Search
258 articles for “computational frameworks”
-
Spintronic Logic Circuits for Ultrafast Processing
Abstract: Spintronic logic has emerged as one of the most promising post-CMOS paradigms capable of addressing the speed, density, and energy challenges of deeply scaled silicon technologies. By relying on the intrinsic properties of electron spin and magnetization dynamics, spintronic devices—particularly Magnetic Tunnel Junctions (MTJs), Spin-Transfer Torque (STT), and Spin–Orbit Torque (SOT) structures—enable ultrafast, non-volatile data processing with significantly reduced energy consumption. Despite remarkable device-level advancements, circuit- level realization of high-speed, …
Published in International Journal of VLSI Circuit Design & Technology · Vol. 3, Issue 2, 2025 · pp. 35–43 Read article
-
Machine Learning Assisted Timing Violation Prediction in Sub-7nm VLSI Physical Design
Abstract: The continuous scaling of semiconductor technology into the sub-7nm regime has introduced significant challenges in timing closure due to process variability, interconnect delay, power density, and manufacturing uncertainties. Conventional static timing analysis techniques often require extensive computational resources and iterative optimization cycles, resulting in increased design complexity and longer turnaround time. This research proposes a Machine Learning Assisted Timing Violation Prediction framework for sub-7nm VLSI physical design to improve early-stage …
Published in International Journal of VLSI Circuit Design & Technology · Vol. 4, Issue 1, 2026 Read article
-
Smart Contract: A new buzz word for reliable decentralized network
Abstract: Blockchain technology has emerged as a foundational distributed-ledger architecture enabling decentralized, transparent, and tamper-resistant data management across diverse digital ecosystems. This paper presents an integrated review of blockchain fundamentals, consensus mechanisms, smart contract design, and real-world applications beyond cryptocurrencies. It discusses the evolution of smart contracts as automated, self-executing programs that remove intermediaries and ensure deterministic execution, while highlighting critical security vulnerabilities such as reentrancy, arithmetic overflows, and improper access …
Published in Journal of Open Source Developments · Vol. 13, Issue 1, 2026 Read article
-
Image-Based Evaluation of Implant Tissue Interface Integrity in Polymer Orthopaedic Devices
Abstract: Polymer orthopedic implants offer radiolucency and mechanical compatibility with bone, but long-term success depends on maintaining a stable implant–tissue interface. Routine imaging is widely available for follow-up, yet interface integrity is commonly judged qualitatively, limiting early detection of fixation compromise and reducing comparability across devices and time points. This work presents an image-based methodology to quantify interface integrity by extracting interpretable interface descriptors from a standardized interface belt around the …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 170–179 Read article
-
A Smart Framework that Combines Data Mining and Optimization for Different Applications
Abstract: Blending predictive data mining with metaheuristic optimization has become essential for tackling tough, real-world problems across all kinds of fields. Most existing methods stick to fixed algorithms, each focused on a tiny slice of the puzzle, barely budging when new variables or unpredictability show up—especially with messy, human-generated data. So, here’s the idea: a Unified Metaheuristic and Predictive Data Mining (UMPDM) framework that finally connects adaptive search methods with powerful …
Published in Research and Reviews : Journal of Computational Biology · Vol. 15, Issue 2, 2026 Read article
-
Contribution Of Indian Historical Technology To Development The AI
Abstract: The Indus Valley Civilization (3300–1300 BCE) was among the first in the world to develop advanced metallurgy. They created bronze tools, copper vessels, and intricate metal ornaments. A testament to ancient Indian metallurgy, this rust-resistant iron pillar, built during the Gupta Empire, still stands without significant corrosion, demonstrating an advanced understanding of material science. The study examines key texts and technologies, including Panini’s Ashtadhyayi (a formal system of grammar resembling …
Published in OmniScience: A Multi-disciplinary Journal · Vol. 15, Issue 3, 2025 Read article
-
Overview of Ionic Polarization: A Model Based Novel Approach
Abstract: This study presents a comprehensive analysis of ionic polarization through a novel model-based approach that integrates theoretical, computational, and experimental methodologies. Ionic polarization, which significantly influences the dielectric properties of materials, is examined through the lens of the Clausius-Mossotti equation and the Debye relaxation model, providing a theoretical framework for understanding the relationship between ionic displacement and dielectric behavior. To explore ionic displacement and polarization at the atomic level, advanced …
Published in International Journal of Cheminformatics · Vol. 2, Issue 2, 2024 · pp. 18–25 Read article
-
Fracture Analysis of Laminated composite plates using Extended Finite Element Method: A Review
Abstract: Laminated composite plates are used in aerospace, automotive, and marine industries. They feature great durability against fatigue, a high strength-to-weight ratio, and mechanical attributes that may be altered. However, they are prone to fracture and delamination under complex loading, requiring accurate fracture analysis for structural integrity. Traditional finite element methods (FEM) need extensive mesh refinement for modelling crack propagation which increases the computational costs. The Extended Finite Element Method (XFEM) …
Published in International Journal of Fracture Mechanics and Damage Science · Vol. 4, Issue 1, 2026 · pp. 16–25 Read article
-
Autonomous 6G Physical Layer Architectures for Space-Air-Ground Integrated Networks
Abstract: The emergence of sixth generation (6G) wireless systems calls for a significant shift away from conventional deterministic communication models. As communication infrastructures evolve into Space- Air-Ground Integrated Networks (SAGIN), traditional physical layer (PHY) techniques struggle to operate effectively under the severe Doppler effects and long propagation delays associated with space environments. This paper examines the role of artificial intelligence embedded directly within the 6G transceiver architecture to enable ultra-reliable and …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 13, Issue 2, 2026 Read article
-
Hybrid Quantum-Classical Reinforcement Learning Enabled Thermal-Aware Electronic Design Automation Framework for Energy-Efficient Next-Generation VLSI Systems Applications
Abstract: Modern Very Large-Scale Integration (VLSI) systems are becoming more complicated, which has increased need for sophisticated Electronic Design Automation (EDA) frameworks that can concurrently optimise thermal behaviour, power consumption, and performance. This study proposes a Hybrid Quantum-Classical Reinforcement Learning (HQCRL) Enabled Thermal-Aware EDA Framework for next-generation energy- efficient VLSI systems. The proposed framework integrates quantum-inspired optimization techniques with classical reinforcement learning algorithms to address the challenges of placement, routing, and …
Published in Journal of Electronic Design Technology · Vol. 17, Issue 2, 2026 Read article
-
The link between electronics and computer science
Abstract: The merging of computer science with electronics has led to major improvements in modern technology, leading to new ideas in areas like embedded systems, the Internet of Things (IoT), artificial intelligence (AI), and robotics. There is a deep and widespread connection between computer science (CS) and electronics. They have a symbiotic relationship in which one subject depends on and improves the other. CS gives systems their intellectual frameworks, algorithms, and …
Published in Journal of VLSI Design Tools and Technology · Vol. 15, Issue 3, 2025 · pp. 11–20 Read article
-
Leveraging Large Language Models for Personalized Document Summarization and Question Answering: An Architecture for Stoner-Friendly Chatbots
Abstract: This study presents a detailed framework for developing personalized chatbots that utilize large language models (LLMs) to process and extract information from extensive documents while effectively responding to user inquiries. The proposed system is designed to mitigate information overload by employing advanced natural language processing techniques, leveraging technologies such as OpenAI, LangChain, and Streamlit. By integrating these tools, the framework enhances knowledge retrieval, simplifies document comprehension, and improves overall productivity. …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 3, 2025 · pp. 88–93 Read article
-
Machine Learning Optimization for VARTM Carbon Polymer Laminates
Abstract: Vacuum-assisted resin transfer moulding (VARTM) is a key low-cost, out-of-autoclave process for manufacturing large-scale carbon-fibre reinforced polymer (CFRP) laminates crucial to aerospace wings, wind-turbine blades, marine hulls, and automotive structures. Unpredictable resin flow often leads to voids, dry spots, and race-tracking defects, resulting in 27.9% scrap rates and lengthy, costly trial-and-error design cycles. Although surrogate models provide rapid impregnation predictions for simple flat-plate geometries, vision-based monitoring is limited to idealized …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 229–245 Read article
-
Integrated Perspectives on Fluid Mechanics and Energy Transport in Complex Flow Systems
Abstract: Fluid mechanics plays a central role in understanding the transport of mass, momentum, and energy in complex flow systems encountered in both natural and engineered environments. This review presents an integrated perspective on fluid behavior by combining fundamental principles with modern approaches to energy transport analysis. The study emphasizes the significance of conservation laws and their application to diverse flow regimes, including laminar, turbulent, compressible, and multiphase flows. Energy transport …
Published in Recent Trends in Fluid Mechanics · Vol. 13, Issue 1, 2026 · pp. 22–31 Read article
-
Exploring the Future of Operating Systems: Architectural Innovations and Kernel Development Trends
Abstract: Modern applications and the rapid evolution of hardware technologies are challenging operating system (OS) design. This paper speculates the future of OS based on revolutionary architecture advancements and emerging possibilities in kernel construction. The growth of multi-core processors, spread-bound processing, and edge architectures have challenged traditional OS paradigms. The paper provides an analysis of the progress in microkernel and monolithic kernel structures, discussing the bandwidth capacity as well as security …
Published in Journal of Operating Systems Development & Trends · Vol. 11, Issue 3, 2024 · pp. 38–47 Read article
-
A Review of Blocking Side-Channel Threats in Parallel Cloud Systems
Abstract: Side-channel attacks (SCAs) pose a critical security threat to parallel computing systems, particularly in shared cloud environments where multi-tenancy and resource contention create exploitable vulnerabilities. This study presents a comprehensive review of SCAs in parallel architectures, analyzing attack vectors such as cache-based exploits (e.g., Prime + Probe, Flush + Reload), timing attacks, power analysis, and network-based covert channels. We examine real-world cases including Spectre and Meltdown vulnerabilities that exposed fundamental …
Published in Recent Trends in Parallel Computing · Vol. 12, Issue 2, 2025 · pp. 15–25 Read article
-
A Review on Artificial Intelligence Techniques for Analyzing Deforestation and Illegal Logging Using Satellite Imagery
Abstract: Deforestation and illegal logging remain critical environmental threats, driving biodiversity loss, climate change, and socio-economic disruption. Conventional monitoring techniques frequently do not yield real-time, large-scale insights. Recent developments in Artificial Intelligence (AI), especially in deep learning and computer vision, have revolutionized the ability to analyze high-resolution satellite images for detecting deforestation and monitoring illegal logging. This review synthesizes recent developments in AI-driven approaches, highlighting convolutional neural networks (CNNs), anomaly detection …
Published in International Journal of Satellite Remote Sensing · Vol. 4, Issue 1, 2026 · pp. 1–9 Read article
-
Topology and Geometry in Data Science: Persistent Homology and Beyond
Abstract: In recent years, the interplay between topology, geometry, and data science has gained substantial momentum, offering powerful frameworks to analyze and interpret complex datasets. Traditional statistical and machine learning methods often rely on linear or metric- based assumptions, which may fail to capture the intrinsic structure of high-dimensional or nonlinear data. In contrast, topological and geometric methods provide shape-oriented, scale- invariant tools that focus on the continuity, connectivity, and global …
Published in Recent Trends in Mathematics · Vol. 1, Issue 2, 2024 · pp. 21–27 Read article
-
Study of Proximity Points and Fixed Points
Abstract: This paper explores the concepts of proximity points and fixed points, which are fundamental in mathematical analysis and nonlinear functional analysis. Fixed-point theorems play a crucial role in optimization, game theory, differential equations, and dynamic systems. Proximity points, an extension of fixed points, provide a more generalized approach, allowing near-coincidence rather than exact identity. The study discusses classical fixed-point theorems, such as Banach’s contraction principle, Brouwer’s fixed-point theorem, and Schauder’s …
Published in Recent Trends in Mathematics · Vol. 1, Issue 2, 2024 · pp. 28–31 Read article
-
Optimized Sentiment Analysis Through TextBlob and Hybrid RNN Models
Abstract: In today’s world, analyzing people’s feelings from what they write online has become very important. This is because there is a large amount of content created by users. To make this analysis accurate and fast, we present a method. This method uses a mix of two approaches: one that looks up words in a dictionary and another that uses computer learning. TextBlob is an affordable tool for getting an initial …
Published in International Journal of Computer Science Languages · Vol. 4, Issue 1, 2026 · pp. 29–28 Read article