Designing of Loss Optimum Regulator for Control of D.C. Electric Drive with Varying Inertia Moment in CoDeSys Programming System by S. O. Novikov, A. V. Paschenko

“…The given software is the most suitable for simulation and development of control system algorithms and execution of semi-full-scale tests without involvement of an actual object. …”
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Toward Digital Twin of Off-Road Vehicles Using Robot Simulation Frameworks by Arianna Rana, Antonio Petitti, Angelo Ugenti, Rocco Galati, Giulio Reina, Annalisa Milella

“…The paper presents the details of model design and implementation while investigating the best choice in developing the digital twin of off-road vehicles operating in the field. …”
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Developing and validating a machine learning-based model for predicting in-hospital mortality among ICU-admitted heart failure patients: A study utilizing the MIMIC-III database by De Su, Jie Zheng, Yue-kai Shao, Jun-ya Liu, Xin-xin Liu, Kun Yu, Bang-hai Feng, Hong Mei, Song Qin

“…LASSO regression was employed for feature selection, and various machine learning algorithms were utilized to train models, including logistic regression (LR), random forest (RF), and gradient boosting (GB), among others. …”
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A machine learning model revealed that exosome small RNAs may participate in the development of breast cancer through the chemokine signaling pathway by Jun-luan Mo, Xi Li, Lin Lei, Ji Peng, Xiong-shun Liang, Hong-hao Zhou, Zhao-qian Liu, Wen-xu Hong, Ji-ye Yin

“…We used machine learning algorithms to analyze small RNAs with significant differences between the two groups, fit the model through training sets, and optimize the model through testing sets. …”
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In-Memory Versus Disk-Based Computing with Random Forest for Stock Analysis: A Comparative Study by Chitra Joshi, Chitrakant Banchorr, Omkaresh Kulkarni, Kirti Wanjale

“…Background: The advancement of big data analytics calls for careful selection of processing frameworks to optimize machine learning effectiveness. Choosing the appropriate framework can significantly influence the speed and accuracy of data analysis, ultimately leading to more informed decision making. …”
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Monitoring and Comparative Analysis of NO₂ and HCHO in Shanghai Using Dual-Azimuth Scanning MAX-DOAS and TROPOMI by Hongmei Ren, Ang Li, Zhaokun Hu, Nannan Shao, Xinyan Yang, Hairong Zhang, Jiangman Xu, Jinji Ma

“…These findings not only reveal the spatiotemporal distribution characteristics of regional pollutants but optimize the sampling time and distance parameters for satellite–ground observation validation, providing data support for improving and enhancing the accuracy of satellite retrieval algorithms.…”
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Correlation between metformin use and mortality in acute respiratory failure: a retrospective ICU cohort study by Yunlin Yang, Jinfeng Liu, Yi Hou, Yuxun Wei, Liang Huang, Liang Huang, Wei Wei

“…Primary outcomes were in-hospital and ICU mortality, while 30-day and 90-day all-cause mortality served as secondary endpoints. …”
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Estimation of gas hydrate and free gas saturation using the rock physics model based on constrained least squares and trust region method in the Shenhu Area, South China Sea by Dajiang Meng, Dajiang Meng, Ruwei Zhang, Ruwei Zhang, Yuan Gu, Yuan Gu, Baojin Zhang, Baojin Zhang, Yunqian Lu, Yunqian Lu, Jiangnan Lin, Jiangnan Lin, Lijie Wang, Lijie Wang

“…We formulated the inversion as a multi-parameter constrained least squares problem and then used the trust region algorithm to find the optimal least-squares solution. …”
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Joint Lagrangian Relaxation and Dynamic Programming Approach for a Multi-Period Multi-Product Location-Inventory Problem by Claudio Araya-Sassi, German Paredes-Belmar, Gabriel Gutierrez-Jarpa, Ricardo Gatica Escobar

“…We propose a Lagrangian relaxation algorithm and the subgradient approach as a solution method. …”
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MAPE-ViT: multimodal scene understanding with novel wavelet-augmented Vision Transformer by Muhammad Waqas Ahmed, Touseef Sadiq, Hameedur Rahman, Sulaiman Abdullah Alateyah, Mohammed Alnusayri, Mohammed Alatiyyah, Dina Abdulaziz AlHammadi

“…The feature discrimination capability is further enhanced through optimization using the Gray Wolf algorithm. The processed features then flow into a dual-stream architecture, where an extreme learning machine handles multi-object classification, while conditional random fields (CRF) manage scene-level categorization. …”
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Enhanced Inverse Model Predictive Control for EV Chargers: Solution for DC–DC Side by Abdullah Berkay Bayindir, Ali Sharida, Sertac Bayhan, Haitham Abu-Rub

“…To address this challenge, the proposed method employs an adaptive estimation strategy utilizing a recursive least square algorithm for online dynamic model estimation. This real-time estimated model enables IMPC to predict optimal switching states with improved reliability. …”
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Application of Quantum Key Distribution to Enhance Data Security in Agrotechnical Monitoring Systems Using UAVs by Makhabbat Bakyt, Luigi La Spada, Nida Zeeshan, Khuralay Moldamurat, Sabyrzhan Atanov

“…QKD is not an encryption algorithm but a secure key distribution protocol that provides information-theoretic security by leveraging the principles of quantum mechanics. …”
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Classification of Cervical Biopsy Images Based on LASSO and EL-SVM by Pan Huang, Shuailei Zhang, Min Li, Jing Wang, Cailing Ma, Bowei Wang, Xiaoyi Lv

“…This paper proposes a method of cervical biopsy tissue image classification based on least absolute shrinkage and selection operator (LASSO) and ensemble learning-support vector machine (EL-SVM). Using the LASSO algorithm for feature selection, the average optimization time was reduced by 35.87 seconds while ensuring the accuracy of the classification, and then serial fusion was performed. …”
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Towards precision agriculture: metaheuristic model compression for enhanced pest recognition by Sana Parez, Norah Saleh Alghamdi, Tahir Mahmood, Waseem Ullah, Muhammad Attique Khan, Taha Houda, Naqqash Dilshad

“…To reduce model complexity and improve deployment feasibility, a metaheuristic optimization algorithm was incorporated that significantly reduces computational overhead without compromising performance. …”
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Maglev Derived Systems: An Interoperable Freight Vehicle Application Focused on Minimal Modifications to the Rail Infrastructure and Vehicles by Jesus Felez, Miguel A. Vaquero-Serrano, William Z. Liu, Carlos Casanueva, Michael Schultz-Wildelau, Gerard Coquery, Pietro Proietti

“…Target speed profiles were precomputed using dynamic programming, while a model predictive control algorithm determined the optimal train state and control trajectories. …”
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Exploring Stand Parameters Using Terrestrial Laser Scanning in <i>Pinus tabuliformis</i> Plantation Forests by Miaomiao He, Yawei Hu, Jiongchang Zhao, Yang Li, Bo Wang, Jianjun Zhang, Hideyuki Noguchi

“…A comparative shortest path (CSP) algorithm was used for individual tree segmentation to investigate the effect of parameter selection on measurement accuracy. …”
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A robust method to simultaneously place sensors and calibrate parameters for urban drainage pipe system models using Bayesian decision theory by Yuan Huang, Junyi Xiong, Jiangjiang Zhang, Feifei Zheng, Yiran Ji, Hoshin Gupta

“…The UDM is sequentially calibrated using an ensemble smoother algorithm with observation data collected from these strategically placed sensors. …”
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A Multi-Sensor Fusion Approach Combined with RandLA-Net for Large-Scale Point Cloud Segmentation in Power Grid Scenario by Tianyi Li, Shuanglin Li, Zihan Xu, Nizar Faisal Alkayem, Qiao Bao, Qiang Wang

“…A data acquisition scheme that integrates LiDAR and a binocular depth camera, implementing the FAST-LIO algorithm, is proposed to achieve the spatiotemporal synchronization and fusion of sensor data. …”
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Widefield ultra-high-density optical breast tomography system supplementing x-ray mammography by Miguel Mireles, Edward Xu, Morris Vanegas, Ailis Muldoon, Rahul Ragunathan, Shijie Yan, Bin Deng, Jayne Cormier, Mansi Saksena, Stefan A. Carp, Qianqian Fang

“…The OMCI system utilizes large field-of-view structured light illumination and single-pixel-camera based detection techniques to produce ultra-high spatial sampling density while ensuring that the inverse problem remains compact via the development of a unique target-adaptive pattern optimization technique to achieve compressive-sensing based measurements. …”
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An Artificial Intelligence-Based Approach With Photoplethysmogram and Heart Rate Variability for Sleep Bruxism Diagnosis by Omer Eris, Mehmet Recep Bozkurt, Seval Bulut Eris, Cahit Bilgin

“…Using four artificial intelligence (AI) algorithms, we built classification models that distinguished bruxism labels from control labels. …”
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