Daily Archives: May 29, 2026

Authors: Souda Pranavi, Vardelli Disharani, Peddamma Stalin, P.V.R.Ravindra Reddy

Abstract: The demand for lightweight, high-strength, and corrosion-resistant structural materials has significantly increased in aerospace, automotive, marine, and civil engineering industries. Carbon–epoxy composite materials have emerged as one of the most promising alternatives to conventional metallic materials because of their superior mechanical and thermal properties . Among various structural configurations, composite I-section beams have attracted considerable attention due to their excellent bending stiffness, high strength-to-weight ratio, fatigue resistance, and structural efficiency. This review paper presents a detailed overview of carbon–epoxy composite I-section beams with emphasis on material properties, fabrication techniques, finite element analysis, experimental investigations, failure mechanisms, optimization strategies, and structural applications. The paper critically examines the influence of fiber orientation, stacking sequence, laminate thickness, curing conditions, and manufacturing defects on the structural performance of composite beams. Advanced fabrication methods such as prepreg layup, vacuum bagging, and autoclave curing are discussed in detail. Recent developments in finite element modeling for stress, strain, deflection, fatigue, and buckling analyses are also reviewed. Furthermore, various non-destructive evaluation techniques used for identifying internal defects and monitoring structural integrity are examined. The review identifies major research gaps in composite beam development and highlights future opportunities for high-performance lightweight structural systems.

DOI: https://doi.org/10.5281/zenodo.20445172

Published by: vikaspatanker

Authors: Gargi Chander

Abstract: This paper examines the relationship between consumer price inflation (CPI) and per capita net state domestic product (PCNSDP) across Indian states using a balanced panel dataset spanning 2014-15 to 2024-25. The study draws on official data from the RBI’s Handbook of Statistics. After constructing a balanced panel of 24 states and Union Territories over 11 years (264 observations), applying a suite of panel econometric estimators: pooled OLS, one-way fixed effects (entity), two-way fixed effects, random effects GLS, between estimator, and first-differences. Model selection follows the Hausman specification test. Unit-root diagnostics using augmented Dickey–Fuller tests indicate that both series carry non-stationary behaviour in levels, motivating the first-differences specification. The two-way fixed effects model—which accounts for both time-invariant state heterogeneity and common macroeconomic shocks—yields a statistically significant positive coefficient on CPI inflation (β = 0.0049, p = 0.046), while the first-difference estimator produces a significant negative coefficient (β = −0.0084, p < 0.001). The Hausman test (p = 0.91) favours random effects over one-way fixed effects. Taken together, these results suggest that the inflation–income relationship in India is nuanced: short-run income growth is dampened by inflationary shocks, but within-period cross-sectional variation, once purged of state and year effects, shows a mild positive co-movement consistent with demand-pull dynamics. The paper contributes a rigorous methodological treatment of India's state-level inflation–income nexus and discusses policy implications for monetary and fiscal coordination.

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Published by: vikaspatanker

Authors: Vishnu Koudgave, Pratik Londhe, Anishka Ahuja, Prasanna Kharbas, Prof. Jyoti Raghatwan

Abstract: With the growing demand for touchless and intelligent computing systems, hand gesture recognition has emerged as an innovative approach for natural human-computer interaction. This paper presents an AI-based Virtual Mouse system that enables real-time cursor control using hand gestures captured through a webcam. The proposed system utilizes MediaPipe for detecting 21 hand landmarks and OpenCV for real-time video processing, while PyAutoGUI is used to perform mouse operations such as cursor movement, clicking, scrolling, and dragging. The system provides smooth, accurate, and low-latency interaction without requiring additional hardware, making it a cost-effective and user-friendly solution. The proposed model enhances touchless human-computer interaction and has potential applications in smart environments, virtual reality systems, gaming, and assistive technologies.

DOI: https://doi.org/10.5281/zenodo.20444460

Published by: vikaspatanker

Authors: Dr. Dinesh D. Patil, Shruti Mangesh Bunde, Nidhi Vinodsingh Pardeshi, Manasvi Rajesh Bauskar

Abstract: The increasing demand for rental accommodation in urban areas has made traditional room searching methods inefficient and time-consuming. Conventional approaches rely heavily on brokers and manual processes, often resulting in higher costs, lack of transparency, and delayed communication. To address these challenges, this paper presents Roomzee, a cross-platform room rental and booking system designed to simplify and digitize the process of finding and booking rental spaces. The proposed system integrates both web and mobile platforms, allowing users to search, view, and book rooms in real time. The frontend of the application is developed using React, providing a responsive and user-friendly interface [6]. The backend services are implemented using Supabase, which offers secure authentication, real-time database management, and efficient data handling capabilities. The use of cloud-based architecture ensures scalability, reliability, and continuous availability of the system [4]. The development process follows Agile methodology to support iterative improvements and adaptability throughout the software development lifecycle [14]. The system reduces dependency on intermediaries and improves overall efficiency in rental management. The results demonstrate enhanced user experience, faster booking operations, and improved data accessibility compared to traditional methods. Furthermore, the system is scalable and can be extended with advanced features such as online payment integration and intelligent recommendation systems.

DOI: https://doi.org/10.5281/zenodo.20444184

Published by: vikaspatanker

Authors: Ms. Anshika Yadav

Abstract: The increasing growth of urbanization and industrialization has intensified the burden on conventional sewage treatment plants (STPs), leading to higher energy consumption, operational inefficiencies, and environmental pollution. Artificial Intelligence (AI) has emerged as a transformative technology capable of improving wastewater treatment processes through predictive analytics, automation, optimization, and real-time monitoring. This research paper explores the concept of AI-powered smart sewage treatment plants and examines how machine learning, deep learning, IoT sensors, and digital twin technologies can enhance sewage treatment efficiency and sustainability. The study reviews existing literature, identifies research gaps, and proposes an AI-integrated smart sewage treatment framework for predictive maintenance, water quality forecasting, and energy optimization. The paper concludes that AI-enabled STPs can significantly reduce operational costs, improve effluent quality, and support sustainable urban water management.

DOI: https://doi.org/10.5281/zenodo.20443923

Published by: vikaspatanker

Authors: K. Amrutha Varshini, Gaddam Jancy, B. Manogna, B. Trisha, Mushti. Ankitha, Nunsavath Shanthi, Someshwar Komati, Dr. Someshwar Komati

Abstract: Nanoparticulate drug delivery systems have gained considerable attention for improving the therapeutic efficacy of poorly soluble anticancer drugs through controlled and targeted delivery. The present study aimed to formulate and characterize Docetaxel-loaded nanoparticles using Poly(lactic-co-glycolic acid) (PLGA) as a biodegradable carrier polymer. Nanoparticles were prepared by nanoprecipitation using optimized drug-to-polymer ratio and stabilizer concentration. The formulations were evaluated for particle size, zeta potential, entrapment efficiency, drug loading, and in-vitro drug release. FT-IR spectroscopy confirmed compatibility between drug and polymer, while zeta potential analysis indicated good colloidal stability. In-vitro release studies demonstrated sustained release of Docetaxel over an extended period. Kinetic analysis using zero-order, first-order, Higuchi, and Korsmeyer–Peppas models suggested a controlled drug release pattern predominantly governed by diffusion. The findings indicate that PLGA-based Docetaxel nanoparticles are a promising approach for targeted anticancer drug delivery with potential to enhance therapeutic efficacy and reduce systemic toxicity. Further in-vivo studies are recommended to confirm clinical applicability.

DOI: https://doi.org/10.5281/zenodo.20443596

Published by: vikaspatanker

Authors: Akula Manasa, Pasula Chandu, Bada Abhinay, Mrs. Y. Ashwini

Abstract: This study analyzes the air quality index (AQI) of Bangalore city over seven years on time period (2018-2024) covered 2,556 days, by using TABLEAU as the primary visualization software, through tableau, the huge and complex datasets will be turn like charts, graphs and more. It focuses on 8 key components of AQI, PM 2.5, PM10, NO2, SO2, CO, NH3, Pb and O3. It’s analyzing that the air quality was changes according to the seasons, where most pollutant air was recorded in the winter months (December-February) and the cleanest air was recorded at Monsoon season (June-August). The year of 2020 the AIR QUALITY recorded lowest average over (AQI-64.47), due to the reason of covid 19 pandemic Lockdown occurred. Approximately 66.8% of days were falls under “Moderate” category, while only 17.4% fall are considered as “Good”. These results share a clear vision to make a good plan for urban developers, city planners to analyse the conditions and improve AIR QUALITY on Bangalore.

Published by: vikaspatanker

Authors: K. Vigneshwar, G.Bharath Simha Reddy, G.Shashidhar, A.Uday Kiran

Abstract: Public safety in public areas has become a significant concern for governments and businesses globally. Video surveillance systems are being increasingly integrated to ensure public safety, with deep learning techniques enhancing their ability to detect potential threats. Traditional video surveillance often relies on passive monitoring, but with advancements in AI, surveillance systems can now actively detect risks such as weapons (guns and knives) in real- time. This paper presents a deep learning-based system for weapon detection using MobileNet- V2, a CNN model known for its computational efficiency. MobileNet-V2 has shown an improvement of approximately 35% in processing speed compared to its predecessor, MobileNet-V1, while maintaining similar accuracy levels. This increase in speed is crucial for real-time weapon detection, where quick identification and response are vital to preventing threats. The study compares two approaches to weapon detection using CNNs, evaluating MobileNet-V1 and MobileNet-V2. The results indicate that MobileNet-V2 outperforms MobileNet-V1 not only in terms of speed but also in its ability to maintain high accuracy, marking a significant advancement in the field of weapon detection through deep learning. These improvements are vital in practical applications, such as public spaces, where large amounts of video data must be processed rapidly. The proposed system demonstrates a clear enhancement over prior methods in detecting guns and knives, offering a reliable, fast solution for real-time surveillance. This research highlights the effectiveness of MobileNet-V2 in improving public safety through advanced AI technology, providing a scalable solution for detecting threats in urban environments.

 

 

Published by: vikaspatanker

Authors: Lagusani Yashwanth Goud, K. Susmitha

Abstract: Generic medications are becoming an essential part of contemporary healthcare due to the growing demand for reasonably priced medications. Despite efforts by the European Medicines Agency (EMA) to harmonize regulations, different European countries have different requirements for marketing authorization of generics. The regulatory framework for the approval of generic drugs in a few European nations, such as Germany, France, the United Kingdom, Spain, and Italy, is compared in this thesis. It draws attention to variations in bioequivalency standards, dossier submission requirements, approval schedules, and review processes. The results highlight the need for additional harmonization to improve patient access to reasonably priced medications and expedite generic drug market access.

DOI: http://doi.org/10.5281/zenodo.20442010

Published by: vikaspatanker

Authors: Shivani, Prof. Seema Kohli

Abstract: Ayurveda is an ancient Indian system of medicine that explains health as a dynamic balance between the body, mind, and the natural environment. According to Ayurvedic philosophy, human life is deeply interconnected with environmental elements such as air, water, land, vegetation, and climate. In the present era, environmental science highlights growing concerns including pollution, climate change, deforestation, and biodiversity loss, all of which pose serious threats to both ecological stability and human health. These challenges emphasize the urgent need for sustainable and preventive approaches to healthcare and environmental protection. Ayurvedic concepts such as Panchamahabhuta (five fundamental elements), Ritucharya (seasonal regimen), and Desha (influence of geographical and environmental factors) explain how changes in the environment directly affect human health and disease patterns. Seasonal variations, climatic conditions, and ecological imbalance play a crucial role in disturbing bodily harmony, leading to the development of various disorders. These principles closely align with environmental science, which also focuses on maintaining ecological balance for healthy living. This paper aims to correlate Ayurvedic principles with environmental science to develop an integrated framework for sustainable healthcare and ecosystem conservation. The study is based on a review of classicalAyurvedic texts, current environmental challenges, and modern scientific research related to medicinal plants, pollution, and ecosystem health. Integrating traditional Ayurvedic knowledge with modern environmental management offers a holistic approach to disease prevention, health promotion, biodiversity conservation, and sustainable development.

DOI: https://doi.org/10.5281/zenodo.20441818

Published by: vikaspatanker