Improved RT-DETR Framework for Railway Obstacle Detection by Peng Li, Yanhui Peng, Su-Mei Wang, Cheng Zhong

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Subtypes detection of papillary thyroid cancer from methylation assay via Deep Neural Network by Andrea Colacino, Andrea Soricelli, Michele Ceccarelli, Ornella Affinito, Monica Franzese

“…Background and Objective: In recent years, DNA methylation-tumor classification based on artificial intelligence algorithms has led to a notable improvement in diagnostic accuracy compared to traditional machine learning methods. …”
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A hybrid framework for heart disease prediction using classical and quantum-inspired machine learning techniques by Ankur Kumar, Sanjay Dhanka, Abhinav Sharma, Rohit Bansal, Mochammad Fahlevi, Fazla Rabby, Mohammed Aljuaid

“…Abstract This research proposes a novel framework for enhancing heart disease prediction using a hybrid approach that integrates classical and quantum-inspired machine learning techniques. …”
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Tree-Based Machine Learning Approach for Predicting the Impact Behavior of Carbon/Flax Bio-Hybrid Fiber-Reinforced Polymer Composite Laminates by Manzar Masud, Aamir Mubashar, Shahid Iqbal, Hassan Ejaz, Saad Abdul Raheem

“…In this research, the effect of change in stacking sequences on the impact performance of bio-hybrid fiber-reinforced polymer (bio-HFRP) composite materials was analyzed and evaluated. …”
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Corrupted Point Cloud Classification Through Deep Learning with Local Feature Descriptor by Xian Wu, Xueyi Guo, Hang Peng, Bin Su, Sabbir Ahamod, Fenglin Han

“…The experimental results show that our model outperforms existing popular algorithms when dealing with corrupted point cloud data. …”
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Fighting Evaluation Inflation: Concentrated Datasets for Grammatical Error Correction Task by Vladimir Starchenko, Darya Kharlamova, Elizaveta Klykova, Anastasia Shavrina, Aleksey Starchenko, Olga Vinogradova, Olga Lyashevskaya

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Contribution of hydrogeological, well logs and machine learning in predicting the aquifer hydraulic properties in arid regions: a case study of Nubian Sandstone aquifer, Farafra Oa... by Ahmed Nosair, Muhammad Nabih, Ahmed Bakry

“…While neutron density logs are commonly used for porosity estimation, our study uniquely employs resistivity logs to calculate porosity due to the scarcity of recorded logs in groundwater exploration. Consequently, this research aims to use conventional well log and hydrogeological data to predict T, K, and PHIE using machine learning (ML) algorithms, including random forest (RF), gradient boosting (GB), linear regression (LR), and support vector machines (SVM). …”
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Intelligent Assessment Systems in Medical Education: A Systematic Review by MAJID ALIZADEH, MARYAM JAFAR SAMERI

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Enhancing Security for Resource-Constrained Smart Cities IoT Applications: Optimizing Cryptographic Techniques with Effective Field Multipliers by Atef Ibrahim, Fayez Gebali

“…Consequently, the streamlined execution of this operation is pivotal, as it will facilitate the effective deployment of encryption algorithms on these resource-limited devices. Therefore, the presented research concentrates on the formulation of a spatially and energetically efficient hardware implementation for the finite-field multiplication operation. …”
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Reinforcement Learning for Mitigating Malware Propagation in Wireless Radar Sensor Networks with Channel Modeling by Guiyun Liu, Hao Li, Lihao Xiong, Yiduan Chen, Aojing Wang, Dongze Shen

“…Finally, the PPO and MAPPO algorithms demonstrate superior performance in control costs and convergence compared to traditional RL algorithms. …”
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Innovative framework for fault detection and system resilience in hydropower operations using digital twins and deep learning by Jun Tan, Raoof Mohammed Radhi, Kimia Shirini, Sina Samadi Gharehveran, Zamen Parisooz, Mohsen Khosravi, Hossein Azarinfar

“…We developed a hybrid approach integrating a Digital Twin model of the hydropower system with advanced Deep Learning algorithms for real-time monitoring and predictive analysis. …”
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Structural health monitoring based on three-dimensional point cloud technology: A systematic review by Yanzong Zhang, Guibo Nie, Duozhi Wang

“…This paper reviews the latest research, methodologies, and applications of 3D point cloud technology in SHM, based on 223 studies published from 2010 to 2024. …”
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Autonomous Aircraft Tactical Pop-Up Attack Using Imitation and Generative Learning by Joao P. A. Dantas, Marcos R. O. A. Maximo, Takashi Yoneyama

“…By applying imitation learning techniques and comparing three algorithms – Multi-Layer Perceptron (MLP), Long Short-Term Memory (LSTM), and Gated Recurrent Unit (GRU) – the research trains models to predict aircraft control inputs through sequences of state-action pairs. …”
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PREGNANCY AND CHILDBIRTH IN PATIENTS WITH RENAL ALLOGRAFT (CASE REPORT) by R. R. Temirbulatov, V. F. Bezhenar, O. N. Reznik, A. N. Anan’ev

“…To identify the most common complications in pregnancy in women with a transplanted kidney, to review the algorithms for maintaining this category of patientsMaterial and methods. …”
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Solar Irradiance Prediction for Zaria Town Using Different Machine Learning Models by Ibrahim Abdulwahab, Sulaiman Haruna Sulaiman, Umar Musa, Ibrahim Abdullahi Shehu, Abdullahi Kakumi Musa, Ismaila Mahmud, Mohammed Musa, Abdullahi Abubakar, Abdulrahman Olaniyan

“… The research is set to predict solar irradiation using various machine learning algorithms. …”
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Frequent use of online medical records: analysis of influence factors based on structural equation modeling by Wei Wang, Lei Qin, Lei Qin, Yang Chen, Yinzhi Wang, Linglong Ye, Ruojia Wang, Yingqiu Zhu

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UAV-Multispectral Based Maize Lodging Stress Assessment with Machine and Deep Learning Methods by Minghu Zhao, Dashuai Wang, Qing Yan, Zhuolin Li, Xiaoguang Liu

“…This study aims to introduce advanced DL algorithms into the maize lodging classification task using UAV-multispectral images and investigate the advantages of DL compared with traditional ML methods. …”
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Bayesian Q-learning in multi-objective reward model for homophobic and transphobic text classification in low-resource languages: A hypothesis testing framework in multi-objective... by Vivek Suresh Raj, Ruba Priyadharshini, Saranya Rajiakodi, Bharathi Raja Chakravarthi

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Machine Learning Introduces Electrophysiology Assessment as the Best Predictor for the Recovery Prognosis of Spinal Cord Injury Patients for Personalized Rehabilitation Approaches by Dionysia Chrysanthakopoulou, Charalampos Matzaroglou, Eftychia Trachani, Constantinos Koutsojannis

“…EPs emerged as the best predictors, comparable to a comprehensive electrophysiology assessment, significantly improving accuracy compared to clinical findings alone. …”
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A novel method for predicting the geochemical composition of tailings with laboratory field and hyperspectral airborne data using a regression and classification-based approach by Yaron Ogen, Michael Denk, Cornelia Glaesser, Holger Eichstaedt

“…Results of this study are not limited to tailing samples but can be applied on other fields of research such as geology, pedology or agriculture.…”
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