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173 articles for “privacy enhancement”
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AI-Driven Micro-Expression Recognition for Early Mental Health Disorder
Abstract: Mental health conditions like anxiety and depression are often undiagnosed because the usual diagnostic methods based on basic regular instruments like questionnaires and clinical interviews have some limitations in them. They are not objective often and may not catch the initial signs of psychological distress. Micro-expressions have become valid measures of repressed or unconscious emotions and can provide greater insight into someone's mental condition. Also, identification and interpretation of these …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 12, Issue 3, 2025 · pp. 40–49 Read article
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Development Of Ai-Driven Systems for Real-Time Joint Movement Detection and Correction in Frozen Shoulder Therapy Using Sensor-Based Shoulder Rehabilitation Devices
Abstract: Frozen shoulder, or adhesive capsulitis, is a common musculoskeletal disorder characterized by progressive pain, stiffness, and restricted range of motion that significantly impairs functional ability and quality of life. Recent advancements in artificial intelligence and sensor-based technologies have enabled the development of intelligent rehabilitation systems capable of real-time joint movement detection and correction. Wearable sensors such as inertial measurement units, electromyography sensors, and flexible strain sensors capture continuous biomechanical data …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 15, Issue 1, 2026 Read article
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A Literature Review on Internet of Medical Things
Abstract: Artificial Intelligence (AI) is transforming healthcare by improving diagnostics, treatment planning, and patient management through data-driven insights and automation. The Internet of Medical Things (IoMT) represents a significant shift in modern healthcare, enabling real-time patient monitoring, data-driven decision-making, and enhanced medical outcomes. This literature review explores the architecture of IoMT, including perception layer, network layer, transport layer and application layer. It also thoroughly explores key challenges like ensuring data security, …
Published in International Journal of Wireless Security and Networks · Vol. 3, Issue 2, 2025 · pp. 23–34 Read article
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Antimicrobial Resistance and AI-Based Strategies for Rapid Pathogen Detection
Abstract: Antimicrobial resistance (AMR) has become a major global health threat, significantly reducing the effectiveness of antimicrobial therapies and increasing the burden of infectious diseases worldwide. The rapid emergence of multidrug-resistant pathogens has created an urgent need for faster, more accurate, and scalable diagnostic approaches to support timely treatment and effective infection control. Artificial intelligence (AI) has emerged as a promising technology capable of transforming pathogen detection and AMR surveillance through …
Published in Recent Trends in Infectious Diseases · Vol. 3, Issue 2, 2026 · pp. 26–36 Read article
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Exploring Artificial Intelligence in the Finance Sector
Abstract: Artificial intelligence (AI), machine learning (ML), and progressive algorithms illustrate a substantial technological leap with wide applications across sectors like automobiles, healthcare, gaming, finance, entertainment, and more. The foremost objective of AI is to produce intelligent, independent systems capable of self-sustaining decision-making. This study delivers a concise summary of AI, concentrating on its transformative influence on finance, especially within banking, asset firms, derivatives markets, and insurance enterprises. It summarizes the …
Published in E-Commerce for Future & Trends · Vol. 11, Issue 3, 2024 · pp. 16–23 Read article
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Enhanced Multimodal Disease Prediction Using Hybrid Ensemble Learning and AutoML Techniques
Abstract: The integration of hybrid ensemble learning and automated machine learning (AutoML) is revolutionizing disease prediction by addressing the complexity, imbalance, and high dimensionality inherent in medical datasets. This paper proposes an advanced pipeline that combines diverse ensemble learning models with AutoML-based optimization to predict chronic diseases such as kidney diseas-e, Parkinson’s disease, and lung cancer. Publicly available datasets from UCI and PhysioNet repositories were preprocessed using outlier removal, normalization, and …
Published in Research and Reviews : Journal of Computational Biology · Vol. 15, Issue 1, 2026 Read article
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AI-Powered Drug Delivery: Revolutionizing Formulation Science
Abstract: Artificial Intelligence (AI) is emerging as a groundbreaking tool in revolutionizing Drug Delivery Systems (DDS), offering promising advancements in precision, efficiency, and personalized treatment strategies. The integration of AI technologies into pharmaceutical research and development is transforming how drugs are formulated, delivered, and monitored in real time. By leveraging machine learning algorithms and data analytics, researchers can design drug delivery models that are not only more effective but also tailored …
Published in Trends in Drug Delivery · Vol. 13, Issue 1, 2026 · pp. 48–61 Read article
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Artificial Intelligence in Early Diagnosis and Personalized Treatment of Alzheimer’s Disease
Abstract: Artificial intelligence (AI) has become a disruptive technology in the medical care industry, with potential solutions to early diagnosis and customized treatment of Alzheimer’s disease (AD), a progressive neurodegenerative disease and the most prevalent cause of dementia globally. Conventional diagnostic techniques, such as cognitive, neuroimaging and biomarker techniques, are usually limited in the ability to detect disease at its most susceptible stage when treatment interventions are most effective. The recent …
Published in International Journal of Brain Sciences · Vol. 3, Issue 2, 2026 · pp. 15–27 Read article
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Enhancing Cyber Security in the Banking Sector Using Biometrics
Abstract: The fast-paced digital evolution within the banking industry has led to a substantial rise in the number of financial transactions conducted through online and mobile platforms. While this transformation has improved customer convenience and service accessibility, it has also exposed banking systems to a wide range of cyber threats, such as identity theft, phishing attacks, credential compromise, and financial fraud. Conventional authentication mechanisms, including passwords and personal identification numbers (PINs), …
Published in International Journal of Wireless Security and Networks · Vol. 4, Issue 1, 2026 · pp. 15–20 Read article
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Artificial Intelligence Technology in Libraries: Transforming Information Access and Management.
Abstract: This article provides an extensive summary of the integration of AI technologies with library services. Examining current applications, benefits, challenges, and future trends, the discussion highlights the transformative potential of AI and advocates for the ethical implementation of execution strategies. As libraries evolve in the digital age, adopting AI in a responsible and informed manner will be crucial to maintaining their role as vital centers of knowledge and community engagement. …
Published in Journal of Advancements in Library Sciences · Vol. 12, Issue 2, 2025 · pp. 1–5 Read article
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Blockchain-Enabled Secure Data Sharing in Mobile IoT Networks
Abstract: The rapid proliferation of mobile Internet of Things (IoT) devices has resulted in an exponential increase in data generation, storage, and sharing, which poses significant challenges related to security, privacy, integrity, and trustworthiness. Traditional centralized architectures for IoT data exchange are inherently vulnerable to single points of failure, unauthorized access, data tampering, and limitations in scalability. Blockchain technology, with its decentralized ledger structure, cryptographic integrity, and consensus mechanisms, provides a …
Published in International Journal of Mobile Computing Technology · Vol. 4, Issue 1, 2026 · pp. 38–44 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
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Smart Cities: How AI and IoT Shape Our Cities
Abstract: In this modern world where urbanization and digital technologies intersect, smart cities have emerged as a symbol of progress and innovation. Smart cities are urban areas built to operate in a more sustainable, connected, and efficient way. As our cities grow and become more complex, it is important to find new ways to address the challenges that arise, such as security, privacy, and mobility. This study examines how AI and …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 13, Issue 3, 2025 · pp. 19–28 Read article
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Artificial Intelligence in intra operative and peri operative management of major oral and maxillofacial surgeries
Abstract: Artificial Intelligence and virtual reality are becoming a part of everyday life and are enhancing our quality of life extensively. It is only natural that the same shall be used in surgery also. The existing body of literature on artificial intelligence (AI) and its integration into various surgical specialties has been extensively reviewed and discussed in this article. These insights, though derived from broader surgical domains, can be effectively translated …
Published in Research and Reviews: A Journal of Dentistry · Vol. 16, Issue 2, 2025 · pp. 1–5 Read article
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IoT-based Black Box Monitoring for Vehicle Crash Data Analysis and Improving Safety
Abstract: Road accidents are a significant global concern. This project proposes an Internet of Things (IoT)-based black box monitoring system for vehicles to enhance road safety through comprehensive crash data analysis. The system expands on traditional black boxes by incorporating various sensors (accelerometers, gyroscopes, GPS) and potentially in-cabin cameras (with privacy safeguards). This data offers a deeper understanding of crash dynamics, including impact severity, vehicle motion, and safety system deployment timing. …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 12, Issue 3, 2024 · pp. 7–13 Read article
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Academia to Industry: The Impact of AI on Information Retrieval Technologies
Abstract: Artificial intelligence (AI) has significantly reshaped the field of information retrieval (IR), bridging theoretical advancements from academia with practical applications across various industries. This article explores the transformative impact of AI on IR technologies, highlighting key contributions from academic research and how they have been adapted for industry-scale implementations. Academic innovations, such as neural ranking models and semantic search techniques, have improved the accuracy and relevance of search results by …
Published in Journal of Advancements in Library Sciences · Vol. 12, Issue 1, 2025 · pp. 1–7 Read article
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Design of an Integrated Health Monitoring System on an IoT-Based Framework
Abstract: With the advent of industrialization, health ailments have become a major cause of concern owing to an inactive and fast lifestyle, polluted environments, and detrimental eating habits. However, IoT has become a boon for the health sector and humanity on account of its countless benefits, rendering improved quality of service and patient-centric care. An Integrated Health Monitoring System (IHMS) is presented in this paper. This new IoT-based framework integrates wearable …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 4, Issue 1, 2026 · pp. 1–7 Read article
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An Analysis of Multimodal Fusion in Deepfake Detection for Video Samples
Abstract: In today’s rapidly evolving digital landscape, deepfake technology stands as both a marvel and a threat to privacy and security. Deepfakes, hyper-realistic synthetic media created using artificial intelligence (AI), can deceive and manipulate on an unprecedented scale, from political propaganda to compromising videos of public figures. This research navigates deepfake detection, focusing on two advanced methodologies: the vision transformers (ViT) image classifier and the Meso4 method. The ViT model utilizes …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 11, Issue 3, 2024 · pp. 19–27 Read article
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Keyless: LQ Based On IOT
Abstract: In recent years, there has been a growing interest in smart home technologies, with smart door locks being one of the focal points due to their potential to enhance security and convenience. Smart door lock systems are transforming access control by offering a keyless alternative for both residential and commercial settings. These electronic locks replace traditional keys with secure methods such as emergency alarms, privacy modes, battery backup, cameras, voice …
Published in Journal Of Network security Read article
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Keyless Lock Based on Internet of Things
Abstract: In recent years, there has been a growing interest in smart home technologies, with smart door locks being one of the focal points due to their potential to enhance security and convenience. Smart door lock systems are transforming access control by offering a keyless alternative for both residential and commercial settings. These electronic locks replace traditional keys with secure methods such as emergency alarms, privacy modes, battery backup, cameras, voice …
Published in Journal Of Network security · Vol. 12, Issue 2, 2024 · pp. 18–21 Read article