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7 articles for “topological space”
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A Note on Fixed-Point Theory
Abstract: In this paper, we narrate in brief the origin and step-by-step development of the fixed-point theory which finds its primary applications in functional analysis. It is a sub-branch of the functional analytic theory in which geometric conditions on the mappings and/or underlying spaces play a crucial role. It is also a major branch of nonlinear functional analysis with close ties to Banach space geometry. In this paper, our main focus …
Published in International Journal of Structural Mechanics and Finite Elements · Vol. 5, Issue 2, 2019 · pp. 12–19 Read article
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Topological Analysis of Artificial Neural Network
Abstract: ABSTRACT This paper analyzes the Artificial Neural Network (ANN) over the metric. The dimension, curvature and mappings are the three characteristics of analysis. The impact of ANN in finite and infinite space is also considered. The Euclidean metric is the limit of generalization. The structure of neuron and its mapping are presented over the finite dimension. The discrete and continuous structure of neurons is studied mathematically and its formulation is …
Published in International Journal of Embedded Systems and Emerging Technologies · Vol. 5, Issue 1, 2019 · pp. 17–21 Read article
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Minimization Theorem and Fixed-Point Theorem in Probabilistic Metric Space
Abstract: This paper is devoted to the study of the basic theory and applications of probabilistic metric spaces (PM-space). In this paper, the topological structure and properties for PM-space are considered. The conditions of metrization and the form of metric functions for PM-spaces, Menger PM-spaces and probabilistic normed linear spaces (PN-space) are given, and the characterizations of various probabilistically bounded sets are presented. As applications, we utilize these results obtained in …
Published in International Journal of Structural Mechanics and Finite Elements · Vol. 5, Issue 2, 2019 · pp. 36–41 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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A Study on AI in 7G Mobile Communication
Abstract: The imminent transition from 5G to the seventhgeneration (7G) mobile ecosystem promises to redefine connectivity through unprecedented data rates, pervasive ultralow latency, and holistic integration of terrestrial, aerial, and spaceborne networks. Central to this evolution is Artificial Intelligence (AI), which is poised to become the nervous system that orchestrates, optimizes, and secures the hyperdynamic 7G fabric. This paper surveys the emerging AIdriven paradigms that will underpin 7G, focusing on three …
Published in International Journal of Broadband Cellular Communication · Vol. 11, Issue 1, 2026 · pp. 29–39 Read article
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Spatiotemporal Dynamics of 100 Coupled Lorenz Oscillators: A Comprehensive Analysis of Chaotic Pattern Formation
Abstract: Chaotic Lorenz systems that interact with one another, resulting in the generation of complex space-time patterns that evolve over time. This comprehensive analysis presents a detailed investigation of spatiotemporal chaos in a network of 100 coupled Lorenz oscillators, revealing the complex interplay between individual chaotic dynamics and collective behavior in nonlinear dynamical systems. Through numerical simulation and extensive analysis, we examine how coupling transforms individual butterfly attractors into rich spatiotemporal …
Published in International Journal of Embedded Systems and Emerging Technologies · Vol. 12, Issue 1, 2026 · pp. 15–21 Read article
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Intelligent Trajectories: Harnessing Artificial Intelligence for Next Generation Missile and Propellant Design
Abstract: The rapid evolution of artificial intelligence (AI) has unlocked transformative pathways for high-performance aerospace engineering, yet its integration into missile and propellant design remains nascent. This study investigates a hybrid AI-driven framework that unites physics-based modeling, data-centric learning, and multi-objective optimization to accelerate the conception, validation, and refinement of missile airframes and solid-propellant formulations. First, a physics-informed neural network (PINN) is trained on a curated database of historic missile geometries, …
Published in International Journal of Energetic Materials · Vol. 12, Issue 1, 2026 · pp. 20–26 Read article