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1971 articles for “advancements” (ranking capped at the first 2,000 matches — narrow the search to see the rest)
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An Extensive Review of IoT and Wireless Power Transfer Based Movable Spotlight
Abstract: This paper provides an in-depth overview of IoT and Wireless Power Transfer-Based Movable Spotlights. The rapid expansion of the Internet of Things (IoT) has created new opportunities for smart gadgets, allowing them to seamlessly integrate into our daily lives. In addition to this trend, wireless power transfer (WPT) technologies have emerged as a transformative alternative for powering devices without traditional connected connections. This paper explores the integration of Internet of …
Published in Recent Trends in Sensor Research & Technology · Vol. 12, Issue 2, 2025 · pp. 16–20 Read article
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An Overview of Natural Fibers and Fillers Reinforced Polymer Composite Materials
Abstract: Polymer composite materials reinforced with natural fibers and fillers are drawing wide spread attention due to their sustainability, eco-friendliness, and a replacement of conventional synthetic composites. Such materials combine strength and stiffness of natural fibers like jute, hemp, flax, and sisal with flexibility and durability of polymer matrices, including thermoplastics, and thermosets. The paper reviews some developments, properties, and applications of natural fiber-reinforced polymer composites (NFRPCs), focusing on their merits, …
Published in Journal of Polymer & Composites · Vol. 13, Issue 4, 2025 · pp. 78–92 Read article
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The Integration of Artificial Intelligence in Sikh Shrines: Enhancing Tradition and Accessibility
Abstract: The purpose of the present study is to expound on the significance of the integration of artificial intelligence in Sikh shrines could enhance tradition and accessibility. Artificial Intelligence (AI) has significantly influenced various facets of human life, including religious and spiritual traditions. As one of the youngest religions, Sikhism paves the way for wider research in Sikh structures, including Sikh Shrines. Sikh Shrines also known as Gurudwaras are an essential …
Published in OmniScience: A Multi-disciplinary Journal · Vol. 15, Issue 3, 2025 Read article
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Horizons in Neuralgia Care: Addressing Unmet Needs and Future Prospects
Abstract: Neuralgia refers to intense, sharp, and often chronic pain resulting from damage or irritation to nerves. It is typically characterized by sudden, shooting pain along the course of a nerve, significantly impairing daily functioning and impacting both physical and emotional well-being. Given its intensity and chronic nature, neuralgia presents a complex challenge in clinical management, emphasizing the importance of timely diagnosis and effective intervention to improve patient outcomes. This comprehensive …
Published in International Journal of Brain Sciences · Vol. 2, Issue 2, 2025 · pp. 1–8 Read article
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Density Functional Theory (DFT): Understanding and Quantifying Molecular Structure of 2-D Materials
Abstract: Density Functional Theory (DFT) has emerged as a cornerstone in computational chemistry and materials science, offering a powerful framework for predicting electronic structures and properties of atoms, molecules, and solids. By focusing on electron density rather than wave functions, DFT simplifies the many-body problem through approximations like the local density approximation (LDA) and generalized-gradient approximations (GGAs). The Hohenberg-Kohn theorems establish the theoretical foundation, proving that ground-state properties are uniquely determined …
Published in Journal of Microelectronics and Solid State Devices · Vol. 12, Issue 2, 2025 · pp. 33–40 Read article
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A Neuromorphic-Inspired, Low-Power VLSI Architecture for Edge AI in IoT Sensor Nodes
Abstract: As the proliferation of Internet of Things (IoT) devices continues to rise, there is an increasing demand for real-time, energy-efficient artificial intelligence (AI) processing directly at the network edge. Traditional edge AI accelerators, often based on deep learning models like convolutional neural networks (CNNs), struggle to meet the ultra-low-power requirements of battery-constrained IoT sensor nodes. In response to this challenge, this study introduces a neuromorphic-inspired, low-power very- large-scale integration (VLSI) …
Published in Journal of Microelectronics and Solid State Devices · Vol. 12, Issue 2, 2025 · pp. 41–47 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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Channel Estimated Modulation Techniques for Wireless Communication Systems: Review
Abstract: The high spectrum and energy capabilities of Multiple Input Multiple Output systems make them a propitious technology for 5th-generation wireless communication systems. The acquisition of channel information is crucial for utilizing the potential gains of the multi-modal systems. Numerous studies have established channel estimation techniques and are still in research which faced several challenges with downlink-uplink overheads, complexities, and pilot contamination. This work discusses the insights obtained from the reviewed …
Published in Trends in Opto-electro & Optical Communication · Vol. 15, Issue 2, 2025 · pp. 1–10 Read article
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Investigative Study of Adaptive Fault Tolerance in Optical Networks
Abstract: Optical networks have become the backbone of modern telecommunications infrastructure, enabling high-speed data transmission across global networks. However, these networks face significant reliability challenges due to component failures, signal degradation, and environmental factors. This investigative study examines adaptive fault tolerance mechanisms in optical networks, focusing on emerging technologies and methodologies that enhance network resilience. The research analyzes various fault detection techniques, including machine learning-based approaches, self-healing protocols, and dynamic reconfiguration …
Published in Trends in Opto-electro & Optical Communication · Vol. 15, Issue 2, 2025 · pp. 24–30 Read article
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Enhancing Terahertz Patch Antennas: The Role and Impact of Graphene
Abstract: Terahertz (THz) communication systems are gaining increasing attention because of their ability for high-speed wireless data transmission, making them suitable for the 6th-generation wireless applications. Patch antennas, commonly used in these systems, play a crucial role in signal transmission and reception. There are various types of conductive materials available for patch antennas, but the unique characteristics of graphene make it a suitable choice. This study explores the significance and contribution …
Published in Trends in Opto-electro & Optical Communication · Vol. 15, Issue 2, 2025 · pp. 41–51 Read article
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Digital Psychiatry: A Narrative Review on AI Positive Role in Mental Health
Abstract: Artificial Intelligence has rapidly evolved into a formidable instrument within the domain of mental healthcare, fundamentally altering the way we understand awareness, diagnosis, intervention and emotional regulation. This narrative review explores AI’s potential to foster positive mental health through tools such as natural language processing, machine learning, deep learning and computer vision. These technologies promise earlier detection of mental disorders, customized treatment plans and responsive emotional support. Yet, alongside these …
Published in Current Trends in Signal Processing · Vol. 15, Issue 3, 2025 · pp. 1–13 Read article
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Energy Efficiency and Awareness in Edge Computing: A Critical Review of Challenges, Strategies, and Future Directions"
Abstract: Edge computing enhances distributed systems by processing data near its source, yet its rapid growth, driven by IoT, 5G, and smart applications, escalates energy consumption across billions of devices. This study critically analyzes energy-saving techniques across hardware, software, and network layers, highlighting the role of AI tools and user education in promoting energy awareness. It explores trade offs between energy efficiency and system performance, identifies scalability challenges in large-scale deployments, …
Published in Journal of Power Electronics and Power Systems · Vol. 15, Issue 3, 2025 · pp. 32–36 Read article
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Joint Estimation of CSI and IQ Imbalance, and Compensation of IQ Imbalance in Spatialy Multiplexed MIMO-OFDM Receivers
Abstract: This study presents a novel method for estimating Channel State Information (CSI) and IQ imbalance and compensating IQ imbalance in a spatially multiplexed MIMO OFDM receiver. Our approach integrates estimation of IQ imbalance with CSI estimation using an OFDM training frame, thus eliminating the need for additional pilot symbols for IQ imbalance estimation. This technique streamlines the process and avoids extra overhead. We conducted simulations on a 2×2 spatially multiplexed …
Published in Journal of Microwave Engineering and Technologies · Vol. 12, Issue 2, 2025 · pp. 11–17 Read article
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Squeeze Casting of Hybrid Aluminum Matrix Composites: A Critical Review of Process Optimization, Reinforcement Strategies, and Performance Outcomes
Abstract: Increasing demand for lightweight, performance-oriented components in automotive, aerospace, and defense industries has driven advancements in squeeze casting, a hybrid technique merging forging and die-casting advantages to produce near-net-shape aluminum matrix composites (AMCs) with superior mechanical-tribological properties. This review critically examines the interplay of process parameters (e.g., squeeze pressure: 70–150 MPa, melt temperature: 650–800°C), reinforcement characteristics (volume fraction ≤10%, particle size: 10–71µm), and interfacial engineering strategies (flux-assisted bonding, ultrasonic dispersion) …
Published in Journal of Materials & Metallurgical Engineering · Vol. 15, Issue 2, 2025 · pp. 52–60 Read article
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IoT Based Electricity Theft Detection System
Abstract: The proliferation of smart grids and advanced metering infrastructure has paved the way for innovative solutions to tackle the longstanding issue of electricity theft. This study presents an IoT-based electricity theft detection system that leverages real-time data analytics and machine learning algorithms to identify potential theft cases. The proposed system utilizes smart meters to collect electricity consumption data, which is then transmitted to a central server for analysis. The system …
Published in Journal of Semiconductor Devices and Circuits · Vol. 12, Issue 2, 2025 · pp. 18–22 Read article
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Role of Reinforcement Learning in Improvement of Semiconductor Doping
Abstract: The semiconductor industry faces increasing challenges in achieving optimal doping profiles as device dimensions shrink and performance requirements intensify. Traditional doping optimization methods, while effective, often struggle with the complex, multi-dimensional parameter spaces characteristic of modern semiconductor manufacturing. This study explores the transformative role of reinforcement learning (RL) in improving semiconductor doping processes, examining how RL algorithms can autonomously optimize doping parameters to enhance device performance, reduce manufacturing costs, and …
Published in Journal of Semiconductor Devices and Circuits · Vol. 12, Issue 2, 2025 · pp. 23–34 Read article
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Structural Behavior of Flexible and Semi-Rigid Beam-Column Joint Connections by FEM
Abstract: This study investigates the structural behavior of flexible and semi-rigid beam-column joint connections in cold-formed steel (CFS) structures, focusing on the use of Finite Element Modeling (FEM) to simulate their performance under various loading conditions. Traditional analysis methods often oversimplify beam-column connections, treating them as either perfectly rigid or fully flexible, which does not accurately capture real-world joint behavior. In reality, many beam-column joints exhibit semi-rigid characteristics, where the stiffness …
Published in Journal of Structural Engineering and Management · Vol. 12, Issue 3, 2025 Read article
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Phytochemical Screening and Biological Activity of Pomegranate Extracts
Abstract: Pomegranates are renowned for their abundance of bioactive compounds that exhibit potent antioxidant, anti-inflammatory, and antimicrobial properties, making them a subject of growing interest in natural medicine. This study aimed to compare the biological activities of ethanolic extracts derived from different parts of the pomegranate plant—specifically, the bark, peel, and leaves. A comprehensive investigation was conducted to evaluate their phytochemical composition and assess their antimicrobial, antioxidant, and anticancer properties. The …
Published in Research & Reviews: A Journal of Pharmacognosy · Vol. 12, Issue 2, 2025 · pp. 64–79 Read article
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Innovations and Comparative Analyses in Foam Concrete: A Review of Emerging Techniques and Materials
Abstract: Foam concrete, recognized for its lightweight and eco-friendly properties, is gaining prominence as a sustainable construction material. However, challenges such as low mechanical strength, performance variability, and limited environmental resistance have prompted significant innovations in recent years. This study synthesizes findings from three key studies focused on enhancing foam concrete’s performance through nanomaterials, natural fibers, and alternative lightweight aggregates. The incorporation of nano-silica and nano-calcium carbonate into coal gangue foam …
Published in Trends in Transport Engineering and Applications · Vol. 12, Issue 3, 2025 Read article
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A Comprehensive Review of CNN-Based Framework for Multi-Sign Detection of Diabetic Retinopathy in Fundus Images Using Public Datasets
Abstract: Diabetic retinopathy (DR) is one of the main causes of vision impairment. Blindness prevention and effective treatment depend on early detection. A thorough deep learning-based framework for the automatic segmentation and simultaneous detection of exudates, hemorrhages, and microaneurysms – three important DR indicators – from retinal fundus images is presented in this work. These three pathological signs’ corresponding annotated image patches, along with background (no-sign) areas, were used to train …
Published in Research and Reviews : Journal of Computational Biology · Vol. 14, Issue 3, 2025 · pp. 14–23 Read article