Optimization of distribution risk of hazardous materials in the production routing problem by Amin Farahbakhsh, Amirsaman Kheirkhah

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Assessing Agricultural Reuse Potential of Treated Wastewater: A Hybrid Machine Learning Approach by Daniyal Durmuş Köksal, Yeşim Ahi, Mladen Todorovic

“…By integrating machine learning models, this research enhances the accuracy and interpretability of wastewater quality predictions, providing a reliable framework for sustainable water resource management. …”
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Development Research on Integrating CNC Machine Tool with Plasma for Online Surface Heat Treatment by Shao-Hsien Chen, Bo-Ting Wang

“…In this study, the plasma was integrated with a lathe, and the online heat treatment was performed to achieve mechanical strength and hardness, to reduce the machining process and handling. However, for online heat treatment of cast iron FC25, it is important to study the parameters of the lathe and plasma, and the research method is used eventually to optimize the process and reduce the machining cost and machining error. …”
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A machine learning neural network architecture for the accelerating universe based modified gravity by Zulqurnain Sabir, Basma Souayeh, Zahraa Zaiour, Alyn Nazal, Mir Waqas Alam, Huda Alfannakh

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Posture Recognition and Behavior Tracking in Swimming Motion Images under Computer Machine Vision by Zheng Zhang, Cong Huang, Fei Zhong, Bote Qi, Binghong Gao

“…The objectives are realized by moving target detection and tracking, Gaussian mixture model, optimized correlation filtering algorithm, and Camshift tracking algorithm. …”
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Learning to rank quantum circuits for hardware-optimized performance enhancement by Gavin S. Hartnett, Aaron Barbosa, Pranav S. Mundada, Michael Hush, Michael J. Biercuk, Yuval Baum

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Harnessing the power of gradient-based simulations for multi-objective optimization in particle accelerators by Kishansingh Rajput, Malachi Schram, Auralee Edelen, Jonathan Colen, Armen Kasparian, Ryan Roussel, Adam Carpenter, He Zhang, Jay Benesch

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Prediction of Optimum Operating Parameters to Enhance the Performance of PEMFC Using Machine Learning Algorithms by Arunadevi M, Karthikeyan B, Anirudh Shrihari, Saravanan S, Sundararaju K, R Palanisamy, Mohamed Awad, Mohamed Metwally Mahmoud, Daniel Eutyche Mbadjoun Wapet, Abdulrahman Al Ayidh, Hany S. Hussein, Mahmoud M. Hussein, Ahmed I. Omar

“…It is clearly observed that the system temperature has significant percentage contribution as 96.92% on FC current and 86.22% on FC voltage compared to other parameters. Different MLAs are modelled to explore the PEMFC performance and results proved that gradient boosting regression provides better predictions compared to other algorithms such as decision tree regressor, support vector machine regressor, and random forest regression.…”
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Exploring New Paradigms in Time Series Prediction by Integrating Computer Simulations and Machine Learning by Pengcheng Wu, Yan Shi, Pengfei Zhao, Zhengzhao Gu

“…To address existing limitations, we propose a novel paradigm that integrates machine learning with computer simulations by embedding simulation-derived constraints and structural priors directly into the model training process. …”
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Epileptic Seizure Detection in EEG Signals Using Machine Learning and Deep Learning Techniques by Hepseeba Kode, Khaled Elleithy, Laiali Almazaydeh

“…This research presents a novel approach to detecting epileptic seizures leveraging the strengths of Machine Learning (ML) and Deep Learning (DL) algorithms in EEG signals. …”
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Mapping the landscape of machine learning in chronic disease management: A comprehensive bibliometric study by Shiying Shen, Wenhao Qi, Sixie Li, Jianwen Zeng, Xin Liu, Xiaohong Zhu, Chaoqun Dong, Bin Wang, Qian Xu, Shihua Cao

“…However, challenges such as limited collaboration, weak model generalization, and data privacy persist. Future efforts should prioritize algorithm optimization and multisource data integration to advance clinical applications.…”
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Machine learning based intrusion detection framework for detecting security attacks in internet of things by V. Kantharaju, H. Suresh, M. Niranjanamurthy, Syed Immamul Ansarullah, Farhan Amin, Amerah Alabrah

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Fall prediction in a quiet standing balance test via machine learning: Is it possible? by Juliana Pennone, Natasha Fioretto Aguero, Daniel Marczuk Martini, Luis Mochizuki, Alexandre Alarcon do Passo Suaide

“…An innovative approach for fall prediction is the machine learning. Machine learning is a computer-science area that uses statistics and optimization methods in a large amount of data to make outcome predictions. …”
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FPGA implementation of high throughput encoder and decoder design of lossless canonical Huffman machine by Erna Guguloth, Saidulu Vadtya, Thirumalesu Kudithi, Muni Rathnam Shanmugam, Ashok Nayak Banoth

“…To address these issues, we introduce a modern hardware architecture based on the Canonical Huffman encoding and decoding computation method, integrated with frequency counting, sorting, state machine optimization, and barrel shifter techniques. …”
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Mill+, an intuitive tool for simulating the milling process: Vibrations, cutting forces and surface quality control by Gorka Urbikain-Pelayo, Daniel Olvera-Trejo, Luis Norberto López de Lacalle, Alex Elías-Zuñiga, Itziar Cabanes

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State of Health Estimation of Li-ion Batteries Based on GWO-LSSVM by Ju-chen LI, Yu-li HU, Jian GAO, Li-teng ZENG, Yi ZHENG, Wen-shuai DAI

“…To address this issue, this study proposed a least-squares support vector machine(LSSVM) algorithm based on the grey wolf optimization(GWO) algorithm to estimate the SOH using the grey relational analysis method to choose constant current charging time as the input characteristic. …”
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Application of Machine Learning Algorithms to Predict Gas Sorption Capacity in Heterogeneous Porous Material by Tasbiha Ibad, Syed Muhammad Ibad, Haylay Tsegab, Rabeea Jaffari

“…Overall, this paper shows that machine learning can be used to forecast shale gas adsorption, and a well-trained model may be incorporated into a large numerical framework to optimize shale gas production curves.…”
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Variational optimization for quantum problems using deep generative networks by Lingxia Zhang, Xiaodie Lin, Peidong Wang, Kaiyan Yang, Xiao Zeng, Zhaohui Wei, Zizhu Wang

“…Abstract Optimization drives advances in quantum science and machine learning, yet most generative models aim to mimic data rather than to discover optimal answers to challenging problems. …”
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Maize Leaf Area Index Estimation Based on Machine Learning Algorithm and Computer Vision by Wanna Fu, Zhen Chen, Qian Cheng, Yafeng Li, Weiguang Zhai, Fan Ding, Xiaohui Kuang, Deshan Chen, Fuyi Duan

“…However, VisLAI consistently outperformed all machine learning models, especially during the grain filling stage, demonstrating superior robustness and accuracy. …”
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Recent Advances in Federated Learning for Connected Autonomous Vehicles: Addressing Privacy, Performance, and Scalability Challenges by Asad Ali, Huang Jianjun, Ayesha Jabbar

“…FL presents a decentralized infrastructure that allows collaborative learning, while also ensuring data privacy, as CAVs increasingly rely on machine learning to process large amounts of sensor data. …”
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