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Research Paper

Next Step: Find the Next Step in your Career

Choosing the right academic specialisation is a pivotal decision in a student's educational journey and has a profound impact on their future career. However, many students struggle with this choice due to a lack of clarity about their interests, strengths, and the job market relevance of different specialisations. The "Next Step" project aims to bridge this gap by offering a data-driven, survey-based guidance system that helps students identify the most suitable specialization based on their interests and aptitudes. The system utilizes a structured questionnaire designed to assess key personal and cognitive traits, such as analytical thinking, creativity, and technical enthusiasm. Based on the responses, the system suggests the most relevant specialisation, such as Artificial Intelligence, Data Science, or Cybersecurity, and subsequently provides a curated list of corresponding job roles. The solution is implemented as a web application, offering students a seamless and interactive experience while also allowing administrators to manage job role data dynamically. This approach not only improves self-awareness among students but also aligns their academic direction with industry demand, thus reducing the skills gap. The "Next Step" platform exemplifies how interest-based guidance can be transformed into an effective educational tool through the integration of survey methodologies, web technologies, and dynamic data mapping. It lays a scalable foundation for future career guidance systems that are personalized, adaptive, and aligned with real-world opportunities.

Published by: Harshal Patil, Divyansh Dubey, Harsh Singh Parihar, Aditya Upadhye, Shahin Makubhai

Author: Harshal Patil

Paper ID: V11I3-1163

Paper Status: published

Published: May 15, 2025

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Research Paper

Design and Development of HEV

Hybrid Electric Vehicles (HEVs) represent a transformative advancement in automotive technology aimed at reducing fuel consumption and minimizing environmental impact. The study conducts a comprehensive analysis of various HEV architectures—including series, parallel, and seriesparallel configurations—to identify the most suitable system for optimal performance and effective energy management. Critical components such as electric motors, battery packs, regenerative braking systems, and power electronics are carefully selected and integrated to achieve an optimal balance between efficiency, performance, and cost. Additionally, special emphasis is placed on wheel alignment optimization to improve vehicle stability and reduce rolling resistance. The resulting prototype exhibits a significant improvement in both fuel economy and emission reduction compared to conventional vehicles, underscoring the potential of hybrid technologies in advancing sustainable transportation.

Published by: Vrushali Shankar Rupnawar, Vishwajeet Vikas Gholap, Giram Dhananjay Ram, Rohan Barikrao Rupnawar, Rohan Manohar Shelak, Dnyaneshwar Sukhadev shinde, Adarsh Siddheshwar Jankar, Rutuja Sanjay Dethe, Gaurav Mahadev Deokate, Vrushali Navnath Waghmare

Author: Vrushali Shankar Rupnawar

Paper ID: V11I3-1171

Paper Status: published

Published: May 15, 2025

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Research Paper

Finger-Print Based Vehicle Starter

The Fingerprint-Based Vehicle Starter system enhances vehicle security by using biometric authentication to control engine access. It replaces traditional keys with a fingerprint sensor, allowing only authorized users to start the vehicle. When a registered fingerprint is detected, the system activates the ignition through a microcontroller. If the fingerprint is unrecognized, the engine remains locked. This method prevents unauthorized access and reduces the risk of theft. The system is reliable, user-friendly, and cost-effective, making it suitable for modern vehicles. It demonstrates the practical use of biometrics in improving automotive safety and access control.

Published by: Gagan D D, Abhilash S G, Kruthika A N, Jnaneshwari G S, Rammurthy D

Author: Gagan D D

Paper ID: V11I3-1172

Paper Status: published

Published: May 15, 2025

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Research Paper

Instagramming Architecture: The Social Media Revolution in Architectural Photography

This research examines the profound impact of Instagram on architectural photography in the 21st century. Once a professional and editorial endeavor, architectural photography has been transformed by social media into a participatory and highly aestheticized activity. Instagram's algorithm-driven visuals, hashtag culture, and global reach have changed how architecture is captured, consumed, and even designed. This paper explores the visual aesthetics promoted by Instagram, the algorithmic pressures on photographers and designers, and the ethical and cultural consequences of a platform-dominated gaze. Through extensive case studies—ranging from Ricardo Bofill’s Muralla Roja and Thomas Heatherwick’s Vessel to India’s Rani ki Vav and Studio Mumbai’s handcrafted works—the study explores both the creative opportunities and serious challenges introduced by this digital revolution. It argues that while Instagram has broadened the audience for architecture, it has also commodified space and design into fleeting visual content, often at the cost of cultural depth and spatial integrity.

Published by: Sourav M S

Author: Sourav M S

Paper ID: V11I3-1161

Paper Status: published

Published: May 13, 2025

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Research Paper

Application of Optical Communication in FMCW Radar

Frequency-modulated continuous waves (FMCW) radars are long-range, frequency-modulated electromagnetic sensors that can perceive their environment in three dimensions. Recent introductions of RADARs with frequencies ranging from 60 GHz to 300 GHz have expanded their possible applications due to their improved precision in angle, range, and velocity. FMCW RADARs have a better resolution and are more accurate than narrowband and ultra-wideband (UWB) RADARs. They offer several important benefits, such as long-range perception, resistance to rain and lightning, and more, and they are less costly than cameras and LiDARs. Even yet, their outputs are less dense and noisy than those of other RADAR technologies, and their ability to measure target velocities requires the employment of specifically created algorithms. Recently, radar sensors have become more and more common in a variety of industries, such as automotive, defense, and surveillance. This is because radar sensors can withstand a wide range of conditions, such as extreme heat, bright light, and bad weather. The simulation results were performed using Optisystem 22.0 and MATLAB (R2024b). The results demonstrate that 40 mW of power is effectively utilized for target identification, with the best technique for moving targets being direct detection.

Published by: Priyanka Shukla, Priti Singh

Author: Priyanka Shukla

Paper ID: V11I3-1151

Paper Status: published

Published: May 12, 2025

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Research Paper

Context Management in Generative AI

Context management is a fundamental challenge in generative AI, directly influencing the coherence, relevance, and quality of AI-generated outputs. This paper explores the concept of context in generative AI, focusing on the difficulties models face in maintaining long-term, dynamic, and global context across interactions. Key challenges include context loss in long-term dialogues, balancing between immediate and overarching context, handling context switching in multi-turn conversations, and addressing ambiguity or incomplete context. Additionally, we examine the impact of contextual drift, scalability issues, and resource constraints. By understanding these challenges, we highlight the importance of developing more sophisticated context management techniques to improve AI's ability to generate consistent, relevant, and user-centered outputs. Finally, we discuss the implications of context management for various applications, including conversational AI, content generation, and personalized recommendations.

Published by: Rushikesh Joshi, Omkar Jainak, Naveena Bhat, Khushal Patil, Dr. Swapnaja Ubale

Author: Rushikesh Joshi

Paper ID: V11I3-1137

Paper Status: published

Published: May 12, 2025

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