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Total publications: 1,998
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On the domination number of proper power graphs of finite groups
(Elsevier, 01-10-2025) Bera, Sudip; Dey, Hiranya Kishore; Patra, Kamal Lochan; Sahoo, Binod Kumar; DA-IICT, Gandhinagar
Explicit Analytical Model of Stretchable Interconnects for Flexible Electronics System
(IEEE, 24-07-2025) Bhatti, Gulafsha; Kumar, Mekala Girish; Sharma, Rohit; Palaparthy, Vinay; Agrawal, Yash; DA-IICT, Gandhinagar
A printed circuit board (PCB) is one of the strong backbones to execute electronic system designs. Due to fast and reliable communication requirements between integrated circuit and other peripheral components over the PCB, there is a quest for the development of board-level designs and layouts. The advancement in technology has led to inventions from conventional rigid to flexible PCBs or flexible electronics (FE). The conformability of FE circuitry majorly depends upon the stretchable interconnects. An interconnect is the medium through which a signal is transmitted. The characteristic of stretchable interconnects is determined through their electrical and mechanical properties. The analytical model and parasitic extraction of the interconnect for rigid PCB structures have been widely explored earlier. However, the analytical formulation of the stretchable interconnect still remains a challenge and meagerly explored till date. Consequently, in this work, an explicit analytical model for the parasitic extraction of stretchable interconnects, viz., resistance (R), inductance (L), and capacitance (C), under stretching and bending effects has been novelly proposed. Five different interconnect materials have been considered for the analysis. The analytical model results have been validated with the ANSYS EDA tool. It is investigated that the proposed analytical model results are in very close agreement with the ANSYS results for all the considered cases.
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, Gandhinagar
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, Gandhinagar
Inductively 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.
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, Gandhinagar