Source-Free Domain Adaptation for Cross-Modality Abdominal Multi-Organ Segmentation Challenges by Xiyu Zhang, Xu Chen, Yang Wang, Dongliang Liu, Yifeng Hong

“…While unsupervised domain adaptation (UDA) has shown promise in addressing these issues by transferring knowledge from a different modality (source domain), its reliance on both source and target data during training presents a practical challenge in many clinical settings due to data privacy concerns. …”
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SensorsConnect Framework: World-Wide Web for Internet of Things by Abdelrahman Elewah, Khalid Elgazzar

“…A motivating scenario illustrates its potential impact in real-life situations, such as finding a drive-thru coffee shop or crossing a country border. Using real-time road status and service occupancy data, SensorsConnect enhances Google Maps service recommendations, not only minimizing customer wait times but also distributing workload more evenly across service points. …”
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Exploring the Frontier: Generative AI Applications in Online Consumer Behavior Analytics by Takuma Kimura

“…Furthermore, the paper discusses the challenges associated with generative AI, emphasizing the need to consider ethical issues, such as bias and data privacy. This comprehensive review contributes to a deeper understanding of generative AI’s role in OCBA, outlining its applications and functionalities from a technical perspective. …”
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Federated learning-based non-intrusive load monitoring adaptive to real-world heterogeneities by Qingquan Luo, Chaofan Lan, Tao Yu, Minhang Liang, Wencong Xiao, Zhenning Pan

“…Recently, federated learning has enabled NILM to learn from decentralized meter data while preserving privacy. However, as real-world heterogeneities in electricity consumption data, local models, and AMI facilities cannot be eliminated in advance, federated learning-based NILM (FL-NILM) may underperform or even fail. …”
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ADF-SL: An Adaptive and Fair Scheme for Smart Learning Task Distribution by Ahmed A. Al-Saedi, Veselka Boeva

“…However, training models within SL is affected by data heterogeneity and sensitivity, and often requires more computational resources than an individual data provider can afford. …”
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From Neural Networks to Emotional Networks: A Systematic Review of EEG-Based Emotion Recognition in Cognitive Neuroscience and Real-World Applications by Evgenia Gkintoni, Anthimos Aroutzidis, Hera Antonopoulou, Constantinos Halkiopoulos

“…Further, related ethical issues with respect to privacy, data security, and machine learning model biases need to be much more proclaimed to responsibly apply research on emotions to areas such as healthcare, human–computer interaction, and marketing. …”
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Impact of Mask-Wearing on Public Attitudes, Perceptions, and Interest in Rhinoplasty During the COVID-19 Pandemic by Mohanad M. Alsuhaim, MD, MBBS, Abdullah A. Fallatah, MD, MBBS, Mohammed H. Shawosh, MD, MBBS, Adil N. Althobaity, MBBS, SB-PLAST, EBOPRAS

“…This study aimed to investigate the influence of mask use on attitudes, perceptions, and interests in rhinoplasty during the COVID-19 pandemic in Saudi Arabia. …”
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Parameter optimization of 3D convolutional neural network for dry-EEG motor imagery brain-machine interface by Nobuaki Kobayashi, Musashi Ino

“…By completing the system on the edge, the privacy of personal MI data can be ensured, and the system is ubiquitous, which improves user convenience. …”
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Predicting Student Dropout Through Text and Media Content Analysis of VKontakte Profiles by Sergei S. Gorshkov, Dmitry I. Ignatov, Anastasia Yu. Chernysheva

“…While this approach depends on publicly available VK data and may be limited by privacy settings, it still provides useful insights. …”
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MAGMA-MICK: A state-of-the-art digital platform facilitating the programmatic implementation of whole genome sequencing for TB care and prevention by Prof Annelies Van Rie, Fulvio Vigilante, Dr. Walter Sanseverino, Prof Annelies Van Rie

“…Methods: We MICK, a state-of-the-art secure digital platform, for the use of NGS to guide the care and prevention of (DR)-TB. …”
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TwinFedPot: Honeypot Intelligence Distillation into Digital Twin for Persistent Smart Traffic Security by Yesin Sahraoui, Abdessalam Mohammed Hadjkouider, Chaker Abdelaziz Kerrache, Carlos T. Calafate

“…This inversion allows the system to learn generalized attack patterns using only limited data, while preserving privacy and enhancing robustness. …”
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Advanced Applications of Artificial Intelligence in Pharmacovigilance: Current Trends and Future Perspectives by Yogesh S Ahire, Jayesh H Patil, Harshita N Chordiya, Rashmi A Deore, Vinod A Bairagi

“…The ethical and legal implications of patient privacy, data security, and regulatory compliance underscore the necessity of cautious artificial intelligence deployment in order to maintain public trust and protect patient rights. …”
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Artificial Intelligence in Bronchopulmonary Dysplasia: A Review of the Literature by Tony Jha, Sana Suhail, Janet Northcote, Alvaro G. Moreira

“…Addressing ethical considerations, such as data privacy and demographic representation, as well as other practical considerations will be essential to ensure the proper implementation of AI clinical tools. …”
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Hierarchical Federated Learning-Based Intrusion Detection for In-Vehicle Networks by Muzun Althunayyan, Amir Javed, Omer Rana, Theodoros Spyridopoulos

“…To enhance IDS robustness and preserve user data privacy, researchers are increasingly adopting federated learning (FL). …”
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Analysis of Encrypted Network Traffic for Enhancing Cyber-security in Dynamic Environments by Faeiz Alserhani

“…At present, encrypted data is the cornerstone of Internet communication, providing the maximum degree of privacy and security protection for all transmitted data while shielding users against potential cyber threats and attacks. …”
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A systematic review of serious games as tools for STEM education by Talia Tene, Diego Fabián Vique López, Paulina Elizabeth Valverde Aguirre, Nilo Israel Cabezas Oviedo, Cristian Vacacela Gomez, Stefano Bellucci

“…Policymakers are encouraged to support these efforts by providing financial resources and promoting frameworks for ethical, data-secure use of serious games in education. Future research should focus on establishing a globally recognized framework for serious games in STEM, conducting longitudinal studies to evaluate long-term impacts, and exploring diverse educational contexts to ensure inclusive and effective integration.…”
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Impact of telemedicine on antenatal care at a teaching institution in Eastern India: An insight into the future of better India by Ipsita Mohapatra, Vikash K. Rai, Subha Ranjan Samantaray

“…Materials and Methods: Primary data were collected by means of a telephonic survey of all the antenatal patients who used telemedicine services of AIIMS, Kalyani, based on a preformed questionnaire. …”
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Revisiting Leakage-Resilient MACs and Succinctly-Committing AEAD by Mustafa Khairallah

“… Pseudo-Random Injections (PRIs) have been used in several applications in symmetric-key cryptography, such as in the idealization of Authenticated Encryption with Associated Data (AEAD) schemes, building robust AEAD, and, recently, in converting a committing AEAD scheme into a succinctly committing AEAD scheme. …”
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5G-MobiCare: A Secure 5G Assisted Remote Mobile Health Monitoring Platform by Hemangi Goswami, Tarun Pandey, Hiten Choudhury

“…This setup generates vast amounts of real-time data, making secure device authentication essential to ensure data privacy and security. …”
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Exploring the Limitations of Federated Learning: A Novel Wasserstein Metric-Based Poisoning Attack on Traffic Sign Classification by Suzan Almutairi, Ahmed Barnawi

“…This reference model is then used to generate an adversarial local model characterized by low accuracy but minimal perturbation. …”
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