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75 articles for “data fusion”
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Secured Communication and Image Authentication: Embedding Encrypted Text Files Into Color Digital Images
Abstract: In today's digital landscape, protecting digital assets, particularly images, is paramount. Researchers have developed various techniques to safeguard these assets, emphasizing their protection and integrity. Simultaneously, steganography plays a crucial role in securely communicating confidential messages. This paper focuses on a dual-purpose technique: watermarking color digital images for protection and embedding secret messages through steganography. This fusion of functionalities represents a significant step in comprehensive asset protection and confidential communication …
Published in International Journal of Information Security Engineering · Vol. 2, Issue 1, 2024 · pp. 10–15 Read article
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A Reviewed Study On Cpu-Optimized Parameter-Efficient Fine- Tuning For Large Language Models To Increase Accuracy Using Lora
Abstract: The fast proliferation of Large Language Models (LLMs) has increased the need to optimize the process of fine-tuning but the existing workflows that require a GPU are still expensive, intensive, and unavailable to most researchers. This paper is driven by the desire to have a more cost-efficient and democratized version by examining a CPU-efficient implementation of Parameter-Efficient Fine-Tuning (PEFT) based on Low-Rank Adaptation (LoRA). The major purpose of the study …
Published in Recent Trends in Parallel Computing · Vol. 13, Issue 1, 2026 Read article
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Diffusion-Based Enhancement of Low-SNR Time- Frequency Signals
Abstract: Traditional enhancing techniques are useless in low signal-to-noise ratio (LSNR) situations because noise drastically interferes with communication signals. Based on an enhanced DiffBIR model, this paper suggests a dual-stage signal improvement approach that combines diffusion with deep learning. By combining the Inception module for multi-scale feature extraction with the Pixel Fusion Attention (PFA) module for significant region highlighting, the model improves signal recovery in the time- frequency domain. Experiments show …
Published in Current Trends in Signal Processing · Vol. 17, Issue 2, 2026 Read article
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Intelligent Robotics using microelectronics Exploring the Future of Smart Machines
Abstract: In the past few years, robotics technology has made remarkable progress. In order to assist humans in their work, robots that can recognise and track people are required; as a result, tools like the "Human Following Load carrier" that can converse and live with people must be created. Localising the robot and its surroundings is one of the primary obstacles in enabling the robot to do different jobs in the …
Published in Journal of Nuclear Engineering & Technology · Vol. 14, Issue 2, 2024 · pp. 10–17 Read article
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AI and IoT in Sustainable Agriculture: A Review
Abstract: Artificial Intelligence (AI) and Internet of Things (IoT) integration have transformed the world of sustainable agriculture, presenting new ways of resource optimization, increasing crop yields, and making environmental sustainability more accessible. The current literature review analyzes the applications of AI and IoT in three significant agricultural systems: aquaponics, hydroponics, and poultry farming. By critically analyzing recent studies, this paper emphasizes how deep learning- enabled computer vision techniques allow for the …
Published in Journal of Instrumentation Technology & Innovations · Vol. 15, Issue 2, 2025 · pp. 32–45 Read article
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AI-Based Software-Defined Satellite in Decision Making: A Study
Abstract: For decades, satellites have been a vital infrastructure, relaying communication signals, observing Earth's climate, and providing critical navigation data. However, the traditional model of satellite operation is often rigid and reactive, relying heavily on pre-programmed instructions and ground-based control. This limits their flexibility and responsiveness in a rapidly changing environment. Enter software-defined satellites (SDS), and now, the game-changer: artificial intelligence (AI). Imagine a satellite that can independently analyze its surroundings, …
Published in International Journal of Satellite Remote Sensing · Vol. 3, Issue 1, 2025 · pp. 63–72 Read article
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Role of Machine Vision in Autonomous Vehicles: A Review
Abstract: The integration of machine vision in autonomous vehicles (AVs) is a critical advancement in the field of intelligent transportation systems. Machine vision systems enable AVs to perceive their environment, understand road conditions, detect obstacles, and make real-time decisions necessary for safe navigation. These systems rely heavily on image processing techniques, which have evolved significantly over the past decade, leading to improved performance in complex driving scenarios. These developments are largely …
Published in Trends in Machine design · Vol. 12, Issue 1, 2025 · pp. 38–43 Read article
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Phytotherapeutic Potential of Melaleuca: An Integrative Review of Phytochemistry and Antimicrobial, Antifungal, Antioxidant, and Antiviral Mechanisms
Abstract: Melaleuca alternifolia and other species of the Melaleuca genus stand out for the broad spectrum of pharmacological properties attributed to their bioactive compounds, such as monoterpenes, sesquiterpenes, flavonoids, and polyphenols. This study aimed to critically review and analyze scientific evidence produced between 2005 and 2025 regarding the antimicrobial, antifungal, antioxidant, and antiviral activities of Melaleuca, correlating its phytochemistry with molecular mechanisms of action. For this purpose, an integrative literature review …
Published in Research & Reviews : Journal of Herbal Science · Vol. 15, Issue 2, 2026 Read article
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Revolutionizing Wireless Communication: AI & ; ML in the Era of 6G
Abstract: With rapid technological advancement, sophisticated techniques are significantly enhancing the performance of wireless networks. In parallel, the growth of artificial intelligence (AI) has empowered systems to perform intelligent decision-making, automate processes, analyze data, generate insights, and predict future outcomes. AI systems are now capable of learning and adapting to dynamic environments. Particularly, machine learning and deep learning techniques have achieved remarkable success across a wide range of applications in recent …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 12, Issue 3, 2025 · pp. 29–36 Read article
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Development of Neuromorphic Polymer Composites Using IoT Sensing and Brain-Inspired Learning Algorithms
Abstract: This research aims to develop neuromorphic polymer composites by combining conductive sensing materials, IoT-based sensing data collection and brain-inspired learning models for adaptive response. Hybrid conductive polymer composites were developed by adding carbon nanofibers and graphene Nano platelets to a thermoplastic polymer. IoT sensors (strain, temperature) were employed to collect real-time sensing data that was combined with environmental data. A material-aware neuromorphic learning algorithm was created with event-driven spike coding …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 755–784 Read article
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Integrating Advanced Technologies for the Scientific Revalidation of Ayurvedic Principles
Abstract: Background: Ayurveda, a 5,000-year-old holistic healthcare system, emphasizes the dynamic balance of body, mind, and spirit. Recent advancements in science and technology have accelerated its integration into global healthcare systems. Objective: This paper explores the contribution of modern tools and methodologies to the scientific validation and enhancement of Ayurvedic principles across education, clinical practice, and research. Methods: A comprehensive literature review was conducted using databases like PubMed, Google Scholar, and …
Published in Research and Reviews: A Journal of Medicine · Vol. 16, Issue 1, 2026 · pp. 1–6 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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A Brief Review on Interfaces of Copper Welded to Different Materials
Abstract: In engineering applications, three metals with high conductivity are primarily used such as copper (Cu), aluminium (Al), and silver (Ag). Each has its unique set of properties that affect specific engineering applications. Infact the choice of conductor depends on a mixture of cost, technical parameters, and environmental conditions. Among these, Copper is widely valued in engineering applications due to its antimicrobial property, excellent electrical (about 100% IACS) and thermal conductivity, …
Published in Trends in Mechanical Engineering & Technology · Vol. 16, Issue 1, 2026 · pp. 25–36 Read article
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Pharmacogenomics: Unlocking the Genetic Basis of Drug Response for Precision Medicine
Abstract: Pharmacogenomics, a fusion of pharmacology and genomics, explores how genetic variations influence individual responses to medications. This field is revolutionizing modern medicine by moving away from a one-size-fits-all approach toward personalized treatment strategies. By identifying specific genetic markers, pharmacogenomics aims to enhance drug efficacy, minimize adverse drug reactions, and improve overall patient outcomes. Key methodologies in this discipline include candidate gene analysis, genome-wide association studies, and haplotype analysis, all of …
Published in Research & Reviews: A Journal of Drug Design & Discovery · Vol. 12, Issue 2, 2025 · pp. 52–59 Read article
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Data-Driven Life Prediction of Fiber-Reinforced Polymer Composites Using IoT Sensing and Machine Learning Algorithms
Abstract: The accurate prediction of fatigue life in fiber-reinforced polymer (FRP) composites remains a major challenge due to their nonlinear, multi-mechanism degradation behavior under variable loading conditions. This study presents a data-driven framework, H-LiProNet, which combines real-time IoT sensing with hybrid machine learning to estimate remaining useful life (RUL) in FRP composites. The proposed system integrates embedded Fiber Bragg Grating (FBG) and acoustic emission (AE) sensors to capture strain and damage …
Published in Journal of Polymer & Composites · Vol. 13, Issue 4, 2025 · pp. 116–130 Read article