Volume 13 | Issue 4 |

 Abstract

Effective home financial management is necessary to achieve long-term security and financial stability. Among the crucial aspects of household financial management that are investigated in this study are budgeting, saving, investing, debt management, and financial planning. It highlights how important it is to set financial goals, keep an eye on income and expenses, and make wise financial decisions in order to optimize resources. The study also examines how asset accumulation and reduced financial stress are caused by financial literacy and disciplined spending habits. By adopting sound financial practices, households can increase their economic resilience and achieve financial independence.

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 Keywords

Household Budgeting, Savings and Investments, Income and Expenditure, Debt Management, Financial Planning, Risk Management, Emergency Fund, Inflation Impact

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Millions of individuals worldwide experience visual impairments that significantly impact their daily lives. This project introduces an AI-Powered Assistive System aimed at addressing these challenges by using cutting-edge technologies. By incorporating real-time object detection, face recognition, and text-to-speech capabilities, the system provides intuitive auditory feedback to help visually impaired users navigate their surroundings more effectively. With advanced integration of machine learning, computer vision, and a user-centric voice interface, the solution fosters independence and enhances the quality of life for users. This initiative strives to redefine assistive technology, promoting accessibility and empowerment.

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 Keywords

AI-powered assistive system, Visual impairment, Object detection, Face recognition, Text-to-speech, Machine learning, Computer vision, Accessibility technology, Real-time feedback, Voice-controlled interface, Optical character recognition (OCR), Automatic speech recognition (ASR), Text reader, Currency detection, Weather updates, User independence, Assistive technology,Deep learning

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The Kalaignar Magalir Urimai Scheme is a transformative initiative aimed at empowering women and promoting economic independence among women in Tamil Nadu, particularly those from economically disadvantaged backgrounds. By providing a monthly financial assistance of INR1,000 to eligible women heads of households, this scheme addresses critical socio-economic challenges and enhances women's roles in their families and communities. The financial support enables women to contribute to household expenses, invest in entrepreneurial ventures, and pursue skill development, thereby fostering self-reliance and financial stability. It also strengthens their decision-making power within families, allowing them to prioritize education, healthcare, and overall well-being. Beyond individual benefits, the scheme challenges deep-rooted gender disparities by recognizing women's contributions and promoting inclusivity. It fosters community and economic development as empowered women actively participate in local economies and societal progress. With its scalable and impactful design, the scheme holds promise for advancing gender equality and reducing economic vulnerability. However, its success hinges on effective implementation, widespread awareness, and addressing challenges like the timely identification of beneficiaries. Ultimately, the Kalaignar Magalir Urimai Scheme serves as a beacon of hope, helping women lead lives of dignity, independence, and confidence while driving societal change toward a more inclusive future.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Women empowerment, Economic independence, Kalaignar Magalir Urimai Scheme, Financial assistance, Gender equality.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

t--The paper presents a healthcare assistance system using NLP and Name entity recognition, enabling human-system interaction to resolve basic health related queries before consult- ing a doctor. The main objective is to analyze users symptoms and provide medical suggestions to reduce the time and cost involved in healthcare consultation. This system communicates with users using NLP, allowing for interaction through natural language inputs. It processes the input, extracts relevant keywords, and provides appropriate responses to users queries. Incorporating machine learning techniques, the system leverages an ADR database to offer solutions regarding users' healthcare concerns. Additionally, users can create profiles to specify their symptoms, receive doctor suggestions, and set dosage reminders. The system can assist users in recognizing potential diseases based on pro- vided symptoms. The system uses Neural networks, specifically deep learning models such as CNN or RNNs, are integrated into the text classification and decision-making process. These networks are trained on vast medical datasets, enabling the system to understand complex medical language and detect patterns in user input. Through these neural networks, the system can accurately interpret symptoms, match them to potential diseases, and suggest appropriate next steps.

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 Keywords

Healthcare assistance system, NLP (Natural Language Processing), Name Entity Recognition (NER), Human- system interaction, Health-related queries, Medical suggestions, Reduce time and cost, Consultation.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The incorporation of the Best Interest Theory in health law serves as a foundational principle for decision-making involving individuals who lack capacity, such as minors and incapacitated adults. This paper explores the ethical and legal dimensions of the theory, examining its application in healthcare settings, including end-of-life care, pediatric treatment, and public health interventions. Through a doctrinal and qualitative methodology, the study analyzes statutory frameworks like the Mental Capacity Act 2005 (UK) and the Patient Self-Determination Act 1991 (US), alongside landmark judicial pronouncements. The research highlights the inherent subjectivity in defining "best interests," conflicts between autonomy and paternalism, and disputes among healthcare providers, families, and legal authorities. Recommendations include standardized guidelines, interdisciplinary ethics committees, and enhanced training for healthcare professionals to ensure equitable and compassionate decision-making. The paper underscores the need for a balanced approach that respects patient dignity while navigating complex ethical and legal challenges.

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 Keywords

Autonomy, Best Interest, Dignity, Informed Consent, Mental capacity, Paternalism, Substitute Decision-Makers, Utalitarianism

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The rise of AI systems raises concerns about privacy violations, data breaches, and unauthorized use of sensitive information. To address these concerns, the European Union (EU) enacted the Artificial Intelligence Act. On December 9, 2023, the EU entered into a provisional agreement to prohibit the use of AI in cases where it may harm citizens' rights. To establish an ethical framework for AI, it is important to explain the risks and opportunities associated with its design and use. The goal is to create an ecosystem that maximizes opportunities while minimizing risks. An ethical approach provides a dual advantage for AI developers and start-ups, allowing them to harness social value by taking advantage of new opportunities that society values. In India, artificial intelligence is still in its early stages due to the country's development status. This technology is ascribed to technical advancements in the 21st century, including the advent of social networking sites and global firms' investment in India began research and development in the field of artificial intelligence. As we see this emerging amazing technology that operates on the human thought process. Today, we may observe the global application of artificial intelligence in all sectors of the economy. It has not only reduced the strain, has also boosted workplace efficiency using smart technology. So, this research paper will focus on the laws which protects the data and will compare this study with other country data protection laws. The article will explore the challenges faced by businesses and policymakers in balancing innovation with privacy rights, as well as the opportunities for creating a robust data protection regime that fosters trust in AI applications.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Key Words: Data Protection, Artificial Intelligence, ethics, policies, laws, EU, business.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This study conducts a comparative analysis of investor satisfaction with mutual funds and stock market returns, aiming to understand investor preferences, risk tolerance, and return expectations. By evaluating financial performance, risk factors, and market trends, the research identifies key determinants influencing investor decisions. Data is collected through surveys and financial reports, analysed using statistical methods to derive insights into satisfaction levels and investment behaviour. The findings offer valuable implications for financial advisors, policymakers, and investors in making informed investment choices.

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 Keywords

Financial Instrument, LIC Housing Finance, Finance, Economic Activities, Business Organization, Capital Management, Financial Performance Analysis, Profitability, Financial Soundness

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 Abstract

The first chapter as an outstanding creative writer, critic, editor and teach, U,R Anantha murthy has had a seminal impact on kannada literature and culture in the last few icates and is one of the most charismatic Indian litereracy personilities living today. This second chapter denotes Samskra presents before us a community of persons who are interlocked with each other through various complex relationship caste, economy, gender societial ,hierarchy ,religious question and taboos ferment a complex web of relationship ,against backdrop of which the story liners been schetched

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 Keywords

, Community, Caste, Economy, Gender and Untouchability

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The advancement of digital technology has transformed the way books are purchased and sold. This paper presents the development of an Online Book Store Management System using XML, Java, Android Application Development, and MySQL to facilitate seamless book transactions. The system allows users to browse, search, and purchase books online, while administrators can manage inventory, orders, and user details efficiently. The system is designed to provide a user-friendly interface, secure transactions, and real-time database management. This research explores the architecture, implementation, and potential applications of the system in enhancing the online book retail experience.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Online Book Store, Android Application, Java, MySQL, XML, E-Commerce.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Emotion recognition from text is a critical task in Natural Language Processing (NLP), with wideranging applications in sentiment analysis, mental health monitoring, and human-computer interaction. Its investigates the application of Bidirectional Encoder Representations from Transformers (BERT) for emotion recognition. BERT's ability to capture contextual dependencies and nuances in text, through its bidirectional transformer architecture, makes it ideal for this task. By fine-tuning pre-trained BERT models on an emotionlabeled dataset, we classify emotions such as happiness, sadness, anger, surprise, fear, and others. The model leverages BERT's pre-trained knowledge of language and its capacity to understand complex syntactic and semantic patterns. Experimental evaluations show that BERT achieves superior accuracy in detecting emotions compared to traditional machine learning models like SVM and logistic regression, due to its deep contextual embeddings. Furthermore, our approach improves generalization across varied emotional expressions, demonstrating BERT's robustness in emotion-aware NLP tasks. These results suggest that BERT-based models hold significant promise for enhancing the accuracy and effectiveness of emotion recognition systems. The main tool we have used in this project is Streamlit. With the appearance of Streamlit, we can create powerful web packages that leverage the power of NLP for emotion detection.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Sentiment Analysis, Probabilistic model, Streamlit, Natural Language Processing, Machine Learning, Bidirectional Encoder Representations from Transformers Algorithm, Feature Extraction, Deep Learning Architectures

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Creative Commons Attribution 4.0 and The Open Definition