Daily Archives: August 2, 2025

Authors: Rahul Solanki, Murlidhar Chourasia, Rahul Kumar Satbhaiya

Abstract: The seismic performance of reinforced concrete (RC) structures is significantly influenced by the geometry and detailing of their columns, which act as the primary load-bearing and energy-dissipating elements during ground motion. Among the available column cross-sections, rectangular shapes have traditionally been used due to ease of construction and integration with architectural plans. However, in high-seismic zones, circular columns are gaining attention for their superior ductility, confinement efficiency, and uniform stress distribution.This study presents a comparative analysis of the seismic behavior of RC frames with rectangular and circular columns, focusing on their performance under lateral loading conditions. An extensive literature review was conducted, highlighting the influence of column shape on key seismic performance parameters such as base shear capacity, lateral drift, energy dissipation, plastic hinge formation, and failure mechanisms. Analytical studies, experimental investigations, and code-based assessments consistently indicate that circular columns outperform rectangular ones in terms of ductility and post-yield behavior. Their symmetrical geometry allows better confinement of core concrete, resulting in enhanced resilience during strong ground shaking.Additionally, the review underscores the limitations of conventional force-based design methods in accurately predicting the inelastic behavior of structures, especially those with irregular geometries. Nonlinear static (pushover) analysis, displacement-based approaches, and accurate modeling of infill-wall interaction emerge as essential tools for realistic seismic performance evaluation.The findings of this study support the strategic replacement or incorporation of circular columns in RC frames to improve seismic resistance, particularly in retrofitting and performance-based design scenarios. While practical challenges such as increased formwork complexity exist, the benefits in structural safety and energy absorption justify their use. This paper serves as a reference for engineers and researchers aiming to optimize RC structures for improved seismic resilience through column geometry selection.

DOI: https://doi.org/10.5281/zenodo.16728432

 

Published by: vikaspatanker

Authors: Sandeep Gajanan Sutar, Dr. Praveen B M, Dr. Amolkumar Jadhav

Abstract: In the era of pervasive cloud computing, ensuring the privacy and integrity of sensitive data has emerged as a critical challenge. Traditional data protection methods often fall short in addressing sophisticated security threats and compliance demands. This study explores the synergistic integration of blockchain technology and homomorphic encryption (HE) as a transformative approach to privacy management in cloud environments. Blockchain's decentralized and immutable architecture ensures transparent, tamper-proof data transactions, while homomorphic encryption enables computation on encrypted data without revealing its contents—thus preserving confidentiality throughout the data lifecycle. The research discusses layered architectural frameworks, real-world implementations across healthcare, IoT, and supply chains, and presents empirical findings that highlight improvements in computational efficiency, security, and regulatory compliance. Despite challenges in scalability and computational overhead, the combined use of blockchain and HE presents a promising pathway for developing resilient, privacy-preserving cloud infrastructures. This integration not only fortifies data governance but also lays the groundwork for next-generation secure cloud services.

DOI: https://doi.org/10.5281/zenodo.16728278

 

Published by: vikaspatanker

Authors: Rahul Solanki, Murlidhar Chourasia, Rahul Kumar Satbhaiya

Abstract: Designing earthquake-resistant structures necessitates ensuring their safety throughout both the construction phase and their operational lifespan, regardless of the intensity or frequency of seismic events. Ground motion effects are particularly complex due to their dynamic and multifaceted impact on structural behaviour. Among the various analytical techniques available, pushover analysis is considered one of the most dependable for evaluating a structure's response to intense seismic forces. This approach is based on the assumption that during seismic events, buildings predominantly respond in their fundamental or lower vibration modes. Therefore, a multi-degree-of-freedom (MDOF) system can be effectively transformed into an equivalent single-degree-of-freedom (ESDOF) model. This ESDOF model is derived using nonlinear static analysis and subsequently subjected to nonlinear time history or response spectrum analysis utilizing constant-ductility or damped response spectra. The seismic demand parameters obtained from the ESDOF model are then mapped back to the MDOF system through modal transformation techniques. In this research, the seismic behaviour of a moment-resisting RC frame structure is analyzed using the pushover method. The study focuses on the effect of changing column shapes and sizes, specifically replacing rectangular columns with circular ones, to assess variations in seismic performance. The static pushover approach incorporates both constant gravity loads and incrementally applied lateral loads at each story level. Capacity curves, illustrating the relationship between base shear and total story drift, are generated using ETABS 2015 to extract critical seismic response parameters. Throughout the simulation, the overall plan dimensions of the building are maintained constant, while only the column dimensions are varied. Three sets of rectangular column sizes are examined for their nonlinear seismic response and subsequently compared with equivalent circular columns. All structural models are designed following the provisions of IS 456:2000 for concrete design and IS 1893:2002 for seismic loading conditions..

DOI: http://doi.org/

Published by: vikaspatanker

Authors: Kiran Kumar, V. Narmada, Sagarika Kulkarni

Abstract: Cardiovascular diseases cause morbidity and mortality. Early detection is critical, as it can detect and the use of AI plays a significant role in and impacts cardiovascular diseases. Since cardiovascular diseases (CVDs) continue to be the world's leading cause of death, improvements in early diagnosis, treatment, and management techniques are vital. The integration of artificial intelligence (AI), machine learning, and deep learning into cardiovascular medicine offers promising avenues to improve patient outcomes. This review explores recent progress in AI applications for CVDs, including automated electrocardiogram (ECG) analysis, medical imaging, wearable sensor technologies, and telemedicine. AI-driven systems have demonstrated potential in enhancing diagnostic accuracy, enabling remote monitoring, predicting disease risk, and supporting clinical decision-making. Despite significant advancements, challenges such as data bias, algorithmic fairness, and the need for rigorous clinical validation remain. Continued research and the responsible deployment of AI technologies can help address the global burden of CVDs through more precise, efficient, and personalized care

DOI: https://doi.org/10.5281/zenodo.16719088

 

Published by: vikaspatanker