Framework for Analysis of Queueing Systems with Correlated Arrival Processes and Simultaneous Service of a Restricted Number of Customers in Scenarios with an Infinite Buffer and R... by Alexander Dudin, Sergei Dudin, Agassi Melikov, Olga Dudina

“…The results can be used for performance evaluation and capacity planning of various queueing models with the Markov arrival process and a variety of different service mechanisms that provide simultaneous service to many customers.…”
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Human Activity Recognition: A Comparative Study of Validation Methods and Impact of Feature Extraction in Wearable Sensors by Saeed Ur Rehman, Anwar Ali, Adil Mehmood Khan, Cynthia Okpala

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Monitoring and Analyzing Driver Physiological States Based on Automotive Electronic Identification and Multimodal Biometric Recognition Methods by Shengpei Zhou, Nanfeng Zhang, Qin Duan, Xiaosong Liu, Jinchao Xiao, Li Wang, Jingfeng Yang

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A Machine Learning Framework for Classroom EEG Recording Classification: Unveiling Learning-Style Patterns by Rajamanickam Yuvaraj, Shivam Chadha, A. Amalin Prince, M. Murugappan, Md. Sakib Bin Islam, Md. Shaheenur Islam Sumon, Muhammad E. H. Chowdhury

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A VIKOR-Based Sequential Three-Way Classification Ranking Method by Wentao Xu, Jin Qian, Yueyang Wu, Shaowei Yan, Yongting Ni, Guangjin Yang

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Combination of Conditioning Factors for Generation of Landslide Susceptibility Maps by Extreme Gradient Boosting in Cuenca, Ecuador by Esteban Bravo-López, Tomás Fernández, Chester Sellers, Jorge Delgado-García

“…In this study, a specific Machine Learning (ML) method was further analyzed due to the good results obtained in the previous stage of this research. The algorithm implemented is Extreme Gradient Boosting (XGBoost), which was used to evaluate the susceptibility to landslides recorded in the city of Cuenca (Ecuador) and its surroundings, generating the respective Landslide Susceptibility Maps (LSM). …”
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Towards Effective Parkinson’s Monitoring: Movement Disorder Detection and Symptom Identification Using Wearable Inertial Sensors by Umar Khan, Qaiser Riaz, Mehdi Hussain, Muhammad Zeeshan, Björn Krüger

“…The proposed pipeline employs and evaluates manual feature crafting for classical machine learning algorithms, as well as an RNN-CNN-inspired deep learning model that does not require manual feature crafting. …”
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An Autoencoder-Based Task-Oriented Semantic Communication System for M2M Communication by Prabhath Samarathunga, Hossein Rezaei, Maheshi Lokumarambage, Thushan Sivalingam, Nandana Rajatheva, Anil Fernando

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Utilizing Cell Transmission Models to Alleviate Accident-Induced Traffic Congestion in Two-Way Grid Networks by Yi-Sheng Huang, Yi-Shun Weng, Chun-Yu Shih

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Using Smartwatches in Stress Management, Mental Health, and Well-Being: A Systematic Review by Nikoletta-Anna Kapogianni, Angeliki Sideraki, Christos-Nikolaos Anagnostopoulos

“…Moreover, it highlights how different algorithms—such as Support Vector Machines (SVMs), Random Forests, Deep Neural Networks, and Boosting methods—perform across various physiological signals (e.g., HRV, EDA, skin temperature). …”
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The Specialist’s Paradox: Generalist AI May Better Organize Medical Knowledge by Carlo Galli, Maria Teresa Colangelo, Marco Meleti, Elena Calciolari

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Self-Supervised Keypoint Learning for the Geometric Analysis of Road-Marking Templates by Chayanon Sub-r-pa, Rung-Ching Chen

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Optimized Energy Consumption of Electric Vehicles with Driving Pattern Recognition for Real Driving Scenarios by Bedatri Moulik, Sanmukh Kaur, Muhammad Ijaz

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Tradeoffs When Building and Running Cohort and Patient-Level Markov Simulation Models by Balázs Nagy, Ahmad Nader Fasseeh, Jonathan D. Campbell, Zoltán Kaló, Kareem Ahmed El-Fass, Rok Hren, Bertalan Németh

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Clinical Validation of a Computed Tomography Image-Based Machine Learning Model for Segmentation and Quantification of Shoulder Muscles by Hamidreza Rajabzadeh-Oghaz, Josie Elwell, Bradley Schoch, William Aibinder, Bruno Gobbato, Daniel Wessell, Vikas Kumar, Christopher P. Roche

“…Prior to use in a clinical setting, this machine learning (ML)-based segmentation algorithm requires rigorous validation. The aim of this study is to conduct shoulder expert validation of a novel deltoid ML auto-segmentation and quantification tool. …”
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The path-label reconciliation (PLR) dissimilarity measure for gene trees by Alitzel López Sánchez, José Antonio Ramírez-Rafael, Alejandro Flores-Lamas, Maribel Hernández-Rosales, Manuel Lafond

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Research on Discrete Dynamic System Modeling of Vocal Performance Teaching Platform Based on Big Data Environment by Xiaohui Gong

“…The collection of data and information is realized from the aspects of students’ class state, vocal music examination results, classroom interaction, etc., and the comprehensive analysis is carried out using the deep recursive neural network algorithm, to realize the multiple analysis and objective evaluation of the whole process of different teaching modes of national vocal music in music colleges and universities, according to the different characteristics and teaching objectives of the teaching process of national vocal music in music colleges and universities The standard requires accurate analysis and evaluation. …”
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Normalized Robust FOPID Controller Regulation Based on Small Gain Theorem by Shuo Zhang, Lu Liu

“…Another parameter, β, is also available to serve as a tuning knob when larger robust evaluation function value is needed. Therefore, the controlled systems can be stabilized and can achieve quite satisfactory robust control performance using the proposed algorithm. …”
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Rehabilitation training method for motor dysfunction based on video stream matching by Hong Yanyan

“…And the patients’ evaluation of the algorithm is high.…”
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Digital twin and contact analysis of ultra-long distance coiled tubing operation structures [version 2; peer review: 1 approved, 2 approved with reservations] by Wenlan Wei, Jiarui Cheng, Hao Qu, Maliang Wang, Wenyuan Wang

“…On this basis, a feedback-corrected contact algorithm is introduced to dynamically identify and correct the contact state of continuous tubing under different downhole running trajectories. …”
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