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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Enhancing high pressure pulsation test bench performance: a machine learning approach to failure condition tracking by Aslı Aksoy, Ömer Haki

“…The utilization of FCTT has enabled the prediction of HPPT failures, the optimization of maintenance schedules, the minimization of downtime, and the improvement of maintenance practices. …”
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Predicting Employee Turnover Using Machine Learning Techniques by Adil Benabou, Fatima Touhami, My Abdelouahed Sabri

“…Background: Employee turnover is a persistent issue in human resource management, leading to significant costs for organizations. This study aims to identify the most effective machine learning model for predicting employee attrition, thereby providing organizations with a reliable tool to anticipate turnover and implement proactive retention strategies.Objective: This study aims to address the challenge of employee attrition by applying machine learning techniques to provide predictive insights that can improve retention strategies.Methods: Nine machine learning algorithms are applied to a dataset of 1,470 employee records. …”
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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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Coal mining equipment lifecycle management system architecture and key technology by Yihui PANG, Jinglong BI, Pengzhe YUAN, Baofu ZHAO, Ziwei DING

“…An optimization algorithm and software platform for comprehensive mining equipment selection were developed, and a method for constructing a series spectrum and coding system for coal mining equipment was proposed. …”
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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 5G network based conceptual framework for real-time malaria parasite detection from thick and thin blood smear slides using modified YOLOv5 model by Swati Lipsa, Ranjan Kumar Dash, Korhan Cengiz, Nikola Ivković, Adnan Akhunzada

“…Conclusion Our model exemplifies how a generic one-stage object detection algorithm, such as YOLOv5x, can be repurposed to detect objects as small as malaria parasites from microscopic visuals in a cost-effective manner over the 5G network. …”
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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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SCL-YOLOv11: A Lightweight Object Detection Network for Low-Illumination Environments by Shulong Zhuo, Hao Bai, Lifeng Jiang, Xiaojian Zhou, Xu Duan, Yiqun Ma, Zihan Zhou

“…Experimental results on the ExDark dataset demonstrate that the proposed algorithm achieves 67.6% mAP@0.5 and 42.4% mAP@0.5:0.95, while reducing parameter count by 38.5% and computational cost by 25.4%. …”
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Application of precision agriculture technologies for crop protection and soil health by Emogine Mamabolo, Makgabo Johanna Mashala, Ephias Mugari, Tlou Elizabeth Mogale, Norman Mathebula, Kabisheng Mabitsela, Kwabena Kingsley Ayisi

“…Among the technologies, spectral imaging emerged as the most widely used for early detection of plant stress, diseases, and pests, followed by machine learning algorithms, UAVs (Unmanned Aerial Vehicles), and IoT (Internet of Things) devices, all of which enable real-time monitoring and targeted interventions. …”
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