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463 articles for “Framework”
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An Extensive Analysis of QC's Difficulties & Restrictions
Abstract: QC constitutes a fundamental shift in computational paradigms by exploiting quantum mechanical phenomena namely superposition, entanglement, and interference to achieve computational advantages over classical systems for specific problem domains. Despite significant theoretical progress, the realization of large-scale, fault-tolerant quantum computers remains impeded by a range of intrinsic and technological constraints. This paper offers a thorough & critical analysis of the principal challenges associated with QC, with a focus on de- …
Published in International Journal of Analog Integrated Circuits · Vol. 12, Issue 2, 2026 Read article
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Integrated Telecommunication Systems: Networking,Security, and Emerging Technologies inNext-Generation Communication Networks
Abstract: Integrated telecommunication systems play a crucial role in enabling reliable, high-speed, and scalablecommunication across modern digital infrastructures. This paper presents a comprehensive review ofintegrated telecommunication systems with a focus on networking architectures, security mechanisms,and emerging technologies in next-generation communication networks. It examines the fundamentalcomponents of communication systems, including transmission media, communication channels, andstandardized networking protocols, highlighting their contribution to efficient data exchange andsystem interoperability. The study explores both wired and …
Published in International Journal of Telecommunications & Emerging Technologies · Vol. 12, Issue 1, 2026 · pp. 36–45 Read article
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Cloud-Based IoT Monitoring System for Pump Canal Operations: A Case Study of Narayanpur Pump Canal, Mirzapur
Abstract: Abstract The technical paper presents a comprehensive analysis of the Internet of Things (IoT)-based cloud monitoring system deployed at the Narayanpur Pump Canal (NPC), Chunar, Mirzapur, Uttar Pradesh. The system, operationalized in September 2024, provides real-time remote monitoring of 15 critical parameters across 14 pump sets through cloud-based analytics, automated alerts, and intelligent dashboards. The paper evaluates the technical architecture, demonstrated operational benefits – including a documented case of preventing …
Published in International Journal of Water Resources Engineering · Vol. 12, Issue 1, 2026 · pp. 49–68 Read article
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AI-Based Deepfake Voice Detection Model for Hindi Language
Abstract: Most current research on deepfake voice detection focuses heavily on English or Mandarin, creating a significant security gap for Hindi speakers. To address this, we developed a detection framework specifically tailored for the Hindi language using a lightweight approach: Mel-Frequency Cepstral Coefficient (MFCC) feature extraction paired with an XGBoost classifier. We trained the system on a large dataset comprising over 99,000 real voice samples and roughly 3,800 synthetic samples, each …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 12, Issue 2, 2026 Read article
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Getting Rid of Carbon: A New Direction for the Chemical Industry
Abstract: The chemical industry is a major contributor to global greenhouse gas emissions due to its reliance on fossil-based feedstocks, energy-intensive processing routes, and long-lived capital infrastructure. Achieving international climate targets therefore requires deep decarbonisation across the entire chemical value chain, a transition complicated by technological limitations, economic risks, and systemic operational barriers. This article critically evaluates key emission-reduction pathways, including electrification of process heat, substitution of fossil resources with bio-based …
Published in International Journal of Chemical Engineering and Processing · Vol. 12, Issue 1, 2026 · pp. 52–61 Read article
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A Comprehensive Review of Convolutional Neural Network Architectures and Evolution
Abstract: Convolutional Neural Networks (CNNs) have become a foundational deep learning framework in computer vision because they can automatically extract layered, increasingly complex features directly from raw image data. CNNs use convolutional, pooling, and activation layers to extract spatial patterns from basic edges to intricate object components, drawing inspiration from the human visual cortex. An overview of CNNs’ basic architecture is given in this study, along with an explanation of important …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 12, Issue 1, 2026 · pp. 32–40 Read article
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Enhancing Facial Expression Analysis Using CNNs: Insights from ML and Deep Learning Comparisons
Abstract: Emotion recognition from facial manifestations increases the interaction between humans and computers by enabling the interaction between humans and computers to effectively explain human feelings. This study presents a comparative analysis of three approaches to the emotional recognition of faces: a custom Convolutional Neural Network (CNN) model, Traditional Machine Learning (ML) methods, and other deep learning architectures such as VGG, ResNet, and Hybrid CNN–RNN models. The proposed CNN-based system, developed …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 12, Issue 1, 2026 · pp. 23–31 Read article
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Intelligent Data Analytics on Cloud Infrastructure:Real-Time Insights and Managed Service Models
Abstract: This paper examines the integration of advanced data analytics and machine learning within modern cloud infrastructure, highlighting how organizations can transform large volumes of unstructured data into actionable business insights that drive competitive advantage. Cloud platforms leverage scalability and elasticity to efficiently process and analyze massive datasets in real time, allowing enterprises to identify hidden patterns, detect operational anomalies early, and generate accurate forecasts of future outcomes. A key factor …
Published in International Journal of Distributed Computing and Technology · Vol. 12, Issue 1, 2026 · pp. 36–46 Read article
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A Study on Securing the Local Area Network with the Immutable Trust of Blockchain
Abstract: The contemporary Local Area Network (LAN) is the digital circulatory system of the modern enterprise, a vital yet perilously vulnerable ecosystem. Traditional security paradigms, built upon centralized authority models – firewalls, intrusion detection systems, and privileged administrators – increasingly resemble medieval castles in an age of artillery. They present a brittle single point of failure: compromise the center, and the entire kingdom falls. This paper proposes a radical architectural shift, …
Published in International Journal of Distributed Computing and Technology · Vol. 12, Issue 1, 2026 · pp. 24–35 Read article
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AI-Driven Predictive Maintenance in Smart Homes: Enhancing Efficiency and Reliability
Abstract: The convergence of Artificial Intelligence (AI) and the Internet of Things (IoT) has transformed smart homes into intelligent, self-regulating environments. Despite these advancements, ensuring the long-term reliability and efficiency of interconnected devices remains a complex challenge due to device heterogeneity, dynamic usage patterns, and continuous data streams. This study investigates AI-driven predictive maintenance (PdM) as a proactive strategy for detecting early signs of equipment degradation in residential settings. The proposed …
Published in International Journal of Distributed Computing and Technology · Vol. 12, Issue 1, 2026 · pp. 1–6 Read article
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Recent Advances in Analytical and Applied Chemistry: A Comprehensive Review
Abstract: Analytical and Applied Chemistry form the backbone of modern scientific progress, connecting fundamental molecular insights with real-world industrial and societal applications. Over the past decade, these fields have undergone significant transformation, driven by the need for sustainability, precision, and efficiency. This review highlights key advancements in green analytical chemistry (GAC), high-resolution mass spectrometry (HRMS), and the incorporation of nanotechnology into chemical sensing, while also examining their broader implications in applied …
Published in International Journal of Analytical and Applied Chemistry · Vol. 12, Issue 1, 2026 · pp. 36–41 Read article
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An Overview on Metal Processing using Machine Learning
Abstract: Metalworking, which is an important part of modern industry, includes a wide range of steps, such as shaping and casting the metal, machining it, and riveting it. The industry has always relied on trial and error and other empirical methods, but machine learning (ML) is now causing a big change. It is expected that this change will lead to higher production, better product quality, and better use of resources. The …
Published in International Journal of Manufacturing and Materials Processing · Vol. 12, Issue 1, 2026 · pp. 43–53 Read article
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AN INTEGRATED COMPUTER-AIDED PROCESS PLANNING SYSTEM FOR THE MANUFACTURING OF A LEAF SPRING
Abstract: Computer-Aided Process Planning (CAPP) is a key enabling technology for integrating product design and manufacturing in a Computer Integrated Manufacturing (CIM) environment. This paper presents the development and implementation of an integrated, feature-based CAPP system for the manufacturing of an automotive leaf spring assembly. The proposed system bridges the gap between CAD and shop-floor activities by directly mapping design features to manufacturing operations. High-level manufacturing features such as base profiles, …
Published in International Journal of Computer Aided Manufacturing · Vol. 12, Issue 1, 2026 · pp. 10–23 Read article
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An Integrated Computer-Aided Approach for Fixture Design and Assembly
Abstract: Fixtures play a crucial role in ensuring dimensional accuracy, productivity, and repeatability in modern manufacturing systems. With the increasing adoption of flexible and computer-integrated manufacturing, there is a growing need for systematic and automated fixture design methodologies. This work presents a computer-aided fixture design and assembly approach that integrates CAD-based modeling, modular fixturing concepts, and virtual assembly techniques. The proposed methodology covers the complete fixture development cycle, including workpiece analysis, …
Published in International Journal of Computer Aided Manufacturing · Vol. 12, Issue 1, 2026 · pp. 24–39 Read article
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Entropy and Efficiency: Thermodynamic Insights into Sustainable Energy Technologies
Abstract: The transition toward sustainable energy systems requires a deeper understanding of the thermodynamic principles that govern energy conversion and utilization. Entropy and efficiency are central to this discussion, as they define the limits of performance and highlight the irreversibility inherent in real processes. This paper examines the role of entropy generation in renewable energy technologies, including solar photovoltaics, wind turbines, bioenergy, and advanced energy storage systems. By applying exergy analysis, …
Published in International Journal of Renewable Energy and its Commercialization · Vol. 12, Issue 1, 2026 · pp. 17–23 Read article
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Generative Lightweighting of Actuator-Integrated Robotic Structures Under Decentralized Additive Manufacturing Constraints
Abstract: This study presents the implementation and structural validation of a constraint-driven generative design methodology for the development of lightweight actuator-integrated robotic components fabricated using decentralized additive manufacturing. Building upon a previously formalized constraint-driven framework, the method was applied to the synthesis of a modular robotic link representative of actuator-integrated structural elements commonly used in legged robotic systems. The baseline component was defined to preserve critical functional interfaces, including actuator mounting …
Published in International Journal of Mechanics and Design · Vol. 12, Issue 1, 2026 · pp. 44–60 Read article
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A Study on Machine-Learning-Driven Insight into theThermal Behavior of Polymers and Composite Materials
Abstract: The thermal performance of polymeric and composite systems underpins their suitability for aerospace, electronics, and energy‑storage applications, yet reliable prediction of temperature‑dependent properties remains a formidable challenge. In this work we present a data‑driven framework that harnesses modern machine‑learning (ML) techniques to forecast key thermal metrics – glass‑transition temperature (Tg), melting point (Tm), thermal conductivity (k), and decomposition onset (Td) – from a chemically informed descriptor space. A curated database …
Published in International Journal of Polymer Science and Engineering · Vol. 12, Issue 1, 2026 · pp. 1–11 Read article
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The Biomechanical Impact of Slipper Sole Compliance on Lumbar Spine Load: A Quantitative Analysis of Indoor Footwear Ergonomics
Abstract: Abstract The global shift toward remote work has significantly increased the duration of indoor footwear usage, yet the ergonomic standards for slippers remain critically under-researched compared to athletic or industrial footwear. While "high-compliance" or soft slippers are traditionally marketed for immediate comfort, excessive mechanical softness may lead to foot instability, altered gait kinetics, and subsequent compensatory stress on the lumbar spine. This study aims to quantify the correlation between varying …
Published in International Journal of Mechanics and Design · Vol. 12, Issue 1, 2026 · pp. 30–35 Read article
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Energy Transition for Sustainable Development in Saudi Arabia: Renewable Energy Growth and Emission Reduction
Abstract: The Kingdom of Saudi Arabia (KSA) is undergoing a major shift toward sustainability under Vision 2030, targeting 58.7 GW of renewable energy (RE) by 2030 and major green hydrogen projects, such as NEOM’s 4 GW plant, to cut oil use by 500,000 barrels daily and achieve net-zero emissions by 2060. This review provides a comprehensive analysis of KSA’s energy transition, assessing the energy landscape, RE development, environmental impacts, and climate …
Published in International Journal of Renewable Energy and its Commercialization · Vol. 12, Issue 1, 2026 · pp. 31–70 Read article
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Phase-Change Material Integrated Semiconductor Circuits for In-Memory Analog Computing Applications
Abstract: The continuous demand for high-speed, energy-efficient computing has intensified the exploration of in- memory analog computing (IMAC) architectures, which aim to minimize the latency and power overhead associated with conventional von Neumann architectures. This research investigates the integration of phase- change materials (PCMs) with semiconductor circuits to realize programmable, non-volatile in-memory analog computing platforms. PCMs exhibit reversible resistance switching between amorphous and crystalline states, enabling precise analog weight storage directly …
Published in International Journal of Analog Integrated Circuits · Vol. 12, Issue 1, 2026 · pp. 32–42 Read article