AI-based early intervention for adolescent suicidal ideation by detecting anxiety and depression.
Depression is a mental illness that affects relationships. Early diagnosis is important for timely intervention and support. This article presents an approach to stress assessment using the power of artificial intelligence AI and multimedia. By integrating audio and video support into AI-based tools, we are revolutionizing the early depression detection process designed to increase user engagement and accessibility. We have introduced the best AI that not only provides appropriate questions but also adapts to user preferences for voice and video chat. This innovation encourages participation in psychological testing by recognizing the diversity of user needs and preferences. Through a rigorous process, we measure the impact of audio and video support on user engagement and overall device performance. Our studies show not only the positive results of multiple participation but also the positive effects of this approach in many aspects. We provide great results, including performance reviews, user recommendations, and in-depth reviews of performance tools. The findings highlight the importance of audio and video support in the early detection of depression, pointing to opportunities to improve user engagement and measurement accuracy. This article contributes to the use of health technology by providing new perspectives on early depression detection and user support. The combination of audio and video support promises to provide a more accessible and engaging approach to psychological assessment, opening new avenues for improving research and practice, mental health, and well-being. This summary, supplemented with audio and video, provides a brief overview of the project's focus, methods, key findings, and contribution to early childhood depression research. Depression is a mental illness that affects relationships.
Published by: Ritesh Tukaram Avachar, Karan Popat Gondal, Sakshi Dnyaneshwarsingh Jadhav, Harshawardhan Ravindra Jare, Shrishail Patil
Author: Ritesh Tukaram Avachar
Paper ID: V10I1-1249
Paper Status: published
Published: April 15, 2024
Social Entrepreneurship
Social entrepreneurship is a distinct form of entrepreneurship that addresses societal environmental issues. Despite challenges like limited resources and regulatory complexities, social entrepreneur remain committed to creating positive change. They employ strategies like such as problem- solving, collaboration community engagement, sustainability practices, advocacy and impact assessment. Female social entrepreneurs like Shiza Shahid, Rachel Brathen and Servane Mouzan have made significant contributions to societal progress and the empowerment of women globally.
Published by: Daksh Kapoor
Author: Daksh Kapoor
Paper ID: V10I1-1307
Paper Status: published
Published: April 13, 2024
The inception of “Group Theatre (GT) ” in India and Odisha
Presently, "Group Theatre (GT) " of various States represents the mainstream theatre in India. There is hardly any Professional-Commercial Theatre. It has its history of inception in India and other states.
Published by: Dr. Samitarani Mohanty
Author: Dr. Samitarani Mohanty
Paper ID: V10I1-1297
Paper Status: published
Published: April 13, 2024
Crime analysis in India using machine and deep learning techniques
Crime analysis is a critical aspect of law enforcement, aiding in the understanding, prediction, and prevention of criminal activities. In a vast and diverse country like India, with its complex socio-economic landscape, traditional methods of crime analysis often fall short in capturing the intricacies and patterns of criminal behavior. In recent years, machine learning (ML) and deep learning (DL) techniques have emerged as powerful tools to analyze crime data, offering the potential to uncover hidden patterns and trends that can enhance law enforcement strategies. This paper presents a comprehensive overview of crime analysis in India utilizing machine learning and deep learning methodologies. We begin by discussing the challenges inherent in traditional crime analysis methods, highlighting the need for more sophisticated approaches to address the complexities of crime dynamics in India. Subsequently, we delve into the theoretical foundations of machine learning and deep learning, providing insights into various algorithms and techniques commonly employed in crime analysis. Drawing upon real-world datasets from Indian cities, we demonstrate the application of machine learning and deep learning techniques in crime prediction, hotspot identification, and criminal profiling.
Published by: Thatikonda Shanmukham, Dr.Md. Riyazuddin
Author: Thatikonda Shanmukham
Paper ID: V10I2-1137
Paper Status: published
Published: April 13, 2024
Indoor navigation using augmented reality
The majority of contemporary competitive commercial navigation programs rely on GPS-based navigation technology. However, it is the interior navigation performance is lower than that in an outdoor situation. Much of the research and development on indoor navigational systems entails the installation of additional equipment, which often comes with a substantial setup charge. A study and comparison were undertaken to identify the best indoor localization, pathfinding, and path navigation systems for an indoor navigation strategy. The goal of this project is to demonstrate a user-friendly and cost-effective indoor navigation system. The recommended solution combines augmented reality technology with the built-in sensors included in the majority of mobile devices to determine the user's location and give an immersive navigation experience. In this project, a smartphone app for indoor navigation was developed and tested. AR Core will use the predicted route to display AR guidance. Surveys were done to assess the methodology's effectiveness and gather input from participants. The method's architecture, an example, and applications are described.
Published by: Mahalakshmi Padam, Dr. Y. Md. Riyazuddin
Author: Mahalakshmi Padam
Paper ID: V10I2-1138
Paper Status: published
Published: April 13, 2024
Online Auction System
The rapid evolution of digital technologies has transformed traditional auction methodologies into dynamic, online platforms. This abstract outlines the development and implementation of an innovative online auction system using the ASP.NET framework. The proposed system aims to provide users with an intuitive and responsive platform for conducting and participating in auctions, offering a seamless and engaging bidding experience. Leveraging ASP.NET's capabilities, the application ensures uniformity and high performance across various devices and operating systems. The development process involves utilizing ASP.NET's rich set of pre-built widgets, facilitating rapid prototyping and efficient UI design. Integration with backend services, employing technologies like Firebase or custom server solutions, ensures smooth data exchange and real-time synchronization. Furthermore, considerations for scalability, performance optimization, and user feedback mechanisms are integral to enhancing the overall user experience and system reliability. In conclusion, this online auction system built on the ASP.NET framework aims to redefine the auctioning landscape by offering a feature-rich, secure, and user-centric platform for both auctioneers and bidders, fostering a dynamic marketplace in the digital realm.
Published by: Harshal Ekhande, Prathmesh Biradar, Abhishek Lahane, Manjeet Singh, Nitin Shivale
Author: Harshal Ekhande
Paper ID: V10I1-1302
Paper Status: published
Published: April 12, 2024
