Search results for: Archana Athawale

Authors: H.B.Kekre, Archana Athawale, Pallavi N.Halarnkar

Abstract:

Steganography, derived from Greek, literally means “covered writing". It includes a vast array of secret communications methods that conceal the message-s very existence. These methods include invisible inks, microdots, character arrangement, digital signatures, covert channels, and spread spectrum communications. This paper proposes a new improved version of Least Significant Bit (LSB) method. The approach proposed is simple for implementation when compared to Pixel value Differencing (PVD) method and yet achieves a High embedding capacity and imperceptibility. The proposed method can also be applied to 24 bit color images and achieve embedding capacity much higher than PVD.

Keywords: Information Hiding, LSB Matching, PVD Steganography.

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Authors: Archana Mukherjee, Aruna Korde, Sudipta Chakraborty, H. D. Sarma, Grace Samuel, M. R. A. Pillai

Abstract:

Radiolabeled cyclic RGD peptides targeting integrin αvβ3 are reported as promising agents for the early diagnosis of metastatic tumors. With an aim to improve tumor uptake and retention of the peptide, cyclic RGD peptide dimer E[c (RGDfK)] 2 (E = Glutamic acid, f = phenyl alanine, K = lysine) coupled to the bifunctional chelator DOTA was custom synthesized and radiolabelled with 68Ga. Radiolabelling of cyclic RGD peptide dimer with 68Ga was carried out using HEPES buffer and biological evaluation of the complex was done in nude mice bearing HT29 tumors.

Keywords: 68Ga peptides, Angiogenesis imaging, Cyclic RGD peptides, PET Imaging.

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Authors: Archana S. Nanoty, A. R. Chudasama

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Three-phase induction machines are today a standard for industrial electrical drives. Cost, reliability, robustness and maintenance free operation are among the reasons these machines are replacing dc drive systems. The development of power electronics and signal processing systems has eliminated one of the greatest disadvantages of such ac systems, which is the issue of control. With modern techniques of field oriented vector control, the task of variable speed control of induction machines is no longer a disadvantage. The need to increase system performance, particularly when facing limits on the power ratings of power supplies and semiconductors, motivates the use of phase number other than three, In this paper a novel scheme of connecting two, three phase induction motors in parallel fed by two inverters; viz. VSI and CSI and their vector control is presented.

Keywords: Field oriented control, multiphase induction motor, power electronics converter.

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Authors: Ankit Jain, Archana Agrawal

Abstract:

With the ever-increasing need for wireless communication and the emergence of many systems, it is important to design broadband antennas to cover a wide frequency range. The aim of this paper is to design a broadband patch antenna, employing the three techniques of slotting, adding directly coupled parasitic elements, and fractal EBG structures. The bandwidth is improved from 9.32% to 23.77%. A wideband ranging from 4.15 GHz to 5.27 GHz is obtained. Also a comparative analysis of embedding EBG structures at different heights is also done. The composite effect of integrating these techniques in the design provides a simple and efficient method for obtaining low profile, broadband, high gain antenna. By the addition of parasitic elements the bandwidth was increased to only 18.04%. Later on by embedding EBG structures the bandwidth was increased up to 23.77%. The design is suitable for variety of wireless applications like WLAN and Radar Applications.

Keywords: Bandwidth, broadband, EBG structures, parasitic elements, Slotting.

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Authors: Alexandros Leontitsis, Archana P. Sangole

Abstract:

This article presents a short discussion on optimum neighborhood size selection in a spherical selforganizing feature map (SOFM). A majority of the literature on the SOFMs have addressed the issue of selecting optimal learning parameters in the case of Cartesian topology SOFMs. However, the use of a Spherical SOFM suggested that the learning aspects of Cartesian topology SOFM are not directly translated. This article presents an approach on how to estimate the neighborhood size of a spherical SOFM based on the data. It adopts the L-curve criterion, previously suggested for choosing the regularization parameter on problems of linear equations where their right-hand-side is contaminated with noise. Simulation results are presented on two artificial 4D data sets of the coupled Hénon-Ikeda map.

Keywords: Parameter estimation, self-organizing feature maps, spherical topology.

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Authors: K. A. Navas, S. Archana Thampy, M. Sasikumar

Abstract:

Medical image data hiding has strict constrains such as high imperceptibility, high capacity and high robustness. Achieving these three requirements simultaneously is highly cumbersome. Some works have been reported in the literature on data hiding, watermarking and stegnography which are suitable for telemedicine applications. None is reliable in all aspects. Electronic Patient Report (EPR) data hiding for telemedicine demand it blind and reversible. This paper proposes a novel approach to blind reversible data hiding based on integer wavelet transform. Experimental results shows that this scheme outperforms the prior arts in terms of zero BER (Bit Error Rate), higher PSNR (Peak Signal to Noise Ratio), and large EPR data embedding capacity with WPSNR (Weighted Peak Signal to Noise Ratio) around 53 dB, compared with the existing reversible data hiding schemes.

Keywords: Biomedical imaging, Data security, Datacommunication, Teleconferencing.

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Authors: M.V Rajesh, Archana R, A Unnikrishnan, R Gopikakumari, Jeevamma Jacob

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The System Identification problem looks for a suitably parameterized model, representing a given process. The parameters of the model are adjusted to optimize a performance function based on error between the given process output and identified process output. The linear system identification field is well established with many classical approaches whereas most of those methods cannot be applied for nonlinear systems. The problem becomes tougher if the system is completely unknown with only the output time series is available. It has been reported that the capability of Artificial Neural Network to approximate all linear and nonlinear input-output maps makes it predominantly suitable for the identification of nonlinear systems, where only the output time series is available. [1][2][4][5]. The work reported here is an attempt to implement few of the well known algorithms in the context of modeling of nonlinear systems, and to make a performance comparison to establish the relative merits and demerits.

Keywords: Multilayer neural networks, Radial Basis Functions, Clustering algorithm, Back Propagation training, Extended Kalmanfiltering, Mean Square Error, Nonlinear Modeling, Cramer RaoLower Bound.

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Authors: Archana Panchapakesan Iyer, Taha Abdullah Kumosani

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Many high-risk pathogens that cause disease in humans are transmitted through various food items. Food-borne disease constitutes a major public health problem. Assessment of the quality and safety of foods is important in human health. Rapid and easy detection of pathogenic organisms will facilitate precautionary measures to maintain healthy food. The Polymerase Chain Reaction (PCR) is a handy tool for rapid detection of low numbers of bacteria. We have designed gene specific primers for most common food borne pathogens such as Staphylococci, Salmonella and E.coli. Bacteria were isolated from food samples of various food outlets and identified using gene specific PCRs. We identified Staphylococci, Salmonella and E.coli O157 using gene specific primers by rapid and direct PCR technique in various food samples. This study helps us in getting a complete picture of the various pathogens that threaten to cause and spread food borne diseases and it would also enable establishment of a routine procedure and methodology for rapid identification of food borne bacteria using the rapid technique of direct PCR. This study will also enable us to judge the efficiency of present food safety steps taken by food manufacturers and exporters.

Keywords: food borne pathogens, PCR, food safety, rapiddetection.

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Authors: Apoorva Vinod, Archana Mathur, Snehanshu Saha

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Though there exists a plethora of Activation Functions (AFs) used in single and multiple hidden layer Neural Networks (NN), their behavior always raised curiosity, whether used in combination or singly. The popular AFs – Sigmoid, ReLU, and Tanh – have performed prominently well for shallow and deep architectures. Most of the time, AFs are used singly in multi-layered NN, and, to the best of our knowledge, their performance is never studied and analyzed deeply when used in combination. In this manuscript, we experiment on multi-layered NN architecture (both on shallow and deep architectures; Convolutional NN and VGG16) and investigate how well the network responds to using two different AFs (Sigmoid-Tanh, Tanh-ReLU, ReLU-Sigmoid) used alternately against a traditional, single (Sigmoid-Sigmoid, Tanh-Tanh, ReLU-ReLU) combination. Our results show that on using two different AFs, the network achieves better accuracy, substantially lower loss, and faster convergence on 4 computer vision (CV) and 15 Non-CV (NCV) datasets. When using different AFs, not only was the accuracy greater by 6-7%, but we also accomplished convergence twice as fast. We present a case study to investigate the probability of networks suffering vanishing and exploding gradients when using two different AFs. Additionally, we theoretically showed that a composition of two or more AFs satisfies Universal Approximation Theorem (UAT).

Keywords: Activation Function, Universal Approximation function, Neural Networks, convergence.

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Authors: Patil Ashwini, Archana Thosar

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This paper addresses the mathematical model of wind energy system useful for designing fault tolerant control. To serve the demand of power, large capacity wind energy systems are vital. These systems are installed offshore where non planned service is very costly. Whenever there is a fault in between two planned services, the system may stop working abruptly. This might even lead to the complete failure of the system. To enhance the reliability, the availability and reduce the cost of maintenance of wind turbines, the fault tolerant control systems are very essential. For designing any control system, an appropriate mathematical model is always needed. In this paper, the two-mass model is modified by considering the frequent mechanical faults like misalignments in the drive train, gears and bearings faults. These faults are subject to a wear process and cause frictional losses. This paper addresses these faults in the mathematics of the wind energy system. Further, the work is extended to study the variations of the parameters namely generator inertia constant, spring constant, viscous friction coefficient and gear ratio; on the pole-zero plot which is related with the physical design of the wind turbine. Behavior of the wind turbine during drive train faults are simulated and briefly discussed.

Keywords: Mathematical model of wind energy system, stability analysis, shaft stiffness, viscous friction coefficient, gear ratio, generator inertia, fault tolerant control.

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