The Mode of Constructing Safe Trajectories of Motion of the Unmanned Aerial Vehicle while Monitoring Power Lines Considering the Influence of their Electromagnetic Fields by Shabanova A.R., Tolstoy I.M., Lebedev I.V.

“…Consequently, maintenance costs of overhead power line service can be optimized.…”
Get full text

Travel time prediction for an intelligent transportation system based on a data-driven feature selection method considering temporal correlation by Amirreza Kandiri, Ramin Ghiasi, Maria Nogal, Rui Teixeira

“…The first stage involves an offline process where interconnected optimisation algorithms are employed to identify the optimal set of features and determine the most effective machine learning model architecture. …”
Get full text

A Multi-Strategy Active Learning Framework for Enhanced Peripheral Blood Cell Image Detection by Yuheng Feng, Jiangtao He, Linjin Wang, Wuchen Yang, Sihan Deng, Lanlin Li, Xinwei Li

“…The framework reduces annotation costs and improves detection performance by combining uncertainty-based selection, diversity querying, and density-based querying to prioritize the most informative and diverse samples. …”
Get full text

Advanced GPU Techniques for Dynamic Remeshing and Self-Collision Handling in Real-Time Cloth Tearing by Jong-Hyun Kim, Jung Lee

“…We also present a method to optimize kernels based on a complete binary tree in arbitrary triangular meshes, improving performance. …”
Get full text

Prediction of alkali-silica reaction expansion of concrete using explainable machine learning methods by Yasitha Alahakoon, Hirushan Sajindra, Ashen Krishantha, Janaka Alawatugoda, Imesh U. Ekanayake, Upaka Rathnayake

“…This research holds significant value for the construction industry, as accurately predicting ASR expansion can lead to optimized material usage and improved structural performance.…”
Get full text

Research Progress on Selective Depolymerization of Waste Plastics to High-Quality Liquid Fuels by Xinze LI, Zhicheng LUO, Rui XIAO

“…Catalytic pyrolysis faces the challenge of rapid catalyst deactivation (resulting in a 30% activity loss after 5 cycles), while microwave systems incur high capital costs. Photocatalysis prioritizes gaseous products (e.g., H2, CH4) with liquid fuel selectivity below 15% for most polymers. …”
Get full text

In vitro machine learning-based CAR T immunological synapse quality measurements correlate with patient clinical outcomes. by Alireza Naghizadeh, Wei-Chung Tsao, Jong Hyun Cho, Hongye Xu, Mohab Mohamed, Dali Li, Wei Xiong, Dimitri Metaxas, Carlos A Ramos, Dongfang Liu

“…Meanwhile, identifying the optimal CAR construct for a researcher to further develop a potential clinical application is limited by the current, time-consuming, costly, and labor-intensive conventional tools used to evaluate efficacy. …”
Get full text

A deep contrastive learning-based image retrieval system for automatic detection of infectious cattle diseases by Veerayuth Kittichai, Morakot Kaewthamasorn, Apinya Arnuphaprasert, Rangsan Jomtarak, Kaung Myat Naing, Teerawat Tongloy, Santhad Chuwongin, Siridech Boonsang

“…Abstract Anaplasmosis, which is caused by Anaplasma spp. and transmitted by tick bites, is one of the most serious livestock animal diseases worldwide, causing significant economic losses as well as public health issues. …”
Get full text

AGW-YOLO-Based UAV Remote Sensing Approach for Monitoring Levee Cracks by HU Weibo, ZHOU Shaoliang, ZHAO Erfeng, ZHAO Xueqiang

“…Comparative experiments indicated that AGW-YOLO outperformed several mainstream object detection algorithms, including Faster R-CNN, YOLOv8n, YOLOv9-tiny, YOLOv10n, RT-DETR-R50, and TPH-YOLO, across most evaluation metrics, offering high recognition accuracy with lower computational complexity. …”
Get full text

A Comprehensive Review of the Diagnostics for Pediatric Tuberculosis Based on Assay Time, Ease of Operation, and Performance by Soumya Basu, Subhra Chakraborty

“…Gaps in the existing diagnostic methods, algorithms, and operational costs were also reviewed. …”
Get full text

Analysis of the state of geometrization development and digital modeling in open-pit mining enterprises by M.S. Kunytska, D.S. Polishchyk, O.V. Shapochnikov

“…It was determined that their integrated application provides an increase in the accuracy of reserve assessment by 15–20 % and a reduction in operating costs by 10–15 %. Key development trends are identified: integration of digital technologies, improvement of methods of collecting and processing geospatial data, introduction of machine learning algorithms for risk prediction. …”
Get full text

Machine Learning Applications in Gray, Blue, and Green Hydrogen Production: A Comprehensive Review by Xuejia Du, Shihui Gao, Gang Yang

“…ML algorithms such as artificial neural networks (ANNs), random forest (RF), and gradient boosting regression (GBR) have been widely applied to predict hydrogen yield, optimize operational conditions, reduce emissions, and improve process efficiency. …”
Get full text

Energy Efficient Heat Exchange Network for the Oil Vacuum Distillation Facility by Ved V.E., Ilchenko M.V., Myronov A.N.

“…The cost curves tools carry out the search of an optimal minimum temperature difference value. …”
Get full text

IoT Based Health Monitoring with Diet, Exercise and Calories recommendation Using Machine Learning by Muhammad Hassaan Naveed, Omar Bin Samin, Muhammad Bilal, Mustehsum Waseem

“…Additionally, machine learning algorithms recommend tailored exercise, diet type, Basal Metabolic Rate (BMR), and daily caloric intake based on individual member data. …”
Get full text

Predicting anemia management in dialysis patients using open-source machine learning libraries by Takahiro Inoue, Norio Hanafusa, Yuki Kawaguchi, Ken Tsuchiya

“…Performance metrics were compared across models, including XGBoost and LightGBM, to identify the most accurate algorithms. Results LightGBM and XGBoost outperformed logistic regression in predicting ESA and iron dosage changes, achieving high accuracy (e.g., area under the curve (AUC) = 0.86 for iron dosing). …”
Get full text

An Intelligent LoRaWAN-Based IoT Device for Monitoring and Control Solutions in Smart Farming Through Anomaly Detection Integrated With Unsupervised Machine Learning by Maram Fahaad Almufareh, Mamoona Humayun, Zulfiqar Ahmad, Asfandyar Khan

“…Therefore, the implementation of IoT devices would give the farmer access to current readings when needed for making decisions and optimizing their resources on the most important parameters for agricultural activity. …”
Get full text

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. …”
Get full text

Machine learning as a tool for diagnostic and prognostic research in coronary artery disease by B. I. Geltser, M. M. Tsivanyuk, K. I. Shakhgeldyan, V. Yu. Rublev

“…It is assumed that the improvement of ML-based models and their introduction into clinical practice will help support medical decision-making, increase the effectiveness of treatment and optimize health care costs.…”
Get full text

The Analysis of the Possibility to Conduct Orbital Manoeuvres of Nanosatellites in the Context of the Maximisation of a Specific Operational Task by Magdalena Lewinska, Michal Kedzierski

“…For example, slight adjustments to the altitude of the orbit with the use of Hohmann transfer proved to be optimal in terms of fuel costs. On the other hand, changes in inclination, although they are definitely energy-consuming, may significantly improve the coverage of the defined area. …”
Get full text

Prediction of porosity, hardness and surface roughness in additive manufactured AlSi10Mg samples. by Fatma Alamri, Imad Barsoum, Shrinivas Bojanampati, Maher Maalouf

“…The results presented in this study provide significant advantages for additive manufacturing, potentially reducing experimentation costs by identifying the process parameters that optimize the quality of the fabricated parts.…”
Get full text