Volume 12 | Issue 3 |

 Abstract

This study unveils cutting-edge developments in augmented reality (AR) tech for educational use, highlighting new strategies in image recognition and LOD optimization. It delves into AR's potential to transform conventional teaching methods, proposing an affordable VR hardware solution for broader access to immersive learning. By merging advanced tech with budget-friendly hardware, the research seeks to foster inclusive and captivating educational journeys for students.

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 Keywords

Augmented Reality , Virtual Reality , Education , Image Recognition , LOD

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Due to growing rivalry and unpredictability, the cellular phone industry in India is one of the most tumultuous and unpredictable ones in existence today. As a result, it points to research on consumer buying habits and brand preferences for selecting a mobile phone brand from a variety of options. This study is aimed at studying the adolescent and young adult population. The goal of this study is to examine the selection criteria utilized by consumers in mobile phone market places by examining the variables that affect young people's and adolescents' brand preferences when they purchase a mobile phone in the Coimbatore town. To achieve the study's goal, a sample of 150 customers was selected using a basic random sampling approach, and the data was then analyzed to produce a more informed recommendation. The tools were used Simple Percentage Analysis, Chi-Square and Rank Correlation.

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Mobile Phone, Coimbatore City, Brand preference

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Agriculture is a biggest economy and largest workforce in India. Farmers are the backbone of our nation and depend on agriculture to fulfil their duties. But in our country farming community is the only community which faces a bunch of problems which starts immediately after the planning of right crop to cultivate still end of harvesting. In India it is not easy to cultivate and harvest a specific variety of crop because of soil conditions of the farmland. When we compare our farming technologies with the western one, we can easily understand that how far we are and in whatever technologies we are lacking. Still in India we are following the traditional way of farming with limited technologies. Today in real life Data analysis, artificial intelligence, and machine learning playing a major role in every industry. With the help of that technologies, we can understand the cropping patterns, and fertilizer recommendation of a specific land area. If we see little deeper, we can understand the quality of soil for example nutrients level, phosphorus level, potassium. level, using the sensors we have fixed already. This technology is very much accurate in understanding and deliver the farmers with good recommendations about fertilizers and crop and this will help the farmers to increase the harvest from the farmland which directly income the farmers gross product.

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Crop and Fertilizer recommendation, Internet of Things, Random Forest, Logistic regression

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This study investigates Consumer Green Purchase Intentions (GPI) in Bihar, emphasizing Sustainable Practices (SP). Employing a Descriptive Research Design, the research comprehensively examines GPI with a specific focus on sustainable practices (SP), Awareness (AW), and Perception (PE). The scope encompasses a thorough exploration of factors influencing Environmentally Conscious Buying Behavior. A sample size of 536 is selected using the Snowball Technique. Data is collected through a questionnaire. The Statistical Package for the Social Sciences (SPSS) is utilized as the analytical tool to unravel patterns and correlations. This research contributes region-specific insights, aiding businesses and policymakers in aligning with environmentally conscious consumer preferences in Bihar.

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 Keywords

Green Purchase Intentions, Sustainable Practices, Statistical Package for the Social Sciences, Environmental Responsibility, Awareness, Perception.

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Artificial Intelligence (AI) is a branch of computer science dedicated to creating systems that can perform tasks that typically require human intelligence. These tasks include learning, reasoning, problem-solving, perception, language understanding, and decision-making. AI algorithms are designed to analyze large amounts of data, recognize patterns, and make predictions or decisions based on that analysis. The goal of AI is to develop machines that can mimic human cognitive abilities and perform tasks more efficiently and accurately than humans. AI has applications across various industries, including healthcare, finance, transportation, education, and entertainment, and it continues to advance rapidly, driving innovation and reshaping the way we live and work.

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"ARTIFICIAL INTELLIGENCE AND ITS ASPECTICAL ANALYSIS"

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By ensuring product quality, safety, and efficacy, formulation development plays a crucial role in pharmaceutical research and is necessary for both therapeutic and commercial success. Up until and including market approval, the many components of formulation development interact with other phases in product development, such as discovery research. Every medication item requires a custom formulation because of the complexity of many routes that could impact product stability, the unique properties of the medicinal molecule, unique patient requirements, and even marketing concerns. Formulation development can be approached in a number of ways, relying on scientific theories and a logical design that applies these insights to thousands of components. This article reviews formulation development and explains pre-formulation and sop handling so that readers can understand the significance of these processes and recognize, respect.

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Formulation Development, Preformulation, SOP, Tablet, Evaluation.

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ABSTRACT Background: Physical Therapy plays an important role in the management of Knee Osteoarthritis (OA). Egoscue exercise is a form of corrective exercise, it is the most convenient method for treating recurrent musculoskeletal pain caused by ageing, accidents, sports injuries, and other disorders. Effectiveness of Egoscue exercise showed that there was marked reduction in knee pain, improvement in body-function and balance in individuals with knee osteoarthritis. Study Purpose: To evaluate the effectiveness of Egoscue exercise on Pain, Body-function and Balance in individuals with Knee Osteoarthritis. Basic Methods: Eighteen (n=18) individuals with grade 2 and grade 3 knee OA were recruited for this study. The individuals were taken according to inclusion criteria and received set of Egoscue exercise for 5days/week for about 3 weeks. The outcome measures were numeric pain rating scale(NPRS), knee injury and osteoarthritis outcome score(KOOS), lower quarter Y balance test(YBT-LQ) assessed at pre and post intervention. Main Results: The study showed statistically significant difference between pre and post treatment within subjects with knee OA after 3 weeks of intervention in pain, body-function and balance in terms of NPRS(p value<0.001), KOOS(p value<0.001), YBT-LQ (p value<0.001) which is highly significant. Principal Conclusion: Egoscue corrective exercises considerably decreased pain in participants with OA knees while also enhancing bodily function and balance. However no discernible changes in the YBT-LQ test for balance in the posteromedial direction of the right leg was noted.

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Keywords: Balance; Body-function; Egoscue Exercises; Knee Osteoarthritis; Knee Pain

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The "Generative Neural Networks Novel Image Generation" project aims to expand the creative and generative capabilities of neural networks beyond traditional discriminative models. In previous contexts, mostly neural networks been utilized for tasks involving input-to-output mappings, such as image classification and text generation. However, this project delves into the realm of generative models, where the focus shifts from making decisions to creating entirely new and unique creative content. At its core, the project equips neural networks that have the power to craft images that encapsulate the style and essence of existing training data. This synthesis of new, yet familiar, visual content introduces diversity and creativity. Beyond artistic value, the project holds practical value in data augmentation, offering a solution to data scarcity by generating synthetic content that can enhance machine learning model performance. The impact of this project extends across industries. In healthcare, it assists medical image analysis by generating realistic data for algorithm training. In fashion, it aids design by creating new patterns and styles. Moreover, the project also addresses data privacy concerns, enabling information sharing without compromising sensitive details. By forging a bridge between technology and creativity, the "Generative Neural Networks to create Innovative Images Generation" project innovation enriches data science. Furthermore, the project underscores the significance of synthetic data in addressing data scarcity and privacy concerns. Synthetic data has the potential to supplement real datasets in scenarios where access to authentic data is limited or protected

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Generative Neural Networks, Novel Image Generation, Creative, Data Augmentation, Synthetic Content, Data Security, Healthcare, Fashion.

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The present study sought to analyze the Indian Research Information Network System (IRINS) instances with particular reference to universities in Tamil Nadu. The study explores the resource impact from scholarly resources, the contributions of top of individual Tamilnadu universities, the h-index, the top faculty of respective state universities, and the h-index. The study finding shows that Annamalai University holds the highest faculties, 1095 (30.25%). Tamil Nadu Agriculture University has the highest 12736 scholarly publications among the state universities of Tamil Nadu state, with Scopus citation 27944 and Crossref citation 22057. Anna University has the highest h-index 942 among the state universities in Tamil Nadu state. Prof. Madhukar Hemamalini (Mother Teresa Women's University) has the highest 527 scholarly resources and Prof. Muthusamy Lakshmanan from Barathidasan University has the highest 9801 Scopus citations and 8988 crossref citations with 50 h-index among the state university faculty members in Tamilnadu

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IRINS, State Universities, INFLIBNET, Tamil Nadu

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Creative Commons Attribution 4.0 and The Open Definition

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The study employs a quantitative approach to estimate the factors affecting the performance of Exchange-Traded Funds (ETFs) concerning Equity Mutual Funds. This study provides both quantitative and qualitative results The study utilizes secondary data, specifically net asset value (NAV) of equity mutual funds and Jakarta Composite Index, obtained from the official websites of Financial Service Authority and Indonesia Stock Exchange. Additionally, data related to ETFs and equity mutual funds, specifically NAV, is collected from various sources like the Association of Mutual Fund in India (AMFI) and financial websites such as Money Control, Growth, and ET Money. The risk taken by the investor return earned through the investment. To evaluation of the performance of equity mutual fund and ETF, after consideration of the return earned for risk incurred by the investor, various risk adjusted performance parameters such as Sharpe Ratio, Jensen's Alpha, Beta, Treynor ratio and Sortino ratio. The findings suggest that the performance drivers differ between Mutual Funds and ETFs. For Mutual Funds, risk plays a crucial role, while for ETFs, both volatility and fund selection skill are significant factors. This information can be valuable for investors seeking to optimize their portfolio based on the specific characteristics of these investment vehicles.

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Mutual Fund, Exchange Trade Fund, Affecting Performance, Factor Analysis, Risk adjusted performance, Qualitative Study

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