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International Journal of Creative and Open Research in Engineering and Management

A Peer-Reviewed, Open-Access International Journal Supporting Multidisciplinary Research, Digital Publishing Standards, DOI Registration, and Academic Indexing.
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ISSN: 3108-1754 (Online)
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ISO Certification: 9001:2015
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License: CC BY 4.0
Peer Review: Double Blind
Volume 02, Issue 8

Published on: August 2026

AI–BLOCKCHAIN-INTEGRATED GENERALIZED FRACTIONAL SINE TRANSFORM FRAMEWORK FOR SUPPLY-CHAIN TRANSPARENCY AND RESILIENCE

Kanade UV Shinde SM Harle SM

INDEPENDENT RESEARCHER
DOI:https://doi.org/10.55041/ijcope.v2i8.198

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Abstract

The generalized two-dimensional fractional sine transform (2D-FrST) is a powerful analytic instrument for the spectral analysis of bivariate signals that arise in multi-scale supply-chain dynamics, hybrid-vehicle systems and resilient logistics networks. In this paper we state and rigorously prove Modulation Theorem-2, which expresses the 2D-FrST of a function modulated by a product of cosines (or by mixed sine–cosine factors) as a linear combination of four fractional sine or cosine transforms evaluated at frequency points shifted by the modulation frequencies. We further establish the Shifting Property, showing that a spatial translation of the original function maps, under the 2D-FrST, into a linear combination of fractional sine and cosine transforms of a phase-modulated version of the function. Both results are derived by means of elementary product-to-sum and angle-addition identities together with a careful accounting of the quadratic-phase factors that appear in the fractional kernel. The theoretical developments are illustrated by concrete applications to artificial-intelligence pattern mining and blockchain-based immutable logging, thereby enhancing transparency, traceability and resilience of digital supply-chain ecosystems. All results are placed in the broader context of the FKF-transform framework and related spectral methods recently introduced for multi-echelon lead-time analysis and secure logistics networks.

Keywords— generalized two-dimensional fractional sine transform; modulation theorem; shifting property; fractional cosine transform; AI–blockchain integration; supply-chain resilience; FKF transform; spectral analysis; transparency; traceability.

How to Cite this Paper

UV, K., SM, S. & SM, H. (2026). AI–Blockchain-Integrated Generalized Fractional Sine Transform Framework for Supply-Chain Transparency and Resilience. International Journal of Creative and Open Research in Engineering and Management, <i>02</i>(8), 1-9. https://doi.org/10.55041/ijcope.v2i8.198

UV, Kanade, et al.. "AI–Blockchain-Integrated Generalized Fractional Sine Transform Framework for Supply-Chain Transparency and Resilience." International Journal of Creative and Open Research in Engineering and Management, vol. 02, no. 8, 2026, pp. 1-9. doi:https://doi.org/10.55041/ijcope.v2i8.198.

UV, Kanade,Shinde SM, and Harle SM. "AI–Blockchain-Integrated Generalized Fractional Sine Transform Framework for Supply-Chain Transparency and Resilience." International Journal of Creative and Open Research in Engineering and Management 02, no. 8 (2026): 1-9. https://doi.org/https://doi.org/10.55041/ijcope.v2i8.198.

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References


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  • Akarshan Gulhane,“ Spectral Differential Properties of the Distributional FKF Transform with Applications to Resilient Supply-Chain Systems,” International Journal of Creative and Open Research in Engineering and Management ISSN: 3108-1754 (Online) Volume 02 Issue 08 Augustl-2026, DOI:  https://doi.org/10.55041/ijcope.v2i8.139

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  • Akarshan Gulhane,“ The FKF Transform: Exponential Modulation Properties And Applications To Secure Digital Supply-Chain Networks,” International journal of Engineering sciences and Advanced Technology, Published:11-12-2025, Issue: Vol. 25 No. 12 (2025), Page Nos: 617 – 623, DOI: Https://doi.org/10.64771/ijesat.2025.v25.i12.3818

  • Akarshan Gulhane, “Spectral Differential Properties of the Distributional FKF Transform with Applications to Resilient Supply-Chain Systems,” International Journal of Creative and Open Research in Engineering and Management ISSN: 3108-1754 (Online) Volume 02 Issue 08 Augustl-2026, DOI: https://doi.org/10.55041/ijcope.v2i8.139.

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  • •Published on: Aug 24 2026
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