Volume 13 | Issue 4

 Abstract

The Kota tribe, an indigenous community in the Nilgiri Hills of Tamil Nadu, has preserved its unique cultural and religious practices for centuries. Despite their relatively small population, the Kotas possess a rich and complex system of rituals that reflect their deep connection with nature, ancestors, and the spiritual realm. This paper explores the untold stories of Kota rituals, shedding light on their birth and death ceremonies, their secretive temple worship, and their lesser-known musical and dance traditions. The study also examines the challenges faced by the Kota community in preserving their heritage amid rapid modernization.

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 Keywords

Kota tribe, Nilgiri Hills, indigenous rituals, ancestral worship, tribal traditions

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The rapid proliferation of food delivery platforms such as Zomato and Swiggy has reshaped consumer dining behaviors and presented both opportunities and challenges for traditional restaurants. This research investigates consumer motivations, perceptions, and the broader implications of online food delivery services on traditional dining practices and restaurant operations. Through a structured survey of 200 consumers and 30 restaurant stakeholders, the study identifies key drivers for food delivery usage, including convenience, time-saving, lack of cooking skills, and promotional incentives, while also evaluating satisfaction levels and perceived impacts on value, quality, and social experiences. Hypothesis testing and statistical models reveal that while factors like convenience and discounts are commonly cited, lack of cooking skills emerges as the only significant predictor of reduced traditional dining. From the restaurant perspective, findings highlight mixed impacts on foot traffic, with varying levels of revenue dependency on food delivery platforms. Notably, restaurants face critical challenges such as increased competition from cloud kitchens, high commission rates, and declining profit margins. The study concludes that while food delivery services offer considerable consumer benefits, they also impose structural pressures on traditional dining models.

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 Keywords

Food Delivery Platforms, Zomato, Swiggy, Consumer Behavior, Dining Preferences, Traditional Restaurants, Online Food Ordering, Convenience, Customer Satisfaction, Restaurant Strategy, Cloud Kitchens, Digital Disruption, Food Tech Industry, Service Quality, Consumer Motivation.

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Water scarcity involves water stress, water shortage or deficits, and water crisis. While the concept of water stress is relatively new, it is the difficulty of obtaining sources of fresh water for use during a period of time and may result in further depletion and deterioration of available water resources. Water shortages may be caused by climate change, such as altered weather patterns including droughts or floods, increased pollution, and increased human demand and overuse of water. A water crisis is a situation where the available potable, unpolluted water within a region is less than that region's demand. Water scarcity is being driven by two converging phenomena: growing freshwater use and depletion of usable freshwater resources.

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Water scarcity

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This review paper studies the various traditional practices of the North East region. The methods of farming system of the region seem to be homogenous with slight variations. Agriculture is not only an economic activity; it is the central them of the cultural identity but sadly there is a rapid decline in the traditional practices which may have a far-reaching adverse impact socio-economic system of the communities of North East. Jhum cultivation is found to be the most common method of cultivation along with terrace rice fields along the hill slopes. Besides rice, many other food crops are grown traditionally to meet the needs and not commercialize but with various socio-economic changes, the traditional practices and food crops are on the decline. There is diversification of crops through modernization with the intention to commercialize.

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 Keywords

Jhum, wet terrace fields, sustainability, traditional knowledge system, homegarden

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In today's digital age, where technology influences every aspect of life, BookNest stands out as a unique platform that redefines the reading experience. By combining personalized book recommendations with community engagement, BookNest offers a space where readers can discover, share, and discuss literature. It creates an interactive environment that transforms the way people experience books by blending solitary reading with social interaction. Key features of BookNest include book exchanges, live discussions, and group reading sessions. These tools enable readers to connect with others who share similar interests, facilitating meaningful conversations around books and their themes. The platform goes beyond traditional reading by turning it into an engaging, social experience that encourages collaboration and community building. Readers can exchange books, discover new authors, and deepen their understanding of the literature through group interactions. In addition to promoting social engagement, BookNest advocates for sustainable reading practices. Through initiatives like book swapping and sharing, the platform encourages readers to make environmentally conscious choices while enjoying literature. These practices contribute to reducing waste and extending the lifespan of books, fostering a more sustainable approach to reading. This study explores how BookNest fosters literary interaction while promoting sustainable reading habits. It highlights the ways in which digital platforms can enhance our connection with books and other readers, offering valuable insights into the potential of technology to transform the reading experience. Ultimately, BookNest illustrates how blending technology with literature can create a richer, more connected way to engage with books in the modern world.

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 Keywords

BookNest, Digital Reading Platform, Community Engagement, Book Exchange, Sustainability, Personalized Recommendations, Social Interaction, Literary Community, AI-powered Features, Reading Experience

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This study investigated the scientific attitude of 5T secondary school students in Boudh district, Odisha due to gender (boys and girls) and locality (rural and urban). The research was followed by descriptive survey research method. A sample of 80 students (40 boys and 40 girls) from Boudh district were randomly drawn from eight sampled 5T secondary schools. These 8 sampled 5T secondary schools were randomly drawn from the three blocks (Boudh, Kantamal and Harabhanga) of Boudh district. The data were collected by using a self-prepared Scientific Attitude Scale contained five points by the investigators. For the analysis and interpretation of data, the researchers had used Mean, Standard Deviation and t-test. It was revealed from the study that there is no significant difference due to locality and there is significant difference due to gender.

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Science, Scientific Attitude, 5T, Secondary school students, gender, and Locality.

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Prime number distribution has been a subject of extensive mathematical exploration, with profound implications in number theory, cryptography, and computational mathematics. Traditional analytical approaches often rely on deterministic algorithms and conjectures, such as the Prime Number Theorem and Riemann Hypothesis. However, recent advancements in machine learning (ML) offer novel perspectives for predicting prime number distributions using data-driven methodologies. This study explores advanced ML-driven regression models to analyze and predict the occurrence of prime numbers within numerical sequences. Various regression techniques are employed to approximate underlying patterns in prime distributions. Comparative evaluations based on accuracy, generalization ability, and computational efficiency highlight the most effective models for prime number prediction. The findings contribute to the growing intersection of machine learning and mathematical research, demonstrating the potential of ML-based regression models in number theory and complex sequence analysis.

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 Keywords

Prime Numbers, Machine Learning, Regression Models, Prime Number Distribution, Predictive Analytics, Number Theory, Data-Driven Approach, Computational Mathematics, Artificial Intelligence.

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This paper looks at how mental health is shown in literature through a comparison of Jane Eyre, Winnie the Pooh, and A Beautiful Mind. Each of these works, created in different time periods, gives a unique perspective on mental health. Jane Eyre explores themes of isolation, emotional struggle, and repression in the Victorian era, showing how mental illness was viewed and treated at that time. The story's portrayal of the main character's emotional battles reflects the era's limited understanding of mental health. In contrast, *Winnie the Pooh* presents mental health issues in a more child-friendly way, using its lovable characters to gently explore topics like anxiety, depression, and the need for support from friends. The story's focus on friendship and understanding provides a more compassionate view of mental health. By looking at these works together, the paper examines how attitudes toward mental health have changed over time. It shows how literature reflects society's evolving views on mental health, helping to understand both the past and present cultural perspectives.

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English literature, mental health, psychology, society, social evolution, modernization

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The increasing demand for health and fitness applications has driven the development of AI- powered systems for food recognition and calorie management. This project utilizes Convolutional Neural Networks (CNN) and Artificial Intelligence (AI) to create a robust food image detection and calorie calculation platform. The system allows users to upload images of food, which are processed using a CNN model trained to recognize a wide variety of food items. Once the food is identified, users can input additional details such as portion size, ingredients, drinks, or preparation method to enhance the accuracy of the calorie estimation. The core functionality of the system revolves around accurate food recognition through CNNs, which are well-suited for image classification tasks. The network is trained on a large dataset of labeled food images to classify the food items and estimate their nutritional content. Based on the identified food, the system calculates the total calorie count using a deep learning model integrated with a nutritional database. In addition to calorie calculation, the system provides personalized exercise recommendations based on the user's calorie intake. By leveraging AI algorithms, the platform suggests various types of exercises (e.g., running, cycling, yoga) and the duration needed to burn the calories consumed, ensuring that users can make informed decisions about their physical activity to maintain a healthy lifestyle. The system can access this information via a Google Gemini API or the pre-trained LLAMA model from Hugging Face for more complex, real-time conversational interactions. This platform not only provides accurate food detection and calorie tracking but also empowers users to make healthier choices by offering actionable insights for maintaining balance between calorie intake and expenditure. The integration of AI technologies ensures a seamless, interactive, and personalized experience for the end-users.

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 Keywords

Mask R-CNN, ROI (Region of Interest), IOU (Intersection Over Union), and Resnet 50

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The paper focus on student's engagement. Employee engagement is the level of enthusiasm, responsibility, and energy they bring to their jobs. To understand how students can be motivated to learning is the main agenda of the study. When they are young, students face a lot of distractions, making it difficult for them to comprehend why they should study. The primary and secondary data is used in preparing the paper. Google forms are used to collect data. 55 convenient samples are used in the paper. MBA student from Mysore are taken. to understand what drives students to learn. Percentage analysis is used to analyze the data. Good friends, Daily learning , extra curricular activities, Positive environment, effective teaching, PPT and interactive method are factors that encourage students to keep engaged learning.

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 Keywords

Good friends, Student engagement, Extra curricular activities, Positive environment and effective teaching.

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Image Super-Resolution (ISR) is a critical problem in computer vision aimed at reconstructing high resolution (HR) images from degraded low-resolution (LR) counterparts. In this paper, we present a deeplearning-based approach leveraging a Convolutional Neural Network (CNN) architecture known as Super Resolution Convolutional Neural Network (SRCNN) to enhance image quality. The SRCNN model,composed of three convolutional layers, is trained on a large-scale dataset with pre-trained weights to improve the perceptual quality of LR images. The model achieves image enhancement by performing feature extraction, non-linear mapping, and reconstruction, primarily focusing on the Y (Luminance) channel of YCrCb color space to retain color fidelity. We evaluate the performance of the SRCNN model using standard metrics such as Peak Signal-to-Noise Ratio (PSNR), Structural Similarity Index (SSIM), and Mean Squared Error (MSE). Additionally, we compare the performance of images before and after enhancement using bar graphs for a comprehensive analysis.

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 Keywords

Image Super-Resolution, Convolutional Neural Network, SRCNN, PSNR, SSIM, Deep Learning.

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Visha (Poison) is a substance that causes vitiation of seven dhatus on ingestion and can also leads to death. Synthetic toxins, pharmaceutical medications, etc are few of the toxins that can enter the body and turning into visha if they aren't completely cleared out of the body. In Ayurvedic texts, it is called Dushivisha (cumulative toxin). Cytotoxicity is an undesired response to drug delivery in which the drug or an active metabolite causes significant cell damage. Chemotherapy, a cancer treatment in which antineoplastic cytotoxic medications accumulate in the body rather than being completely removed, causes toxicity with signs and symptoms comparable to Dushivisha.

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Dushivisha, cumulative toxicity, chemotherapy toxicity, latent poison.

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Perumal Murugan's One Part Woman depicts the lives of a childless couple, exposing the societal stigmas and cultural responsibilities associated with infertility. This study investigates how the novel illustrates the emotional, psychological, and social problems of infertile persons in rural India, underlining how societal expectations, cultural standards, and patriarchal ideals contribute to marginalisation.

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 Keywords

Infertility, Societal Stigmas, Cultural burden, Patriarchy.

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Agriculture is a essential region that faces demanding situations consisting of unpredictable climate situations, soil degradation, and inefficient useful resource control. The Crop and Soil control device is a web-primarily based application designed to assist farmers by means of integrating artificial Intelligence (AI) and gadget getting to know (M L) for precision farming. Th is gadget presents crop yield p rediction, fertilizer pointers, and soil health evaluation to assist farmers make records-pushed selections and imp rove productivity.

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 Keywords

Agriculture portal, AI-based crop predict ion, Machine

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This project presents the development of an innovative voice-activated desktop system aimed at redefining user interaction with computers. By utilizing cutting-edge voice recognition technologies, the system enables users to control desktop functionalities through intuitive natural language commands. The application is designed to execute tasks such as file operations, application navigation, and online searches, promoting a seamless and hands-free computing experience. Special emphasis is placed on accuracy, user accessibility, and real-time responsiveness. This approach not only enhances productivity but also caters to the needs of individuals with physical disabilities, offering an inclusive solution for modern desktop environments.

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Voice Activated Desktop

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The liver is an important organ for metabolism and removing harmful substances from the body. However, liver injury and dysfunction are major issues for healthcare, the pharmaceutical industry, and regulatory agencies. The liver can be harmed by various toxic substances, including certain antibiotics, chemotherapy drugs, environmental toxins like carbon tetrachloride and thioacetamide, excessive alcohol, and microbial infections. Current treatments often involve synthetic drugs that may worsen liver damage. Therefore, herbal medicines are gaining interest as potential alternatives for liver disease treatment. These remedies have been used for centuries, and this review aims to provide an overview of effective plant-based phytochemicals tested in liver damage models. The goal is to identify natural compounds that can protect and promote liver health.

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 Keywords

Hepatoprotective, survey, Marketed product, Kalmegh, Milk Thistle, Jewel Orchid, Neem.

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 Abstract

This study is mainly focused on how civilizational conflict develops through multiple layers consisting of language intersecting with identity formation, ethnic divisions, and religious beliefs joined by post-colonial practices. This study highlights how these elements, which tend to stay isolated from each other, share deep connections because powerful entities historically worked to create strict civilizational structures and social hierarchies. The chapter studies how modern conflicts emerged from colonial disruptions of indigenous cultures and foreign governance systems that were enforced upon native populations. This study also challenges the dominance of Eurocentric paradigms in international relations and critiques the tendency to universalize Western experiences as normative. It instead calls for a re-evaluation of how civilizational narratives are constructed, maintained, and contested. Through this framework, the chapter establishes that civilizational conflict is not a clash of fixed identities but a dynamic struggle over meaning, memory, and power in a world still shaped by colonial histories.

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 Keywords

Civilisational conflict, Identity, Religion, Colonialism, Ethnicity and Language

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Real time object detection and navigation for blind people

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The field of human-computer interaction has seen significant advancements with the development of virtual mouse and gesture recognition systems. These technologies aim to create intuitive and seamless ways for users to interact with digital environments, eliminating the need for traditional input devices like keyboards and physical mice. Gesture recognition enables users to control applications through natural hand movements, enhancing accessibility and efficiency. The evolution of these systems has been driven by advancements in artificial intelligence, machine learning, and computer vision, enabling real-time tracking and interpretation of human gestures with remarkable accuracy. The development of virtual mouse technology and gesture recognition has undergone a transformative journey, incorporating innovations in sensor technologies, deep learning models, and pattern recognition algorithms. Early implementations relied on simple motion detection, but modern approaches utilize sophisticated techniques such as convolutional neural networks and 3D depth sensing for precise gesture mapping. These advancements have broadened applications in fields such as gaming, augmented reality, assistive technologies, and medical rehabilitation. As research continues, the integration of these technologies into everyday digital experiences is expected to further enhance user interaction, making computing more immersive and accessible.

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 Keywords

Open-cv, Mediapipe, Pyautogui, Numpy, python, Virtual mouse

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 Abstract

Various technology used in the past some years and this is rise in the field of technology, and one of the technique like machine learning is widely used in various fields. Now it has various applications in the health industry. It works as a helping hand for the field of health industry. By the help of various learning algorithms, we can make various models for predicting the results through the large amount of dataset present in medical field. This comprises of efficient used in predicting disease through symptoms. As, the health industry has a very huge amount of data for various fields so, we want to make a system where we can use various other applications of machine learning on health industry. This all had been done to make the best medical decisions and also for rise in the accuracy. As early accurate analysis predict disease through some symptoms and helps in the patient care and the human services. These all challenges can be easier by the help of various tools, algorithms and framework provided by the prediction system

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 Keywords

AI chatbot, healthcare, natural language processing, rural healthcare, appointment booking, IOT enabled

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