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173 articles for “privacy enhancement”
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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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Blockchain-Assisted Electronic Voting: A System Design Perspective
Abstract: Voting plays a vital role in upholding democratic principles by allowing individuals to express their preferences and take part in shaping the decisions that affect their lives. Despite its importance, traditional voting systems—whether manual or digital—continue to encounter major obstacles. These include a lack of transparency, declining voter turnout, vulnerability to fraud, and concerns around manipulation. While digital voting platforms offer a modern alternative, they often face skepticism due to …
Published in Journal of Electronic Design Technology · Vol. 16, Issue 2, 2025 · pp. 9–16 Read article
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E-Voting Application Using Blockchain
Abstract: Electronic voting (e-voting) is increasingly recognized as a method for improving the electoral process by enhancing security, accessibility, and efficiency. However, traditional e-voting systems present challenges, including security vulnerabilities, lack of transparency, and privacy concerns. This study presents an e-voting system powered by blockchain technology, designed to enhance decentralization, security, and protection against fraud. By leveraging blockchain’s features such as immutability, transparency, and cryptographic security, this model mitigates risks related …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 12, Issue 2, 2025 · pp. 12–21 Read article
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Crime Prediction and Criminal Identification System Using Machine Learning
Abstract: Advanced machine learning and data analytics-driven crime prediction and criminal identification systems have become game-changing instruments for contemporary law enforcement. Utilizing past crime statistics, surveillance footage, and additional resources, these systems forecast criminal activity, manage resources efficiently, and improve investigation capacities. With an emphasis on their importance in enhancing public safety and lowering crime rates, this paper presents an overview of criminal identification and prediction systems. Examining the technologies and …
Published in International Journal of Electronics Automation · Vol. 2, Issue 1, 2024 · pp. 28–34 Read article
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Analysis and Identification of Malicious Mobile Applications Using Machines Learning
Abstract: Over the past few years, malware attacks on the Android platform have surged, posing significant risks to users' financial security, personal information, and device integrity. In the first half of 2019 alone, approximately 25 million smartphones were infected, highlighting the severity of these threats. The model ranks manifest features based on their frequency in normal and malicious apps, identifying key components that distinguish benign from malicious applications. To improve detection …
Published in Journal of Microcontroller Engineering and Applications · Vol. 12, Issue 2, 2025 · pp. 17–24 Read article
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Predicting Multiple Diseases Using Machine Learning: A Data-Driven Approach
Abstract: The increasing prevalence of chronic and life-threatening diseases highlights the need for innovative healthcare solutions that enable early detection and proactive management. The Multiple Disease Prediction Platform is a web-based system utilizing machine learning (ML) and deep learning (DL) algorithms to analyze user-inputted health data, generating real-time predictions of potential health risks. By leveraging Python’s Streamlit library, the platform provides an interactive and accessible diagnostic experience, eliminating the need for …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 2, 2025 · pp. 16–35 Read article
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Routing Protocols in FANETs with Future Enhancements
Abstract: Flying Ad Hoc Networks (FANETs), which are swarms of Unmanned Aerial Vehicles (UAVs), are an emerging solution which revolutionized the area of mission-critical and infrastructure-less communication systems. These networks provide real-time data transfer for use cases such as disaster relief, battlefield observation, environmental monitoring, and 6G-based smart cities. However, the dynamic profile of FANETs, which is defined by high 3D mobility, limited energy resources, unstable wireless links, and constant topology …
Published in Journal of Aerospace Engineering & Technology · Vol. 15, Issue 3, 2025 · pp. 8–13 Read article
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A Review on Applications of Artificial Intelligence (AI) in Parkinsons’s Disease Diagnosis and Treatment and Its Future Challenges
Abstract: Parkinson’s disease (PD) is a long-term, progressive neurodegenerative disorder that mainly occurs in people older than 60 years, affecting nearly 1% of this population. It is chiefly marked by the loss of dopaminergic neurons in the substantia nigra, a crucial brain region responsible for controlling motor functions. The resultant dopamine deficiency significantly disrupts motor control, manifesting in clinical symptoms such as tremors, bradykinesia, muscle rigidity, and postural instability. While PD …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 15, Issue 3, 2025 · pp. 1–15 Read article
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Enhancing Security in Unified Software Architecture for Smart Computing IoT Devices via Mobile App Authentication Using Quantum-Based Encryption
Abstract: Security remains a critical concern in the landscape of smart computing for IoT devices, necessitating robust measures to safeguard sensitive data and user privacy. In this context, the utilization of quantum-based encryption presents a promising avenue to enhance security in unified software architecture. This study proposes a model aimed at fortifying the security of IoT devices by integrating mobile app authentication with quantum-based encryption techniques. The model leverages Quantum Key …
Published in Recent Trends in Parallel Computing · Vol. 12, Issue 3, 2025 · pp. 41–48 Read article
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Parallel Privacy-Preserving Adaptive Federated Learning on GPU-Enabled Multi-Core Architectures
Abstract: The increasing deployment of parallel and distributed intelligent systems has intensified the need for privacy-preserving learning frameworks that can exploit multi-core and GPU-based architectures without centralizing sensitive data. This work proposes a parallel Adaptive Federated Learning (AFL) framework that integrates Differential Privacy and Secure Aggregation over heterogeneous multi-core and GPU platforms to enhance both data confidentiality and convergence efficiency. The framework dynamically adjusts client participation, learning rates, and aggregation weights …
Published in Recent Trends in Parallel Computing · Vol. 13, Issue 1, 2026 Read article
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Enhancing Remote Patient Monitoring with Ai-Powered Virtual Assistants
Abstract: Artificial Intelligence (AI) is transforming personalized education by tailoring learning materials to meet the distinct needs, preferences, and progress of individual students. This paper explores how AI technologies—such as machine learning, natural language processing, and adaptive learning systems are improving the effectiveness of personalized learning experiences. Through AI, students benefit from timely feedback, access to intelligent tutoring systems, and data-driven insights that enable educators to enhance their teaching strategies. Additionally, …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 4, Issue 1, 2026 Read article
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Deep Learning Algorithms for Medical Image Encryption to Ensure Secure Data Transfer
Abstract: Deep learning has significantly impacted various fields, including medical imaging, by offering new ways to encrypt medical images for secure data transfer. This research work examines how deep learning algorithms are used to enhance medical image security during transmission. Given the high sensitivity and privacy requirements of medical data, it’s crucial to maintain its confidentiality. Traditional encryption techniques, while reliable, often struggle with issues like scalability, computational efficiency, and the …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 11, Issue 3, 2024 · pp. 28–36 Read article
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IoT-Based Industrial Safety Management Systems
Abstract: The integration of the Internet of Things (IoT) in industrial safety management has transformed workplace safety by enabling real-time monitoring, predictive analytics, and automated hazard mitigation. IoT-Based Industrial Safety Management Systems utilize interconnected sensors, wearable devices, and intelligent analytics platforms to proactively detect and respond to potential risks in high-risk environments such as manufacturing, oil and gas, and construction. These systems continuously monitor critical safety parameters, including temperature, pressure, gas …
Published in Journal of Industrial Safety Engineering · Vol. 12, Issue 1, 2025 · pp. 18–22 Read article
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Exploring the Future of Smart Homes: Voice Control Technologies and Applications
Abstract: With the use of voice commands, smartphones, and the Internet of Things, homeowners may utilise an intelligent house automation system, a technology-driven solution, to control and automate a variety of home systems and gadgets from a central hub. The system typically includes equipment such as smart thermostats, smart lighting, smart locks, security systems, and entertainment systems. With the increasing prevalence of IoT, smart homes have become increasingly popular, and automation …
Published in International Journal of Electrical Machine Analysis and Design · Vol. 2, Issue 1, 2024 · pp. 31–37 Read article
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Adaptive E-Learning Algorithms and Heutagogy: A Systematic Analysis
Abstract: The proliferation of artificial intelligence (AI) and machine learning (ML) technologies has transformed the digital education landscape by enabling adaptive e-learning systems capable of personalizing content and optimizing learning paths. This study provides a systematic analysis of adaptive e-learning algorithms within the framework of heutagogy, an educational paradigm that emphasizes learner autonomy, self-direction, and capability development. The convergence of adaptive technologies with heutagogical principles offers new avenues for creating more …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 3, 2025 · pp. 33–38 Read article
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Federated Learning for Energy Management in Next Generation Smart Cities
Abstract: Federated learning has emerged as a promising approach for addressing the challenges of energy management in next-generation smart cities. This decentralized approach to machine learning allows collaborative model training among distributed data sources, while safeguarding data privacy and security. In this study, we explore the application of federated learning techniques to optimize energy consumption, enhance grid stability, and promote sustainability in smart city environments. By aggregating data from diverse sources …
Published in Journal of Communication Engineering & Systems · Vol. 14, Issue 1, 2024 · pp. 19–27 Read article
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The Digital Lifeline: How Computers Shape Everyday Life
Abstract: Computers have become an integral part of everyday life, significantly influencing the way the common man interacts with the world. From revolutionizing communication to transforming industries, education, healthcare, and entertainment, computers have reshaped the fabric of modern society. This study explores the multifaceted impact of computers on daily life, examining how they have made tasks easier, faster, and more efficient. While enhancing productivity and connectivity, computers have also introduced new …
Published in Current Trends in Information Technology · Vol. 15, Issue 3, 2025 · pp. 33–47 Read article
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The Future of Mathematics Education in the Era of Artificial Intelligence
Abstract: The rapid integration of Artificial Intelligence (AI) into education is fundamentally reshaping the landscape of mathematics teaching and learning. This study examines how AI-powered tools are converting conventional math training into inclusive, individualized, and data-driven learning environments. Through an in-depth examination of global case studies—including Squirrel AI, Carnegie Learning’s MATHia, Khan Academy, Microsoft Math Solver, DIKSHA, Photomath, ALEKS, and BYJU’S—the study highlights AI’s ability to tailor content, deliver real-time feedback, …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 12, Issue 2, 2025 · pp. 37–44 Read article
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21st Century Cognitive Landscapes: Integrating ICT-Driven Pedagogies for Holistic, Inclusive Education
Abstract: The rapid advancement of Information and Communication Technology (ICT) has revolutionized digital pedagogies, reshaping modern education by improving accessibility, learner engagement, and academic outcomes. This review critically explores the psychological ramifications of digital learning environments while assessing the effectiveness of ICT tools in fostering inclusive and sustainable education. By integrating insights from contemporary research, this paper examines the impact of digital pedagogies on cognitive function, emotional health, and social interactions …
Published in International Journal of Education Sciences · Vol. 2, Issue 2, 2025 · pp. 75–81 Read article
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Employee Well-Being: Deep Learning Approaches to Stress Detection
Abstract: Stress has become a major concern for employee health, productivity, and overall well-being in today's fast-paced work environment. It is a growing global issue, affecting both individual employees and the productivity of organizations. Work-related stress occurs when the demands of a job surpass an individual's ability to manage, whether because of long hours, overwhelming responsibilities, or other pressures. Factors such as conflicts with coworkers or supervisors, constant changes, and job …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 12, Issue 1, 2025 · pp. 52–58 Read article