Cross-Layer Analysis of Machine Learning Models for Secure and Energy-Efficient IoT Networks by Rashid Mustafa, Nurul I. Sarkar, Mahsa Mohaghegh, Shahbaz Pervez, Ovesh Vohra

“…To address these IoT issues, we propose a cross-layer IoT architecture employing machine learning (ML) models and lightweight cryptography. …”
Get full text

DRFW-TQC: Reinforcement Learning for Robotic Strawberry Picking with Dynamic Regularization and Feature Weighting by Anping Zheng, Zirui Fang, Zixuan Li, Hao Dong, Ke Li

“…Strawberry harvesting represents a labor-intensive agricultural operation where existing end-effector pose control algorithms frequently exhibit insufficient precision in fruit grasping, often resulting in unintended damage to target fruits. Concurrently, deep learning-based pose control algorithms suffer from inherent training instability, slow convergence rates, and inefficient learning processes in complex environments characterized by high-density fruit clusters and occluded picking scenarios. …”
Get full text

Machine Learning in Biomedical Informatics: Optimizing Resource Allocation and Energy Efficiency in Public Hospitals by Agostino Marengo, Vito Santamato, Massimo Iacoviello

“…This paper presents a computational framework that combines supervised machine learning and multi-objective optimization to support data-driven decision-making for resource allocation in public healthcare systems. …”
Get full text

Automated multi-model framework for malaria detection using deep learning and feature fusion by Osama R. Shahin, Hamoud H. Alshammari, Raed N. Alabdali, Ahmed M. Salaheldin, Neven Saleh

“…This study proposes an advanced, automated diagnostic framework for malaria detection using a multi-model architecture integrating deep learning and machine learning techniques. The framework employs a transfer learning approach that incorporates ResNet 50, VGG16, and DenseNet-201 for feature extraction. …”
Get full text

Effect of model’s skill level and frequency of feedback on learning of complex serial aiming task by Gh. Lotfi, F. Hatami, F. Zivari

“…Background and Study Aim : Modelling in observational learning and feedback are most important sources of information for learning of a new task. …”
Get full text

Enhancing Machine Learning Models Through PCA, SMOTE-ENN, and Stochastic Weighted Averaging by Youngjin Han, Inwhee Joe

“…This study provides insights into how machine learning techniques can be effectively combined to solve classification challenges in real-world scenarios.…”
Get full text

Machine learning with label-free Raman microscopy to investigate ferroptosis in comparison with apoptosis and necroptosis by Joost Verduijn, Eva Degroote, André G. Skirtach

“…The potential of Raman microscopy in biology, in combination with machine learning pipelines, can be applied to a broader field of cell biology, not limited to regulated cell death.…”
Get full text

Learning curve in the endovascular treatment of chronic post-thrombotic syndrome in a French center by Paul Segui, Valérie Monnin-Barès, Monira Nou, Sébastien Bommart, Hamid Zarqane, Juliette Vanoverschelde, Hélène Vernhet-Kovacsik

“…Improvement in this technique comes with faster procedures, and a reduction of the occurrence of peri-procedural and long term thrombotic events. …”
Get full text

Precise Sizing and Collision Detection of Functional Nanoparticles by Deep Learning Empowered Plasmonic Microscopy by Jingan Wang, Yi Sun, Yuting Yang, Cheng Zhang, Weiqiang Zheng, Chen Wang, Wei Zhang, Lianqun Zhou, Hui Yu, Jinghong Li

“…Here, it is demonstrated that deep learning‐empowered plasmonic microscopy (Deep‐SM) enables precise sizing and collision detection of functional chemical and biological nanoparticles. …”
Get full text

Diagnostic framework to validate clinical machine learning models locally on temporally stamped data by Maximilian Schuessler, Scott Fleming, Shannon Meyer, Tina Seto, Tina Hernandez-Boussard

“…Presently, there are few easy-to-implement, model-agnostic diagnostic frameworks to vet machine learning models for future applicability and temporal consistency. …”
Get full text

Prediction Model of Powdery Mildew Disease Index in Rubber Trees Based on Machine Learning by Jiazheng Zhu, Xize Huang, Xiaoyu Liang, Meng Wang, Yu Zhang

“…Powdery mildew, caused by <i>Erysiphe quercicola</i>, is one of the primary diseases responsible for the reduction in natural rubber production in China. This disease is a typical airborne pathogen, characterized by its ability to spread via air currents and rapidly escalate into an epidemic under favorable environmental conditions. …”
Get full text

POD-Based Machine Learning Approach for Coupled EM-Thermal Analysis in Microwave Heating by Jeong-Wan Lee, Gyu-Sik Choi, Sung-Jun Yang

“…In this paper, we propose a machine learning-based approach for reduced-order modeling that efficiently predicts the specific absorption rate (SAR) distributions in coupled EM and thermal analyses. …”
Get full text

Will rivers become more intermittent in France? Learning from an extended set of hydrological projections by T. Jaouen, L. Benoit, L. Héraut, E. Sauquet

Get full text

Machine learning based risk analysis and predictive modeling of structure fire related casualties by Andres Schmidt, Eric Gemmil, Russ Hoskins

Get full text

IncSAR: A Dual Fusion Incremental Learning Framework for SAR Target Recognition by George Karantaidis, Athanasios Pantsios, Ioannis Kompatsiaris, Symeon Papadopoulos

“…Deep learning techniques have achieved significant success in Synthetic Aperture Radar (SAR) target recognition using predefined datasets in static scenarios. …”
Get full text

Federated Learning for Scalable Anomaly Detection and Pattern Discovery in IoT-Enabled Aquaponics Systems by Saghar Shafaati, Javad Mohammadzadeh

“…This study introduces a federated learning-based architecture designed to support highly scalable and decentralized anomaly detection in IoT-integrated aquaponics systems. …”
Get full text

A Learning Emotion Recognition Model Based on Feature Fusion of Photoplethysmography and Video Signal by Xiaoliang Zhu, Zili He, Chuanyong Wang, Zhicheng Dai, Liang Zhao

“…The ability to recognize learning emotions facilitates the timely detection of students’ difficulties during the learning process, supports teachers in modifying instructional strategies, and allows for personalized student assistance. …”
Get full text

Automated Breast Cancer Detection in Mammograms using Transfer Learningbased Deep Learning Models by Preeti Katiyar, Krishna Singh

“…The present study employs deep learning models trained using Transfer Learning (TL) techniques. …”
Get full text

A Predictive Model of the Position of Plasmapause Based on Lunar Phase and Deep Learning Framework by Yajun Li, Chao Xiao, Quanqi Shi, Hongtao Huang, Huizi Wang, Anmin Tian, Die Duan, Ganming Ren, Tao Tang, Yang Lin, Chenghao Li, Jiajia Suo

Get full text

Valuation of Urban Public Bus Electrification with Open Data and Physics-Informed Machine Learning by Upadhi Vijay, Soomin Woo, Scott J. Moura, Akshat Jain, David Rodriguez, Sergio Gambacorta, Giuseppe Ferrara, Luigi Lanuzza, Christian Zulberti, Erika Mellekas, Carlo Papa

“…We estimate about 50% health cost reduction by electrifying only 4 routes out of 15 to 19 routes in each city. …”
Get full text