamuda Rahaman, Evguenia Nepotchatykh, Mohamed Elbakry, Wesam Elremaly, Anita Franco, Marie Beauséjour, Anne-Marie Laberge, Stefan Parent, Hubert Labelle, Carl-Éric Aubin, Jean Lachaine, Alain Moreau

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Enhanced fibrotic potential of COL1A1hiNR4A1low fibroblasts in ischemic heart revealed by transcriptional dynamics heterogeneity analysis at both bulk and single-cell levels by Cheng Luo, Cheng Luo, Cheng Luo, Baoping Tan, Luoxiang Chu, Liqiang Chen, Xinglong Zhong, Yangyang Jiang, Yuluan Yan, Fanrui Mo, Hong Wang, Fan Yang, Fan Yang

“…Differentially expressed genes (DEGs) for the specific cell cluster with the highest fibrotic transcription dynamics were identified and integrated with bulk RNA sequencing data for analysis. Multiple machine learning models were employed to identify the optimal gene panel for diagnosing ischemic heart disease (IHD) based on the intersected DEGs. …”
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A Data-Driven Approach to Analyzing Fuel-Switching Behavior and Predictive Modeling of Liquefied Natural Gas and Low Sulfur Fuel Oil Consumption in Dual-Fuel Vessels by Hyunju Kim, Sangbong Lee, Jihwan Lee, Donghyun Kim

“…This study examines the energy consumption patterns of dual-fuel engines powered by LNG and develops machine learning models using LightGBM to predict fuel usage for both fuel oil (FO) and gas (GAS) modes. …”
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