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73 articles for “layered architecture”
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A Comparative Study of the Structure-Property Relationships in CAD/CAM Milled vs. 3D-Printed High-Performance Polymers: Impact of Molecular Orientation on Abrasive Wear
Abstract: Background: The transition from subtractive to additive manufacturing in prosthetic dentistry has introduced significant variations in the macromolecular architecture of high-performance polymers. While CAD/CAM milling utilizes high-density, industrially polymerized blocks, 3D printing (Additive Manufacturing) relies on layer-by-layer deposition, which may induce anisotropic molecular orientation. This retrospective study investigates how these distinct manufacturing "thermal histories" influence the long-term abrasive wear resistance of PEEK and PEKK restorations.Materials and Methods: Data were retrospectively …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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An Empirical Analysis of Bluetooth Low Energy Reliability Challenges for Offline Messaging Applications
Abstract: In today's hyper-connected world, modern communication relies heavily on centralised internet infrastructure, making robust offline messaging solutions increasingly essential. A crucial vulnerability is revealed by network failures, natural disasters, and distant region deployments: communication breaks down when internet connectivity does. Due to its low power consumption and almost ubiquitous availability in contemporary smartphones, Bluetooth Low Energy (BLE) has become a promising candidate for offline, device-to-device communications. This study presents an …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 13, Issue 2, 2026 Read article
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Animal Species Prediction Using Deep Learning
Abstract: In the face of escalating biodiversity loss, effective monitoring of animal species is critical for conservation efforts. This study presents a deep learning approach for species detection and a multimodal feature identification technique for animals vulnerable to poaching. The suggested prediction system recognizes objects automatically by the application of deep learning techniques to detect objects and then recognize them by using computer vision techniques, and it is triggered when an …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 13, Issue 1, 2026 · pp. 14–22 Read article
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Bridging Brain-Inspired Learning and Quantum Reasoning for Future AGI Systems
Abstract: This research paper presents a novel neuromorphic–quantum hybrid computing framework envisioned to advance intelligent systems toward artificial general intelligence. The architecture integrates brain-inspired spiking networks for adaptive, energy-efficient learning with quantum processors for non-classical optimization and reasoning. A shared synaptic–quantum memory layer enables dual information representation, while neuromorphic adaptive controllers provide real-time stabilization of noisy quantum circuits. While quantum processors offer features like superposition- enabled exploration and entanglement-based correlations that …
Published in Current Trends in Signal Processing · Vol. 16, Issue 1, 2026 Read article
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Histological Effects of the Antibiotic Gentamicin on the Ovarian Tissue of Female White Laboratory Rats
Abstract: This study aimed to evaluate the histological alterations induced by Gentamicin in the ovarian tissue of white laboratory rats. A total of 12 adult female rats were used and randomly divided into two groups, with each group consisting of six animals. The experimental group received Gentamicin at a dose of 120 mg/kg body weight administered as an injection once daily, while the control group received an equivalent volume of normal …
Published in International Journal of Antibiotics · Vol. 3, Issue 1, 2026 · pp. 1–8 Read article
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A Systematic Literature Review on Security Challenges in Cloud–Edge Hybrid Systems
Abstract: Cloud–edge hybrid systems have become a key framework in today’s distributed computing landscape, combining fast, near-source data processing at the edge with the flexible scalability and resource richness of centralized cloud infrastructures. However, this in- tegration introduces a complex security landscape where tradi- tional perimeter- based cloud security measures are insufficient for resource- constrained and physically exposed edge nodes. This literature review synthesizes findings from established research publications (2020–2025), focusing …
Published in International Journal of Wireless Security and Networks · Vol. 4, Issue 1, 2026 Read article
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Integrating Digital Twins, Smart Materials, and Human Machine Collaboration for Sustainable Smart Manufacturing: Smart CNC & Industry 4.0 Applications
Abstract: The rapid evolution of Industry 4.0 and the emerging transition toward Industry 5.0 have been catalyzed by the convergence of intelligent digital technologies such as digital twins, cyber–physical systems (CPS), artificial intelligence (AI), the Internet of Things (IoT), and human-in-the-loop (HITL) frameworks. These technologies have transformed traditional manufacturing into adaptive, data-centric ecosystems capable of real-time optimization and predictive decision-making. In recent years, the fusion of computer numerical control (CNC) machines, …
Published in International Journal of Manufacturing and Production Engineering · Vol. 3, Issue 2, 2025 · pp. 1–8 Read article
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Thin Film Solar Cells: Progress in Materials, Fabrication, and Efficiency Enhancements
Abstract: Thin film solar cells (TFSCs) have drawn a lot of interest because of their potential for efficient and reasonably priced photovoltaic energy conversion. Their flexibility, low weight, and lower material consumption make them a desirable substitute for conventional solar cells made of crystalline silicon. This review explores recent advancements in TFSC technology, with a focus on materials, fabrication techniques, and efficiency improvements.Various thin-film materials, such as amorphous silicon (a-Si), perovskite, …
Published in Journal of Thin Films, Coating Science Technology & Application · Vol. 12, Issue 1, 2025 · pp. 37–42 Read article
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Development and Experimental Investigation of a Light Weight Hybrid Electric Vehicle Using Lithium-Ion Battery and EDLC Supercapacitor Integration
Abstract: Lightweight hybrid electric vehicles (HEVs) have gained significant attention as an environmentally friendly and efficient mode of transportation. However, their energy storage systems (ESS) often face challenges such as limited battery lifespan, inadequate power delivery during peak demand, and inefficient energy recovery during braking. This research focuses on the development and experimental evaluation of a hybrid energy storage system (HESS) integrating Lithium-Ion Batteries (LIB) and Electric Double-Layer Capacitors (EDLC) for …
Published in Journal of Automobile Engineering and Applications · Vol. 12, Issue 1, 2025 · pp. 26–40 Read article
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Building Scalable Microservices with Micronaut, Kotlin, and AWS DynamoDB: A Comprehensive Architecture Study
Abstract: The evolution of enterprise software has trended steadily toward microservice architectures due to their inherent scalability and resilience advantages over monolithic systems. This research explores a comprehensive implementation approach using Micronaut, an innovative JVM-based framework specifically designed for resource-efficient microservices. The study combines Micronaut with Kotlin programming language and leverages AWS DynamoDB as a scalable NoSQL persistence layer, with Apache Kafka providing event-driven communication capabilities. We explore the critical role …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 12, Issue 2, 2025 · pp. 40–57 Read article
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An Overview on VLSI based Hardware Security in IoT Node
Abstract: In the coming era, security will not be a feature we add to an IoT device; it will be a property inherent to its transistor-level design. By encoding security into the VLSI architecture, we move away from the fragile "software-only" paradigm and toward a future where the identity of the device is as immutable as the laws of physics. The rapid proliferation of Internet of Things (IoT) devices has transformed …
Published in International Journal of VLSI Circuit Design & Technology · Vol. 4, Issue 1, 2026 Read article
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An Overview on Intelligent Operating Systems (iOS)
Abstract: The rapid convergence of artificial intelligence techniques with core operating system services is ushering in a new class of platforms—Intelligent Operating Systems (Intelligent OS)—that can anticipate, adapt, and optimize on behalf of both applications and users. This paper surveys the architectural shifts required to embed learning, reasoning, and self healing capabilities into the kernel, scheduler, memory manager, and I/O subsystems. We present a prototype framework, NeuroKernel, that augments traditional OS …
Published in Journal of Operating Systems Development & Trends · Vol. 13, Issue 1, 2026 Read article
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Deep Learning Architectures for Predictive Modeling in Financial Time Series
Abstract: This study investigates the application of deep learning architectures, particularly convolutional neural networks (CNNs), to the challenging task of financial time series forecasting. Financial markets are inherently complex and influenced by a range of factors, making accurate prediction of price movements a difficult problem. In this research, historical financial data including stock prices, volumes, and other relevant indicators are used to train CNN models aimed at capturing the underlying patterns …
Published in Current Trends in Signal Processing · Vol. 15, Issue 3, 2025 · pp. 45–55 Read article
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Adaptive Task Scheduling And Resource Optimization Using Ai Middleware
Abstract: Modern distributed and heterogeneous computing systems face significant challenges in dealing with dynamically changing workloads, resource fragmentation, and changing latencies; existing traditional, or rule-based, schedulers are no longer useful in achieving the best system performance. Such limitations highlight the importance of the adaptive scheduling paradigms that are able to learn, to forecast and reaction to the real red conditions in the system. The middleware of artificial-intelligence is also an attractive …
Published in Recent Trends in Parallel Computing · Vol. 13, Issue 1, 2026 Read article
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Advancing Light Emission: A Comprehensive Review of Recent Electroluminescence Material Developments
Abstract: This paper explores the remarkable strides made in the field of electroluminescence and their profound impact on luminescence research. The emission of light because of excitation is known as luminescence. Electroluminescence, a specific form of luminescence triggered by an electric field, has emerged as a promising area of investigation. The underlying principles of luminescence and the intricate mechanisms driving electroluminescence have been examined. Furthermore, recent breakthroughs in electroluminescent materials, device …
Published in Journal of Alternate Energy Sources & Technologies · Vol. 14, Issue 2, 2024 · pp. 08–16 Read article
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Crypto Talk Voice Shield: Secure Speech Communication System Using Arduino
Abstract: In the rapidly evolving landscape of communication security, this study presents a system designed around Arduino Uno technology, specifically engineered for the secure encoding, transmission, and decoding of speech data. By integrating advanced encryption algorithms, the system ensures that speech data is transmitted in segmented bit chunks, each enveloped in multiple layers of security to prevent unauthorized access or interception. This multi-tiered encryption approach establishes a highly secure communication channel, …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 13, Issue 1, 2025 · pp. 23–30 Read article
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Malicious Network Traffic Detection Using Hybrid Feature Selection with Ensemble Neural Network
Abstract: The detection of malicious network traffic is a critical aspect of cybersecurity, aiming to protect sensitive data and maintain the integrity of network systems. This study introduces a novel approach that combines hybrid feature selection with ensemble neural networks to enhance the accuracy and efficiency of malicious network traffic detection. The dataset used in this study was obtained from Kaggle and offers a wide-ranging and varied collection of network traffic …
Published in Nano Trends – A Journal of Nano Technology & Its Applications · Vol. 27, Issue 3, 2025 Read article
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Overview AI-Driven Antenna Technologies and Privacy- Preserving Methods for Next-Generation 6G Wireless Systems
Abstract: The next generation of wireless communications, 6G, will be built on the convergence of artificial intelligence (AI) and advanced antenna systems. AI-driven antennas are poised to address the unprecedented requirements for data rate, reliability, adaptability, and ubiquity in future networks. An overview of current advancements in AI-enabled antenna systems for 6G networks is provided in this study. From traditional base station deployments to distributed, cell-free, and user-centric frameworks, it examines …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 13, Issue 1, 2026 · pp. 28–34 Read article
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Hybrid Material Systems for Flexible Electronics Electro-Mechanical Performance and Future Prospects
Abstract: Flexible electronics are transforming the landscape of modern electronic systems, enabling devices that are lightweight, stretchable, and adaptable to complex surfaces. These technologies are particularly impactful in applications such as wearable health monitors, soft robotics, energy harvesting systems, and implantable biomedical devices. At the heart of this evolution are hybrid material systems—engineered composites that combine organic polymers and inorganic nanomaterials to achieve synergistic electro-mechanical properties. These materials address the limitations …
Published in International Journal of Electro-Mechanics and Material Behaviour · Vol. 3, Issue 1, 2025 · pp. 7–12 Read article
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Activating agents control the morphology of activated carbon materials from biomass
Abstract: The stems of the plant Calotropis gigantea (Cg) were were used as a feedstock for the activated carbon material. Carbonate (K 2 CO 3 ) and oxalate (Na 2 C 2 O 4 ) were used as chemical activating agents. The morphological features of the activated carbon materials were characterized using FEG-SEM. The morphology of the activated carbon materials is found to depend on the type of activating agent used. …
Published in Journal of Catalyst & Catalysis · Vol. 12, Issue 1, 2025 · pp. 27–38 Read article