http://localhost:80/xmlui/handle/123456789/816 2026-01-09T22:11:39Z http://localhost:80/xmlui/handle/123456789/1277 Title: Atomic drift-less electromigration model for submicron copper interconnects Authors: Dr. Arijit Roy; Aparna Adhikari; Cher Ming Tan Abstract: Electromigration in chip level interconnect is commonly described by atomic drift due to electron-wind force that arises from electron-ion momentum transfer. As an alternative to this model, in early 1980’s, Sah proposed a two dimensional analytical ‘void-surface bond-breaking’ model by dropping the atomic drift term that resulted from electron-wind force (in his book ‘Fundamentals of Solid-State Electronics’) and the rate of change of area of void is computed. Due to the continuous down scaling and evolution of interconnect patterning technologies, the void growth process in modern interconnect becomes more complex and electromigration failures are found to be catastrophic in nature instead of gradual type failures observed in early days. In this work, Sah’s model is revisited from the perspective of its applicability to modern submicron copper interconnects. The electromigration-induced resistance change behavior is analytically derived considering a three-dimensional atomic drift-less model. A good correlation between the findings of our model with experimental observations is presented. 2022-07-07T00:00:00Z http://localhost:80/xmlui/handle/123456789/1276 Title: Construction and remote demonstration of an inexpensive but efficient linear differential variable transformer (LVDT) for physics or electronics teaching during COVID-19 pandemic Authors: Dr. Arijit Roy; Durjoy Roy; Abhishek Mallick Abstract: A linear variable differential transformer is termed as LVDT in short. A simple miniature and inexpensive LVDT was constructed for laboratory teaching. Starting from the fundamental physics of LVDT, a complete demonstration was presented. The heart of an LVDT is three coils that were taken from the electrical ‘Ding-dong’ doorbell. A universal laboratory experiment kit named ‘ExpEyes-17’ is used to drive the LVDT and display the input and output signals on a laptop screen. Thus, a compact LVDT system was developed. Displacement experiments were conducted, and the well-known V-shape response for our LVDT was obtained. The theory and experiment were presented with a high degree of clarity for ease of understanding. A complete demonstration was given to a group of students while teaching the theory of LVDT, and an excellent response from the group was obtained. Moreover, online demonstration of LVDT experiments using our kit was easily achievable. The authors have used the setup for 2023-01-01T00:00:00Z http://localhost:80/xmlui/handle/123456789/1271 Title: Accurate diagnosis of liver diseases through the application of deep convolutional neural network on biopsy images Authors: Abhishek Mallick; Sudipta Das; Kartik Sau; Soumyajit Podder; Dr. Arijit Roy Abstract: Accurate detection of non-alcoholic fatty liver disease (NAFLD) through biopsies is challenging. Manual detection of the disease is not only prone to human error but is also time-consuming. Using artificial intelligence and deep learning, we have successfully demonstrated the issues of the manual detection of liver diseases with a high degree of precision. This article uses various neural network-based techniques to assess non-alcoholic fatty liver disease. In this investigation, more than five thousand biopsy images were employed alongside the latest versions of the algorithms. To detect prominent characteristics in the liver from a collection of Biopsy pictures, we employed the YOLOv3, Faster R-CNN, YOLOv4, YOLOv5, YOLOv6, YOLOv7, YOLOv8, and SSD models. A highlighting point of this paper is comparing the state-of-the-art Instance Segmentation models, including Mask R-CNN, U-Net, YOLOv5 Instance Segmentation, YOLOv7 Instance Segmentation, and YOLOv8 Instance Segmentation. The extent of severity of NAFLD and non-alcoholic steatohepatitis was examined for liver cell ballooning, steatosis, lobular, and periportal inflammation, and fibrosis. Metrics used to evaluate the algorithms’ effectiveness include accuracy, precision, specificity, and recall. Improved metrics are achieved by optimizing the hyperparameters of the associated models. Additionally, the liver is scored in order to analyse the information gleaned from biopsy images. Statistical analyses are performed to establish the statistical relevance in evaluating the score for different zones. 2023-04-07T00:00:00Z http://localhost:80/xmlui/handle/123456789/1270 Title: Application of nature inspired optimization algorithms in bioimpedance spectroscopy: simulation and experiment Authors: Dr. Arijit Roy; Abhishek Mallick; Atanu Mondal; Somnath Bhattacharjee Abstract: Accurate extraction of Cole parameters for applications in bioimpedance spectroscopy (BIS) is challenging. Precise estimation of Cole parameters from measured bioimpedance data is crucial, since the physiological state of any biological tissue or body is described in terms of Cole parameters. To extract Cole parameters from measured bioimpedance data, the conventional gradient-based non-linear least square (NLS) optimization algorithm is found to be significantly inaccurate. In this work, we have presented a robust methodology to establish an accurate process to estimate Cole parameters and relaxation time from measured BIS data. Six nature inspired algorithms, along with NLS are implemented and studied. Experiments are conducted to obtain BIS data and analysis of variation (ANOVA) is performed. The Cuckoo Search (CS) algorithm achieved a better fitment result and is also able to extract the Cole parameters most accurately among all the algorithms under consideration. The ANOVA result shows that CS algorithm achieved a higher confidence rate. In addition, the CS algorithm requires less sample size compared to other algorithms for distinguishing the change in physical properties of a biological body. 2023-04-07T00:00:00Z