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5 articles for “random logic”
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VLSI – Power, Expansion and Versatility
Abstract: The evolution of Very Large-Scale Integration (VLSI) technology has significantly transformed the landscape of modern electronics, driving innovations across diverse industries. This article explores the key attributes of VLSI, focusing on its power, expansion, and versatility. VLSI's power lies in its ability to integrate thousands to millions of transistors on a single chip, enabling the development of high-performance, energy-efficient devices. The expansion of VLSI technology is exemplified by its application …
Published in International Journal of VLSI Circuit Design & Technology · Vol. 3, Issue 1, 2025 · pp. 1–8 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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Development of Game Theory Strategy for Estimating Mobility Variety in Approaching Wireless Networks
Abstract: Game theory designed with a set of structured tools with an evaluation tool for the tedious interaction among logical players. This theory approaches for analyzing of communication networks, which functions with autonomous structured networks and the designed network devices can take rational decisions according to network congestion. The proposed structure consists of mixture frame for channel allocation for random probability for accessing channel. The main objective of this work is …
Published in Recent Trends in Electronics Communication Systems Read article
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Optimizing Sampling Techniques Using Fuzzy Set Theory: A Comprehensive Approach
Abstract: Sampling is a critical process in statistics, used to estimate population parameters without needing to examine the entire population. Traditional sampling methods, such as simple random sampling, stratified sampling, and cluster sampling, face limitations when applied to complex or heterogeneous populations with imprecise boundaries. These methods often fail to accurately represent populations with overlapping characteristics or missing data, resulting in sampling bias and reduced accuracy. To address these challenges, this …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 12, Issue 1, 2025 · pp. 29–43 Read article
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Implementing Machine Learning in Data Classification
Abstract: Data classification forms an essential aspect of artificial intelligence (AI) and soft computing, helping a great deal in the transformation of raw data into knowledge that forms the basis of numerous applications, such as fraud detection, medical diagnostics, and natural language processing. This study discusses the challenges and the state of the art in data classification, as far as scalability, noise handling, and feature selection optimization are concerned. It gives …
Published in International Journal of Data Structure Studies · Vol. 3, Issue 2, 2025 · pp. 15–22 Read article