GDPR and Large Language Models: Technical and Legal Obstacles by Georgios Feretzakis, Evangelia Vagena, Konstantinos Kalodanis, Paraskevi Peristera, Dimitris Kalles, Athanasios Anastasiou

“…Large Language Models (LLMs) have revolutionized natural language processing but present significant technical and legal challenges when confronted with the General Data Protection Regulation (GDPR). …”
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A Mini-Review on Multi-Hurdle Control of <i>Salmonella</i> Along Poultry Production Continuum by Eniola Betiku, T. Tiwa Ogundipe, Tanmaie Kalapala, Tomi Obe

“…Collaborative efforts between researchers, industry stakeholders, and policymakers are necessary to address emerging issues and enhance overall effectiveness.…”
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Multi-Modal Federated Learning Over Cell-Free Massive MIMO Systems for Activity Recognition by Seyed Mohammad Sheikholeslami, Pai Chet Ng, Jamshid Abouei, Konstantinos N. Plataniotis

“…To tackle these issues, we propose a late-fusion model architecture that allows flexible client participation with any combination of data modalities, and formulate an optimization problem to jointly minimize latency and global loss in MFL. …”
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Fault-Tolerant Scheduling Mechanism for Dynamic Edge Computing Scenarios Based on Graph Reinforcement Learning by Yuze Zhang, Geming Xia, Chaodong Yu, Hongcheng Li, Hongfeng Li

“…With the proliferation of Internet of Things (IoT) devices and edge nodes, edge computing has taken on much of the real-time data processing and low-latency response tasks which were previously managed by cloud computing. …”
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Hazard Identification and Risk Assessment of Sensor Maintenance Work Activity on The Suramadu Bridge Steel Box Girder Area by Nabylla Sharfina Sekar Nurriwanti, Y. Denny A. Wahyudiono, Indriati Paskarini, Ayu Pertimasari Sekar Handayani

“…The secondary data of the study include a job safety analysis document issued by the Suramadu Bridge Structural Health Monitoring System (SHMS). …”
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Improving the Accuracy of Indoor Object Localization in the Internet of Things Using Recurrent Neural Networks (LSTM) in Challenging Environments by Hussein Aqeel Hussein, Mehdi Hamidkhani, Nasseer K. Bachache, Mohammadreza Soltan Aghaei

“…Increased optimization is a positive side-effect of harmonizing sparse autoencoders based on a feature selection process, and deep learning classifiers. The discovery must be the result of a cheap and deployable information technology, apart from crucial issues such as energy, noise, and the behavior of the moving objects, and actuators.…”
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Retinal-ESRGAN: A Hybrid GAN Model Approach for Retinal Image Super-Resolution Coupled With Reduced Training Time and Computational Resources for Improved Diagnostic Accuracy by K. Deepthi, Aditya K. Shastry

“…Medical Image Super-Resolution has always been a subject of interest in medical image processing. However, super-resolved retinal images are a requisite tool for doctors to properly diagnose and treat ophthalmic diseases. …”
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Towards Ensemble Feature Selection for Lightweight Intrusion Detection in Resource-Constrained IoT Devices by Mahawish Fatima, Osama Rehman, Ibrahim M. H. Rahman, Aisha Ajmal, Simon Jigwan Park

“…However, most IoT devices are resource-constrained with limited processing power, memory storage, and energy sources. …”
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A Comprehensive Review of Food Safety Culture in the Food Industry: Leadership, Organizational Commitment, and Multicultural Dynamics by Ashwini Sadashiv Pai, Swarna Jaiswal, Amit K. Jaiswal

“…This article also provides a comparative analysis of FSC across various sectors, such as meat and dairy processing, identifying sector-specific challenges and best practices. …”
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Pyramidal Predictive Network V2: An Improved Predictive Architecture and Training Strategies for Future Perception Prediction by Chaofan Ling, Junpei Zhong, Weihua Li, Ran Dong, Mingjun Dai

“…While PPNV1 employed a temporal pyramid architecture and demonstrated promising results, its innate signal processing led to aliasing in the prediction, restricting its application in robotic navigation. …”
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A Symmetric Projection Space and Adversarial Training Framework for Privacy-Preserving Machine Learning with Improved Computational Efficiency by Qianqian Li, Shutian Zhou, Xiangrong Zeng, Jiaqi Shi, Qianye Lin, Chenjia Huang, Yuchen Yue, Yuyao Jiang, Chunli Lv

“…This paper proposes a data security training framework based on symmetric projection space and adversarial training, aimed at addressing the issues of privacy leakage and computational efficiency encountered by current privacy protection technologies when processing sensitive data. …”
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Threshold-Optimized Swarm Decomposition Using Grey Wolf Optimizer for the Acoustic-Based Internal Defect Detection of Arc Magnets by Qinyuan Huang, Qiang Li, Maoxia Ran, Xin Liu, Ying Zhou

“…Swarm decomposition (SWD) is conducive to processing acoustic signals, but it is still confronted with threshold optimization problems. …”
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Edge-Based Dynamic Spatiotemporal Data Fusion on Smart Buoys for Intelligent Surveillance of Inland Waterways by Ruolan Zhang, Chenhui Zhao, Yu Liang, Jingfeng Hu, Mingyang Pan

“…This study addresses the challenge of real-time processing and synchronization of voluminous video and AIS data for effective waterway management. …”
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Defect Identification and Diagnosis for Distribution Network Electrical Equipment Based on Fused Image and Voiceprint Joint Perception by An Chen, Junle Liu, Silin Liu, Jinchao Fan, Bin Liao

“…Baseline 1 is a long short term memory (LSTM)-based algorithm that performs separate feature extraction and processing for image and voiceprint signals without coupling the features of the two modalities, and Baseline 2 is a traditional CNN algorithm that uses classical convolutional layers for feature learning and classification through pooling and fully connected layers. …”
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Optimizing Digital Image Quality for Improved Skin Cancer Detection by Bogdan Dugonik, Marjan Golob, Marko Marhl, Aleksandra Dugonik

“…This study addresses these issues by evaluating color reproduction accuracy across various imaging devices and lighting conditions. …”
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Synthetic data generation for anomaly detection on table grapes by Ionut M. Motoi, Valerio Belli, Alberto Carpineto, Daniele Nardi, Thomas A. Ciarfuglia

“…Computer vision and robotics are increasingly employed for the automatic detection of such issues, particularly using data-driven solutions. …”
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Machine Learning-Based Computer Vision for Depth Camera-Based Physiotherapy Movement Assessment: A Systematic Review by Yafeng Zhou, Fadilla ’Atyka Nor Rashid, Marizuana Mat Daud, Mohammad Kamrul Hasan, Wangmei Chen

“…Depth cameras, particularly the Kinect series (65.4%), dominated data collection methods. Data processing approaches primarily utilized RGB-D (55.6%) and skeletal data (27.8%), with algorithms split between traditional machine learning (44.4%) and deep learning (41.7%). …”
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Advances in Monitoring Crop and Soil Nutrient Status: Proximal and Remote Sensing Techniques by Pedro Tomas Bulacio Fischer, Alessandro Carella, Roberto Massenti, Raudhatul Fadhilah, Riccardo Lo Bianco

“…Soil and water pollution caused by excessive use of fertilizers and resource scarcity are critical issues in modern horticulture. Although laboratory tests are reliable, they take time and use chemical reagents that must be disposed of and complex protocols. …”
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ON SOME ASPECTS OF THE ASSESSMENT OF NEGATIVE ANTHROPOGENIC IMPACT ON THE QUALITY OF SURFACE WATER BODIES IN THE ENVIRONMENTAL SAFETY ENSURING SYSTEM by Roman N. Bubenov, Vasiliy I. Borisenko, Andrey A. Danilenko, Lyubov A. Bubenova

“…In turn, this will allow the authorities and relevant federal agencies to respond more quickly to issues of ensuring environmental safety, it will also allow using the budget funds allocated for environmental protection more rationally.…”
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Foods for Sleep Improvement: A Review of the Potential and Mechanisms Involved by Rui Fan, Yingmin Jia, Zhou Chen, Siting Li, Bing Qi, Aijin Ma

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