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The rapid evolution of sustainability legislation, including the CSDDD and CSRD, has created a complex dual mandate for modern enterprises. Organizations are now required to provide granular transparency into their suppl...

Abstract Federated Learning (FL) has been widely used in Internet of Things (IoT) environments as a promising decentralized framework capable of collaborative model training without exposing local data. Despite its advan...

Aim: This study was conducted to examine the relationship between the ethical values of students enrolled in health programs who are receiving clinical training in a hospital setting and patient privacy. Method: The rese...

Abstract While multi-access edge computing (MEC) enables flexible task offloading, the inherent dynamism and complexity of real-world environments, accompanied by various uncertainties, exacerbate the challenges in offlo...

Abstract Object classification in decentralized environments is critically hindered by data heterogeneity and privacy constraints, which cause models to learn spurious, client-specific correlations rather than generaliza...

The emergence of the Metaverse as a persistent, immersive, and interoperable digital ecosystem introduces system-level challenges in identity management, security, and privacy protection across networked extended reality...

Tehran Privacy is home to nearly 16 million people. This privacy has been local until now to attack the land grabbers and the invasion of the poor and even some official organizations in the form of cooperatives that the...

Abstract BackgroundAs Saudi Arabia aims to enhance the adoption and utilization of mobile health (mHealth) apps in the health care sector, it is vital to identify the potential challenges that may be faced in...

Abstract The rapid proliferation of wireless body area networks (WBANs) has intensified the need for architectures that simultaneously guarantee quantum-resistant security, patient privacy, and clinical-grade diagnostic ...

Abstract The increasing adoption of Industrial Internet of Things (IIoT) devices introduces significant cybersecurity and privacy challenges, particularly anomaly detection and secure data sharing. This study presents Se...

People are increasingly reliant on the internet for communication and various devices in their daily lives. The Internet of Things (IoT) has dramatically changed many industries by allowing more automation and easy data ...

The power system event detection process must accelerate and become more precise with increasing penetration of renewable energy systems into the grid. The authors discuss a federated learning LSTM (FL-LSTM) that serves ...

Abstract Smart home networks are a rapidly evolving part of the Internet of Things (IoT), where connected devices exchange information to automate energy use, enhance comfort, and improve user safety. Despite their benef...

Federated Learning (FL) has emerged as a privacy-preserving distributed learning paradigm that enables collaborative model training without sharing raw data. Despite its advantages, ensuring trustworthy FL deployment rem...

Abstract The ability to monitor the safety of natural gas pipelines is guaranteed by leak detection. Systems are capable of responding quickly, and very precisely to events because delays during such events can lead to s...

The further promotion and application of new media technologies present new opportunities for psychiatric specialty hospitals in areas such as health education, doctor-patient communication, service extension, and brand ...

The integration of Artificial Intelligence (AI) in higher education presents both opportunities and ethical challenges. In Malaysia, private universities are adopting AI at a pace that often outshines the development of ...

Background: The imbalance in nurse-to-patient ratio and shortage of nurses is the main drive for care provision by a nurse of the opposite gender. On the other hand, while nurses must recognise and respect the role of p...

Abstract In the contemporary digital era, the storage of Electronic Health Records on open platforms presents significant security and privacy challenges. Addressing these concerns requires standardizing the clinical dep...

Abstract Differentially private stochastic gradient descent is a standard algorithm for training deep models on sensitive data, but under tight privacy budgets it must add large noise to every step, which slows convergen...

The article is dedicated to a comprehensive analysis of the phenomenon of virtual reality as an innovative sociocultural formation that significantly changes the ways of human existence, perception, communication, and in...

The individuals on the ground nowadays often observe objects distantly hover over the sky, which raises the question of who might be operating the object or what the object might record. Unmanned Aircraft Systems (UAS) o...

Chilling effects are inhibitions of legitimate behaviors and are an important ethical side effect of surveillance. With the centrality of media users’ data for digital communication it is important to gain insights int...

Infant cry paralinguistics provides a non-invasive signal for early assessment of physiological and affective states. Yet, most learning approaches implicitly assume that the mapping between acoustic patterns and semanti...