Browsing by Author "Bhatt, Upendra Mohan"

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Analysis of Hybrid Wavelet Transformed Images to Improve Image Pixel Quality
(IEEE, 2022-08) Bhatt, Upendra Mohan
Visual information exchange in the form of a digital picture has become ubiquitous in the world of communication. During the transmission of images, the information is distorted due to noise. This noise component distorts the quality of images. De-noising methods are used to expand the grade of picture pixels or to restore the original form of incoming data. In this article, we will be introducing a de-noising method for upgrading the excellence of the image. A multiscale LMMSE estimation method using un-decimated wavelet transforms (UWT) has been proposed. To generate the wavelet transformed images, Daubechies & Biorthogonal filters are used. In this proposed method, a Hybrid filter is generated using these two filters. Image produced using this method seems to be agreeable as compared to individual filters. The result is observed by the PSNR & MSE value for the quantitative measure.
Analysis of temperature sensitive electrical performance of sputter grown Ni and Ni–Cr Schottky contacts on 4 H-SiC
(Springer, 2024-11) Singh, Dheerendra; Mourya, Satyendra Kumar; Bhatt, Upendra Mohan
This paper studies the temperature-dependent electrical transport properties of nickel (Ni) and nickel–chromium (Ni–Cr) sputtered on n-type 4 H-SiC substrate. Barrier inhomogeneities have been found to affect the electrical parameter of the Schottky barrier diode (SBD) from 323 to 423 K temperature range, We have done current–voltage characterization of Ni and Ni–Cr Schottky junctions. The barrier height , reverse saturation current , ideality factor and series resistance were obtained from I–V characteristics of Ni and Ni–Cr and these parameters are observed to be highly dependent on temperature. It has been observed that Ni–Cr contact has exhibited better electrical characteristics as well as thermal sensitivity as compared to Ni. This may be attributed to the smaller number of barrier inhomogeneities at the Ni–Cr/4 H-SiC interface. In the temperature range from 323 to 423 K, Ni and Ni–Cr-based Schottky contacts, Following observation has been noticed (a). Schottky barrier height (SBH) increased from 1.24 to 1.37 eV and 1.15 to 1.45 eV, (b). Ideality factors reduced from 3.76 to 2.61 and 3.20 to 2.53, (c). Series resistance decreased from 10.22 to 3.37 and 2.45 to 1.16 , and (d). Reverse leakage current to A and to A respectively. The V–T curves for both SBDs are investigated (for the same temperature range) to calculate their thermal sensitivity at and A, respectively. The V–T curves with linear behavior are used to calculate the thermal sensitivity coefficient , which was found to be 7.11 to 7.93 mV/K for the Ni–Cr SBD, and 7.1 to 20.01 mV/K for the Ni/4 H-SiC contacts. The sensitivity-current characteristics for the Ni/4 H-SiC SBD were found to be a non-linear comparison with Ni–Cr/4 H-SiC SBD, which may be attributed to the presence of a highly resistive and non-uniform coating of Ni at the interface.
Application of Deep Neural Networks for Weed Detection and Classification
(IEEE, 2023-06) Bhatt, Upendra Mohan
Weeds compete for natural resources both in forest areas, harming the development of native vegetation, and in agricultural areas, affecting crop quality. The need then arises to classify these species, so that mechanical or chemical methods can be applied appropriately to contain the pests. This research presents the application and comparison of machine learning techniques, with the aim of automating the classification of images for agricultural challenges, such as the detection of defective seeds, and weeds and the category between these and native vegetation, while finally, the architecture of a convolutional neural network is presented. As a differential, the network's self-learning ability stands out, as images are captured in less than ideal conditions at varying heights and lighting levels in most cases. This research is expected to provide important information on artificial intelligence techniques that can be used in the classification of weed images, a factor that will contribute to the forestry and agricultural sector.
Automated Designing of Single Stage Operational Amplifier and Its Teleportation Among Different Technology Nodes
(IEEE, 2020-06) Bhatt, Upendra Mohan
Analog circuits play a vital role in advanced electronic systems and they cannot be replaced because of their need to provide an interface with the natural analog world. In this paper we have presented an analog design flow for Automated Designing and Teleportation (ADT) of analog circuits, Further ADT for a single-stage operational amplifier (single-stage op-Amp, i.e., differential amplifier) has been presented to demonstrate the complete process flow which provides accurate results in a shorter span of time using the trained machine learning models.
Cloud Based Smart Kitchen Automation and Monitoring
(IEEE, 2023-03) Bhatt, Upendra Mohan
In order to simplify our day-to-day lives, a combination of technical and imaginative skills is needed. Leveraging the Internet and its various technology enhancements, everyday objects can now be networked and identified uniquely. Increasing efficiency, accuracy, comfort, and economic benefits are the main goals of the Internet of Things. It allows our lives to be easier by automating every task around us. IoT has revolutionized human life. In both commercial and residential kitchens, incidents involving the kitchen have increased in recent years. Frequently, people cook food in the kitchen. But if the gas cylinder leaks, it may be dangerous. Using IoT technologies, we try to lower these risks. Our solution has merged Node MCUs with gas sensors, temperature sensors, MQ3 sensors, alarm systems, exhaust fans, and load cells on the hardware side. Mobile apps and integrated Node MCUs have been utilized on the software side. The gas sensor will transmit a warning message to the user if it discovers a gas leak, and the stove's knob will switch off automatically as a result. A gas leakage monitoring system is created to increase home security. When a gas leak is discovered, the system notifies the user through SMS, and as a safety precaution, it shuts off the electricity while sounding an alarm. This sensor-based IoT-based system aims to monitor the quality and freshness of food. In addition to detecting the freshness of household food items like dairy items, fruits, and food items, this smart device prevents suffocation and explosion caused by gas leaks. The temperature of the smart kitchen is monitored, and if it exceeds a certain threshold, the exhaust fan is activated. It also monitors all software's functionality.
Comparative Study and Analysis of DWT-SPIHT with DWT-EZW Method for Image Compression
(IEEE, 2023-05) Bhatt, Upendra Mohan
The use of digital photographs has increased along with the development of digital technologies. Due to the vast amounts of information it contains, digital photographs need a lot of storage space, as well as bigger transmission bandwidths and longer transmission times. Therefore, on compressing the images all the redundant bits of information present in the image under test are removed while keeping only the essential information needed to reconstruct the image later on. In this study, DWT-SPIHT technique is introduced, which may be used to compress and reconstruct images at various degrees of wavelet decomposition across wavelet families that were initially a subdivision of the MATLAB wavelet family. Simulations have been conducted on Cameraman Image during this work of different resolution at different levels of decomposition and for different types of thresholding techniques to prove that this algorithm works well and provide us with the good reconstruction quality of the image. The simulation results demonstrate that, when compared to the DWT-EZW algorithm, the proposed DWT-SPIHT algorithm performs significantly better in terms of evaluation parameters like peak signal to noise ratio (PSNR), mean square error (MSE), and visual perception at higher compression ratios (CR) and low bit per pixel values (BPP).
Comparision between sizes of original HR images and images obtained through super resolution
(IEEE, 2018-02) Bhatt, Upendra Mohan
Getting high detailed information through LR(low resolution) images is not possible, so research in the field of computer science leads toward converting the LR images to the HR(high resolution) images and this process is known as Super resolution. In this paper a super resolution algorithm is proposed which uses DWT and SWT to downsampled the images and to preserve the edges Canny edge extractor and to remove the noise NLM filter is added to the algorithm. This paper shows the comparision between the sizes of original HR images on which experiment is done and the images obtained after converting LR image to HR with this algorithm. Result shows that the HR image obtained after the experiment is so much lesser in size than original HR image
Detection of suspicious lesions in mammogram using fuzzy C-means algorithm
(IEEE, 2016-11) Bhatt, Upendra Mohan
Breast cancer is one of the most incurable diseases, which leads to the death of women globally every year. For initial detection of a tumor in the breast, the most useful technique called `Mammography' is used, which is an X-ray inspection of the breast, which can be used to detect the breast tumor which may lead to breast cancer. Using Mammography, a small lump that may lead to breast cancer can be detected at the initial stage. Sometimes it is not possible to recognize very small tumors because of noisy, blurred, and fuzzy images. Therefore, they need to be enhanced to increase the contrast for better visual perception and reduce the noise from it for better diagnosis. In this work, FCM algorithm is used to detect the suspicious lesions in a mammogram. To achieve the objective of this work, MIAS (Mammographic Image Analysis Society) and INbreast databases are used, which contain 322 and 412 images of the breast (both left and right breast) respectively. In these databases, every image is examined by the expert radiologists. The effectiveness of the algorithm is measured in terms of MSE and PSNR.
DWT and sparse representation based image super resolution
(2016) Bhatt, Upendra Mohan
Spatial resolution of images are restricted by the size of CMOS sensors. Spatial resolution can be increased by increasing no of COMS sensors resulting in decrease in size of CMOS sensors which cause shot noise. In this paper attempts have been made to enhance the spatial resolution of different images. DWT is applied to obtain the sub bands and sparse representation is used to get the better results. Bicubic interpolation is being applied in the intermediary stage and HR image is retrieved through this method and the result of this method is being compared with some other state of the art works and this work shows better result than other super resolution algorithms based on image quality parameter PSNR and MSE
DWT based image super resolution performance analysis
(IJRET, 2016-12) Bhatt, Upendra Mohan
In computer vision field, Image resolution enhancement has become the most current research area. Improving image resolution by applying costly hardware is expensive and time-consuming. Many algorithms have been developed by researchers based on Projection Onto Convex Set (POCS), Maximum-aposteriori (MAP) and Maximum Likelihood (ML) In this paper, we analyzed a super resolution algorithm based on Discrete Wavelet Transform (DWT). Single frame super resolution can be achieved by use of different interpolation method but this scheme generates blur at the edges of images. Hence in this paper we relied on wavelet transform for super resolution algorithm with different orthogonal and bi-orthogonal filters. Quality aspect of images such as MSE, PSNR, SSIM and Correlation Coefficient (CC) are calculated with this proposed algorithm.
Effect of String Tapering on Threshold Voltage Distribution and Its Mitigation in a Vertical Channel 3D NAND Flash Memory
(ICSDM, 2018) Bhatt, Upendra Mohan
In this work, we have investigated the impacts of taper angle and channel doping on the performance parameters of a vertical channel 3D NAND flash memory. It is found that string current and threshold voltage (VT) distribution of the word lines (WLs) along the string is influenced by both, taper angle and channel doping. Therefore, nonuniformity in VT distribution of different WLs due to string tapering is minimized by optimizing the channel doping along the string from top to bottom. Moreover, optimized channel doping leads to an improved string current. These results are crucial for the designing of high performance and reliable future 3D NAND flash memories.
Fabrication and modeling of β-phase PVDF-TrFE based flexible piezoelectric energy harvester
(Elsevier, 2020-04) Bhatt, Upendra Mohan
There is increased interest in flexible substrate-based piezoelectric energy harvester (PEH) for self-powered wireless sensor nodes, due to their low-cost and environmental friendliness. However, it presents fabrication challenges due to the low-temperature process and formation of a highly polar β-phase of a polymer film on a flexible substrate. In this work, first, we optimize the deposition parameters to grow the polar β-phase of poly vinylidene fluoride trifluoroethylene (PVDF-TrFE) film on Polyethylene terephthalate (PET) substrate. Using optimized PVDF-TrFE film, rectangular shape PEH is fabricated on a flexible Mo/PET substrate and characterized for voltage and power. It is found that the maximum measured power is 6.83 μW with input acceleration of 1.0 g. Further, we develop a novel analytical approach using a mass-spring damper model of PEH to predict the resonance frequency and output power. The fabricated and model results are shown to match well with mechanical and induced electrical damping as fitting parameters. The maximum measured power density from the flexible substrate based PEH is found to be 312.85 μW/cm3. The obtained power density is better than similar reported devices, with the advantage of low-cost material and fabrication. The optimized and low frequency PEHs reported in this work have a high potential for the wireless sensor node applications, such as monitoring of water bodies and plant health monitoring in agriculture, etc.
Image super resolution based on discrete and Stationary wavelet transform using Canny edge extraction and non local mean
(IEEE, 2017-01) Bhatt, Upendra Mohan
This paper addresses the issue of generating a high-resolution(HR) image from single low quality or low-resolution(LR) image. In this work, Discrete wavelet transform (DWT) is used with the Stationary wavelet transform (SWT) to generate or increase the resolution of the image. SWT reduces the translation invariance presence in DWT. To preserve the edges Canny edge extraction is used to get the sharper image. To interpolate the image into the intermediary stage of proposed algorithm Lanczos interpolation is used and to reduce the artifacts introduced by the DWT Non-local mean(NLM) filter has been used. The experimental result shows that the proposed algorithm gives good results based on image quality parameters as compared with the state-of-the-art works in super resolution (SR) process.
Impact of channel tapering on threshold voltage variation in multi-layer word line 3 dimensional NAND structures
(CRC Press, 2024) Bhatt, Upendra Mohan
This work investigates the problems caused by the new multi-layer word line (WL) counts in 3D NAND flash memory, a technology that radically changes conventional memory designs. This study explores the effects of channel doping and taper angle on the electrical properties of vertical 3D NAND Flash memory to deliver issues related to increasing overall mold height and channel tapering. Operating Sentaurus technology computer-aided design (TCAD) tools, the investigation inspects the threshold voltage (Vth) appropriation among word lines (WLs) along the string. The goal is to assess current difficulties and propose a viable way to deal with achieving stable Vth dissemination. This includes breaking down the impacts of various shape points and channel doping levels on the electrical attributes of vertical 3D NAND flash memory. The results are expected to help improve the technology behind 3D NAND Flash memory.
Intelligent Virtual Laboratory Development and Implementation using the RASA Framework
(IEEE, 2023-04) Bhatt, Upendra Mohan
Virtual environments for learning with intelligent support are in high demand right now. This is due to the fact that smart e-learning environments must be built internally in order to increase students' hands-on abilities. Through inquiry and demonstration in a smart e-lab environment, these talents are linked to several disciplines of science and engineering. Students and instructors may make the transition from working in virtual environments to doing experiments using actual materials. Lab assistants often spend the bulk of their time making the same mistakes. As a result, this research looked at the technology, proposed approach, and implementation of an intelligent virtual C programming laboratory. This ensures that virtual assistants employ chatbots to fix student faults. The environment is based on his NLP (natural language processing) and machine learning models, with web application development using his MERN stack and virtual assistant production using the RASA, Artificial Intelligence (AI) framework.
Leaf classification and identification using Canny Edge Detector and SVM classifier
(IEEE, 2017-10) Bhatt, Upendra Mohan
Plants are to be considered as one of the important things that plays a very essential role for all living beings exists on earth. But due to some unawareness and environment deterioration, some very rare plants are on the verge of extinction. Knowledge of rare leaves used for medicine and other plants is very critical in future. Leaf identification and classification plays a vital role for plant species recognition. In recent years, most of the researchers dedicate their work on leaf characterization. Leaf shape is the major parameter to classify plants. A new approach is to extract 15 features from the leaf using Canny Edge Detector and classify 22 different kinds of plants with SVM classifier.
A machine learning framework for predictive electron density modelling to enhance 3D NAND flash memory performance
(Elsevier, 2024-12) Bhatt, Upendra Mohan
Data storage in electronic devices has been revolutionised by 3D NAND flash memory. However, polycrystalline silicon and grain boundaries offer issues that greatly affect memory performance in terms of string current and Program-Erase Threshold Voltage window (Vt –Window). Scientists need to learn more about how grain size, channel thickness, and trap density affect electron behaviour to improve the efficiency of memory chips. Regression models are used in this work to forecast fluctuations in electron density along the channel in 3D NAND string devices. The dataset, which was derived using TCAD simulations, has a sizable number of samples that show the electron density as a function of channel length. We assess their performance using R2 scores and RMSE values using regression models such as Linear Regression, Random Forest, K-Neighbour Regressor, Decision Tree, Gradient Boosting, XGBRegressor, CatBoosting Regressor, and AdaBoost Regressor. By improving our knowledge of how electrons behave in transistor channels, this work contributes to the optimisation of 3D NAND flash memory.
Message from TPC Co-Chairs
(IEEE, 2024-06) Bhatt, Upendra Mohan
Mitigating Pillar-to-Pillar Variability of Ground Select Transistor in 3-D NAND Flash Memory
(IEEE, 2020-08) Bhatt, Upendra Mohan
The threshold voltage variability of the select transistors is an important issue in the development of 3-D NAND flash memory. Particularly, pillar-to-pillar variations in threshold voltage (VT) of the ground select transistor (GST) are critical across the wafer. The VT variation is attributed to the nonuniformity in the plug height of the epitaxially grown silicon layers in different pillars. In this article, we propose different techniques to achieve performance uniformity in different strings across the wafer in terms of VT distribution of GST. We show that by optimizing the channel doping and gate metal work function (WF) of the GST, the NAND string VT nonuniformity can be eliminated. It is also shown that VT variability can be further minimized by optimizing GST gate length. Further, we present a two-MOSFET model for the pillar-to-pillar VT variation across the wafer. This study providesimportant results for designing 3-D NAND memories with higher performance uniformity for the pillar-to-pillar variations in strings across the wafer.
Mitigating the Impact of Channel Tapering in Vertical Channel 3-D NAND
(IEEE, 2020) Bhatt, Upendra Mohan
The channel tapering from top to bottom in vertical channel 3-D NAND is a major concern. This leads to nonuniformity in the NAND string performance, including cell current (Icell) and threshold voltage (VT) variation along the vertical NAND string. In this article, we show that the variation in the electric field due to the difference in the channel radius from bottom to top is the root cause behind the VT variation along the string. For the first time, we propose novel techniques to minimize the adverse effects of the channel tapering on VT variations. It is shown that graded channel doping (~1018 cm-3 at the bottom to ~ 1015 cm-3 at the top) results in the narrowing of the VT variation by ~90% along the vertical string. Further, we propose that a nonuniform block oxide thickness along the string can be used to enhanced uniformity of VT distribution from bottom to top. Additionally, we investigate and show that the uniformity in VT distribution among word line (WL) transistors can also be achieved by optimizing the amplitude and duration of the position-dependent program/erase voltages. The proposed techniques in this article have a high potential for designing variation tolerant and reliable 3-D NAND memories having enhanced uniformity in the program/erase VT and Icell distribution.