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Differentiating Fault Current from Leakage Current during IC Testing

Differentiating Fault Current from Leakage Current During IC Testing As integrated circuit technology advances, the intricacies related to fault identification and leakage current evaluation have increased markedly. Although conventional I_DDQ (quiescent supply current) testing protocols exhibit effectiveness in detecting major defects, they often struggle to distinguish between typical leakage currents and those reflective of genuine faults, thereby prolonging testing durations. Consequently, current sensors typically initiate measurements once transitions are finalized. In this investigation, we utilize a simulation technique to corroborate the effectiveness of an innovative methodology articulated in [1], which can be used to improve the throughput of the current testing process by detecting the faults using AC components of the current, thereby overcoming a constraint of traditional methods.

Published by: Yasser A. Ahmed

Author: Yasser A. Ahmed

Paper ID: V11I1-1488

Paper Status: published

Published: March 27, 2025

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Research Paper

2D Platformer Game Development with Godot Engine

This paper explores the development of a 2D platformer using the Godot Engine, emphasizing its node-based design and procedural generation. By adopting an agile workflow, the project achieved stable 60 FPS on mid-tier hardware, with user tests (n=50) highlighting responsive controls (93% approval) and dynamic levels. Godot’s efficiency and open-source flexibility proved ideal for indie teams, though advanced debugging tools were limited. Findings affirm its viability for cost-effective, engaging 2D game development.

Published by: Neeraj Pradeep Bharambe, Yash Prasad Mhaddalkar, Harsh Manohar Yeram, Vidhi Santosh Jadhav

Author: Neeraj Pradeep Bharambe

Paper ID: V11I1-1501

Paper Status: published

Published: March 27, 2025

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Research Paper

Intelligent Network Intrusion Detection using ML

With the rapid expansion of cybercrime, attackers are exploiting vulnerabilities in cloud computing and network infrastructures, posing significant security threats. Traditional Intrusion Detection Systems (IDS) struggle to cope with the dynamic and sophisticated nature of cyber-attacks, necessitating the development of intelligent and adaptive security techniques. Machine learning (ML) has emerged as a powerful tool in cybersecurity, offering improved detection rates, reduced false alarms, and lower computational costs. ML techniques have been applied to various cybersecurity domains, including intrusion detection, malware classification, spam filtering, and phishing detection. While ML cannot fully automate cybersecurity systems, it enhances threat detection efficiency, alleviating the burden on security analysts. This study proposes an intelligent network attack detection framework utilizing deep learning models. The Cyber-Physical System (CPS) is represented as a coordinated network of agents, with one agent acting as a leader, guiding the others. The attack detection phase employs deep neural networks to identify threats in their early stages, ensuring a proactive defense mechanism. To further enhance security, robust control algorithms are integrated to isolate compromised agents using a reputation-based mechanism. Experimental results demonstrate that deep learning techniques significantly outperform traditional IDS methods in detecting and mitigating network attacks. This approach improves cybersecurity by making threat detection more efficient, proactive, and cost-effective, addressing the limitations of conventional security mechanisms.

Published by: Ankita Sambhaji Gorde

Author: Ankita Sambhaji Gorde

Paper ID: V11I1-1502

Paper Status: published

Published: March 27, 2025

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Review Paper

The Impact of Advancement in Robotics on the Medical Sector

This paper investigates the impact of robotics on the medical sector, discussing the benefits and negatives of this new intervention. While robots have brought in certain efficiencies in the delivery systems, the human element and its reassuring presence, the cost of using robots, putting human life into the hands of an unresponsive machine, and the job loss that they might bring to a thriving sector are some of the huge concerns. Surgical robots, rehabilitation robots, and telepresence robots are all examples of medical robots. Their increasing use in health care is bound to alter the health care landscape, and it would be interesting to understand the long-term implications of this technology induction.

Published by: Madhav Agarwal

Author: Madhav Agarwal

Paper ID: V11I1-1507

Paper Status: published

Published: March 27, 2025

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Research Paper

Time & Motion Study

Time and motion study is one form of work measurement to note down and study the time employed in performing specified work under prescribed conditions. Time and motion study helps managers streamline the operations of their companies through segmentation of tasks into simpler parts and setting the standards for executing the same. This research sets up normal time for task execution, identifies opportunities for improvement, and suggests realistic measures for enhancing performance, typically in conjunction with wage-incentive systems to enhance employees' motivation levels.

Published by: Mohit Choudhary, Aditya Kharat, Bhumik Mhatre, Vikas Sawant, Sanskruti Dharmale

Author: Mohit Choudhary

Paper ID: V11I1-1473

Paper Status: published

Published: March 17, 2025

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Research Paper

Patient Perception of Dental Camp and Factors Influencing Non-Return to Hospital

Oral health on an essential aspect of overall health and well–being. Dental camps provide oral health care to underserved populations, but their effectiveness depends on patient perception. this study explores patient perception views on the usefulness of dental camps and understands their experience and satisfaction with these community-based initiatives.

Published by: Sharmila Singarayar, Periyasamy Arulraj Pooja, Jemima Jebakani, Prabahar Lydia, Vezhavendhan Nagaraja

Author: Sharmila Singarayar

Paper ID: V11I1-1436

Paper Status: published

Published: March 17, 2025

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