Volume 11 | Issue 12 |

 Abstract

Abstract In this article, we aim to demonstrate that the work of Christian educational institutions in various parts of India has been effective without any negative intentions. Educational development is found to occur where institutions are active, especially among those who are deprived, poor, exploited, and excluded from mainstream society. The institutions have given hope to these individuals, who have been striving to assist in educational, social, economic, and political ways. This research, based on the empirical studies of two taluks, namely Mysore and Heggadadevanakote, in the Mysore district in Karnataka State, concerning the role of Christian educational institution schools in tribal education, found many issues of relevance. 2020-2021 saw the collection of data from students between the ages of 6 and 14. Other groups of individuals were also included in the data, including NGO representatives, tribal and non-tribal people, local leaders, administrators, and elected representatives. It endeavors to concentrate on areas of study that are not yet explored. Christian institutions in educational development in the State of Karnataka, India have been empirically examined in the paper for the first time. The various forms of their contribution to educating the tribal people of Karnataka can be understood through this study, which has policy implications. The H.D. Kote taluk of Mysore district was confirmed by this study. Due to only one government school in this taluk, the education level of the tribals was significantly lower than that of Mysore.

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Keywords: tribal education, Christian institutions, pragmatic work , Karnataka

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Marketing of traditional and handmade products become very complex and strategic view to create a market for them. The Handloom industry has contributed many credits to the Indian economy with its unique and specialized work. Therefore, it is the second largest sector that provides employment for rural people after the agriculture sector and increases foreign exchange earnings by attracting the global market. However, the industry is not free from sickness and which is highest compared to other traditional and small rural-based industries. The Government of India has initiated many programs and welfare schemes to recall the historical importance even in the globalization process. The main intention behind this is to safeguard the interest of stakeholders through strategic arrangements for marketing of their final outputs. In this background, the Government has created proper backward and forward linkages to avoid hurdles in supply chain management. This paper carries important strategies developed by the Governments for appropriate marketability and parking of handloom products both in domestic and international markets. The paper is developed based on personal interviews with handloom weavers, Government officials, and respective stakeholders. However, the majority of work is being done from secondary sources of data. Finally, the paper enlightens on strategies adopted for marketing handloom products and concludes with for and against the policy measures.

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Government, Handloom, Marketing, Strategies, Supply-chain

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National dye is found from natural source such as from plant animal and mineral. Natural dyed cloth is more eco-friendly product. It is giving non-toxic, chemical free product and this does not harmful environment nature. In this study dyeing of cotton fabric with natural dye from Haldi, Anar, Katha extract. To know the effect of natural and chemical modern fixation of dye cotton fabric and fastness to repeated washing. The study adopted an experimental method. 100% cotton fabric(bleached) were taken for sample. The process of mordanting is done for increasing colour fastness of natural dye. Each mordant give different shades and its fastness is also different. The fastness of a natural dye on cotton fabric can be increased by using alum or potassium dichloride and or vinegar during pre-mordanting and mordanting process. Dyeing through National dye avoid pollution in the atmosphere and it is also cheap. In view of these advantage use of natural dye should be promoted.

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Natural dye, Mordant, Shades, Fastness, Washing

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A wafer, a thin semiconductor slices crucial for microelectronic devices, notably in integrated circuits (ICs), plays a fundamental role in various industries, such as computing, solar cells, and optics. We created a machine learning model utilizing Python, Flask, and PyCharm, as well as Random Forest and XG Boost Classifiers to anticipate the need to replace wafers based on sensor inputs. Wafer fault detection is essential in semiconductor production, enhancing fabrication yield by identifying non-functioning wafers. The dataset includes wafer names and 590 sensor value columns, with the last column indicating "Good/Bad" status, transmitted in batches for analysis. The two classes, +1 and -1, signify the working condition and the need for replacement, respectively, ensuring efficient identification and prediction of faulty wafers without impacting other resources

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wafer, integrated circuits, computing, machine learning model, fault detection, sensor inputs, classification, replacement.

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The aim of this study to investigate the influence of political stability on the relationship between the fiscal policy, fiscal deficit, and economic growth in South Asian countries. This study used the panel data from 2001 to 2018 and used pooled mean group approach for estimation. Results indicated that political stability and human capital had a positive effect on the economic growth. Moreover, the gross capital formation, labor force, and government expenditure had a positive, whereas inward FDI and fiscal deficit had negative effects on economic growth. These findings support the Keynesian view on the fiscal policy and the neoclassical theory on fiscal deficit in the presence of political stability. The study suggested that the expansionary fiscal policy, reduction in fiscal deficit, and political stability can enhance the economic growth in South Asian economies. The findings have significant implications for policy makers and can contribute to the existing literature.

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government expenditures; fiscal deficit; political stability; the pooled mean group approach; South Asian economies

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Ginger (Zingiber officinale) is a flowering plant whose rhizome, ginger root or ginger, is widely used as a spice and a folk medicine. Ginger is loaded with antioxidants, compounds that prevent stress and damage to your body's DNA. They may help your body fight off chronic diseases like high blood pressure, heart disease, and diseases of the lungs, plus promote healthy aging. Doctors recommend consuming a maximum of 3-4 grams of ginger extract per day. If you're pregnant, don't consume more than 1 gram of ginger extract per day. Ginger is not recommended for children under the age of 2. The first written record of ginger comes from the Analects of Confucius, written in China during the Warring Statesperiod (475-221 BC). Though it is grown in many areas across the globe, ginger is "among the earliest recorded spices to be cultivated and exported from southwest India".

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Zingiber officinale, Rhizome, Ginger, Anti- inflammatory, Resins.

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Assess, knowledge & pediatric thalassemia

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Innovative research attempts have been spurred by the constant difficulty of shadows affecting image quality in the field of computer vision and image processing. This research explores the creation of a reliable and effective shadow removal system using state-of-the-art image processing methods. Shadows reduce image clarity and interfere with visual perception, frequently serving as obstacles in a variety of applications. This research attempts to tackle this problem from all angles in order to revolutionize image processing. Naturally occurring in images are shadows cast by obstructing light sources, which cause colour distortion and decreased visibility. Shadows impede precise object identification and scene comprehension in computer vision. The limits of traditional shadow removal technologies require the investigation of more sophisticated strategies in order to address these issues. The common appearance of shadows in images, which restricts applications like automated surveillance, object detection, and medical imaging, is the driving force behind this research. Eliminating shadows improves automated systems' accuracy and dependability in addition to their visual appeal. This work has broad implications for many domains where accurate image processing is critical. The creation of a novel shadow removal system that can precisely detect and remove shadows from photos is the main result of this research. The suggested method ensures accurate removal without sacrificing image integrity by using advanced algorithms and machine learning models to discern between shadows and real objects. After a great deal of testing and verification, the system performs exceptionally well in a range of lighting scenarios with complicated shadows. By combining powerful image processing algorithms with machine learning approaches, this study presents a revolutionary methodology. The system's capacity to adaptively learn and distinguish shadows from other picture elements, guaranteeing great accuracy and efficiency, is what makes it innovative. Furthermore, the addition of real-time processing capabilities represents a significant development and enables the system to be used in time-sensitive applications. In conclusion, this study not only tackles the ubiquitous problem of shadows in photos but also makes a significant contribution to the field of image processing. The system that was created is evidence of the collaboration between state-of-the-art algorithms and creative approaches, opening the door to improved image quality and the development of computer vision applications.

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Computer Vision, Machine Learning, DeepLearning.

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Blockchain technology streamlines business operations and minimizes reliance on intermediaries. This technology also automates processes such as contract execution, payment processing, etc. to save time and boost productivity. Blockchain technology is now being used in a variety of educational settings, including the creation of transparent and secure decentralized learning platforms. Limited research has been done to determine the awareness and adaptation of blockchain technology in academic environments. The use of blockchain technology in the academic setting has the potential to significantly enhance intellectual property protection, secure data sharing, etc. This research paper will analyze the understanding and awareness of academics about blockchain technology applications in academic environments such as administration and learning management systems. This research study recommends a framework model called the EX-TAM, to help understand the intentions of academic stakeholders towards blockchain technology. Stakeholders' intentions and understanding of technology adoption are critical for ensuring successful implementation, maximizing adoption, and return on investment. Many research studies have found that there are multiple factors that are responsible for the successful adoption of any technology. According to the academic database Google Scholar, using the keywords "blockchain technology adoption factors" generated over 20,000 results as of April 2023. However, some of them focused on the issues influencing the adoption of blockchain technology, while others examined more general issues such as blockchain benefits and drawbacks, how it affects various industries, and what potential uses it might have. The proposed research model Ex-TAM is influenced by the TAM model. The model will help to identify the factors responsible for the adoption of blockchain technology in academic environments and understand the level of awareness. This proposed study is particularly effective in generating momentum for the adoption of blockchain technology in academic institutions to improve efficiency, reduce costs, and increase transparency.

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Blockchain technology, academics, technology model, adoption, factors, stakeholders.

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The retail industry is undergoing a rapid transformation as artificial intelligence (AI) automates the once manual tasks associated with running a successful business. By allowing businesses to see the potential outcomes of different pricing methods, AI apps for retail outlets might aid enterprises in product pricing. In order to do this, systems collect data on various goods, promotional activities, sales figures, and other relevant information. Finding out how AI has affected the retail sector is the driving force for the research. The research was conducted in Vijayawada, Andhra Pradesh, India, using 145 samples from different retail establishments. In this study, we employ primary and secondary sources of information. Factor analysis was used to assess the study. Studies of data show that most people are aware that AI is used in India's retail industry. People have also noticed that most stores are using AI into their business strategies. In particular, AI helps the Indian retail sector with order processing, shipping, and inventory management.Also, it has been shown that the majority of retail owners are cognizant of the ways AI might affect their company and are already incorporating AI strategies into their operations to adapt to the industry's evolving needs.

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Artificial Intelligence, Machine Learning, Retail sector,Business

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Creative Commons Attribution 4.0 and The Open Definition