Impact of Concrete Sealer and Salt Usage on Concrete Bridge Deck Condition and Life Cycle Cost by Wei Huang, Hao Wang, Danny Xiao

“…To achieve this goal, machine learning models were built to predict the evolution of bridge deck rating. …”
Get full text

Red Fox Optimization-Based Estimation Algorithms for Splitting Tensile Strength of Basalt Fiber Reinforced Concrete by Xiao Wu, Daoyong Zhu, Qin Yan

“…This study aimed to evaluate the predictive ability of multiple methods based on machine learning (ML) for the STS of BFRC and to clarify their fundamental concepts. …”
Get full text

How Can Business Analytics Enhance Decision-Making in Oil and Gas Surface Facilities? by Agung Prasetya, Meditya Wasesa, Yos Sunitiyoso

“…Predictive analytics enables proactive maintenance through machine learning, while prescriptive analytics optimizes operations using simulations and multi-objective decision models. …”
Get full text

Framework for Groove Rating in Exercise-Enhancing Music Based on a CNN–TCN Architecture with Integrated Entropy Regularization and Pooling by Jiangang Chen, Junbo Han, Pei Su, Gaoquan Zhou

“…The integration of entropy pooling and regularization is critical, with their omission leading to notable reductions in R² values. Our method also surpasses the performance of CNN and other machine-learning models, including long short-term memory (LSTM) networks and support vector machine (SVM) variants. …”
Get full text

Tunable Energy-Efficient Approximate Circuits for Self-Powered AI and Autonomous Edge Computing Systems by Shubham Garg, Kanika Monga, Nitin Chaturvedi, S. Gurunarayanan

“…Moreover, this problem becomes more complex while deploying computationally intensive heavy machine learning (ML) models on energy-constrained edge devices. …”
Get full text

A neural network-based synthetic diagnostic of laser-accelerated proton energy spectra by Christopher J. G. McQueen, Robbie Wilson, Timothy P. Frazer, Martin King, Matthew Alderton, Ewan F. J. Bacon, Ewan J. Dolier, Thomas Dzelzainis, Jesel K. Patel, Maia P. Peat, Ben C. Torrance, Ross J. Gray, Paul McKenna

“…Abstract Machine learning can revolutionize the development of laser-plasma accelerators by enabling real-time optimization, predictive modeling and experimental automation. …”
Get full text

Impurity rates detection for pepper harvesting based on YOLOv8n-Seg-ASB and random forest by Lijian Lu, Jin Lei, Chenming Cheng, Shiguo Wang, Chengfu Wang, Xinyan Qin

“…Experimental results show that the YOLOv8n-Seg-ASB model achieves enhanced combined segmentation performance, with a 14.3 % increase in mAP@0.5, a 17.35 % reduction in model parameters, and an inference speed of 82.2 FPS. …”
Get full text

A Hybrid Artificial Intelligence Approach for Down Syndrome Risk Prediction in First Trimester Screening by Emre Yalçın, Serpil Aslan, Mesut Toğaçar, Süleyman Cansun Demir

“…The final features are classified using machine learning algorithms, including Bagged Trees and Naive Bayes. …”
Get full text

An explainable AI-based framework for predicting and optimizing blast-induced ground vibrations in surface mining by Charan Kumar Ala, Zefree Lazarus Mayaluri, Aman Kaushik, Nikhat Parveen, Surabhi Saxena, Abu Taha Zamani, Debendra Muduli

“…This study proposes a novel hybrid artificial intelligence (AI) framework that integrates physics informed neural networks (PINNs) with conventional machine learning (ML) algorithms for the accurate prediction and optimization of BIGV. …”
Get full text

Sustainable Geothermal Energy: A Review of Challenges and Opportunities in Deep Wells and Shallow Heat Pumps for Transitioning Professionals by Tawfik Elshehabi, Mohammad Alfehaid

“…Sustainable practices, including reinjection, machine learning-driven fracture modeling, and the use of corrosion-resistant alloys, enhance well integrity and long-term performance. …”
Get full text

An Integrated Algorithm with Feature Selection, Data Augmentation, and XGBoost for Ovarian Cancer by Jingxun Cai, Zne-Jung Lee, Zhihxian Lin, Chih-Hung Hsu, Yun Lin

“…With the rapid development of machine learning, numerous efficient classification prediction models have emerged. …”
Get full text

Optimization of Sensor Targeting Configuration for Intelligent Tire Force Estimation Based on Global Sensitivity Analysis and RBF Neural Networks by Yu Zhang, Guolin Wang, Haichao Zhou, Jintao Zhang, Xiangliang Li, Xin Wang

“…To address the demand for accurate tire force prediction in active safety control systems under various operating conditions, this paper proposes an intelligent tire force estimation method, integrating sensor-measured dynamic response parameters and machine learning techniques. A 205/55 R16 radial tire was selected as the research object, and a finite element model was established using the parameterized modeling approach with the ABAQUS finite element simulation software. …”
Get full text

SGA-Driven feature selection and random forest classification for enhanced breast cancer diagnosis: A comparative study by Abrar Yaqoob, Navneet Kumar Verma, Mushtaq Ahmad Mir, Ghanshyam G. Tejani, Nashwa Hassan Babiker Eisa, Hind Mamoun Hussien Osman, Mohd Asif Shah

“…The mean accuracies ranged from 85.35 to 94.33%, highlighting a balance between feature reduction and classification accuracy. Future work will explore the integration of other nature-inspired algorithms and deep learning models to further enhance performance and clinical applicability.…”
Get full text

Impact of climate change on snow avalanche activity in the Swiss Alps by S. Mayer, M. Hendrick, A. Michel, B. Richter, J. Schweizer, H. Wernli, A. van Herwijnen

“…We assess avalanche activity by employing machine learning models trained with observed records of avalanches. …”
Get full text

Enhancing precision flood mapping: Pahang's vulnerability unveiled. by Tahmina Afrose Keya, Siventhiran S Balakrishnan, Maheswaran Solayappan, Saravana Selvan Dheena Dhayalan, Sreeramanan Subramaniam, Low Jun An, Anthony Leela, Kevin Fernandez, Prahan Kumar, A Lokeshmaran, Abhijit Vinodrao Boratne, Mohd Tajuddin Abdullah

“…The objective of the research was to create a flood susceptibility map for the designated area by employing an Ensemble Machine Learning (EML) algorithm based on geographic information system (GIS). …”
Get full text

Enhancing student success prediction in higher education with swarm optimized enhanced efficientNet attention mechanism. by Meshari Alazmi, Nasir Ayub

“…Predicting student performance is crucial for providing personalized support and enhancing academic performance. Advanced machine-learning approaches are being used to understand student performance variables as educational data grows. …”
Get full text

Early Detection and Dynamic Grading of Sweet Potato Scab Based on Hyperspectral Imaging by Xiaosong Ning, Qiyao Xia, Fajiang Tang, Ziyu Ding, Xiawei Ding, Fanguo Zeng, Zhangying Wang, Hongda Zou, Xuejun Yue, Lifei Huang

“…This study investigates the early detection of sweet potato scab by using hyperspectral imaging and machine learning techniques. The research focuses on developing an accurate, economical, and non-destructive approach for disease detection and grading. …”
Get full text

Gut microbiome alterations and hepatic encephalopathy post-TIPS in liver cirrhosis patients by Shengpeng Li, Zhengguo Xu, Hua Diao, An Zhou, Dianji Tu, Sumin Wang, Yunxuan Feng, Xiaojie Feng, Yi Lai, Shiming Yang, Bo Tang

“…Conclusion Multiple machine learning models revealed that P.vulgatus may serve as a significant predictive microbe for hepatic encephalopathy after TIPS, which may be closely related to its ability to metabolize ammonia. …”
Get full text

Real-Time Dolphin Whistle Detection on Raspberry Pi Zero 2 W with a TFLite Convolutional Neural Network by Rocco De Marco, Francesco Di Nardo, Alessandro Rongoni, Laura Screpanti, David Scaradozzi

“…These advancements enable low-cost devices for real-time cetacean presence detection, offering transformative potential for bycatch reduction and adaptive deterrence systems. This study bridges artificial intelligence innovation with ecological stewardship, providing a scalable framework for deploying machine learning in resource-constrained settings while addressing urgent conservation challenges.…”
Get full text

A service-oriented microservice framework for differential privacy-based protection in industrial IoT smart applications by Dileep Kumar Murala, K. Vara Prasada Rao, Veera Ankalu Vuyyuru, Beakal Gizachew Assefa

“…The architecture integrates Differential Privacy (DP) mechanisms into the machine learning pipeline to safeguard sensitive information. …”
Get full text