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36 articles for “privacy preservation”
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Role of Functional Programming Languages in Blockchain Applications
Abstract: Functional programming (FP) languages play an increasingly influential role in blockchain applications, offering features that address critical challenges such as security, scalability, and reliability. The inherent characteristics of FP—immutability, pure functions, statelessness, and concurrency support—align well with blockchain’s decentralized and deterministic structure, making FP languages a natural fit for developing secure and verifiable smart contracts. Languages like Haskell, OCaml, and Erlang have proven effective in minimizing code errors, enabling formal …
Published in Recent Trends in Programming languages · Vol. 11, Issue 3, 2024 · pp. 21–27 Read article
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Recent Advances in Content-based Image Retrieval: Techniques and Applications
Abstract: Content-based image retrieval (CBIR) plays a vital role in computer vision, driven by the increasing need for fast and accurate image retrieval across fields like healthcare, e-commerce, and digital libraries. This study offers a detailed review of CBIR methodologies, charting their progression from traditional feature extraction techniques, such as Local Binary Patterns (LBP), to contemporary deep learning-driven methods. The transformative impact of convolution neural networks (CNNs) is highlighted, emphasizing their …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 1, 2025 · pp. 67–71 Read article
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Machine Learning-Based Approach for Heart Disease Prediction
Abstract: Heart disease is a significant global health challenge, with early diagnosis and prediction being essential for reducing mortality rates. Machine Learning (ML), an efficiently developing field within Artificial Intelligence, provides innovative methods for analyzing complex clinical data to predict heart disease. This review examines the basic machine learning techniques, data, and metrics used in cardiovascular disease prediction. It explores the role of supervised learning, such as decision trees and logistic …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 2, 2025 · pp. 64–73 Read article
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Facial Emotion Detection and Its Applications
Abstract: Facial emotion detection (FED) is an interdisciplinary field that integrates artificial intelligence, computer vision, and machine learning to recognize and interpret human emotions based on facial expressions. The development of FED systems has been propelled by advancements in deep learning, particularly convolutional neural networks (CNNs) and recurrent neural networks (RNNs), which enhance recognition accuracy. Feature extraction techniques, including geometric and appearance-based methods, play a crucial role in classifying emotional states. …
Published in International Journal of Optical Innovations & Research · Vol. 3, Issue 1, 2025 · pp. 8–12 Read article
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A Comprehensive Review on Federated Learning in Disease Detection
Abstract: Healthcare data, which is frequently dispersed among various organisations, has enormous potential to improve predictive analytics and illness identification. However, there are substantial privacy & legal obstacles to sharing this private data for centralised model training. Federated Learning is a paradigm shift that allows several organisations to work together to build a global model without disclosing raw patient information. Federated Learning uses a larger dataset to provide more reliable insights …
Published in Emerging Trends in Personalized Medicines · Vol. 3, Issue 1, 2026 · pp. 1–21 Read article
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Multi-Layered AI-Driven Security in Wireless Ecosystems
Abstract: The proliferation of next-generation wireless technologies, from 5G/6G networks to the pervasive Internet of Things (IoT), has birthed a hyperconnected digital ecosystem of unprecedented scale and dynamism. This interconnectedness, however, introduces a vast and volatile attack surface, rendering conventional, signature-based security paradigms fundamentally obsolete. This paper posits that the only viable defense is an offensive, self-adaptive one, predicated on the integration of artificial intelligence (AI) directly into the wireless security …
Published in International Journal of Wireless Security and Networks · Vol. 4, Issue 1, 2026 · pp. 21–28 Read article
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A Comprehensive Review on IoT and Edge Computing in Electronics: Trends, Challenges, and Future Directions
Abstract: The Internet of Things (IoT) transformed the electronics industry by enabling ubiquitous connectivity between billions of devices. This has created an unprecedented amount of data, challenging traditional cloud-based architectures with latency, bandwidth, and security issues. Edge computing came as an additive architecture by distributing computation and bringing intelligence to IoT edges to provide real-time responsiveness and reduce dependence on centralized infrastructure. This study offers a thorough analysis of current developments …
Published in Journal of Electronic Design Technology · Vol. 17, Issue 1, 2026 · pp. 1–9 Read article
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Proof-of-Minimum Privacy Leak Consensus Strategy in Blockchain
Abstract: In this study, we propose a novel consensus algorithm to preserve the security and privacy of a transaction. We propose a Proof-of-Minimum Privacy Leak consensus strategy. This means that the competing nodes which participate in the competition to mine the next block should give a proof of minimum privacy leak during its transaction. Only this proof will give highest votes to that node, and it will be elected as the …
Published in E-Commerce for Future & Trends Read article
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A Comprehensive Review of Digital Transformation in Healthcare: Addressing Privacy, Security, and Usability Challenges in Electronic Health Records
Abstract: The healthcare industry’s shift toward digitalization through electronic health records (EHRs) and advanced health information technology (HIT) promises improved patient care but brings forth challenges in safeguarding patient data privacy, confidentiality, and security (PCS). Researchers are exploring innovative solutions like block chain and cryptography to address these concerns while ensuring usability for healthcare professionals. Additionally, the impact of regulatory frameworks on data sharing and security is being studied, emphasizing the …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 13, Issue 3, 2024 · pp. 9–14 Read article
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IoT Security: Issues, Best Practices, and Open Challenges
Abstract: The internet of things (IoT) provides the facility to connect different devices and communicate and share information over the internet. IoT has emerged as a transformative and pervasive technological paradigm, revolutionizing how we interact with our environment and infusing intelligence into everyday objects and devices. This interconnected ecosystem has unleashed a wave of innovative applications across diverse domains, including healthcare, transportation, agriculture, industrial automation, and smart cities. However, as the …
Published in International Journal of Information Security Engineering · Vol. 1, Issue 2, 2023 · pp. 7–13 Read article
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Emotionally Intelligent AI: The Future of Mental Health Care and Emotional Well-being
Abstract: With the potential to improve emotional well-being through sophisticated AI systems, emotionally intelligent AI (EI-AI) represents a revolutionary frontier in mental health treatment. EI-AI can recognize, understand, and react to human emotions in real- time by utilizing recent advancements in machine learning, natural language processing, and emotion detection. These features are being used more and more in mental health settings, where chatbots and other AI-driven interventions help with emotional regulation, …
Published in Recent Trends in Social Studies · Vol. 2, Issue 1, 2025 · pp. 17–21 Read article
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Human-Robot Interactions and Social Robotics in Legal, Ethical, and Social Dimensions
Abstract: Human-robot interaction and social robotics have emerged as transformative fields, reshaping human engagement with intelligent machines. This evolution brings profound legal, ethical, and social challenges that demand critical exploration. Also, legal firms often struggle to keep pace with the advancements, raising questions about liability, accountability, and privacy in human-robot interaction. However, social robots, designed to operate in dynamic human environments, present ethical dilemmas around autonomy, trust, and preserving human dignity. …
Published in Journal of Advancements in Robotics · Vol. 12, Issue 1, 2025 · pp. 09–11 Read article
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Comparative of Encryption-Decryption Performance of (Binary, Gray- Scale, Color) Images Using Discrete Fractional Fourier Transform (DFRFT)
Abstract: The Discrete Fractional Fourier transform (DFRFT) provides an effective model of image encryption by further developing the classic Fourier transform by adding fractional orders, which increase the degrees of freedom. Owing to the omnipresence of digital media in many industries like education, healthcare, and entertainment, the mobility of visual data has become a significant issue to keep confidential. Images form one of the main ways of exchanging information and, therefore, …
Published in Research & Reviews : Journal of Physics · Vol. 15, Issue 1, 2026 · pp. 54–65 Read article
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Pharmacy Teachers' Contribution to Preserving Education's Integrity and Quality in the AI Era
Abstract: Artificial Intelligence through its modern approach supports the development of pharmacy education through customized methods and automatic evaluation systems and computerized training exercises. Students benefit from AI tools which include intelligent tutoring systems together with virtual assistants and simulation platforms because these tools improve their knowledge of pharmacology and drug formulation as well as clinical practice. The transition to AI-controlled education creates new academic integrity issues and ethical problems and …
Published in Research and Reviews: A Journal of Pharmacology · Vol. 15, Issue 3, 2025 · pp. 20–42 Read article
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A Secured Architecture of Internet of Things (IoT) in the 5G Age
Abstract: Internet of things (IoT) is a technology capable of connecting vast number of devices of many types worldwide via the internet using unique IP addresses. The connected devices can communicate ubiquitously anywhere, anytime for any given user. Such globally distributed networks require a high level of connectivity among its components like smart sensors, workstations as well as networking devices. Thankfully, with the aid of the recently emerged 5G technology, which …
Published in International Journal of Mobile Computing Technology · Vol. 3, Issue 1, 2025 · pp. 33–43 Read article
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Cloud-based Application Development and Optimization
Abstract: As cloud computing powers today’s applications, optimizing cloud-based development is crucial to achieve performance, cost effectiveness, and scalability. This research focuses on enhancing the design, deployment, and maintenance of cloud applications, tackling challenges in resource management, scalability, and resilience. We specifically explore dynamic resource allocation algorithms that use predictive analytics for auto-scaling based on workload variations, aiming to cut costs while preserving high performance. The study also investigates cross-cloud optimization …
Published in Journal of Open Source Developments · Vol. 12, Issue 1, 2025 · pp. 37–42 Read article