Spicer Adventist University

Access to legal services is a major challenge for many common people in India due to high lawyer fees, lack of legal awareness, and complex legal procedures. Many individuals do not understand their rights or the legal steps required to resolve their issues. To address this problem, this paper presents AI Lawyer – Smart Legal Support for Common People. The proposed system uses Artificial Intelligence to provide basic legal guidance through a digital platform. The system allows users to ask legal questions related to common issues such as property disputes, cybercrime, consumer rights, family law, and basic legal procedures. The AI-based system analyzes the user query and provides simplified legal information and suggested steps. The system also includes features such as legal document guidance, case information, and awareness about government laws and rights. By using AI technology, the platform makes legal knowledge more accessible, affordable, and understandable for common people. This solution helps bridge the gap between legal professionals and citizens while promoting legal awareness and digital justice support.

The Smart School Bell with Timetable Display is an automated system designed to modernize the traditional school bell mechanism and improve the overall management of academic schedules. In most educational institutions, bell systems are still operated manually or use simple timers that do not provide any visual information about the ongoing or upcoming periods. This often leads to human errors, delayed bells, confusion during schedule changes, and increased workload for administrative staff. The proposed system aims to overcome these limitations by introducing an intelligent, programmable, and reliable bell system integrated with a real-time timetable display. One of the major advantages of the Smart School Bell with Timetable Display is the elimination of manual intervention. This reduces the possibility of missed bells and ensures uniformity and punctuality across all classes. It also helps administrators save time and effort that would otherwise be spent managing bell schedules manually. Moreover, the display provides clear and continuous information to students and teachers, improving communication and time awareness within the campus The system can be further extended to include advanced features such as holiday scheduling, emergency alert messages, special announcements, and wireless timetable updates. With minor enhancements, it can also be integrated into a larger smart campus or Internet of Things based environment for centralized monitoring and control.

Artificial Intelligence has recently become synonymous with any technology, be it in any field; the paradigm shift is being observed in every sector, and the ongoing discourse is being dominated by this talk. With its growing influence on individuals and, as a whole, on society, it is imperative to reflect on its outcomes. The growing integration of artificial intelligence (AI) in the education sector has been transforming the traditional learning and socialization process, and it is also presenting concerns. This paper dives into a primary understanding of AI technology, specifically its influence on the development of young students in terms of social interactions and cultural dynamics. This paper studied the AI’s influence on socialization and cultural dynamics through the lens of Vygotsky’s sociocultural theory and Bandura’s social learning theory. While the analysis reveals that AI does enhance personal learning and global collaborations, there is a risk of a reduction in face-to-face interactions, which could weaken skills such as empathy and nonverbal communication. Further, the finding also suggests that AI facilitates cross-cultural exposure, but there is a possible risk of cultural homogenization, which could marginalize the homegrown traditions. Data privacy, algorithmic bias, and social isolation are the other areas of concern that would further complicate AI’s role in education.

The fastest development of AI is a great challenge for copyright law, especially when copyrighted material is used to train AI models. Study focuses on the background of AI and copyright act. How does copyright law help in the digital era? Here study covered how AI models learn. Copyright law framework and principal, fair use and fair dealing, jurisdictional comparison. Legal analysis of AI training and copyright infringement. Ethical and policy consideration, Policy recommendation and proposed solution studied here. Copyright Act 1957 is the primary source of information while studying. Different cases and references used to examine the AI use. It’s difficult to identify the work generated by AI and original in some cases because AI generates accurate information like original if original dataset used for training, in that case need to focus on authors ownership and rights. The study ends with the conclusion that there are no confirmed laws against the use of copyrighted material in training the AI model but courts are working on the same and there are provisions available. In India till date laws are not ready but we are taking the reference of foreign law as per the case. Keywords: AI, Content, Copyright, Policy, Laws

This study investigates the implementation of artificial intelligence (AI)-driven pattern recognition methodologies within digital education frameworks, with a specific emphasis on machine learning (ML) techniques for educational data mining (EDM). We meticulously analyze diverse AI approaches, including neural networks, deep learning, and adaptive learning systems, to discern student behavioral trends and thereby enhance pedagogical effectiveness. Through a rigorous systematic review of 335 pertinent research articles and the practical application of multiple machine learning algorithms, this research establishes that AI-powered systems can achieve a classification accuracy of <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$70-75 \%$</tex> in predicting student academic performance. Concurrently, the global market for AI in education is projected to expand significantly, reaching an estimated USD 32.27 billion by 2030. Our findings delineate four distinct behavioral archetypes prevalent in digital learning environments: Browse, social interaction, information seeking, and environment configuration. Furthermore, the study reveals a substantial adoption rate among university instructors, with 58% currently integrating generative AI into their routine pedagogical practices. This research offers innovative methodologies for pattern recognition in educational contexts and provides robust frameworks for the deployment of AI-centric personalized learning systems.

Objective: The respiratory systems of adults and children differ anatomically and physiologically, which results in varying respiratory evaluation and treatment parameter values. An accessible clinical method for evaluating lung function at the bedside is the Chest Expansion (CE) examination. However, there isn't enough data in the literature to support the use of this assessment technique in the pediatric population. In order to ascertain the intrarater and interrater reliability of chest expansion in children aged 5 to 12, the current study was conducted. Method: A Cross-sectional Observational study was done on 385 students between 5 to 12 years of age group&amp; normal BMI were selected by convenient sampling method. Two independent investigators, both blinded, assessed the Chest expansion at 2nd, 4th, 6th intercostal spaces (ICS) using a non-elastic measuring tape with child in sitting position. An average of three such readings at each level were taken into consideration. These readings were taken at 3 timeframes. To assess interrater reliability CE was checked on the same day at 20-minute interval, by 2 independent assessors, and CE assessment was repeated after a weeks interval by one assessor to evaluate the intrarater reliability. The mean value of 3 repetitions was used to calculate the intraclass correlation coefficient ICC and Cronbach’s Alpha by using the SPSS Software. Result: The Cronbach’s Alpha for both Intrarater and Interrater reliability was &gt;0.8 for 2nd, 4th and 6th ICS. Conclusion: Chest Expansion assessment in Healthy Children Between 5-12 years of Age Group has is an Excellent Intrarater and Interrater Reliability

The immune system ailment rheumatoid joint pain (RA) principally influences the joints and is persistent (durable). At the point when the body's safe reaction, which frequently supports shielding the body against ailment and contamination, focuses on its own tissues, RA results. Joint uneasiness, edema, strength, and decrease in capability are side effects of the condition. There is a lengthy tradition of using herbal remedies and their formulations to cure illnesses in people. It has long been believed that herbal extracts can provide novel, practical medications. Approximately 62% of pharmaceuticals that are sold commercially have natural product origins, according to Cragg's research. Remorsefully, flow clinical information for the most part tends to the illness' side effects that is, joint agony and irritation and there is still no demonstrated successful prescription to treat rheumatoid joint inflammation. The aggravation and irritation in the joints can be diminished by involving spices and plants in various ways. Anti-rheumatoid arthritis properties have been demonstrated for a variety of therapeutic herbs. Subsequently, rheumatoid joint inflammation is treated with plants and plant items that offer striking advantages. The restorative plants with hostile to rheumatoid joint pain activity are the primary subject of this audit.

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