Daily Archives: November 26, 2024

Abstract-Virtual meetings have become an essential mode of communication in contemporary professional environments. However, the fast-paced nature of virtual meetings undermines the ability to remember critical information accurately as even making notes is an imperfect mundane task, manual note-taking is both time- consuming and error-prone, often resulting in overlooked decisions and action items. SummrAIze is an AI-powered meeting assistant designed to address these challenges by automating the transcription, [1]summarization, and extraction of actionable insights during virtual meetings on platforms like Google Meet and Microsoft Teams. Using advanced machine learning algorithms, SummrAIze produces real-time summaries, highlights key points, and identifies action items, enabling participants to engage fully in discussions without sacrificing documentation accuracy. Integrated with productivity tools, SummrAIze not only reduces manual effort but also ensures that all essential information is recorded and accessible, enhancing team collaboration and workflow continuity. This paper presents the design, methodology, and potential impact of SummrAIze, a tool that redefines productivity in the context of virtual meetings.

Abstract-With the advent of the “e-” revolution starting in 2000, the issue of cyber security, cyber-attacks and cyber threats which included domains, but not e-business, e-government, e-; commerce etc. only occurred because for the issue of cybersecurity in e- learning is under-explored, the aim of this paper is to present methods that focus on monitoring cybersecurity issues related to e- learning processes on. In addition, this article aims to present some good examples of cybersecurity management strategies in e- learning and cybersecurity trends in this area.[2] This paper will present possibilities for increasing information security and cyber- security awareness in education and e-learning that will inspire future cybersecurity professionals to navigate their career path.[3].

Abstract-The cost of commuting to and from school is a burden for many people, especially in urban areas. While ride-hailing services are popular worldwide, most students face issues with accessibility and convenience. The aim of this work is to create and use fairShare. A web platform that allows students to connect and share rides, thereby reducing transportation costs and reducing the environment around them. Users can register, post trips,and compete with other students using the same route. Early tests of the platform have shown that it reduces student travel costs and provides a good user experience. The platform also promotes sustainable practices for students. fairShare demonstrates the potential of student-friendly carsharing to reduce transportation costs and improve social interaction. The platform has the ability to measure a broader and more effective way for students to take action.

Abstract-Employing generative adversarial networks, specifically with regard to cycle consistency loss and mask vectors, mainly concentrates on the colorization of Synthetic Aperture Radar (SAR). Most SAR imagery is devoid of chromatic information. Contemporary deep learning techniques are the predominant approach for SAR colorization. The methodology proposed herein employs a multidomain cycle-consistency generative adversarial network (MC-GAN). It enhances performance through the integration of a mask vector and cycle-consistency loss. The approach does not necessitate the availability of paired SAR-optical imagery. The multidomain classification loss contributes to the precision of the color output. The methodology has been evaluated using the SEN1-2 dataset for urban and terrain areas.

Abstract-This study focuses on the design and analysis of a hollow shaft for an EV go-kart, optimizing weight reduction and structural integrity. Using SolidWorks for design and ANSYS for Finite Element Analysis (FEA), the shaft’s performance under mechanical stresses and cyclic loads was evaluated. Results demonstrated significant weight savings while maintaining strength, rigidity, and durability, enhancing the go-kart’s efficiency and reliability. This work highlights the potential of hollow shafts in improving EV performance through lightweight design.