Projecting future changes in potato yield using machine learning techniques: a case study for Prince Edward Island, Canada by Dania Tamayo-Vera, Kai Liu, Antonio Bolufé-Röhler, Xiuquan Wang

Get full text

Deep learning in microbiome analysis: a comprehensive review of neural network models by Piotr Przymus, Krzysztof Rykaczewski, Adrián Martín-Segura, Jaak Truu, Enrique Carrillo De Santa Pau, Mikhail Kolev, Mikhail Kolev, Irina Naskinova, Aleksandra Gruca, Alexia Sampri, Alexia Sampri, Marcus Frohme, Alina Nechyporenko, Alina Nechyporenko

“…However, despite their potential, deep learning approaches face significant challenges in microbiome research. …”
Get full text

Impact of Machine Learning on Intrusion Detection Systems for the Protection of Critical Infrastructure by Avinash Kumar, Jairo A. Gutierrez

Get full text

Field-programmable robotic folding sheet by Hyunkyu Park, Yongrok Jeong, Woojong Kim, Jungrak Choi, Junseong Ahn, Jun-Ho Jeong, Inkyu Park, Jung Kim

“…Electronic layouts, computational algorithms, and closed-loop control schemes present an intuitive means of blending user intent in situ, yielding a servoed, swift, and robust fold-programming process. …”
Get full text

A Review of Smart Grid Evolution and Reinforcement Learning: Applications, Challenges and Future Directions by Na Xu, Zhuo Tang, Chenyi Si, Jinshan Bian, Chaoxu Mu

“…This study compares the applicability, advantages, and limitations of different reinforcement learning algorithms in practical scenarios, and reveals core challenges such as state space complexity, learning stability, and computational efficiency. …”
Get full text

On development of in-core fuel system for PWR reactors: Part I generation of macroscopic cross sections using SCALE 6.0 for use in nodal calculation by Pedro Henrique Silva Rodrigues, José Rubens Maiorino, Roberto Asano Júnior

Get full text

Enhanced CLIP-GPT Framework for Cross-Lingual Remote Sensing Image Captioning by Rui Song, Beigeng Zhao, Lizhi Yu

“…Remote Sensing Image Captioning (RSIC) aims to generate precise and informative descriptive text for remote sensing images using computational algorithms. Traditional “encoder-decoder” approaches face limitations due to their high training costs and heavy reliance on large-scale annotated datasets, hindering their practical applications. …”
Get full text

AGU2-Net: Multi-Scale U²-Net Enhanced by Attention Gate Mechanism for Image Tampering Localization by Kefei Wu, Lin Li, Qingyan Li

“…Although deep learning algorithms based on convolutional neural networks (CNNs) have made notable progress in image forgery detection, they still face certain limitations in effectively detecting and localizing tampered areas due to the subtle nature of existing manipulation traces. …”
Get full text

RWA-BFT: Reputation-Weighted Asynchronous BFT for Large-Scale IoT by Guanwei Jia, Zhaoyu Shen, Hongye Sun, Jingbo Xin, Dongyu Wang

“…Traditional centralized IoT architectures often face issues such as single points of failure and insufficient reliability, while blockchain, with its decentralized and tamper-resistant properties, offers a promising solution. …”
Get full text

Aircraft Sensor Fault Diagnosis Based on GraphSage and Attention Mechanism by Zhongzhi Li, Jinyi Ma, Rong Fan, Yunmei Zhao, Jianliang Ai, Yiqun Dong

“…Traditional deep learning-based fault diagnosis methods often face challenges, such as limited data representation and insufficient feature extraction. …”
Get full text

Congestion forecast framework based on probabilistic power flow and machine learning for smart distribution grids by Alejandro Hernandez-Matheus, Kjersti Berg, Vinicius Gadelha, Mònica Aragüés-Peñalba, Eduard Bullich-Massagué, Samuel Galceran-Arellano

“…Distribution system operators (DSOs) face several challenges while operating their grids in such conditions. …”
Get full text

NID-DETR: A novel model for accurate target detection in dark environments by Qingyuan Pan, Qiang Liu, Wei Huang

“…Current mainstream algorithms face challenges in extracting meaningful features under low-light conditions, which significantly limits their effectiveness. …”
Get full text

Global miniaturization of broadband antennas by prescreening and machine learning by Slawomir Koziel, Anna Pietrenko-Dabrowska, Ubaid Ullah

“…Identifying truly minimum-size designs requires a global search approach, as the popular nature-inspired algorithms face challenges related to computational efficiency and the need for reliable full-wave electromagnetic (EM) simulation to evaluate device’s characteristics. …”
Get full text

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

“…Obstacle intrusion detection in railway systems is a critical technology for ensuring the operational safety of trains. However, existing algorithms face challenges related to insufficient multiscale object detection, high model redundancy, and poor real-time performance. …”
Get full text

Integration of Regression-Based Guidance Ant for Enhanced Exploration and Convergence in Ant Colony Optimization (ACO) by Desi W. Sari, Suci Dwijayanti, Bhakti Y. Suprapto

“…Traditional Ant Colony Optimization (T-ACO) algorithms often face challenges in dynamic environments, particularly the tendency to become trapped in local minima, resulting in suboptimal path planning. …”
Get full text

Adaptive Beam Tracking in 5G/6G mmWave Networks: A Clustered Federated Learning Approach by Amjad Ali, Yevgeni Koucheryavy

“…However, mmWave signals are highly susceptible to attenuation and blockage, necessitating directional beamforming antennas and efficient beam tracking algorithms. Traditional machine learning-based approaches, such as centralized learning (CL) and federated learning (FL), face significant challenges. …”
Get full text

VAMP-Based Kalman Filtering Under Non-Gaussian Process Noise by Tiancheng Gao, Mohamed Akrout, Faouzi Bellili, Amine Mezghani

“…Numerical results using sparse noise dynamics with different sparsity ratios demonstrate unambiguously the effectiveness of the proposed VAMP-KF algorithm and its superiority over state-of-the-art algorithms both in terms of reconstruction accuracy and computational complexity.…”
Get full text

Enhanced Conformer-Based Speech Recognition via Model Fusion and Adaptive Decoding with Dynamic Rescoring by Junhao Geng, Dongyao Jia, Zihao He, Nengkai Wu, Ziqi Li

“…While its development drives global information infrastructure and AI strategies, current models still face challenges such as overfitting, local optima, and inefficiencies in decoding accuracy and computational cost. …”
Get full text

HAF-YOLO: Dynamic Feature Aggregation Network for Object Detection in Remote-Sensing Images by Pengfei Zhang, Jian Liu, Jianqiang Zhang, Yiping Liu, Jiahao Shi

“…The growing use of remote-sensing technologies has placed greater demands on object-detection algorithms, which still face challenges. This study proposes a hierarchical adaptive feature aggregation network (HAF-YOLO) to improve detection precision in remote-sensing images. …”
Get full text

State-of-the-Art on IoV-Based Deep Learning Framework for Enhanced Driving Behavior Recognition: Recent Progress, Technology Updates, Challenges, and Future Direction by Hongguang Li, Shafrida Sahrani, Mahidur R. Sarker, Yinglin Xiao

“…However, these advanced algorithms still face several challenges. We analyze relevant literature from 2015 to 2024, to uncover key trends and gaps in the development of applications for identifying dangerous driving behaviors, with a primary focus on optimizing integration to improve the accuracy and real-time capability of driving behavior prediction. …”
Get full text