Volume 14 | Issue 5 |

 Abstract

This paper presents the design and development of an intelligent AI-powered travel planning system titled Dynamic Affective Geo-Recommendation Engine for Transformative Mile-Based Engagement. The proposed platform functions as a web-based conversational assistant that enables users to plan trips through Natural Language Processing (NLP) and machine learning techniques. Unlike conventional travel portals that demand manual navigation across fragmented resources, the system interprets user queries in plain conversational language, extracts contextual parameters such as budget, travel duration, and personal interests, and delivers organized, personalized destination recommendations. The recommendation engine employs a trained intent-classification model built on the NLTK toolkit and a Multi-Layer Perceptron (MLP) neural network. The chatbot module communicates in real time, offering relevant destination insights and structured travel guidance. The system architecture is modular and scalable, consisting of a user interface layer, an NLP processing engine, a machine learning classification module, a structured intent knowledge base, and a map visualization component for location-based output. Evaluation results demonstrated consistent accuracy in intent recognition and recommendation relevance across varied user input types. The system effectively reduces decision-making complexity, enhances user interaction quality, and supports efficient trip planning through an intelligent, user-centric interface.

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 Keywords

AI Travel Planner, Natural Language Processing, Chatbot, Destination Recommendation, Itinerary Planning, Machine Learning, NLTK, Intent Recognition, Personalized Recommendations.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Access to justice is a basic right as per Article 39A of the Constitution of India, whereby the state is committed to providing equal justice and free legal assistance. Yet, the Indian judicial framework has been infested with delays, arrears, and procedural complexity for years, rendering most individuals inaccessible to justice. As of 2024, more than 50 million cases are pending across Indian courts, with some remaining on the shelf for decades. This crisis calls for a revolution of Alternative Dispute Resolution (ADR) mechanism, which provides quicker, cheaper, and amicable solutions to disputes' has mechanisms like arbitration, mediation, conciliation, and negotiation, which operate outside the conventional court litigation. They are becoming more and more observed internationally for their applications to clear congestion from courts and make justice more accessible. Indian laws like the Arbitration and Conciliation Act, 1996, and the Legal Services Authorities Act, 1987, have provided legal acceptance to ADR. ADR has not been utilized to its potential, though, by way of unawareness, institutional capacity, and problems of enforcement. This research paper discusses the current state of ADR in India, determines the defining challenges, and proposes reforms to strengthen ADR mechanisms for improved access to justice. The study relies on a mix methodology wherein legal provisions, judicial precedents, and empirical studies are examined to assess the effectiveness of ADR.

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 Keywords

Alternative Dispute Resolution (ADR), Access to Justice, Arbitration and Mediation, Judicial Reforms, Legal Framework in India

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 Abstract

Tuberculosis (TB) remains a major communicable disease burden in India, requiring efficient case notification, treatment monitoring, follow-up, and documentation. The Government of India has introduced the Nikshay App as a digital platform under the National Tuberculosis Elimination Programme to strengthen TB case management. Nursing students, as future healthcare providers, play a crucial role in utilizing such digital tools; however, inadequate knowledge regarding the application may hinder effective TB control. This study aimed to assess the effectiveness of a structured teaching programme on knowledge regarding the role of the Nikshay App in TB case management among nursing students in selected nursing institutes of Hyderabad. A quantitative research approach was adopted with a sample size of 102, accounting for a 5% attrition rate, and participants were selected using purposive sampling. Data were collected using a self-structured questionnaire and analyzed using descriptive and inferential statistics. The final study included 100 participants. Pre-test findings revealed that 61% of students had inadequate knowledge, 37% had moderate knowledge, and only 2% had adequate knowledge. Following the structured teaching programme, there was a marked improvement, with only 8% demonstrating inadequate knowledge, 71% having moderate knowledge, and 21% achieving adequate knowledge. The mean post-test knowledge score (19.97) was significantly higher than the pre-test score (12.87) and paired t-test analysis confirmed a statistically significant difference, indicating the effectiveness of the intervention. Chi-square analysis showed significant associations between knowledge and variables such as age, gender, prior curriculum exposure to the Nikshay App, and participation in related training, while no significant association was found with year of study, prior awareness, or clinical postings in TB-related settings. The study concludes that structured teaching programmes are effective in enhancing knowledge and competency of nursing students in utilizing digital health tools for TB case management. Keywords: Tuberculosis, Nikshay App, Nursing students

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 Keywords

Tuberculosis, NIKSHAY App, Nursing students, NTEP, DOTS

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This study examines the financial behavior of Gen Z investors with special focus on Hyderabad district, aiming to understand the factors influencing their investment decisions, risk preferences, and financial goals. The research adopts a quantitative approach and is based on primary data collected through a structured Likert-scale questionnaire administered to 90 Gen Z respondents who are registered members of Angel One. A convenience sampling technique was employed, and statistical tools such as percentage analysis, regression analysis, and factor analysis were used to interpret the data. The findings reveal that the majority of respondents are mid-Gen Z professionals aged 24-26 with moderate income levels and stable salaried employment as their primary investment source. Despite being digitally active, Gen Z investors show a stronger preference for safer investment avenues such as Fixed Deposits and Recurring Deposits over high-risk assets like cryptocurrencies and NFTs, indicating a moderate risk appetite. Learning and experimentation emerged as the most influential factor driving investment decisions, followed by long-term wealth creation and retirement planning. The study also highlights the significant role of peer reviews, financial advisors, and technology-enabled investment tools in shaping informed decision-making. Overall, the research concludes that Gen Z investors in Hyderabad are goal-oriented, knowledge-driven, and technologically empowered, with a strong focus on long-term financial security rather than short-term speculative gains.

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Financial Behavior, Gen Z Investors, Investment Decisions, Risk Preferences, Financial Literacy, Long-Term Wealth Creation.

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Louise Erdrich is widely recognized as a major contemporary Native American writer whose fiction explores identity, justice, and the socio political realities of Indigenous communities. The Round House offers a powerful examination of justice within a reservation setting, where legal authority is fragmented and often ineffective. This paper analyzes the representation of justice through visual, symbolic, and structural elements in the novel. By focusing on the journey of Joe Coutts, a young boy seeking justice for his mother, the study reveals how justice operates not as a linear legal outcome but as a cyclical and culturally embedded process. The analysis emphasizes the importance of space, particularly the round house, as a symbol of continuity and moral balance. Furthermore, the paper explores themes of trauma, legal failure, and community resilience to demonstrate how Erdrich critiques institutional systems while highlighting Indigenous perspectives on justice and healing.

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 Keywords

identity, justie, symbol, trauma

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Creative Commons Attribution 4.0 and The Open Definition

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Rapid urbanization in India, particularly across emerging Tier-2 cities, has intensified transportation and infrastructure pressures. Increasing population density and the growing number of private vehicles have contributed to challenges such as road congestion, environmental degradation, poor public transport integration, and unplanned land consumption. In response to these concerns, Transit-Oriented Development (TOD) is being recognized as an effective urban planning strategy that supports sustainable and integrated city growth through development concentrated around mass transit corridors. This study explores the significance of Transit-Oriented Development in enhancing urban mobility in Tier-2 Indian cities. It analyses the impact of TOD concepts including compact urban form, mixed-use land patterns, pedestrian-friendly environments, and improved accessibility to public transportation systems. The study focuses on how these measures can minimize reliance on personal vehicles while strengthening the efficiency and sustainability of urban transport networks. The research methodology is based on secondary sources such as planning policies, government publications, academic studies, metro rail documentation, and urban development reports. The analysis reveals that TOD has considerable potential to increase public transport usage, promote non-motorized transportation such as walking and cycling, decrease traffic-related problems, and encourage environmentally responsible urban expansion. However, several barriers continue to hinder its effective implementation, including limited inter-agency coordination, insufficient pedestrian and cycling infrastructure, financial constraints, and challenges related to land administration and regulation. The paper concludes that coordinated integration between transportation systems and land use planning is necessary for the successful adoption of Transit-Oriented Development in Indian cities.

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Transit-Oriented Development, Urban Mobility, Sustainable Planning, Public Transport, Tier-2 Cities, Urban Development.

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This research explores the adaptive reuse of a ruined Portuguese-era church located in the campus of Our Lady of Fatima Convent School, Moti Daman. The project proposes transforming the structure into a children's learning and living centre, combining a heritage library with residential facilities for orphan children. The study focuses on interior design strategies that preserve historical identity while integrating modern functionality. Through literature study, case studies, and site analysis, the research demonstrates how adaptive reuse can serve both heritage conservation and social welfare.

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 Keywords

Adaptive reuse, heritage conservation, children's centre, ruined church, interior design, Daman, Portuguese architecture.

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Creative Commons Attribution 4.0 and The Open Definition

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Career guidance is an integral yet underrepresented part of education that helps students decide on what course they want to pursue post-secondary. In India, career guidance for students is either not available or available to only some extent because students do not have structured guidance. Moreover, the traditional career guidance is generic, sporadic, and does not cater to personal preferences of the students. This paper proposes the design and development of an Artificial Intelligence-powered Career Guidance Platform known as AI Guruji. This platform uses various features like AI, psychometric assessment, and conversation-based recommendation engines to offer personalized career recommendations to the users based on their profile and preferences. Some of the technical aspects of this platform include React18 as a frontend, Nodejs Backend, Supabase Database, and Gemini AI-powered recommendation engine. The users go through multidimensional psychometric assessments of interest, aptitude, and unconventional careers along with chatbot-powered career guidance. The user validation test revealed that most of the time students receive no career guidance at school. Moreover, all the respondents expressed an immense desire for AI Career Guidance.

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 Keywords

AI Career Guidance, Psychometric Assessment, Gemini API, NLP, Personalized Recommendation, Conversational Chatbot

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Creative Commons Attribution 4.0 and The Open Definition

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ABSTRACT Background: The COVID-19 pandemic caused significant psychological distress among healthcare workers. Psychological First Aid (PFA) is an early intervention that helps reduce distress and improve coping abilities. Methods: A pre-experimental one-group pre-test and post-test design was conducted among 40 staff nurses on COVID-19 duty in selected hospitals in Bengaluru. Participants were selected using purposive sampling. A structured knowledge questionnaire was used for data collection. After the pre-test, a Structured Teaching Programme (STP) was administered, and a post-test was conducted after 7 days.Results: The mean pre-test knowledge score was 12.3%, which increased to 22.34% in the post-test, showing an improvement of 10.04%. The difference was statistically significant at the 5% level. No significant association was found between pre-test knowledge and socio-demographic variables (P > 0.05). Conclusion: The study revealed inadequate knowledge among staff nurses, and STP was effective in improving knowledge regarding PFA.

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Key words:PFA- psychological first aid, STP-structured teaching programme

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

ABSTRACT Background: Covid-19 is really an infectious disease caused by a recently discovered corona virus. The majority of Covid-19 virus-infected individuals will develop mild to severe respiratory disease and recover without the need for special care. The elderly and individuals who have underlying medical diseases such cancer, diabetes, lung disease, and cardiovascular disease are more prone to have serious illnesses. COVID-19 affects different people in different ways. Methods: In this study quantitative approach with pre-experimental research design was used. The setting of the study was selected rural area of Valsad district. Sample size was 30. In this study non-probability sampling technique convenient sampling technique was done. Structured questionnaire was used. Data analysis was done mainly using descriptive statistics paired t -test for hypothetical testing and chi square test was done for association. Result: The present study evaluates the knowledge of post COVID patients regarding prevention of post COVID complications and found that 13.33% of the samples had poor knowledge 80% of people had average knowledge and 6.67% of people had good knowledge in the pre-test. The overall mean percentage of knowledge in pre-test was 9.36 with the standard deviation of 3.52. In the post test the overall mean percentage of knowledge in post-test was 14.5 with the standard deviation of 3.98. Conclusion: Analysis data shows that the post test knowledge score has significantly higher than the pre test knowledge score at p < 0.05 level of significance i.e. mean difference is 5.19. There was a significant improvement in knowledge of post COVID patients. The study revealed that structured teaching programme was observed to be very effective method to improving knowledge on prevention of post COVID complications.

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 Keywords

Knowledge, Prevention, Post, Covid, Complication

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Creative Commons Attribution 4.0 and The Open Definition