Volume 11 | Issue 3 | March-2023

 Abstract

In this paper an attempt has been made to optimize ply stacking sequence of single piece E-Glass/Epoxy, HM Carbon /Epoxy and Boron/Epoxy composite drive shafts using Particle swarm Optimization (PSOA). PSOA programme is developed using MATLAB V 7 to optimize the ply stacking sequence with an objective of weight minimization. The weight savings of the E-Glass/Epoxy, HM Carbon /Epoxy and Boron /Epoxy shaft are 51%, 87%and 85 % of the steel shaft respectively. The optimum results of PSOA obtained are compared with results of genetic algorithm (GA) and found that PSOA yields better results than GA.

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 Keywords

Design Optimization of Automotive Composite Drive Shaft using Particle Swarm Optimization Algorithm

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In this study, we examine the canonical position of the "Trinity" of Karnatic music--Tyagaraja, Muthuswamy Dikshitar, and Syama Sastri--through the historical, cultural, and musicological prisms, and we critically assess their legacy. By analyzing their individual contributions, stylistic divergences, and the sociopolitical processes that elevated them to collective prominence, the study challenges the homogenizing narrative of the "Trinity" framework. While their compositions--Tyagaraja's devotional kritis, Dikshitar's Sanskrit scholasticism, and Syama Sastri's rhythmic innovations--revolutionized Karnatic music, the research reveals how their canonization reflects 20th-century nationalist agendas and caste-gender biases. Critiques highlight the exclusion of contemporaries like Swati Tirunal and Oottukkadu Venkata Kavi, as well as marginalized voices such as non-Brahmin and women musicians. Despite these critiques, the Trinity's enduring influence on pedagogy, global dissemination, and cultural identity underscores their artistic merit. The paper concludes that while their genius is undeniable, their legacy must be recontextualized within inclusive historiography to acknowledge Karnatic music's diverse evolution.

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 Keywords

Karnatic Music,Trinity of Karnatic Music,Tyagaraja,Bhakti Movement,Syama Sastri

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This study aimed to assess the level of academic stress among school going children and associated demographic factors viz., gender, type of management and medium of instructions with reference to academic stress among school going children. The sample consist of 200 8th class students (100 boys and 100 girls) among them 63 private and 47 government school students were considered. Scale for Assessing Academic Stress (SAAS) by Sinha, Sharma and Mahendra (2001) was used to find out the level of academic stress of the subjects. The suitable statistical tests were used to analyze the data. Findings suggested that gender, type of management and medium of instruction have shown significant influence on academic stress among secondary school students Girl students studying at private schools and who are opted Telugu as a medium of instructions were experienced more stress than their counterparts.

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Gender, Medium of Instruction, Type of Management ,Academic Stress and 8th Class Students

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This extensive research paper meticulously scrutinizes and compares air pollution dynamics in four major cities of Madhya Pradesh - Indore, Bhopal, Gwalior, and Jabalpur. Drawing from real-time data provided by The Informative Pollution Recorders and Panel Boards installed in the cities and some research papers and focusing on specific air quality parameters, the study endeavours to uncover nuanced variations in air quality levels, elucidate predominant pollutants, and present comprehensive recommendations for effective mitigation strategies.

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A Comprehensive Comparative Study of Air Pollution in Indore, Bhopal, Gwalior, and Jabalpur, Madhya Pradesh: A Multifaceted Analysis of Key Air Quality Parameters and Nuanced Recommendations.

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Abstract The advent of cloud computing has revolutionized data processing and analytics, with Amazon Web Services (AWS) leading the charge in providing scalable, efficient, and flexible data pipeline solutions. Optimizing data pipelines is essential for organizations to harness the full potential of their data, ensuring timely insights and informed decision-making. This paper delves into the best practices and techniques for optimizing data pipelines in AWS, focusing on architectural principles, cost management, security, and performance enhancements. Data pipelines are integral to modern data ecosystems, facilitating the flow of data from diverse sources to various endpoints for analysis and storage. AWS offers a suite of services like AWS Data Pipeline, AWS Glue, Amazon Kinesis, and Amazon Redshift that empower organizations to build robust data pipelines. However, the complexity of managing data across these platforms necessitates a comprehensive understanding of optimization strategies. One of the primary considerations in optimizing AWS data pipelines is architectural design. Implementing a modular architecture enhances flexibility and scalability, allowing components to be independently developed, deployed, and maintained. This modularity supports the seamless integration of new data sources and processing technologies, enabling organizations to adapt to evolving business needs. Additionally, employing serverless architectures with AWS Lambda can reduce operational overhead and improve resource utilization by scaling automatically based on demand. Cost management is another critical aspect of optimizing data pipelines. AWS offers various pricing models, and selecting the most appropriate one requires a thorough understanding of data volume, processing frequency, and required throughput. Organizations can minimize costs by leveraging spot instances for batch processing, employing data compression techniques, and using lifecycle policies to manage data retention in services like Amazon S3. Monitoring and analyzing cost metrics through AWS Cost Explorer and AWS Budgets allows organizations to identify cost-saving opportunities and adjust their strategies accordingly.

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Keywords: AWS, data pipelines, optimization, best practices, cloud computing, architectural design, cost management, security, performance enhancement, automation.

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Abstract Network traffic analysis is super important in today's cybersecurity world. It's like a careful at what's happening on a network find any bad stuff going on. This kind of work keeps our digital places safe from the sneaky threats that hide in cyberspace. By examining the many ways data moves around, security experts can spot odd patterns that usually mean trouble is nearby. One key part of this task is keeping a close eye on network traffic. This means capturing and breaking down data packets to find useful information. When analysts look at these digital pieces, they can see when things don't match up with what's expected--like strange amounts of traffic, surprise data transfers, or weird communication methods. These unusual signs are like warning flags that encourage them to dig deeper and take action if needed. To uncover the hidden secrets in network traffic, analysts use various tricks. For example, statistical analysis helps them spot anything that stands out or doesn't fit with "normal" behavior. Machine learning algorithms can also play a big role! These smart tools learn from huge sets of data and can identify complex patterns that might signal harmful activities. Plus, behavioral analysis looks at how users and systems act, helping to catch subtle oddities that regular detection tools might miss. The success of network traffic analysis really depends on telling the difference between good traffic and bad traffic. That's why researchers have come up with advanced models for classifying this data. These models use a mix of details like protocol info, what the content is, and how traffic behaves. They train these models using lots of normal traffic and attack samples so they can make smarter decisions about what they see happening on the network.

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Key Words Network traffic analysis, Intrusion detection, Cybersecurity, Malicious activities, Network monitoring, Data packet analysis, Anomalies, Statistical analysis, Machine learning, Behavioral analysis, Traffic classification, Classification models, Cyberattacks, Databreaches, Threat landscape

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Creative Commons Attribution 4.0 and The Open Definition

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Champaran, Chini Udyog, Samaj, Arthvyawastha, Ganna, Raiyat

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"If we have to promote the development of our country then our country mission has to be skill development and skilled India" ... Shri Narendra Modi Skill India programme was initiated by the Government of India it is considered to be a major central and state government policy and agenda in the past few years. Countries having higher & better skilled people can easily face challenges and grab opportunities in their work. The demographic status of India consists 67% of population between the age group of 16 - 60 years, their aspirations and industry demand has led to focus on skill development. In India, the informal sector employs nearly 90% of the workforce, most of them are either non-skilled or inadequately skilled, and there is very little investment or opportunity for formal skilling. According to a National Sample Survey Organization (NSSO) report, two types of vocational training are available in India. According to the NSSO report, vocational training is received by only 12% of people aged between 15 and 29 years. Out of this, only 3% receives formal training and non-formal training constitutes the remaining 9%. In case of formal training received by that particular age group, only 3% is employed.

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Skill India Programme, Government Initiatives, NSSO, Formal and informal sectors, Training , Skill development programme

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Creative Commons Attribution 4.0 and The Open Definition

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Pride and Prejudice is the second novel by English author Jane Austen, published in 1813. A novel of manners, it follows the character development of Eligabeth Bennet, the protagonist of the book, who learns about the repercussions of hasty judgements and comes to appreciate the difference between superficial goodness and actual goodness. Mr. Bennet, owner of the Longbourn estate in Hertfordshire, has five daughters, but his property is entailed and can only be passed to a male heir. His wife also lacks an enheritance, so his family faces becoming poor upon his death. Thus, it is emperative that at least one of the daughters marries well to support the others, which is a primary motivation driving the plot. Pride and Prejudice has consistently appeared near the top of lists of "most loved books" among literary scholars and the reading public. It has become one of the most popular novels in English literature, with over 20 million copies sold and has inspired many derivatives in modern literature.

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Protagonist, Pride, Prejudice, Perception, Impression.

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Kasturba Gandhi Balika Vidyalaya (KGBV) Scheme was come in to force in the year 2001under the umbrella of Ministry of Human Resource Development, Government of India and implemented under the scheme of Sarva Siksha Abhiyan to build the Indian education organism more accessible to the needs of disadvantage girls and to improve their access and retention. Under the scheme, residential schools for girls at upper primary to Sr. Secondary levels were set up in the Educationally Backward Block (EBB)s, which are identified by the SSA. In identification of the EBB, due consideration was given to the state government views. Under the KGBV scheme, girls children between 10-18 years of age group of SC, ST, OBC, Minority Community and BLP community get the change of free quality education. 21st century is the age of education and knowledge. The students having knowledge and skill can get better opportunity compared to other less knowledgeable person. Thus now a day's every education system provide significant amount of importance on performance based learning i.e. learning achievement of the students. Many literatures has already proved that the education system which have a better poll of students with quality learning achievement carries better job opportunities than their other counterpart. Better job opportunities means they can contribute more for their country's socio- economic development. The children learning (academic achievement) plays an crucial responsibility in producing the best quality graduates who will become great leaders and human resource for the country, thus helping the country's economic and social development (Ali, et.al , 2009).

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Learning Achievement of the girls students studying in class IX in Mathematics: A case study of Kasturba Gandhi Balika Vidyalaya (KGBV) students residing in Hostel under Nagaon district of Assam

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