Conference Papers
Permanent URI for this collectionhttps://idr.nitk.ac.in/handle/123456789/28506
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Item Comparative study of ocean wave spectrum using ENVISAT SAR data and wave rider buoy data(2006) Pai, J.; Kumar, R.; Sarkar, A.; Hegde, A.V.; Dwarakish, G.S.A comparative study of ENVISAT ASAR data and corresponding wave rider buoy data has been attempted. An algorithm has been developed to retrieve Ocean Wave Spectrum from SAR data. The resulting spectrum is compared with the wave rider buoy measured wave spectrum. To compute the 2-D image spectrum from multi-look SAR data, various corrections to the original SAR data has been applied. Thereafter, Modulation Transfer Function has been computed and utilized to convert image spectrum to the Ocean Wave Spectrum. This final ocean wave height spectrum is used to estimate the ocean wave spectral parameters and has been compared with the in-situ measurements and model derived wave spectrum. An attempt has also been made to process the Single Look Complex (SLC) data to reduce the speckle noise in the SAR data using Fast Fourier Transform (FFT).Item Lossless compression of digital mammography using fixed block segmentation and pixel grouping(2008) Kumar, R.; Koliwad, S.; Dwarakish, G.S.A mammography is a specific type of imaging that uses low-dose x-ray system to examine breasts. This is an efficient means of early detection of breast cancer. High resolution is a common characteristic of such images. Archiving and retaining these data for at least three years is expensive, difficult and requires sophisticated data compression techniques. In this paper an efficient method is proposed for lossless compression of mammography images. After performing de-correlation of the image using two efficient predictors, the residue image is divided into 4x4 blocks. The blocks with all-zero pixels are identified using one bit code. Later, Second order of pixel grouping is employed to the remaining blocks to increase the coding efficiency. Such blocks are coded using Base offset method. Special techniques are used to save the header information. The method is tested using 25 mammograms from the MIAS database, each having a resolution of 1024x1024 pixels with 8 bits/pixel. Experimental results indicate better compression ratio when compared to JPEG 2000, JPEG-LS, PNG and JBIG. © 2008 IEEE.Item Exploring the effectiveness of social capabilities and goal alignment in computer supported collaborative learning(2010) Ai, H.; Kumar, R.; Nguyen, D.; Nagasunder, A.; Rosé, C.P.In this study, we describe a conversational agent designed to support collaborative learning interactions between pairs of students. We describe a study in which we independently manipulate the social capability and goal alignment of the agent in order to investigate the impact on student learning outcomes and student perceptions. Our results show a significant interaction effect between the two independent variables on student learning outcomes. While there are only a few perceived differences related to student satisfaction and tutor performance as evidenced in the questionnaire data, we observe significant differences in student conversational behavior, which offer tentative explanations for the learning outcomes we will investigate in subsequent work. © 2010 Springer-Verlag.Item Design of series, Fi=Fi-1+Fi-3 for the denominators (1, 2,6) of switched capacitor converter(Institute of Electrical and Electronics Engineers Inc., 2017) Subburaj, V.; Jena, D.; Kumar, R.; Deshmukh, A.V.; Nayak, B.; Bansal, H.This paper proposes, the concept of generalized Fibonacci switched capacitor converter for Fi=Fi-1+Fi-3 series. The proposed converter have more efficiency and less equivalent resistance. Generalized Fibonacci switched capacitor converters (SCCs) are technologically advanced which operates on fixed conversion ratio. Different target ratios of Fibonacci series have already been carried out by the researchers to step-up and stepdown configuration. But, different target ratios of Fi=Fi-1+Fi-3 series has not yet proposed. In this paper different fractions 1/4,3/4,1/6,5/6 for SCC is proposed for both step-up and stepdown configurations. Theoretical results and simulation results are verified using PSIM. © 2016 IEEE.Item Optimization of adaptive resonance theory neural network using particle swarm optimization technique(Springer Verlag service@springer.de, 2018) Satpute, K.; Kumar, R.With the advancement of computers and its computational enhancement over several decades of use, but with the growth in the dependencies and use of these systems, more and more concerns over the risk and security issues in networks have raised. In this paper, we have proposed approach using particle swarm optimization to optimize ART. Adaptive resonance theory is one of the most well-known machine-learning-based unsupervised neural networks, which can efficiently handle high-dimensional dataset. PSO on the other hand is a swarm intelligence-based algorithm, efficient in nonlinear optimization problem and easy to implement. The method is based on anomaly detection as it can also detect unknown attack types. PSO is used to optimize vigilance parameter of ART-1 and to classify network data into attack or normal. KDD ’99 (knowledge discovery and data mining) dataset has been used for this purpose. © Springer Nature Singapore Pte Ltd. 2018.Item Non-invasive blood components measurement using optical sensor system interface(Institute of Electrical and Electronics Engineers Inc., 2018) Raikham, P.; Kumar, R.; Shah, R.K.; Hazarika, M.; Sonkar, R.K.In this paper, a non-invasive technique to measure glucose, hemoglobin, SpO2 and heart beat using both IR and Red LEDs is presented. The device is made to simultaneously measure the blood components in real time. A comparison with invasive measurements is also shown. © 2018 IEEE.Item A 73% PAE, Highly Gain Inverse Class-F Power Amplifier for S-Band Applications(Springer Science and Business Media Deutschland GmbH, 2021) Naik, J.D.; Gorre, P.; Kumar, R.; Kumar, S.; Song, H.This paper proposes a continuous-mode inverse Class F power amplifier (PA) achieving wide bandwidth, high output power, and high efficiency. This work includes transmission line-based output/input matching networks and single-ended topology. The main focus of the work is to achieve a high gain with wide bandwidth. The proposed structure incorporates a termination of even and odd harmonics to deliver voltage and current waveform isolation with minimal matching network (MN) design complexities. The analyses simulated in Keysight Technologies Advanced Design System (ADS), which results in a wideband PA design. The results are quantified by using high power-added efficiency (PAE) and output power. PAE of 72.6% and output power more than 41 dBm obtained over wide bandwidth 2–4.2 GHz at −3 dB gain compression. The proposed PA could overcome the traditional performance and utilize for green communication. © 2021, Springer Nature Singapore Pte Ltd.Item Reducing False Prediction on COVID-19 Detection Using Deep Learning(Institute of Electrical and Electronics Engineers Inc., 2021) Bhowmik, B.; Varna, S.A.; Kumar, A.; Kumar, R.This paper proposes a custom deep neural network-based scheme for coronavirus disease 2019 (COVID-19) detection. The proposed method takes X-ray images that use transfer learning techniques on pre-trained models. One objective of this work is to quickening the detection of the virus. Another goal is to reduce the number of falsely detected cases by a significant margin. The experimental setup demonstrates promising results on the selected dataset, which achieve up to 99.74%, 99.69%, 98.80% as classification, precision, and recall accuracy. © 2021 IEEE.Item Next-Generation Technologies Empowered Future IoV(Institute of Electrical and Electronics Engineers Inc., 2022) Rajasekhar, K.; Kumar, R.; Manjappa, M.; Rammohana Reddy, G.The Internet of Vehicles is a network of connected automobiles that can communicate with one another. In the IoV environment, vehicles and sensors, pedestrians, mobile devices, and networking devices are the primary components; improving road safety, proper guidance while driving, autonomous driving, traffic management, infotainment, and entertainment. But with rapid growth in the number of automobiles, high vehicle mobility and networking devices; it isn't easy to achieve the requirements needed for the operation and management of IoV. Next-generation technologies such as 5th Generation (5G) and Software Defined Network (SDN) technologies can significantly address these challenges. These technologies will provide potential solutions for efficient management, enhance the performance of IoV. In this paper, we performed simulation with these technologies in the real world vehicular network along with performance evaluation. In comparison to traditional vehicle networks, our findings show that 5G and software-defined vehicular networks have a lower transmission delay and higher throughput. © 2022 IEEE.Item Survey on Game Theory-Based Security Framework for IoT(Springer, 2023) Joshi, P.; Kamediya, S.; Kumar, R.; Chandavarkar, B.R.The large network of smart devices and the complexity of networks have made it almost impossible to make the data and communication between devices more secure. The number of cyber-attacks on these IoT devices has been steadily increasing. So here a survey on game theory model is presented, and the attackers are rational human beings, so they try to harm the system to their best of ability and so their moves can be predicted which can be used by the defenders with some game theory concepts to take proper security decisions and make an efficient security framework. This chapter is a survey on game theory-based security frameworks and explores and evaluates different types of threats, security requirements and constraints related to IoT, how Game Theory can be used in field of IoT, along with the game theory models used is to develop security frameworks for IoT. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.