Unsupervised Anomaly Detection on Metal Surfaces Based on Frequency Domain Information Fusion by Wenfei Wu, Tao Tao, Jinsheng Xiao, Yichu Yao, Jianfeng Yang

“…In addition, a feature selection module is designed to improve the anomaly detection capability and reduce the computational redundancy by selecting the most representative subset of features. …”
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Spatiotemporal Correlation Based Fault-Tolerant Event Detection in Wireless Sensor Networks by Kezhong Liu, Yang Zhuang, Zhibo Wang, Jie Ma

“…Reliable event detection is one of the most important objectives in wireless sensor networks (WSNs), especially in the presence of faulty nodes. …”
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High precision water quality retrieval in Dianchi Lake using Gaofen 5 data and machine learning methods by Yuewen Feng, Jun Zhang, Sanjie Guo, Yunbai Zhang, Zhongwei Zhang

“…The Back Propagation Nondominated Sorting Genetic Algorithm-II (BP-NGA) model consistently yielded positive results for most WQI. (2) Water quality in Dianchi varied significantly by region and season. (3) It was recommended to build wetlands and ecological parks on the southwest side of Dianchi and improve sewage interception pipelines on the northeast side to lessen the risk of eutrophication by reducing the inflow of nitrogen and phosphorus.…”
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An Optimised Method for Fetching and Transforming Survey Data based on SQL and R Programming Language by Hasan et al.

“…The development of information systems in recent years has contributed to various methods of gathering information to evaluate IS performance. The most common approach used to collect information is called the survey system. …”
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Real-time temperature prediction of large-scale lithium battery module driven by data based on few measurement points by Jiajie HAN, Qingyang YUAN, Yu LI, Bo ZHANG, Ke XUE, Tian LAN

“…This slight error increase is attributed to the complex heat transfer dynamics near cooling interfaces, which pose challenges for most data-driven models. This study highlights the effectiveness of the Gappy POD algorithm in managing the thermal dynamics of large-scale energy storage systems in real time. …”
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Prediction of Diabetes in Middle-Aged Adults: A Machine Learning Approach by Gideon Addo, Bismark Amponsah Yeboah, Michael Obuobi, Raphael Doh-Nani, Seidu Mohammed, David Kojo Amakye

“…Future research should explore genetic, lifestyle, and environmental factors to improve diagnostic accuracy.…”
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Machine learning analysis of molecular dynamics properties influencing drug solubility by Zeinab Sodaei, Saeid Ekrami, Seyed Majid Hashemianzadeh

“…Through rigorous analysis, the properties with the most significant influence on solubility were identified and subsequently used as input features for four ensemble machine learning algorithms: Random Forest, Extra Trees, XGBoost, and Gradient Boosting. …”
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Minding the gap. Drug-related problems among breastfeeding women by Karolina Morze, Edyta Szałek, Magdalena Waszyk-Nowaczyk

“…Future research should focus on developing evidence-based guidelines for medication use during lactation and improving healthcare provider education to optimize maternal and infant health.…”
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Blockchain-Assisted Verifiable and Multi-User Fuzzy Search Encryption Scheme by Xixi Yan, Pengyu Cheng, Yongli Tang, Jing Zhang

“…Locality-sensitive hashing and bloom filters are used to realize multi-keyword fuzzy search, and the bigram segmentation algorithm is optimized for keyword conversion to improve search accuracy. …”
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Enhanced engine misfire diagnosis through integration of vibration and acoustic emission signals using artificial neural networks by Mohamed H. Abdelati, M. Mourad, Al-Hussein Matar, M. Rabie

“…After all the features were put into a complete matrix, the selection algorithms chose the most essential ones for classifying the data. …”
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Optimising the Selection of Input Variables to Increase the Predicting Accuracy of Shear Strength for Deep Beams by Mohammed Majeed Hameed, Faidhalrahman Khaleel, Mohamed Khalid AlOmar, Siti Fatin Mohd Razali, Mohammed Abdulhakim AlSaadi

“…The feature-section algorithm based on the combination of genetic algorithm and information theory (GAITH) was used to select the most important input combinations and introduce them into the prediction models. …”
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Accelerating RRT* convergence with novel nonuniform and uniform sampling approach by Sivasankar Ganesan, Mohanraj Thangamuthu, Balakrishnan Ramalingam, Madan Mohan Rayguru, Sethu Narayanan Tamilselvan

“…Due to its asymptotic optimality, the optimal rapidly-exploring random tree (RRT*) algorithm is the most widely used among these. …”
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Artificial Intelligence in Glioblastoma—Transforming Diagnosis and Treatment by Alen Rončević, Nenad Koruga, Anamarija Soldo Koruga, Robert Rončević

“…In treatment planning, AI could improve approaches by optimizing surgical resection, radiotherapy regimen, and chemotherapy protocols. …”
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Reduction of Multiplicative Noise in Radar Images by A. A. Tuzova, V. A. Pavlov, A. A. Belov

“…The proposed algorithm allowed optimal parameters for several speckle noise filters to be determined. …”
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Machine Learning-Based Prediction of First Trimester Down Syndrome Risk in East Asian Populations by Chen YT, Chen GJ, Lin YS

“…This study employed multiple machine learning models to perform risk prediction and result exploration for first-trimester Down syndrome in East Asian populations, aiming to identify an optimal risk prediction model that will enhance future predictions of Down syndrome risk and improve the efficiency of the screening process.Patients and Methods: This study collected data from the Down syndrome screening database at Taipei Chang Gung Memorial Hospital from May 1, 2018, to February 29, 2024. …”
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A Minimal Path-Based Method for Computing Multistate Network Reliability by Xiu-Zhen Xu, Yi-Feng Niu, Can He

“…Most of modern technological networks that can perform their tasks with various distinctive levels of efficiency are multistate networks, and reliability is a fundamental attribute for their safe operation and optimal improvement. …”
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Mechanism for data recovery as a result of data corruption, infection and/or unauthorized modification by L. V. Cherkesova, V. A. Savelyev, E. A. Revyakina, A. R. Polulyakh, M. A. Sementsov

“…To develop the software module, a reversible incremental backup algorithm was chosen as the most suitable for the developed algorithm and more convenient to use.Conclusion. …”
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An AIoT-Based Automated Farming Irrigation System for Farmers in Limpopo Province by Relebogile Langa, Michael Nthabiseng Moeti, Thabiso Maubane

“…A machine learning precipitation prediction algorithm optimizes water usage. The paper also describes a system with multiple sensors that detect soil parameters, and automatically irrigate land based on soil moisture by switching the motor on/off. …”
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Predictive framework of vegetation resistance in channel flow by Fengcong Jia, Weijie Wang, Yu Han, Jiayu Du, Yue Zhang, Zihan Liu, Hairong Gao

“…This study introduces a machine learning-based framework for predicting vegetation flow resistance, incorporating nine ML methods, including SVM, XGBoost, and BP. To improve predictive performance, optimization algorithms such as PSO, WSO, and RIME were applied. …”
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An Efficient Design of DCT Approximation Based on Quantum Dot Cellular Automata (QCA) Technology by Ismail Gassoumi, Lamjed Touil, Bouraoui Ouni, Abdellatif Mtibaa

“…Optimization for power is one of the most important design objectives in modern digital image processing applications. …”
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