Facial Feature Recognition with Multi-task Learning and Attention-based Enhancements by M. Rohani, H. Farsi, S. Mohamadzadeh

“…This paper proposes a novel multi-task learning (MTL) model that leverages the powerful Efficient-Net architecture and incorporates attention-based learning with two key innovations. …”
Get full text

Blended Ensemble Learning for Robust Normal Behavior Modeling of Wind Turbines by Jianghao Zhu, Tingting Pei, Le Su, Bin Lan, Wei Chen

“…ABSTRACT The increasing scale of wind farms demands more efficient approaches to turbine monitoring and maintenance. Here, we present an innovative framework that combines enhanced kernel principal component analysis (KPCA) with ensemble learning to revolutionize normal behavior modeling (NBM) of wind turbines. …”
Get full text

A Deep Learning Model for Spectral Reconstruction of Arrayed Micro-Resonators by Xinyi Zhou, Cheng Zhang, Zhenyu Zheng, Hongbin Li, Chao Peng

“…Nevertheless, achieving an optimal balance among spectral resolution, detection range, and device compactness remains challenging, particularly when complex nonlinear mappings, inter-pattern correlations, and noise interference are involved. In this work, we present ESTspecNet, a deep learning framework that integrates EfficientNet, the Swin Transformer, and spatial-channel attention mechanisms to improve spectral reconstruction accuracy. …”
Get full text

Local corner smoothing based on deep learning for CNC machine tools by Bai Jiang, Rong Sun, Ze-long Li, Liang Xu, Huang Liao, Xiao-yan Teng, Bing Li

“…Finally, three simulations are presented to verify the effectiveness of the proposed method.…”
Get full text

Hybrid extreme learning machine for real-time rate of penetration prediction by Abdelhamid Kenioua, Omar Djebili, Ammar Touati Brahim

“…Abstract This study presents a comparative analysis of hybrid Extreme Learning Machine (ELM) models optimized with metaheuristic algorithms Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Whale Optimization Algorithm (WOA), and Grey Wolf Optimizer (GWO) for real-time Rate of Penetration (ROP) prediction in drilling operations. …”
Get full text

Evaluating Global Machine Learning Models for Tropical Cyclone Dynamics and Thermodynamics by Pankaj Lal Sahu, Sukumaran Sandeep, Hariprasad Kodamana

“…Abstract Machine Learning Weather Prediction (MLWP) models have recently demonstrated remarkable potential to rival physics‐based Numerical Weather Prediction (NWP) models, offering global weather forecasts at a fraction of the computational cost. …”
Get full text

The Adoption of Online Learning during the Pandemic: Issues, Challenges, and Future Directions by Kingie Micabalo, Winnie Marie Poliquit, Estela Ibanez, Robert Pabillaran, Carla Malait, Jesszon Cano

“…The study concluded that E-learning is a platform that should be present in the teaching and learning modalities in all institutions regardless of the situation. …”
Get full text

A machine learning framework for predicting healthcare utilization and risk factors by Yead Rahman, Prerna Dua

“…Medicaid data, with its vast scale and heterogeneity, presents significant challenges in predictive modeling and healthcare analytics. …”
Get full text

Optimizing Time-Sensitive Software-Defined Wireless Networks With Reinforcement Learning by Hyeontae Joo, Sangmin Lee, Seunghwan Lee, Hwangnam Kim

“…Meanwhile, software-defined networking (SDN) has successfully presented its efficiencies in ensuring quality of service for network traffic to accommodate many functions of network control and management. …”
Get full text

Learning a prior on regulatory potential from eQTL data. by Su-In Lee, Aimée M Dudley, David Drubin, Pamela A Silver, Nevan J Krogan, Dana Pe'er, Daphne Koller

“…The problem is particularly challenging in populations with significant linkage disequilibrium, where traits are often linked to large chromosomal regions containing many genes. Here, we present a novel method, Lirnet, that automatically learns a regulatory potential for each sequence polymorphism, estimating how likely it is to have a significant effect on gene expression. …”
Get full text

Psychological and Pedagogical Technologies of Working with Teenagers to Level the Manifestations of Learned Helplessness by Shalaginova K.S., Dekina E.V., Kulikova T.I.

“…The article presents the materials of an empirical study obtained on a sample of teenagers in grades 5-6 in the number of 66 students who had a state of learned helplessness. …”
Get full text

Deep Learning Based Early Intrusion Detection in IIoT using Honeypot by Abbasgholi Pashaei, Mohammad Esmaeil Akbari, Mina Zolfy Lighvan, Asghar Charmin

“…The increasing number of Industrial Internet of Things (IIoT) devices presents hackers with a huge attack surface from which to conduct possibly more destructive assaults. …”
Get full text

Machine learning–enhanced screening funnel for clinical trials in Alzheimer's disease by Scott Gladstein, Liuqing Yang, Dustin Wooten, Xin Huang, Robert Comley, Qi Guo, the Alzheimer's Disease Neuroimaging Initiative

“…The funnel incorporates machine learning (ML)–based disease progression models. The ML model identifies patients with progression rate optimal for clinical trials. …”
Get full text

Semantic priming supports infants' ability to learn names of unseen objects. by Elena Luchkina, Sandra Waxman

“…Human language permits us to call to mind representations of objects, events, and ideas that we cannot witness directly, enabling us to learn about the world far beyond our immediate surroundings. …”
Get full text

Enhancing Manatee Aggregation Counting Through Augmentation and Cross-Domain Learning by Matteo Zaramella, Xingquan Zhu, Irene Amerini

Get full text

Predicting Optimum Moisture Content by the individual and hybrid approach of machine learning by Yinghui Yang, Yahui Dai, Qunting Yang

“…Existing methods to determine OMC are both expensive and time-intensive. Machine learning offers a promising alternative by enabling the creation of advanced predictive models and algorithms that can improve the accuracy and efficiency of OMC predictions compared to traditional empirical methods. …”
Get full text

Enhancing Learners’ Motivation and Speaking Skill through Cooperative Learning Activities by Rym Ghosn El Bel CHELBI

“… The present research aims at investigating EFL learners’ motivation and English speaking skill development through the implementation of Cooperative Learning activities at the Department of Letters and English at Constantine University, with a sample of third year Didactics. …”
Get full text

Structural Health Monitoring of Laminated Composites Using Lightweight Transfer Learning by Muhammad Muzammil Azad, Izaz Raouf, Muhammad Sohail, Heung Soo Kim

“…However, the direct application of these models is restricted by a lack of training data, necessitating the use of transfer learning. The commonly used transfer learning models are computationally expensive; therefore, the present research proposes lightweight transfer learning (LTL) models for the SHM of composites. …”
Get full text

Pulse‐Level Quantum Robust Control with Diffusion‐Based Reinforcement Learning by Yuanjing Zhang, Tao Shang, Chenyi Zhang, Xueyi Guo

“…This paper proposes a diffusion‐based reinforcement learning method for pulse‐level quantum robust control (PQC‐DBRL) to enhance the robustness of pulse‐level quantum gate control. …”
Get full text

Learning From Natural Images in Few-Shot SAR Target Classification by Songhao Shi, Xiaodan Wang, Yafei Song

“…The intricate imaging attributes of synthetic aperture radar (SAR) present a formidable challenge to the prevailing few-shot target classification. …”
Get full text