Browsing by Author "Ramana, V."

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Machine Learning Models with Optimization for Clothing Recommendation from Personal Wardrobe
(Institute of Electrical and Electronics Engineers Inc., 2020) Jain, M.; Singh, S.; Chandrasekaran, K.; Rathnamma, M.V.; Ramana, V.
In the present-day scenario, several clothing recommender systems have been developed for the online e-commerce industry. However, when it comes to recommending clothes that a person already possesses, i.e, from their personal wardrobe, there are very few systems that have been proposed to perform the task. In this paper, we tackle the latter issue, and perform experimental analysis of the various Machine Learning techniques that can be used for carrying out the task. Since the recommendations must be made from a user's personal wardrobe, the recommender system doesn't follow a traditional approach. This is explained in detail in the following sections. Further, the paper contains a complete description of the results obtained from the experiments conducted, and the best approach is specified, with appropriate justification for the same. Â© 2020 IEEE.
Modified Current Control for Tracking Global Peak Under Fast Changing Partial Shading Conditions
(Institute of Electrical and Electronics Engineers Inc., 2022) P, P.; Vignesh Kumar, V.; Balasubramanian, B.; Ramana, V.
The power - voltage (P-V) characteristics of photovoltaic (PV) systems exhibit multiple power peaks under partially shaded conditions. Several global maximum power point tracking (GMPPT) algorithms in the literature recognize the irradiance change, only after the convergence of operating point to global peak, or use additional hardware to call GMPPT subroutine at definite time intervals to detect any insolation change, and thus track the global peak. However, during fast changing partial shading conditions, these methods are less effective, as they do not detect any irradiance change during the tracking phase of any shading pattern. This paper proposes a novel modified current control approach that uses current as a parameter to detect the insolation change during the tracking phase and track the global peak under fast changing partial shading conditions without any additional hardware. The proposed technique improves the tracking efficiency by as much as 39%, thus proving to be effective under fast-changing partial shading conditions. The superior tracking performance of the proposed algorithm over the existing techniques in terms of its tracking efficiency, dynamic tracking capability, tracking speed, and convergence to the global peak is demonstrated with extensive simulations using MATLAB/Simulink and experimental results. © 1986-2012 IEEE.
Stride-based threat modeling for blockchain-based healthcare supply chain management system
(Bentham Science Publishers, 2025) Harish, S.V.; Chandrasekaran, K.; Rathnamma; Divakarla, U.; Ramana, V.
The increasing use of blockchain technology in supply chain management has made it imperative to understand the possible security risks associated with its implementation. This research aims to identify important security issues related to supply chain management's use of blockchain technology by doing a thorough analysis of the body of existing literature and looking at actual cases of blockchain deployments. These dangers include the possibility of data privacy breaches, smart contract weaknesses, and 51% attack vulnerability. The report also offers suggestions for reducing these risks, including using multi-factor authentication, regularly carrying out security audits, and enforcing strict access rules. The study's conclusions broaden our knowledge of the security risks associated with blockchain-based supply chain management (BC-SCM) and offer useful guidance to companies thinking about implementing this technology. © 2025 Bentham Science Publishers. All rights reserved.