Volume 13 | Issue 4 |

 Abstract

Abstract-Crankshaft supporting bearings in internal combustion (IC) engines are critical for maintaining structural integrity, reducing friction, and ensuring smooth operation, especially at high engine speeds. However, premature wear of these bearings can lead to increased noise, vibration, and potential engine failure, posing significant challenges in automotive engine reliability. This research investigates the causes of whining noise and vibration issues observed in 160cc motorcycle engines which are attributed to defects in the crankshaft bearings. The primary objective is to analyze and identify bearing defects through vibration analysis, comparing faulty bearings with healthy counterparts. The study explores the development and progression of bearing defects over time, focusing on common failure modes such as damage to rolling elements, inner races, outer races, and cages. The research aims to establish methodologies for early detection and diagnosis of bearing faults. By pinpointing the root causes of bearing degradation and providing diagnostic solutions, this work contributes to improving thedurability and performance of motorcycle engines. The findings are expected to enhance engine reliability, reduce warranty costs, and offer a better user experience by addressing complaints related to bearing-related noise from engine and vibration issues.

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 Keywords

Rolling Element Bearing, Bearing Defect, Vibration Measurement

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Abstract The Historical Place Badami along with Aiholle, Pattadakal and some other sites in and around the valley of the River Malaprabha in Bagalkot District of Karnataka, contain some of the earliest temples built in stone of southern India, beginning with the constructions of the Early Chalukyan dynasty, which ruled from Badami (ancient Vatapi) during the 6th to 8th centuries CE. However, the history of construction of monuments in stone go back much farther in time, as evidenced by the large number of megalithic monuments that are distributed at several sites in the Malaprabha Valley. In continuation of our earlier work which argues that the Chalukyas and their successors were continuing the tradition of commemoration exemplified by the megaliths into later monumental architecture - ranging from temples to miniature shrines to other forms of commemoration, this paper examines the immediate landscape around the Bhutanath Temple at Badami (Vatapi) and interpret it as a memorial landscape with various forms of commemorative structures.

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 Keywords

Keywords: Huligemmana Kolla, , Bhutanath Temple, Megalithic, Ranganath Gudda, Agastya Teertha, Mahishasuramardini Durga, Hemakuta Hill and Kappearabhata

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 Abstract

Day by day the cases of heart diseases are increasing at a rapid rate and it's very Important and concerning to predict any such diseases beforehand. Heart disease cases are increasing rapidly every day, so it's really important to predict and detect them early. Catching the disease in time can help save lives and improve treatment. This research project focuses on predicting whether a person is likely to have heart disease, based on their medical information and history. To do this, we built a heart disease detection system that uses machine learning. We used several machine learning algorithms like Logistic Regression, K-Nearest Neighbors (KNN), Support Vector Machine (SVM), Decision Tree, and Random Forest to analyze the data and predict if a patient has heart disease or not. The system looks at patterns and trends in the collected medical data to make smart predictions. After testing the performance of these models, we found that they can help improve medical care, make early diagnoses, and even lower healthcare costs. This project helped us gain valuable knowledge about how machine learning can be used to detect heart disease. The system was developed using a pynb (Jupyter Notebook) file format.

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 Keywords

Machine learning, Heart Disease, Diagnosis, Algorithm _

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This study examines the effectiveness of Google Gemini, an AI-powered tool, for academic use among Arts and Science college students in Coimbatore City. It explores students' awareness, usage patterns, and the perceived benefits and challenges of using the tool for tasks like research, assignments, and exam preparation. Data was collected through a structured questionnaire. The findings reveal that while many students find Google Gemini helpful in enhancing learning, concerns remain regarding accuracy and ethical use. The study suggests promoting digital literacy to improve the effective use of AI in Education.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Google Gemini, Artificial Intelligence, Academic Purpose, Student Perception, Digital Learning.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This paper discusses Arvind Adiga's debut novel, The White Tiger, for which he received the Booker Prize in 2008. This groundbreaking work shows the harsh realities of 21st-century globalised Indian society, which is ridden with class conflicts. The Marxian class struggle between the bourgeoisie and the proletariat drives the whole plot of the novel. The narrative is characterised by the master/slave and have/have-not dichotomies. It is written in epistolary form. The narrator, Balram Halwai, exposes the dark underbelly of society where the means of production are in the hands of those who wield power in the system. However, Balram shows an exceptional vigour for revolution to bring about a new order in the world where the tables have turned, and the proletariat topples the bourgeoisie regime. Following the same Marxist strain, we will explore the concepts of 'Hegemony' and 'Organic Intellectuals' introduced by the prominent Italian Marxist thinker Antonio Gramsci, ways to overcome it through revolution, and the Foucauldian ideas of 'Power and Resistance', which are embodied in the character of Balram in the novel.

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 Keywords

Bourgeoisie, Class-struggle, Hegemony, Intellectuals, Proletariat, Power, Resistance.

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This study examines the effectiveness of AI software in enhancing training and development at Thermax Global Limited. It evaluates AI's impact on employee engagement, skill development, and well-being. The research aims to assess how AI influences performance monitoring and managerial support. A structured questionnaire was used to collect data from 150 employees. Data analysis was conducted using percentage analysis, weighted average, correlation, and chi-square tests. The findings offer recommendations to improve AI integration for better employee satisfaction and organizational efficiency.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

AI Software, Training and Development, Employee Engagement, skill development, reduce stress.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The research examines how variations in soil CBR affect the required thickness of different pavement layers to ensure durability and cost-effectiveness. Additionally, the role of GSB, WMM, CTSB, and CTB in load distribution, stability, and longevity is analyzed using standard design methodologies such as IRC guidelines. The findings highlight that an optimal combination of high-strength base and sub-base layers can reduce pavement thickness, enhance service life, and lower maintenance costs. The study provides practical insights for engineers and policymakers in designing sustainable and economically viable flexible pavements

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 Keywords

GSB-Granular Subbase, WMM-Wet Mix Macadam, CTSB-Cement Treated Subbase, CTB-Cement Treated base

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This research examines the emerging technology of food delivery drones and their potential to transform the restaurant industry's last-mile delivery systems. With increasing consumer demand for faster, more efficient food delivery services, drone technology offers a promising solution to overcome traditional transportation constraints. This study investigates the operational capabilities, regulatory frameworks, consumer acceptance, and economic viability of drone-based food delivery systems across urban environments. Data collected from pilot programs between January 2022 and December 2024 reveals that drone deliveries can reduce delivery times by up to 70% and decrease delivery costs by 30% compared to traditional methods, while maintaining food quality and temperature standards. However, challenges including air traffic management, battery limitations, weather constraints, and privacy concerns present significant hurdles to widespread implementation. The findings suggest that food delivery drones represent a viable solution for urban food logistics that could substantially disrupt current delivery models while offering environmental and economic benefits.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Food delivery drones, last-mile logistics, urban aerial mobility, contactless delivery, sustainable transportation

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Creative Commons Attribution 4.0 and The Open Definition

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This research examines the implementation and effectiveness of artificial intelligence (AI) techniques for navigation and obstacle avoidance in unmanned aerial vehicles (UAVs). As drone applications proliferate across commercial, industrial, and consumer sectors, the demand for robust autonomous navigation capabilities has become increasingly critical. This study analyzes various AI approaches including deep reinforcement learning, computer vision algorithms, sensor fusion techniques, and path planning methodologies that enable drones to navigate complex environments without human intervention. Data collected from experimental trials conducted between March 2023 and January 2025 demonstrates that AI-powered navigation systems achieve 94% obstacle detection accuracy in dynamic environments and reduce navigation errors by up to 78% compared to traditional algorithms. The research identifies key challenges including computational constraints, environmental variability, and sensor limitations, while highlighting promising developments in edge computing and neuromorphic processors that may overcome these obstacles. The findings suggest that AI-based navigation represents a transformative technology for drone operations that will significantly enhance safety, efficiency, and application versatility across numerous sectors.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Drone navigation, obstacle avoidance, artificial intelligence, deep learning, sensor fusion, autonomous systems

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Badalte samajik mulyon aur samkalin mahila rachnakaro ke sahitya me nari vimarsh

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Badalte samajik mulyon aur samkalin mahila rachnakaro ke sahitya me nari vimarsh

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Creative Commons Attribution 4.0 and The Open Definition