http://repository.iiitd.edu.in/xmlui/handle/123456789/960 Mon, 13 Apr 2026 11:16:25 GMT 2026-04-13T11:16:25Z http://repository.iiitd.edu.in/xmlui/handle/123456789/1233 HoppaQ : self checkout shopping cart Sarkar, Arka; Singla, Utsav; Jerripothula, Koteswar Rao (Advisor) With the growing population in major cities the need of groceries is essential for everyone, this makes the supermarkets get flooded with consumers looking for a quick shop, but all comes to a halt when one realises a huge queue to checkout their purchases costing them valuable time. We propose our self-checkout cart as a viable solution to this problem. This cart is fully automated and is specifically to designed to eliminate the need to queues in supermarkets. The user is supposed to use this cart as a normal cart for shopping purposes, the cart will itself detect what items are put into it and keep a track of everything that occurs inside, once the consumer is done shopping they can just walk out of the store, the credit will automatically be deducted from their account without any need for further manual checkout. Sat, 01 May 2021 00:00:00 GMT http://repository.iiitd.edu.in/xmlui/handle/123456789/1233 2021-05-01T00:00:00Z http://repository.iiitd.edu.in/xmlui/handle/123456789/1232 Reinforcement learning in network survivability, routing, modulation and spectrum allocation in elastic optical networks Buxy, Sudarshan; Mitra, Abhijit (Advisor) The report provides an overview of the motivation behind using reinforcement learning in network survivability and routing, modulation and spectrum allocation. The reinforcement learning algorithms that were explored throughout the study, namely Multi-armed bandit algorithms, Monte Carlo Methods, Q-Learning, and Deep Q-Networks, have found various applications in Q-Networks. This study aims to assess the application of these reinforcement learning frameworks to Routing, Modulation and Spectrum Allocation in Elastic Optical Networks. After considerable literature review, a deep Q-Learning based application of routing, modulation and spectrum allocation has been decided as the baseline for the research work. Wed, 01 Dec 2021 00:00:00 GMT http://repository.iiitd.edu.in/xmlui/handle/123456789/1232 2021-12-01T00:00:00Z http://repository.iiitd.edu.in/xmlui/handle/123456789/969 Before stress overcomes you, we overcome it : a digital solution to predict and relieve acute stress in young adults Katyal, Akshyta; Gupta, Anushika; Shukla, Jainendra (Advisor) Stress is natural, especially during this unprecedented COVID-19 crisis that has brought various emotions and challenges. However, stress experienced over an extended period can lead to serious health problems. It is therefore important to timely detect and overcome it. Studies conducted in the past have shown the signi_cance of Electrodermal Activity (EDA) and Heart Rate Variability (HRV) in stress detection. We present a digital solution that involves both stress prediction and mitigation with the help of an Android Application. We use incremental learning to personalize the machine learning model that predicts stress arousal using HRV indices and EDA measurements collected continuously via a wearable device. If the user is found stressed at any moment, the application provides personalized recommendations for a stress-relieving activity. To provide personalized recommendations, we use a clustering algorithm preceded by Thompson Sampling to determine user activity preferences in the cold start phase. Sat, 01 May 2021 00:00:00 GMT http://repository.iiitd.edu.in/xmlui/handle/123456789/969 2021-05-01T00:00:00Z http://repository.iiitd.edu.in/xmlui/handle/123456789/961 Robust fake news detection Gautam, Akansha; Jerripothula, Koteswar Rao (Advisor) Recently, news consumption using online news portals has increased exponentially due to several reasons, such as low cost and easy accessibility. However, such online platforms inadvertently also become the cause of spreading false information across the web, as we have seen during the recent COVID-19 pandemic. They are being misused quite frequently as a medium to disseminate misinformation and hoaxes. Such malpractices call for a robust automatic fake news detection system that can keep us at bay from such misinformation and scams. This thesis pro-poses a robust fake news detection system, named PaGE (based on Paraphrasing, Grammar, andEmbedding), leveraging the tools for paraphrasing, grammar-checking, and word-embedding. In this project, I try to unearth such tools' potential in jointly detecting a news article's authenticity. Notably, I leverage Spinbot (for paraphrasing), Grammarly (for grammar-checking), andGloVe (for word-embedding) tools for accomplishing this. While Spinbot and Grammarly aretext-oriented tools, GloVe is just a word-oriented tool. Since the proposed system's input is a text, not a word, the proposed approach involves two novel GloVe-based tools that act like text-oriented tools. While one uses the codebook-based approach, another uses the spatial-pyramid-pooling-based approach. Using all these tools, I extract novel features that yield state-of-the-art results on three fake news datasets after combining them with some essential features. More importantly, it empirically shows that the proposed method is more robust than existing ones through cross-domain analysis, multi-domain analysis, and learning curve experiments. This thesis also focuses on the importance of Grammarly features in identifying legit news articles. Tue, 01 Jun 2021 00:00:00 GMT http://repository.iiitd.edu.in/xmlui/handle/123456789/961 2021-06-01T00:00:00Z