Modeling of Flow Stress of 2026 Al Alloy under Hot Compression by Zheng-bing Xiao, Yuan-chun Huang, Yu Liu

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A Swarm-Based Multi-Objective Framework for Lightweight and Real-Time IoT Intrusion Detection by Hessah A. Alsalamah, Walaa N. Ismail

“…MOOIDS-IoT combines a Genetic Algorithm (GA)-based feature selection technique with a multi-objective Particle Swarm Optimization (PSO) algorithm. PSO optimizes convergence speed, model complexity, and classification accuracy by dynamically adjusting the weights and thresholds of the deployed classifiers. …”
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Improving thermal state preparation of Sachdev–Ye–Kitaev model with reinforcement learning on quantum hardware by Akash Kundu

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Robust Cross-Validation of Predictive Models Used in Credit Default Risk by Jose Vicente Alonso, Lorenzo Escot

“…Model validation is a challenging Machine Learning task, usually more difficult for consumer credit default models because of the availability of small datasets, the modeling of low-frequency events (imbalanced data), and the bias in the explanatory variables induced by the train/test sets split of the validation techniques (covariate shift). …”
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Predicting Student Behavior Using a Neutrosophic Deep Learning Model by Ahmed Mohamed Shitaya, Mohamed El Syed Wahed, Saied Helemy Abd El Khalek, Amr Ismail, Mahmoud Y. Shams, A. A. Salama

“…An intelligent system was designed to assess the difficulty level of preliminary exams and select top-performing advanced students using a Neutrosophic Deep Learning Model. The dataset was randomly split into training (80%) and testing (20%) sets, and the model, trained with the Adam optimizer at a 0.001 learning rate over 50 epochs, incorporated early stopping based on validation loss. …”
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Ensemble ecological niche modeling of West Nile virus probability in Florida. by Sean P Beeman, Andrea M Morrison, Thomas R Unnasch, Robert S Unnasch

“…This model was created through the weighted averaging of three separate machine learning models-boosted regression tree, random forest, and maximum entropy-developed for this study using sentinel chicken surveillance and remote sensing data. …”
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DEVELOPMENT OF A MULTI-OBJECTIVE PRODUCTION PLANNING MODEL FOR A SAWMILL by SEGUN ABIODUN ALONGE, CHRISTOPHER OSITA ANYAECHE

“… Based on the objectives set out for a Sawmill, a goal programming model was developed to simultaneously consider the production volumes goal, sales revenue goal, production cost goal, and machine utilization goal in order to develop its production plans for a horizon. …”
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Modelling of Metal Removal Rate in Copper Alloy Milling Using MATLAB by Musaddak Maher Abdul Zahra, Ekrem Yanmaz, T. Bothichandar

“…In order to secure reliable machining operations, these models were designed for customer recommendation and cutting data optimization. …”
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Research on Control System for Material Transport Vehicle Based on Stacking Model by LIU Yuanming, TANG Lingsi, Zen Shuhua

“…This paper introduces an automatic control system for material transport vehicles, specifically designed to improve their working efficiency, ensure loading quality, and enhance work safety. Firstly, a stacking model was established according to material characteristics, enabling accurate prediction of material distribution to prevent partial loading. …”
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Professional Development Analytics: A Smart Model for Industry 5.0 by Natalia Tusquellas, Raúl Santiago, Ramon Palau

“…The model’s main focus is to provide a new design model that concentrates on how artificial intelligence (AI) can optimize personalized training and how it can improve employees’ technical and soft skills, enabling companies to create their talent map at the same time. …”
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Universal IoT-Enabled Smart Battery Charging Optimization: Leveraging AI, Automata Theory, and Real-Time Data for Enhanced Lifespan and Efficiency by Arora Divyansh, Goswami Ananya, Ranjan Mritunjay, Sattar Arif Md

“…The system utilizes Artificial Intelligence (AI), Automata Theory, and sensor data in real-time to develop a dynamic context-aware charging strategy that learns from the unique usage patterns and battery status of every device. By applying machine learning models like Kalman Filters, Recurrent Neural Networks (RNNs), and Finite State Machines (FSM), the system charges behaviors smartly, optimizing power consumption, charging efficiency, and battery life. …”
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Exploring the prognostic impact of triglyceride-glucose index in critically ill patients with first-ever stroke: insights from traditional methods and machine learning-based mortal... by Yang Chen, Zhenkun Yang, Yang Liu, Yuanjie Li, Ziyi Zhong, Garry McDowell, Coleen Ditchfield, Taipu Guo, Mingjuan Yang, Rui Zhang, Bi Huang, Ying Gue, Gregory Y. H. Lip

“…We aims to explore the relationships between TyG with ICU all-cause mortality and other prognosis, and to develop machine learning (ML) models in predicting ICU all-cause mortality in the first-ever strokes. …”
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UCSwin‐UNet model for medical image segmentation based on cardiac haemangioma by Jian‐Ting Shi, Gui‐Xu Qu, Zhi‐Jun Li

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Integrating protein language models and automatic biofoundry for enhanced protein evolution by Qiang Zhang, Wanyi Chen, Ming Qin, Yuhao Wang, Zhongji Pu, Keyan Ding, Yuyue Liu, Qunfeng Zhang, Dongfang Li, Xinjia Li, Yu Zhao, Jianhua Yao, Lei Huang, Jianping Wu, Lirong Yang, Huajun Chen, Haoran Yu

“…Abstract Traditional protein engineering methods, such as directed evolution, while effective, are often slow and labor-intensive. Advances in machine learning and automated biofoundry present new opportunities for optimizing these processes. …”
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Assessment on electrical discharge machining of ultrasonication assisted stir-casted AA8081-B4C-Gr hybrid composites and prediction using Levenberg-Marquardt technique by M. Vivekanandhan, N. Senthilkumar, B. Deepanraj, Nithesh Naik

“…Desirability analysis finds the optimal machining condition as Ton of 3 μs, Toff of 8.63 μs, and DI of 20 A, providing a higher MRR (0.25 g/min), lower OC (0.278 mm), and TWR (0.058 g/min) with a desirability value of 0.776. …”
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Mixture of Expert Large Language Model for Legal Case Element Recognition by YIN Hua, WU Zihao, LIU Tingting, ZHANG Jiajia, GAO Ziqian

“…Compared with earlier methods based on deep learning and machine reading comprehension, the generative element recognition approach using large language models (LLM) holds greater potential for complex reasoning. …”
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Bioenergy Model of Plant Raw Materials and Assessment of Feed Production Technologies by M. A. Kerimov, D. V. Ivanov

“…Efficiency assessment criteria are proposed for the mechanical energy consumption during fodder crop cultivation, plant material processing and feed storage. A mathematical model is developed making it possible to study implicit variables in a complex system of accumulation and entropy of feed exchange energy, take optimal engineering decisions to justify and improve the technologies for feed cultivation, harvesting and preparation, as well as its effective use.…”
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Exploring the fresh and rheology properties of 3D printed concrete with fiber reinforced composites (3DP-FRC): a novel approach using machine learning techniques by Risul Islam Rasel, Md Minaz Hossain, Md Hasib Zubayer, Chaoqun Zhang

“…In conclusion, the ML models were effectively trained and optimized, resulting in accurate and highly predictive capabilities for the parameters of interest.…”
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Utilizing Circadian Heart Rate Variability Features and Machine Learning for Estimating Left Ventricular Ejection Fraction Levels in Hypertensive Patients: A Composite Multiscale E... by Nanxiang Zhang, Qi Pan, Shuo Yang, Leen Huang, Jianan Yin, Hai Lin, Xiang Huang, Chonglong Ding, Xinyan Zou, Yongjun Zheng, Jinxin Zhang

“…We developed a comprehensive machine learning framework that initiated with preprocessed ECG signal in one-hour intervals to extract CMSE-based heart rate variability (HRV) features, then utilized machine learning models such as linear regression (LR), Support Vector Machines (SVMs), and random forests (RFs) with recursive feature elimination for optimal LVEF estimation. …”
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Numerical Modeling on the Damage Behavior of Concrete Subjected to Abrasive Waterjet Cutting by Xueqin Hu, Chao Chen, Gang Wang, Jenisha Singh

“…Based on the parametric analysis, two optimized abrasive waterjet configurations are proposed: one tailored for rock fragmentation in tunnel boring machine (TBM) operations; and another for cutting reinforced concrete piles in shield tunneling applications. …”
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