Automated Recognition of Conidia of Nematode-Trapping Fungi Based on Improved YOLOv8 by Enming Zhao, Hongyi Zhao, Guangyu Liu, Jianbo Jiang, Fa Zhang, Jilei Zhang, Chuang Luo, Bobo Chen, Xiaoyan Yang

“…Our approach integrates an efficient channel attention (ECA) mechanism within the backbone layer of YOLOv8l, improving the algorithm’s capability to detect global information effectively. …”
Get full text

Systematic review of AI/ML applications in multi-domain robotic rehabilitation: trends, gaps, and future directions by Giovanna Nicora, Samuele Pe, Gabriele Santangelo, Lucia Billeci, Irene Giovanna Aprile, Marco Germanotta, Riccardo Bellazzi, Enea Parimbelli, Silvana Quaglini

“…ML is reported as highly effective in predicting movement intentions, assessing clinical outcomes, and detecting compensatory movements, providing insights into the future of personalized rehabilitation interventions. …”
Get full text

Optimized Wireless Sensor Network Architecture for AI-Based Wildfire Detection in Remote Areas by Safiah Almarri, Hur Al Safwan, Shahd Al Qisoom, Soufien Gdaim, Abdelkrim Zitouni

“…The system also integrates artificial intelligence (AI) algorithms (multiclass logistic regression) to process sensor data and predict fire risk levels with 99.97% accuracy, enabling proactive wildfire mitigation. …”
Get full text

Harnessing AI forward and backward chaining with telemetry data for enhanced diagnostics and prognostics of smart devices by Muhammad Shoaib Farooq, Rizwan Pervez Mir, Atif Alvi, Kilian Tutusaus, Eduardo Garcia Villena, Fadwa Alrowais, Hanen Karamti, Imran Ashraf

“…This study proposes a novel AI-driven framework that integrates forward chaining and backward chaining algorithms to analyze telemetry data from IoT devices. …”
Get full text

Variability-Aware Machine Learning Model Selection: Feature Modeling, Instantiation, and Experimental Case Study by Cristina Tavares, Nathalia Nascimento, Paulo Alencar, Donald Cowan

“…In general, although the current literature provides a wide variety of ML techniques and algorithms, there is a lack of design approaches to support algorithm selection. …”
Get full text

Multiscale Modeling of Meandering Fluvial Reservoir Architecture Based on Multiple-Point Geostatistics: A Case Study of the Minghuazhen Formation, Yangerzhuang Oilfield, Bohai Bay... by Jia Li, Chengyan Lin, Xianguo Zhang, Chunmei Dong, Yannan Wei, Wenyan Ning, Changcheng Han, Wei Guo

“…The produced model conforms geologically realistically and enables the prediction of interwell permeability variation to enhance oil recovery.…”
Get full text

Review of Urban Rail Transit Ticket Clearing Methods by WANG Yao, LI Jiming, GAO Shen, LIU Guangjie, XU Zhongquan

“…A more scientific and reasonable clearing scheme needs to further strengthen big data research on the AFC (automatic fare collection) system, and more importantly, relying on existing technologies and computing models is required to strengthen the real-time analysis and overtime prediction accuracy of passengers′ path selection behavior, so as to enable the clearing mechanism accurately make adaptive dynamic adjustments according to actual operating conditions.…”
Get full text

Study on the relationship between vaginal dose and radiation-induced vaginal injury following cervical cancer radiotherapy, and model development by Fei Kong, Ziqin Yan, Liying Gao, Jianping Long, Xu Wang, Zhangcai Zheng

“…Univariate and multivariate analyses were conducted to identify key factors influencing radiation-induced vaginal injury, and five distinct algorithms were applied to develop predictive models. …”
Get full text

Assessing CO2 separation performances of IL/ZIF-8 composites using molecular features of ILs by Hasan Can Gulbalkan, Alper Uzun, Seda Keskin

“…The accurate prediction power of these ML models was shown by comparing their estimates with the experimental and simulation data. …”
Get full text

The clinical performance of an office-based risk scoring system for fatal cardiovascular diseases in North-East of Iran. by Sadaf G Sepanlou, Reza Malekzadeh, Hossein Poustchi, Maryam Sharafkhah, Saeed Ghodsi, Fatemeh Malekzadeh, Arash Etemadi, Akram Pourshams, Paul D Pharoah, Christian C Abnet, Paul Brennan, Paolo Boffetta, Sanford M Dawsey, Farin Kamangar

“…Most of these risk score algorithms have been based on a long array of risk factors including blood markers of lipids. …”
Get full text

Digital twin-driven method for determining wind force coefficients of a bridge deck section by Hao-Yang Li, You-Lin Xu, Hai-Li Liao, Lin Huang, Qi Wang

“…The results show that the digital twin-driven method can provide more accurate prediction than wind tunnel tests or CFD simulations.…”
Get full text

Integrating bioinformatics and machine learning to investigate the mechanisms by which three major respiratory infectious diseases exacerbate heart failure by Yiding Yu, Quancheng Han, Juan Zhang, Jingle Shi, Huajing Yuan, Yitao Xue, Yan Li

“…DSigDB prediction results showed that 6 drugs such as acetohexamide may have potential therapeutic effects on HF aggravated by respiratory diseases. …”
Get full text

Notice of Violation of IEEE Publication Principles: Ground-Based Cloud Image Recognition System Based on Multi-CNN and Feature Screening and Fusion by Ma Jingyi, Tiejun Zhang, Jing Guodong, Yan Wenjun, Yang Bin

“…The recognition of ground-based cloud images has rich application prospects in many aspects such as weather prediction, astronomical site selection, and meteorological observation. …”
Get full text

An Overview of Deep Learning Applications in Groundwater Level Modeling: Bridging the Gap between Academic Research and Industry Applications by Ahmed Shakir Ali Ali, Farhad Jazaei, Peyman Babakhani, Muhammad Masood Ashiq, Alireza Bakhshaee, Brian Waldron

“…As a critical component of sustainable water management, groundwater level prediction plays a vital role in mitigating droughts and ensuring adequate water supply. …”
Get full text

A review on artificial intelligence thermal fluids and the integration of energy conservation with blockchain technology by Abdullah Ayub Khan, Asif Ali Laghari, Syed Azeem Inam, Sajid Ullah, Laila Nadeem

“…In order to support sustainable energy goals, these highlighted machine learning algorithms offer a potent environment for optimising energy flow, temperature regulation, and application stability. …”
Get full text

Deep learning radiomics based on MRI for differentiating tongue cancer T - staging by Zhaoyi Lu, Bowen Zhu, Hang Ling, Xi Chen

“…Abstract Objective To develop a deep learning-based MRI model for predicting tongue cancer T-stage. Methods This retrospective study analyzed clinical and MRI data from 579 tongue cancer patients (Xiangya Cancer Hospital and Jiangsu Province Hospital). …”
Get full text

Replicating PET Hydrolytic Activity by Positioning Active Sites with Smaller Synthetic Protein Scaffolds by Yujing Ding, Shanshan Zhang, Xian Kong, Henry Hess, Yifei Zhang

“…Recent breakthroughs in protein structure prediction and de novo design, powered by artificial intelligence, now enable to create enzymes with desired functions without solely relying on traditional genome mining. …”
Get full text

Short-Term Electricity Price Forecasting Using the Empirical Mode Decomposed Hilbert-LSTM and Wavelet-LSTM Models by Kunal Shejul, R. Harikrishnan, Amit Kukker

“…The proposed techniques show better performance in terms of rank correlation, mean square error, and root mean square error compared to the existing algorithms of LSTM and CNN-LSTM. The prediction results achieved with wavelet-LSTM and Hilbert-LSTM (1-month dataset of 8 years) are rank correlation 0.9746 and 0.9749, MSE 0.2962 and 0.1363, and RMSE 0.5443 and 0.3692, respectively. …”
Get full text

Detection of Malicious Office Open Documents (OOXML) Using Large Language Models: A Static Analysis Approach by Jonas Heß , Kalman Graffi

“…Existing machine learning approaches are capable of identifying sophisticated features that enable the prediction of a file’s nature, achieving sufficient results on existing samples. …”
Get full text

Integrating direct observation and environmental DNA data to enhance species distribution models in riverine environments by Luca Carraro

“…When eDNA and direct sampling sites are spatially arranged in an optimized fashion, the highest prediction skill for a fixed total number of sampling sites deployed is reached when both data types are included in the model fitting. …”
Get full text