Volume 13 | Issue 4

 Abstract

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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 Keywords

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

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

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The Employee Performance Appraisal System in a BPO (Business Process Outsourcing) environment is designed to evaluate and enhance employee productivity, identify training needs, and align individual goals with organizational objectives. In the high-paced and target-driven BPO sector, timely and accurate performance evaluation is critical for maintaining service quality and employee satisfaction. This system automates the appraisal process using key performance indicators (KPIs) such as attendance, quality of work, target achievement, customer feedback, and teamwork. It provides a transparent and structured framework for performance reviews, incorporating self-assessment, peer reviews, and managerial evaluations. By leveraging data analytics and user-friendly dashboards, the system ensures fair assessment, reduces manual bias, and helps in identifying top performers and underperformers. The overall goal is to foster a performance-driven culture, support career development, and improve organizational efficiency.

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project disclose the present appraisal system and future expectations in AI based system

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Identity endorsements by Celebrities act as a fundamental factor which determines how consumers view brands and establish trust as well as brand devotion. This research analyzes trustworthiness as well as brand endorsement effects through an evaluation of 150 subject participants. A celebrity controversy has the power to damage brand image and visibility and steer customers toward different choices about the brand's quality and cost. Future research must analyze if influencer sponsorships create more effective brand and attractiveness endorsements than traditional celebrity endorsements do. Trust from consumers emerges as a factor but its authority depends on how much fame and expertise the celebrity possesses. Product research should analyze monetary benefits of expanded knowledge about endorsement approaches even though brand recognition benefits from endorsements.

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Celebrity Endorsement, Brand Trust, Consumer Behavior, Advertising Strategy, Social Media Marketing, Brand Awareness

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 Abstract

Janapada Loka mattu Kannada Sanskrrti

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Janapada Loka mattu Kannada Sanskrrti

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The main focus of the research is to study strength characteristics of pervious concrete and it's permeability. Pervious concrete's high porosity often leads to a honeycomb structure, which can compromise its strength compared to conventional concrete. Pervious concrete is a special kind of concrete which allows water to flow through it because of its high porosity and therefore high permeability. Therefore the pervious concrete can be used as solutions to many problems such as drainage problems, ground water table recharge, sustainable development. In pervious no fine aggregates are used or sometimes fine aggregates are used to very little extent. There are various application of pervious concrete. It can be used in basement drainage, pedestrian walkways, local streets, low traffic highway, parking lots.

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Pervious Concrete, Porous Concrete, Permeability, No-fine Concrete.

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Herbal medicine, being derived from plants, has been practiced for centuries by various cultures due to its therapeutic use. Natural remedies are now becoming popular in modern society since they are thought to be safe, accessible, and even potent in healing many health conditions.

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: Natural Healing, Immunity Boost, Anti-inflammatory, Digestive Health, Skin Care.

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 Abstract

i want to survey people and ask them about variety topics

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electric two-wheeler automobiles, consumer perception

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The Indian Sign Language (ISL) is essential for communication among the deaf and hard-of-hearing community. However, the lack of widespread ISL understanding creates a communication gap. This research focuses on developing an ISL recognition system using Long Short-Term Memory (LSTM) networks and OpenCV to process video inputs, extract features, and recognize dynamic hand gestures in real-time. The system employs pose estimation techniques to detect hand movements and classifies them using LSTM-based deep learning models. The proposed approach achieves high accuracy, ensuring a robust and scalable solution for real-time ISL interpretation.

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 Keywords

Indian Sign Language (ISL), LSTM, OpenCV, Gesture Recognition, Deep Learning, Real-Time Processing, MediaPipe, Neural Networks, Computer Vision, Assistive Technology.

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Creative Commons Attribution 4.0 and The Open Definition