A review of recent artificial intelligence for traditional medicine by Chengbin Hou, Yanzhuo Gao, Xinyu Lin, Jinchao Wu, Ning Li, Hairong Lv, William Cheng-Chung Chu

“…By leveraging advanced algorithms and models, AI can improve decision-making efficiency, optimize diagnosis accuracy, enhance patient experience, and reduce costs. …”
Get full text

Dynamic Multibody Modeling of Spherical Roller Bearings with Localized Defects for Large-Scale Rotating Machinery by Luca Giraudo, Luigi Gianpio Di Maggio, Lorenzo Giorio, Cristiana Delprete

“…Early fault detection in rotating machinery is crucial for optimizing maintenance and minimizing downtime costs, especially in medium-to-large-scale industrial applications. …”
Get full text

A Survey on UAV Control with Multi-Agent Reinforcement Learning by Chijioke C. Ekechi, Tarek Elfouly, Ali Alouani, Tamer Khattab

“…Despite significant progress, the field remains fragmented, with a wide variety of algorithms, architectures, and evaluation metrics spread across domains. …”
Get full text

Automatic Ladle Tracking with Object Detection and OCR in Steel Melting Shops by Kabil Murugan, Mahinas Senthilmurugan, Venbha V. Senthilkumar, Harshita Velusamy, Karthiga Sekar, Vasanthan Buvanesan, Manikandan Venugopal

“…A ladle tracking system in steel production plants is essential for optimizing the ladle transportation between different processing units. …”
Get full text

Enhancing Ophthalmic Diagnosis and Treatment with Artificial Intelligence by David B. Olawade, Kusal Weerasinghe, Mathugamage Don Dasun Eranga Mathugamage, Aderonke Odetayo, Nicholas Aderinto, Jennifer Teke, Stergios Boussios

“…Furthermore, AI is being utilized to develop personalized treatment plans by analyzing large datasets to predict individual responses to therapies, thus optimizing patient outcomes and reducing healthcare costs. …”
Get full text

Enhancing Crop Type Mapping in Data-Scarce Regions Through Transfer Learning: A Case Study of the Hexi Corridor by Jingjing Mai, Qisheng Feng, Shuai Fu, Ruijing Wang, Shuhui Zhang, Ruoqi Zhang, Tiangang Liang

“…As target domain data were gradually incorporated, the total accuracy for all models ranged from 0.77 to 0.92, with F1-scores ranging from 0.76 to 0.92, showing a consistent improvement in model performance. This study highlights the feasibility of employing transfer learning for crop mapping in the Hexi Corridor, demonstrating its potential to reduce labeling costs for target domain samples and providing a valuable reference for crop mapping in regions with limited sample availability.…”
Get full text

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. …”
Get full text

Cross-sectional and longitudinal Biomarker extraction and analysis for multicentre FLAIR brain MRI by J. DiGregorio, A. Gibicar, H. Khosravani, P. Jabehdar Maralani, J.-C. Tardif, P.N. Tyrrell, A.R. Moody, A. Khademi

“…Large-scale, automated cross-sectional and longitudinal cerebral biomarker extraction from FLAIR datasets could progress disease characterization, improve disease monitoring, and help to determine optimal intervention times. …”
Get full text

Words high-frequency drying processes simulation of wooden tangent towers in a vacuum chamber by A. N. Kachanov, D. A. Korenkov, A. A. Revkov, V. V. Maksimov, O. V. Vorkunov

“…At the same time, there are promising electrotechnological drying installations that can reduce the duration and improve drying quality at comparable specific energy costs. …”
Get full text

Hardware-software simulator for modeling indoor temperature and humidity processes by О.M. Yevseienko

“…This makes it a reliable tool for forecasting and optimizing the operation of the object, which is important for further improvement of the control system.…”
Get full text

Emerging Imaging Technologies in Forensic Medicine: A Systematic Review of Innovations, Ethical Challenges, and Future Directions by Feras Alafer

“…Emerging imaging modalities enhance diagnostic precision and facilitate non-invasive examinations, offering culturally sensitive alternatives to traditional autopsies. However, high costs, algorithmic biases, data security risks, and the lack of standardized forensic imaging protocols present significant challenges. …”
Get full text

A comprehensive review of data analytics and storage methods in geothermal energy operations by Ali Basem, Ahmed Kateb Jumaah Al-Nussairi, Dana Mohammad Khidhir, Narinderjit Singh Sawaran Singh, Mohammadreza Baghoolizadeh, Mohammad Ali Fazilati, Soheil Salahshour, S. Mohammad Sajadi, Ali Mohammadi Hasanabad

“…The study also delves into the potential of machine learning to optimize geothermal design, monitor performance, improve performance, find errors, and more. …”
Get full text

Unveiling nature's secrets: Deep learning for enhanced biogenic emission resolution by Antonio Giganti

“…As a result, various ground-based measurement techniques have been developed to sample BVOC emissions at multiple scales, from the leaf level to regional and global scales.However, current BVOC measurements are often limited in space and time, as generating a fine-grained map of BVOC emissions over a large region is costly and time-consuming. Consequently, many existing BVOC emission maps may not be fully suitable for reliable atmospheric, climate, and forecasting model simulations.My research aims to explore and assess the use of novel AI-based algorithms to improve the spatiotemporal modeling of BVOC emissions. …”
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

“…Predominantly, the study also indicates precision in the temperature variation prediction model through the use of the predictive model based on the linear regression and random forest algorithms. This improves smart farming practices developed for precision agriculture in terms of efficiency, productivity, and sustainability.…”
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

“…Despite the promise of these technologies, significant barriers hinder widespread adoption, including high costs, skill gaps, limited awareness, and resistance to change. …”
Get full text

A self-configuration framework for balancing services in the fog of things by Edson Mota, Jurandir Barbosa, Gustavo B. Figueiredo, Maycon Peixoto, Cássio Prazeres

“…The experimental results demonstrate significant improvements in network performance, response time, and load balancing. …”
Get full text

Machine Learning-Driven Prediction of One-Year Readmission in HFrEF Patients: The Key Role of Inflammation by Ma F, Hu Y, Han P, Qiu Y, Liu Y, Ren J

“…Predicting one-year readmission risk is crucial for optimizing treatment and reducing costs.Methods: We conducted a single-center retrospective study on adult HFrEF patients admitted to the Cardiovascular Department of the First Affiliated Hospital, Zhejiang University School of Medicine on January 2020 and March 2023. …”
Get full text

Developing a Machine Learning Model for Predicting 30-Day Major Adverse Cardiac and Cerebrovascular Events in Patients Undergoing Noncardiac Surgery: Retrospective Study by Ju-Seung Kwun, Houng-Beom Ahn, Si-Hyuck Kang, Sooyoung Yoo, Seok Kim, Wongeun Song, Junho Hyun, Ji Seon Oh, Gakyoung Baek, Jung-Won Suh

“…ConclusionsOur prediction models outperformed the widely used Revised Cardiac Risk Index in predicting MACCE within 30 days after noncardiac surgery, demonstrating superior calibration and generalizability across institutions. Its use can optimize preoperative evaluations, minimize unnecessary testing, and streamline perioperative care, significantly improving patient outcomes and resource use. …”
Get full text

Benchmarking Federated Few-Shot Learning for Video-Based Action Recognition by Nguyen Anh Tu, Nartay Aikyn, Nursultan Makhanov, Assanali Abu, Kok-Seng Wong, Min-Ho Lee

“…Additionally, we explore three meta-learning paradigms and three FL algorithms to investigate their effectiveness and suggest the optimal choices for performance improvement. …”
Get full text

The application of blockchain with a comparative approach and its impact on risk, flexibility and internal control evaluation by mohammadsadegh aminipoor, HamidReza GholamniaRoshan, azadeh kiapour, Iman Dadashi

“…Overall, blockchain can help improve risk, flexibility and internal control assessment. …”
Get full text