Journal Article
Permanent URI for this collectionhttps://ir.daiict.ac.in/handle/123456789/37
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Publication Metadata only Capacity of a quantum memory channel correlated by matrix product states(Springer, 2018-04-01) Mulherkar, Jaideep; V, Sunitha; DA-IICT, GandhinagarWe study the capacity of a quantum channel where channel acts like controlled phase gate with the control being provided by a one-dimensional quantum spin chain environment. Due to the correlations in the spin chain, we get a quantum channel with memory. We derive formulas for the quantum capacity of this channel when the spin state is a matrix product state. Particularly, we derive exact formulas for the capacity of the quantum memory channel when the environment state is the ground state of the AKLT model and the Majumdar�Ghosh model. We find that the behavior of the capacity for the range of the parameters is analytic.Publication Metadata only Hybrid and parallel GAN architecture with non-IID noise input(Springer, 10-06-2025) Gohel, Prashant; Joshi, Manjunath V; DA-IICT, GandhinagarPublication Metadata only UASPAR: Utility-based Adaptive Sensor Placement and Reconfiguration for Energy Efficient Wireless Sensor Networks(IEEE, 23-07-2025) Sheth, Chaitanya; Devmurari, Kandarp; Kumar, Manish; Rajput, Kunwar Pritiraj; DA-IICT, GandhinagarPublication Metadata only Data-Driven Soft Sensor for Optical Intensity Estimation in High-Power Plasma Source(IEEE, 15-07-2025) Tyagi, Himanshu; Joshi, Manjunath V; Bandyopadhyay, Mainak; Singh, M J; DA-IICT, GandhinagarInductively coupled plasma (ICP) sources are used in multiple industrial and research applications varying from material reactors, semiconductor fabrication, and nuclear fusion-based reactors. Experiments using ICP source are prone to noise due to the presence of high-power radio frequency (RF) radiation as well as the high voltage (HV). In order to operate such plasma sources, we need rich set of diagnostics that supports the control system as well as the operators in order to derive the important plasma parameters. Some of these sensors are prone to degradation and need constant maintenance and testing that creates challenges during operations. In order to monitor the performance and also mitigate the risks associated with the sensor failure, soft sensors can offer an alternative low-cost approach in estimating the physical parameters. Although soft sensors have found applications in industrial environments, limited implementation has been seen in experimental systems. Hence, in this article, we propose a soft sensor model for an optical (light) sensor which is one of the critical sensors used in ICP and other plasma sources. The proposed model is developed using data-driven machine-learning (ML) and deep-learning (DL) algorithms for a plasma-based system operating under noisy environments. After a thorough exploration, a comparatively better performance was observed using the artificial neural network (ANN)-based models. The ANN model was trained with various hyper parameters in order to obtain a test R2 score of 0.91 that was able to model the transient behavior of the sensor. After the model development, it was used for performing fault identification in the signal by comparing the predicted signal with actual signal. The article presents the steps followed in developing the data-driven models for the plasma light sensor and its application for sensor fault identification along with associated challenges.Publication Metadata only Reliability Assessment using Electrical and Mechanical Characterization of Stretchable Interconnects on Ultrathin Elastomer for Emerging Flexible Electronics System(IEEE, 10-07-2025) Bhatti, Gulafsha; Sharma, Rohit; Kumar, Mekala Girish; Palaparthy, Vinay; Agrawal, Yash; DA-IICT, GandhinagarPublication Metadata only VeriProd: A Privacy-Preserving and Verifiable FL Framework for Secure Aggregation and Dropout Resilience(Wiley, 01-07-2025) Saraswat, Deepti; Das, Manik Lal; Tanwar, Sudeep; DA-IICT, GandhinagarPublication Metadata only Exploring Topic Trends in COVID-19 Research Literature using Non-Negative Matrix Factorization(IEEE, 12-06-2025) Patel, Divya; Parikh, Vansh; Patel, Om; Shah, Agam; Chaudhury, Bhaskar; DA-IICT, GandhinagarPublication Metadata only A survey on Crowd Behavior Analysis through indoor localization(Taylor & Francis, 07-05-2025) Panja, Ayan Kumar; Sasidhar, P S Kalyan; Royand, Moumita; Chowdhury, Chandreyee; DA-IICT, GandhinagarPublication Metadata only Scheduling Computing Tasks on Smartphones: Comparative Case Studies of Metaheuristic Algorithms on Real World Applications(Springer, 18-03-2025) Tripathi, Pramod; Sasidhar, P S Kalyan; Mistry, Harsh; Shah, Vyom; DA-IICT, GandhinagarPublication Metadata only In-House Developed Graphene-Based Leaf Wetness Sensor With Enhanced Stability(IEEE, 01-06-2025) Patle, Kamlesh; Yogi, Pooja; Maru, Devkaran; Palaparthy, Vinay; Moez, Kambiz; Agrawal, Yash; DA-IICT, Gandhinagar