Volume 13 | Issue 1 |

 Abstract

The dairy sector in India is contributing significantly to the national economy. India is the largest producer and consumer of milk in the world. Dairy farming is becoming more possible because of data-driven approaches used in Dairy sector. Dairy farming is one of the leading component of agricultural activities in almost all parts of the world including India. India is the world's largest producer of dairy products by volume and has the world's largest dairy animal population. Demand of milk is continuously increasing due to increasing population of the world. Dairy farming has been an important part of the agricultural scenario for thousands of years. India being a predominantly agrarian economy has about 70 per cent of its population living in villages, where livestock play a crucial role in the socio-economic life. Livestock provide high-quality foods such as milk, cheese, butter, ghee, etc. India is not only one of the top producers of milk in the world, but also the largest consumer of milk and milk products in the world. Due to the shortfall in supply, we have to import significant amounts of milk products to meet internal demand. Dairy farming is a form of agriculture that is dedicated to the production of milk and dairy products from the care and feeding of cattle, mainly dairy cows. Dairy farmers focus on managing the health, welfare, and milk production of animals to obtain the highest quantity and quality of milk possible.

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 Keywords

Dairy Farming in India and Abroad, Dairy Sector, Animal Husbandry, Specific Guidelines, Review of Literature, Findings and Suggestions.

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Advancements in machine learning, particularly convolutional autoencoders (CAEs) and generative adversarial networks (GANs), have revolutionized fingerprint recreation, enabling precise and efficient reconstruction even from low-quality or partial data. This paper reviews key contributions from recent literature, highlighting convolutional neural network (CNN) architectures, multi-loss optimization techniques, and sparse encoding methods to enhance reconstruction accuracy. By synthesizing insights from these studies, the review discusses challenges such as dataset quality, adversarial robustness, and scalability, offering a roadmap for future developments in fingerprint reconstruction using machine learning.

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 Keywords

Fingerprint reconstruction, convolutional autoencoders, deep learning, biometrics, latent fingerprint analysis, biometric security, image reconstruction, ridge patterns, minutiae patterns, low-quality fingerprint enhancement, forensic fingerprint reconstruction, machine learning.

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Indian diaspora plays an important role for accelerate social and cultural development. If we look at the world culture, one thing is can be noticed is the Indian Diaspora that incorporates unique force in some veneration. The incorporation of the British Empire in India can be linked to the continuation of modern Indian Diaspora all over the world. If we look back to nineteenth century, India concurred labour was taken over to the British colonies in different parts of the world. Countries like Fiji, Mauritius, Guyana, Trinidad, Surinam, Malaysia, South Africa, Sri Lanka and so on leave the foot prints of Indian immigration in a peculiar way. Over two million Indian people fought on behalf of the empire in various wars fought abroad. Moreover in Boer War and the two World Wars and some remained behind to claim the land on which they had fought as their own. In the early part of 20th century many traders from Gujarat left for East Africa in large numbers s if it's an emulation of the ancestors. In this paper an attempt will be undertaken to reveal the social development and the relation of Indian Diaspora from colonial period to post independence period.

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 Keywords

Diaspora, India and Development

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The banking sector is the backbone and key component of the financial system that drives economic development. As a key driver of economic growth, the bank supports economic activity and meets the financial needs of all sections of society. This study employs ratios and trends to evaluate the banks financial performance in terms of capital adequacy, asset quality, earning capacity, management efficiency, and liquidity. We found that the majority of the selected banks are complying with Basel minimum capital requirement norms and earning adequately. However, it is further found that as banks earning increased non-performing asset component in bank books also increased.

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 Keywords

Basel Norms, Earning capacity, Financial position, Capital adequacy, NPA

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This paper serves as a primer on the mechanics of stock price movements, examining the factors behind price fluctuations. It highlights how autoregressive models can help explain these changes and distinguishes between stationary and non-stationary processes in stock prices. The paper also explores how market shocks influence prices. In efficient markets, new information is quickly reflected in stock prices, making them difficult to predict due to the presence of a unit root. However, investor emotions such as fear, greed, and overconfidence can lead to irrational behavior, causing mispricing and the formation of price bubbles. These psychological factors can create patterns of herd behavior that, while seemingly random, can be analyzed using technical tools like Moving Averages and the Relative Strength Index (RSI). Ultimately, the paper shows that while stock prices may appear unpredictable, human emotions and collective behavior generate recurring patterns that can be studied and used for forecasting.

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 Keywords

Stock Prices, Autoregression, Random Walk, Efficient Market Hypothesis, Behavioural Finance, Leading Indicators, Lagging Indicators, Volatility

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The climate change is one of the very typical issues, its impact now considered as common global issue by all the countries and looking for best controlling ways in view of future unpredictable situations. Though the problem recognised a few decades earlier, its present situational impact attracting immediate attention. Apart from human beings witnessing the adverse effects, all the plants, animals and other living beings are also not an exception. Several reports suggest climate change mostly depends on three important factors, population, environment, and utility of resources in diversified ways. Lead termination of green belts also reported as vital reason. Reports evidenced that huge variation found in average earth atmosphere prior to industrial era. East and West Godavri districts in the state of Andhra Pradesh in India have significant global identity because of its rich heritage, culture, climatic conditions, and as a profound supplier of food materials. These areas are very famous for agriculture and the quality of many products like rice, sugar cane, coconut. The aqua food cultivation made these districts wealthy enough. However, lot of changes are being observed in the typical maintenance of agriculture and other sustainment due to significant changes in seasonal weather conditions due to climate change. In view of this, it is also found at cases that people are migrating to other places for their sustainment. Typical investigations with important surveys carried out for the identification of observable impact of climate change in these areas and people. Possible scientific suggestions for mitigation of the issues were made.

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 Keywords

Godavari Districts, Andhra Pradesh, India, Agri and Aqua Culture, Climate Change, Impact on Sustainment, Scientific Suggestions.

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Method development and validation are critical components of analytical chemistry, particularly for UV-Visible (UV-Vis) spectroscopy and High-Performance Liquid Chromatography (HPLC). These techniques are widely used for the qualitative and quantitative analysis of pharmaceuticals, environmental samples, and food products. Over the past decade, advancements have focused on improving accuracy, precision, robustness, and sensitivity in analytical methods. For UV-Vis spectroscopy, the emphasis has been on optimizing wavelength selection, solvent compatibility, and linearity in absorbance-concentration relationships. Enhanced chemometric approaches and advanced software tools have streamlined method development, reducing time and improving reliability. In HPLC, method development has centered around optimizing chromatographic conditions such as mobile phase composition, flow rate, column selection, and detection methods. Novel stationary phases, gradient elution techniques, and the integration of mass spectrometry have expanded HPLC's applicability. Validation strategies, guided by ICH (International Council for Harmonisation) guidelines, ensure the reliability of methods through rigorous testing of parameters like accuracy, precision, linearity, limit of detection, and limit of quantification

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 Keywords

Method development, Validation, Analytical method, UV spectroscopy, High-Performance Liquid Chromatography (HPLC), Quantitative analysis, Qualitative analysis, Assay, Chromatographic separation, Analytical techniques.

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 Abstract

"Marriage: A Historical Survey"

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"Marriage: A Historical Survey"

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Facial gesture-based cursor control presents a novel, hands-free interaction system that leverages computer vision and machine learning to translate facial expressions into cursor movements. This system utilizes algorithms such as Convolutional Neural Networks (CNNs) to identify facial landmarks, while classifiers like Support Vector Machines (SVMs) or k-Nearest Neighbors (k-NN) interpret gestures, including blinking, smiling, and raising eyebrows, to execute actions like cursor navigation, clicks, and scrolling. Additionally, integrated voice commands provide a seamless way to articulate mouse actions, enhancing the system's functionality. By analyzing real-time video input, this technology delivers an intuitive and accessible interface, enabling gesture-driven control for individuals with mobility challenges and offering an innovative alternative for hands-free interaction.

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 Keywords

Computer Vision, Machine Learning, Convolutional Neural Networks (CNNs), Support Vector Machines (SVMs), Support Vector Machines (SVMs), Voice commands, Hands-free interaction

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The Office Prediction Project aims to predict the likelihood of a person working in an office setting. This review paper provides an overview of the existing literature on office prediction, highlighting the key challenges, methodologies, and results. We also identify gaps in current research and propose future directions for the project. The film industry invests heavily in producing and marketing movies, making accurate box office revenue predictions crucial for minimizing financial risks. This literature review examines the application of linear regression models in machine learning for predicting box office revenue. A comprehensive analysis of existing studies reveals that linear regression models can effectively forecast box office performance using variables such as production budget, genre, release date, and social media buzz. The review discusses the strengths and limitations of linear regression models in this context, including issues related to data quality, feature selection, and model interpretability. The findings of this review provide insights for film industry stakeholders seeking to optimize production and marketing strategies using data-driven approaches. Future research directions are identified, including the exploration of ensemble methods and deep learning techniques to improve prediction accuracy.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Box office revenue prediction, Linear regression, Machine learning, film industry, data-driven decision making.

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Creative Commons Attribution 4.0 and The Open Definition