...signal. For multimodal optimization we better to use natural-inspired algorithms such as Firefly Algorithm (FA). We compare the firefly algorithm with particle swarm optimization technique. The proposed algorithm contains three module techniques. Those are preprocessing module, optimization module and spectral filtering module. The signals are taken from Loizou’s database and Aurora database for evaluating proposed technique. In this paper we calculate the perceptional evolution of speech quality (PESQ) and signal to noise (SNR) of the enhanced signal. The results of firefly algorithm and PSO are to be compare then we observe that the proposed technique...
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...advantages that it offers like high spectral efficiency, resistance to multipath fading and resistance to frequency selective fading. M oreover, it lends itself to simple channel equalization. Conventional single carrier systems do not provide such advantages and hence, OFDM would almost ubiquitously be used for high speed wireless data transmission. However, the main drawback of such systems over single carrier systems is that in the presence of noise, there is an increased computational complexity at the receiver end to decode the data. In this paper, a low complexity detection algorithm is proposed for OFDM systems. M aximum likelihood detection is taken as the baseline detection algorithm and the proposed algorithm is compared with M L detection algorithm. Comparison results are plotted and conclusions are drawn. Reference [4] provides an iterative detection scheme for OFDM in presence of impulsive noise while [5] proposes an impulsive noise mitigation scheme for over-sampled OFDM systems. Performance and design of impulse noise detector for OFDM systems is provided in [6]. Reference [7] proposes an MM SE detection...
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...Conference on Emerging Trends in Engineering and Technology Rough Set Approach for Feature Reduction in Pattern Recognition through Unsupervised Artificial Neural Network A. G. Kothari A.G. Keskar A.P. Gokhale Rucha Pranjali Lecturer Professor Professor Deshpande Deshmukh agkothari72@re B.Tech Student B.Tech Student diffmail.com Department of Electronics & Computer Science Engineering, VNIT, Nagpur Abstract The Rough Set approach can be applied in pattern recognition at three different stages: pre-processing stage, training stage and in the architecture. This paper proposes the application of the Rough-Neuro Hybrid Approach in the pre-processing stage of pattern recognition. In this project, a training algorithm has been first developed based on Kohonen network. This is used as a benchmark to compare the results of the pure neural approach with the RoughNeuro hybrid approach and to prove that the efficiency of the latter is higher. Structural and statistical features have been extracted from the images for the training process. The number of attributes is reduced by calculating reducts and core from the original attribute set, which results into reduction in convergence time. Also, the above removal in redundancy increases speed of the process reduces hardware complexity and thus enhances the overall efficiency of the pattern recognition algorithm Keywords: core, dimensionality reduction, feature extraction, rough sets, reducts, unsupervised ANN as any type of ANN is the most...
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...HadoopJitter: The Ghost in the Cloud and How to Tame It Vivek Kale∗ , Jayanta Mukherjee† , Indranil Gupta‡ , William Gropp§ Department of Computer Science, University of Illinois at Urbana-Champaign 201 North Goodwin Avenue, Urbana, IL 61801-2302, USA Email: ∗ vivek@illinois.edu, † mukherj4@illinois.edu, ‡ indy@illinois.edu, § wgropp@illinois.edu Abstract—The small performance variation within each node of a cloud computing infrastructure (i.e. cloud) can be a fundamental impediment to scalability of a high-performance application. This performance variation (referred to as jitter) particularly impacts overall performance of scientific workloads running on a cloud. Studies show that the primary source of performance variations comes from disk I/O and the underlying communication network [1]. In this paper, we explore the opportunities to improve performance of high performance applications running on emerging cloud platforms. Our contributions are 1. the quantification and assessment of performance variation of data-intensive scientific workloads on a small set of homogeneous nodes running Hadoop and 2. the development of an improved Hadoop scheduler that can improve performance (and potentially scalability) of these application by leveraging the intrinsic performance variation of the system. In using our enhanced scheduler for data-intensive scientific workloads, we are able to obtain more than a 21% performance gain over the default Hadoop scheduler. I. I NTRODUCTION Certain...
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...RSA Key Extraction via Low-Bandwidth Acoustic Cryptanalysis∗ Daniel Genkin Technion and Tel Aviv University danielg3@cs.technion.ac.il Adi Shamir Weizmann Institute of Science adi.shamir@weizmann.ac.il Eran Tromer Tel Aviv University tromer@cs.tau.ac.il December 18, 2013 Abstract Many computers emit a high-pitched noise during operation, due to vibration in some of their electronic components. These acoustic emanations are more than a nuisance: they can convey information about the software running on the computer, and in particular leak sensitive information about security-related computations. In a preliminary presentation (Eurocrypt’04 rump session), we have shown that different RSA keys induce different sound patterns, but it was not clear how to extract individual key bits. The main problem was that the acoustic side channel has a very low bandwidth (under 20 kHz using common microphones, and a few hundred kHz using ultrasound microphones), many orders of magnitude below the GHz-scale clock rates of the attacked computers. In this paper we describe a new acoustic cryptanalysis key extraction attack, applicable to GnuPG’s current implementation of RSA. The attack can extract full 4096-bit RSA decryption keys from laptop computers (of various models), within an hour, using the sound generated by the computer during the decryption of some chosen ciphertexts. We experimentally demonstrate that such attacks can be carried out, using either a plain mobile phone placed...
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...S.Bhavani et. al. / (IJCSE) International Journal on Computer Science and Engineering Vol. 02, No. 05, 2010, 1429-1434 A Survey On Coding Algorithms In Medical Image Compression S.Bhavani Department of ECE Sri Shakthi Institute of Engineering & Technology Coimbatore, India Abstract— In medical imaging, lossy compression schemes are not used due to possible loss of useful clinical information and as operations like enhancement may lead to further degradations in the lossy compression. Hence there is a need for efficient lossless schemes for medical image data. Several lossless schemes based on linear prediction and interpolations have been proposed. Currently, context based approach has gained popularity since it can enhance the performance of above schemes due to the exploitation of correlation within the frame. Since the conception of Mesh based Compression from early 1990’s many algorithms has been proposed and the research literature on this topic has experienced a rapid growth which is hard to keep track of. This paper gives a brief description about the various coding algorithms and advancements in this field. Keywords- Image compression, prediction, medical image, context based modeling, object based coding, wavelet transform. Dr.K.Thanushkodi Director Akshaya College of Engineering & Technology Coimbatore, India image compression schemes, the probability assignment is generally divided as i) A prediction step, in which a deterministic value is guessed for the...
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...A Novel Channel Estimation Algorithm for 3GPP LTE Downlink System Using Joint Time-Frequency Two-Dimensional Iterative Wiener Filter Jinfeng Hou, Jian Liu School of Communication and Information Engineering University of Electronic Science and Technology of China (UESTC) Chengdu 611731, China Email: houjinfeng@gmail.com, liuj@uestc.edu.cn Abstract—The channel estimation algorithms are employed in 3GPP Long Term Evolution (LTE) downlink system to assist the coherent demodulation of Orthogonal Frequency Division Multiplexing (OFDM) symbols. Based on the comparison of several exiting different channel estimation algorithms, we propose a joint time-frequency two-dimensional iterative Wiener filter (IWF) channel estimation algorithm for 3GPP LTE downlink system. In this scheme, we first apply the linear minimum mean square error (LMMSE) algorithm based on singular value decomposition (SVD) for IWF in frequency domain, and then the values after the first filtering in frequency domain are used to achieve the second IWF in time domain. Comparing to the conventional algorithms, the channel estimation algorithm proposed by this paper brings up lower bit error rate (BER) and adds little computational complexity. I. I NTRODUCTION In December 2004, the Third Generation Partnership Program (3GPP) members started a feasibility study on the enhancement of the Universal Terrestrial Radio Access (UTRA) in the aim of continuing the long time frame competitiveness of the 3G Universal Mobile Telecommunications...
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...Rather, they are stored in whatever way makes them easiest to use, such as: ASCII text from word processors, binary code that can be executed on a computer, individual samples from a data acquisition system, etc. Typically, these easy-to-use encoding methods require data files about twice as large as actually needed to represent the information. Data compression is the general term for the various algorithms and programs developed to address this problem. A compression program is used to convert data from an easy – to - use format to one optimized for compactness. Likewise, an uncompressing program returns the information to its original form. World over, the rapid growth in information and communication technologies has led to an explosive demand for effective means to compress and store data. And this data is no longer simple text, but encompasses a variety of formats from text, images to moving pictures. Despite the continuous research in compression technologies and the emergence of compression standards for audio, video, images and text, the quest for the perfect compression algorithm is still on. Many companies have entered the gun lap in the race to define compression standards, especially for the most complex and demanding format of all, the moving pictures. Here we examine the new innovation ABO (Adaptive Binary Optimization). INTRODUCTION Compression approaches have been many and diverse. Most of these, especially when it comes to images, revolve around the technique...
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...Study On The Reduction Of Speckle Noise In Ultrasound Images Mrs.Parineeta Suman1,Mrs.Deepa Parasar2,Dr Vijay Rathode3 1 Student (M.E), SCOE, Mumbai 2 Assistant Professor, SCOE, Mumbai 3 Ph.D, IIT Roorkee In summary, the ultrasound images, the speckle noise is inherent in medical ultrasound images and it is the cause of reduced contrast-to-noise ratio and resolution. The presence of speckle noise is not attractive because it reduces the image quality and affects the tasks of the individual interpretation and paper diagnosis.This this study various techniques to reduce speckle noise from ultrasound images Post acquisition method as the only scale spatial filtering method and multi-scale method. Keywords- noising, speckle noise, isotropic scattering transform Contourlet 1. Introduction Ultrasound images are widely used in the medical field as it is relatively safe, economical, adaptable and transferable. Despite many advantages, ultrasound images contain noise called "speckle" that corrupts the image resolution and contrast makes the interpretation of the physical structure lying below extremely difficult for physicians. Speckle noise in ultrasound image is introduced due to the nature of the consistency of the imaging modality, the interference of backscattered...
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...mechanomyogram (MMG) signal is observable at the surface of the muscle due to the movement of the muscle fibers underneath. A VMG sensor is able to capture muscle force data in real time. New research becomes necessary to improve the efficiency of MMG systems and increase their application in rehabilitation, clinical and other health areas. 1.2 Problem Statement In many researches, microphones and accelerometers are used to capture muscle signal especially MMG signal. Sometimes our signal disturbed by noise and environmental condition. To overcome this noise problem, many authors conduct researches to find best solution. There is also some specific condition that make MMG signal to give accurate readings. 1.3 Objective of the project • To establish an accurate experiment procedure to collect MMG signal. • To develop an experimental set up to collect MMG signals generated by the forearm muscles during different types of hand gesture. • To develop various feature extraction algorithms software that can identify multiple hand gesture using MMG signal. • To develop a system that monitor muscle activities. • To incorporate machine learning for the purpose of hand gesture recognition. 1.4 Scope of the project This research is to study recognition of multiple hand gesture using MMG signal. There are some subjects that involves in this project that learn in class such as signal and system, machine vision, artificial intelligent, mathematics, technical writing and others. This project...
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...SELF NAVIGATING AUTONOMOUS BOT Major-Project Report by Arjun Surendran B080001EC Deepak Venga B080027EC Nandu Raj B080585EC Priyanka G Das B080312EC Sanjay George B080270EC Under the guidance of Dr. S. M. SAMEER Submitted in Partial Fulfillment of the Requirements for the degree of Bachelor of Technology In ELECTRONICS AND COMMUNICATION ENGINEERING DEPARTMENT OF ELECTRONICS AND COMMUNICATION ENGINEERING NATIONAL INSTITUTE OF TECHNOLOGY CALICUT Kerala, India April 2012 NATIONAL INSTITUTE OF TECHNOLOGY CALICUT DEPARTMENT OF ELECTRONICS AND COMMUNICATION ENGINEERING CERTIFICATE This is to certify that this report titled SELF NAVIGATING AUTONOMOUS BOT is a bona fide record of the major-project done by Arjun Surendran Deepak Venga Nandu Raj Priyanka G Das Sanjay George B080001EC B080027EC B080585EC B080312EC B080270EC In partial fulfillment of the requirements for the award of Degree of Bachelor of Technology in Electronics and Communication Engineering from National Institute of Technology, Calicut. Dr. S. M. Sameer (Project Advisor) Assistant Professor Dr. P S Sathidevi Professor & Head April 2012 NIT Calicut i ACKNOWLEDGEMENT We would like to thank Dr. S. M. Sameer, Assistant Professor, Department of Electronics and Communication Engineering for his guidance and inspiration in helping us complete this project. We are also grateful to Dr. P S Sathidevi, Professor and Head, Department of Electronics and Communication...
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...The approach introduced in this paper is totally depending on the shape parameters of the hand gesture. It does not consider any other mean of hand gesture recognition like skin color, texture because these image based features are extremely variant to different light conditions and other influences. To implement this approach we have utilized a simple web cam which is working on 20 fps with 7 mega pixel intensity. On having the input sequence of images through web cam it uses some pre-processing steps for removal of background noise and employs K-means clustering for segmenting the hand object from rest of the background, so that only segmented significant cluster or hand object is to be processed in order to calculate shape based features. This simple shape based approach to hand gesture recognition can identify around 45 different gestures on the bases of 5 bit binary string resulted as the output of this algorithm. This proposed implemented algorithm has been tested over 450 images and it gives approximate recognition rate of...
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...Oil Price Prediction using Artificial Neural Networks Author: Siddhant Jain, 2010B3A7506P Birla Institute of Technology and Science, Pilani Abstract: Oil is an important commodity for every industrialised nation in the modern economy. The upward or downward trends in Oil prices have crucially influenced economies over the years and a priori knowledge of such a trend would be deemed useful to all concernd - be it a firm or the whole country itself. Through this paper, I intend to use the power of Artificial Neural Networks (ANNs) to develop a model which can be used to predict oil prices. ANNs are widely used for modelling a multitude of financial and economic variables and have proven themselves to be a very powerful tool to handle volumes of data effectively and analysing it to perform meaningful calculations. MATLAB has been employed as the medium for developing the neural network and for efficiently handling the volume of calculations involved. Following sections shall deal with the theoretical and practical intricacies of the aforementioned model. The appendix includes snapshots of the generated results and other code snippets. Artificial Neural Networks: Understanding To understand any of the ensuing topics and the details discussed thereof, it is imperative to understand what actually we mean by Neural Networks. So, I first dwell into this topic: In simplest terms a Neural Network can be defined as a computer system modelled on the human brain and nervous system...
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...Document Type: Prentice Hall Author: John G. Proakis and Masoud Salehi Book: Communication Systems Engineering Copyright: 2002 ISBN: 0-13-061793-8 NI Supported: No Publish Date: Sep 6, 2006 Multicarrier Modulation and OFDM Overview This tutorial is part of the National Instruments Signal Generator Tutorial series. Each tutorial in this series, will teach you a specific topic of common measurement applications, by explaining the theory and giving practical examples. This tutorial covers multicarrier modulation and OFDM. For additional signal generator concepts, refer to the Signal Generator Fundamentals main page. Table of Contents 1. Multicarrier Modulation and OFDM 2. Further Reading 3. Relevant NI products Multicarrier Modulation and OFDM In the preceding sections, we considered digital transmission through nonideal channels and observed that such channels cause intersymbol interference when the reciprocal of the system rate is significantly smaller than the time dispersion (duration of the impulse response) of the nonideal channel. In such a case, a channel equalizer is employed at the receiver to compensate for the channel distortion. If the channel is a bandpass channel with a specified bandwidth, the information-bearing signal may be generated at the baseband and then translated in frequency to the passband of the channel. Thus, the information-bearing signal is transmitted on a single carrier. We also observed that intersymbol interference usually results...
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...Learning Automata 6 Chapter 2 Literature Review 7 2.1 Edge Detection: Methodology 7 2.1.1 First Order Derivative Edge Detection 7 2.1.1.1 Prewitts Operator 7 2.1.1.2 [pic] Sobel Operator 8 2.1.1.3 Roberts Cross Operator 11 2.1.1.4 Threshold Selection 11 2.1.2 Second Order Derivative Edge Detection 11 2.1.2.1 Marr-Hildreth Edge Detector 11 2.1.2.2 Canny Edge Detector 12 2.1.3 Soft Computing Approaches to Edge Detection 13 2.1.3.1 Fuzzy Based Approach 14 2.1.3.2 Genetic Algorithm Approach 14 2.1.4 Cellular Learning Automata 15 Chapter 3 Fuzzy Image Processing 18 3.1 Need for Fuzzy Image Processing 19 3.2 Introduction to Fuzzy sets and Crisp sets 20 3.2.1 Classical sets (Crisp sets) 20 3.2.2 Fuzzy sets 21 3.3 Fuzzification 22 3.4 Membership Value Assignment 22 3.5 Defuzzification 23 3.6 Enhancing Edges Using Cellular Learning Automata 26 3.6.1 Divide the Edgy Image Into Overlapping 3 × 3 Windows 26 3.6.2 Penalty and Rewards. 27 Chapter 4 Implementation 30 4.1 Simple algorithm for edge detection using Fuzzy Logic 30 Chapter 5 Conclusion 38 References 39 Appendix A : Acronyms 41 Appendix B : Review Card 42 Appendix C: Compliance Report of Review...
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