Volume 10 | Issue 12 |

 Abstract

Uttar Pradesh or better we call it " Uttam " Pradesh because the economy of Uttar Pradesh is increasing by leaps and bounds . The economy of Uttar Pradesh is the third largest state in India with Nominal GDP of Rs 21.74 trillion for the year 2022 - 2023 . GDP growth rate is expected to be 17.1% in 2022 - 23 as compared to 2021 - 22 and this is mainly due to the Automobile sector. Automobile industry is the key driver of any economy. That's why once Peter Drucker has called the automobile industry " The Industry of Industries " . The economy of any region , country or state is directly related to the automobile sector . The growth of the economy without automobiles is like " Life without oxygen " which is not possible . The contribution of the automobile industry in India is 12.1% in Gross Value Added (GVA ) in the manufacturing sector . It is recognized as a core sector . As per Economic Times , The auto Industry is contributing to 49% in India manufacturing GDP and this sector is responsible for 32 million jobs . In this Research paper you will come to know Automobile roles , benefits , Contribution of Automobile industry in Uttar Pradesh economy. Uttar Pradesh economy aims to reach 1 trillion-dollar economy , In this research paper you will come to know how it is possible through Electric Vehicle policy 2022 .According to the mercomindia.com , Uttar Pradesh economy aims to invest Rs. 400 Billion till 2024 in the Electric Vehicles automobiles sector . Uttar Pradesh registered more than 139000 electric vehicles ( EVs ) which is highest in India and the third largest of Faster Adaptations and manufacturing of Hybrid and Electric Vehicles ( FAME ) . In this research paper you will have a look at this too.

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 Keywords

Uttar Pradesh Economy , Automotive Industry , Gross state domestic product, Per capita income, Sectoral growth, Economic infrastructure , Electric mobility , Uttar Pradesh Electric vehicle policy 2019 , Uttar Pradesh Electric Vehicle policy 2022

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

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job burnout?management education

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 Abstract

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Index Terms - Continuing Education, Teachers, Basic Education.

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Agriculture has undergone a digital transformation that has transformed various management functions into artificially intelligent systems in an effort to extract value from the growing amount of data coming from various sources. Machine learning, a branch of artificial intelligence, has a great deal of potential to address many difficulties in the development of knowledge-based farming systems fully reviewing recent scholarly literature using the keywords machine learning" along with crop management, water management, soil management, and livestock management," and current study aims to shed light on machine learning in agriculture. Only journal articles that were released between 2018 and 2020 were deemed eligible. The findings showed that this topic is relevant to various disciplines that support global convergence research. Furthermore, it was noted that crop management was the main focus. There were many different machine learning algorithms used, with artificial neural network-based algorithms being the most effective. Additionally, the most extensively studied crops and animals were wheat and maize, along with cattle and sheep. In order to obtain trustworthy input data for the data analyses, a variety of sensors mounted on satellites and unmanned ground and aerial vehicles have been used.

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 Keywords

Machine learning; water management; soil management; livestock management; artificial intelligence; crop management;

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The purpose of this study is to analyze the factors that influence people's recycling intention to recycle e-waste. Research on the factors that encourage household interactions in sorting waste or recycling waste is a priority due to low participation in the e-waste recycling process. This study aims to build a model and examine the relationship between variables. It is based on the Theory of Planned Behavior (TPB). We studied mobile phone and laptop users who had changed their phones. A total of 324 respondents were selected by the purposive sampling method. Multiple regression was used to analyze the data. The results show that Theory of Planned Behavior and additional variables (environment awareness & knowledge, convenience and recycling costs) are also positively related to household recycling intention. Using the results, policy implications and research limitations were discussed.

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 Keywords

Theory of Planned Behavior,Environmental Awareness and Knowledge, cost of recycling, convenience.

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Corona virus disease has become a major health concern worldwide from its outbreak since 2019. Till today, it accounts for the 3.4% deaths around the world from its reported cases. The pandemic leads to development of various Covid-19 vaccines such as Covaxin, Covishield, Covovax, Sputnik V, Moderna etc. from worldwide pharmaceutical companies. Despite the usefulness of covid-19 vaccines and their protective action against severe infection still these are refused by many individuals. Some people have still not accepted the efficacy of covid-19 vaccines in their everyday life. However, some individuals accept covid-19 vaccines eventually. This study explores the covid-19 vaccination acceptance and enthusiasm among community members for vaccination drive. In this cross-sectional qualitative study, one hundred and thirty four individuals of Bathinda and nearby area were included. People were interviewed as per a semi structured questionnaire and the collected data was analysed statistically. One hundred and thirty-four patients were included in this study: 63.4 % female and 36.6 % male. Most of the volunteers i.e. 64.9 % were belong to 20-30 age group and same percentage community members belong to urban background. Nearly 70 % were educated from all 134 individuals. 91.8 % were fully vaccinated while only 84.3% people considered Covid-19 vaccination safe. Among all included members, 73.1% thought that corona virus vaccine effective however, 22.4% disagreed. The individuals thought that benefits of vaccination are more than its risks (71.6%), while 20.1% disagreed and 8.2 % had no idea about this. Some people (11.9%) were not agreed that vaccination could help to reduce further covid-19 infection but most of the members (79.1%) agreed to this notion. Almost one fourth individuals thought that vaccination could not prevent from future variants of covid-19 virus. However, still more than 80% people considered that vaccination should be mandatory for all human beings and they would also motivate other community members to get the covid-19 vaccination. Our most significant finding is that 85.8 % people thought that they would also motivate other community members to get the covid-19 vaccination. This finding in return suggested the acceptance of covid-19 vaccination among community. However, still more awareness regarding vaccination of Corona virus is needed to reach the 100% milestone.

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 Keywords

Corona virus; vaccination; pandemic.

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To achieve the purpose of this study, the investigator select forty-five college Men basketball players from various affiliated colleges of University of Madras, Chennai, Tamilnadu. The subjects were selected randomly and their age ranged from 18 to 21 years. They were assigned into three groups, of which one group served as a Circuit Training group, the second group served as a Skill training group and the third group served as a combined Circuit training and Skill training group. The experimental groups participated in their respective training programmes for a period of six weeks. The selected subjects were measured by their shooting by lay up shooting test before and after the training period of six weeks. The differences between the initial and final scores of shooting were subjected to statistical treatment using Analysis of Covariance (ANCOVA). The results further revealed that, compared with other groups, the combined group significantly improved shooting. It was concluded that a combined training group was better than a Circuit training group and Skill training group.

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Circuit training group, Skill Training,Shooting.

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 Abstract

The goal is to classify various types of wireless assaults, such as those that take advantage of vulnerable systems or rogue access points. There are a number of techniques that can be used to identify a rogue user at a specific point of entry. Such strategies and methods are quickly categorised into fundamental subfields, such as the client side, the server side, the wired side, the wireless side, the temporal aspects, etc. Every conceivable tactic has both advantages and disadvantages. The goal of this study is to discuss the difficulties and restrictions of existing strategies for detecting Rogue APs. Apply a machine learning (ML) technique to a real-time dataset constructed from these issues. With the use of ML-based methods, rogue APs were detected and analysed.

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Rogue AP, Rogue AP detection methods, ML based techniques, WLAN threat

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Abstract- Financial services are used everywhere and operate in a very complex manner. With the increase in online transactions comes an alarming increase in fraud. An automatic fraud detection system is therefore required. With millions of transactions in progress, it is virtually impossible to detect fraud manually with good speed and accuracy. We design a system that provides a robust, cost-effective, efficient, yet accurate solution for fraud detection in both online payment transactions and credit card payments. The proposed solution is a machine learning model that will be used to detect "fraudulent" and "genuine" transactions in real time. This is beneficial for all sectors that are even slightly attuned to finance. The solution will help them analyse based on various factors whether an ongoing transaction may be malicious and prevent many unfortunate incidents.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

fraud detection, Retail Frauds, credit card, online payments, fraudulent.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

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 Keywords

Anarchy, Bioterrorism, Germ warfare, Science Fiction, Weaponization

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