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    2523 research outputs found

    A HARD REAL-TIME SCHEDULER ALGORITHM FOR SOLID STATE DEVICE

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    This paper presents an approach to use the solid state devices in hard real time application where delay in retrieval or write of data to and fro to them can result in a catastrophe. This new algorithm proposes a new approach of scheduling by considering the deadline’s associated with data’s, multiple synchronous read or write requests along with the algorithm for overcoming the problem of performing new block writes resulting in I/O bottleneck

    CONSTRAINT ROBUST PORTFOLIO SELECTION BY MULTIOBJECTIVE EVOLUTIONARY GENETIC ALGORITHM

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    The problem of portfolio selection is a very challenging problem in computational finance and has received a lot of attention in last few decades. Selecting an asset and optimal weighting of it from a set of available assets is a critical issue for which the decision maker takes several aspects into consideration. Different constraints like cardinality constraints, minimum buy in thresholds and maximum limit constraint are associated with assets selection. Financial returns associated are often strongly non-Gaussian in character, and exhibit multivariate outliers. Taking these constraints into consideration and with the presence of these outliers we consider a multi-objective problem where the percentage of each available asset is so selected that the total profit of the portfolio is maximized while total risk is minimized. Nondominated Sorting Genetic Algorithm-II is used for solving this multiobjective portfolio selection problem. Performance of the proposed algorithm is carried out by performing different numerical experiments using real-world data

    The Design and Development of Microstrip Patch Antenna using simulation studies by ADS

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    The matching network of a Microstrip Patch Antenna at 10.65 GHz was designed and developed using the software Advanced Design System (ADS). ADS is a powerful software for designing microwave electronic circuits. The Microstrip Patch antenna thus developed was tested at 10m Far Field Antenna Anechoic Chamber and Momentum Simulation studies of the same was carried out using a Network Analyzer that can analyze signals in GHz range

    SECURE DEPENDABLE SELECTIVE STORAGE SERVICES AND SUPPORT FOR DYNAMIC DATA OPERATIONS IN CLOUD COMPUTING

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    Cloud computing has been envisioned as the next generation architecture of IT enterprise. It moves the application software and databases to the centralized large data centers where management of data and services may not be fully trustworthy. This unique paradigm brings out many new security challenges like, maintaining correctness and integrity of data in cloud. Integrity of cloud data may be lost due to unauthorized access, modification or deletion of data. Lacking of availability of data may be due to the cloud service providers (CSP), in order to increase their margin of profit by reducing the cost, CSP may discard rarely accessed data without detecting in timely fashion. To overcome above issues, flexible distributed storage, token utilizing, signature creations used to ensure integrity of data, auditing mechanism used assists in maintaining the correctness of data and also locating, identifying of server where exactly the data has been corrupted and also dependability and availability of data achieved through distributed storage of data in cloud. Further in order to ensure authorized access to cloud data a admin module has been proposed in our previous conference paper, which prevents unauthorized users from accessing data and also selective storage scheme based on different parameters of cloud servers proposed in previous paper, in order to provide efficient storage of data in the cloud. In order to provide more efficiency in this paper dynamic data operations are supported such as updating, deletion and addition of data

    Steganography and Steganalysis : Different Approaches

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    Steganography is the technique of hiding confidential information within any media. Steganography is often confused with cryptography because the two are similar in the way that they both are used to protect confidential information. The difference between the two is in the appearance in the processed output; the output of steganography operation is not apparently visible but in cryptography the output is scrambled so that it can draw attention. Steganlysis is process to detect of presence of steganography. In this article we have tried to elucidate the different approaches towards implementation of steganography using ‘multimedia’ file (text, static image, audio and video) and Network IP datagram as cover. Also some methods of steganalysis will be discussed

    An Intelligent Agent Based Intrusion Detection System Using Fuzzy Rough Set Based Outlier Detection

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    Since existing Intrusion Detection Systems (IDS) including misuse detection and anomoly detection are generally incapable of detecting new type of attacks. However, all these systems are capable of detecting intruders with high false alarm rate. It is an urgent need to develop IDS with very high Detection rate and with low False alarm rate. To satisfy this need we propose a new intelligent agent based IDS using Fuzzy Rough Set based outlier detection and Fuzzy Rough set based SVM. In this proposed model we intorduced two different inteligent agents namely feature selection agent to select the required feature set using fuzzy rough sets and decision making agent manager for making final decision. Moreover, we have introduced fuzzy rough set based outlier detection algorithm to detect outliers. We have also adopted Fuzzy Rough based SVM in our system to classify and detect anomalies efficiently. Finally, we have used KDD Cup 99 data set for our experiment, the experimental result show that the proposed intelligent agent based model improves the overall accuracy and reduces the false alarm rate

    Motion Detection in Low Resolution Grayscale Videos Using Fast Normalized Cross Correrelation on GP-GPU

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    Motion estimation (ME) has been widely used in many computer vision applications, such as object tracking, object detection, pattern recognition and video compression. The most popular block based similarity measures are the sum of absolute differences (SAD), the sum of squared differences (SSD) and the normalized cross correlation (NCC). Similarity measure obtained using NCC is more robust under varying illumination changes as compared to SAD and SSD. However NCC is computationally expensive and application of NCC using full or exhaustive search method further increases required computational time. Relatively efficient way of calculating the NCC is to pre-compute sum-tables to perform the normalization referred to as fast NCC (FCC). In this paper we propose real time implementation of full search FCC algorithm applied to gray scale videos using NVIDIA’s Compute Unified Device Architecture (CUDA). We present fine-grained optimization techniques for fully exploiting computational capacity of CUDA. Novel parallelization strategies adopted for extracting data parallelism substantially reduce computational time of exhaustive FCC. We show that by efficient utilization of global, shared and texture memories available on CUDA, we can obtain the speedup of the order of 10x as compared to the sequential implementation of FCC

    Convolutional Coding Using Booth Algorithm For Application in Wireless Communication

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    Convolutional codes are preferred types of error control codes which can achieve low BERs at signal to noise ratio (SNR) very close to Shannon limit. Here, a new method of convolutional encoding is proposed using the general Booth algorithm for multiplication. This algorithm follows a fast multiplication process and achieves a significantly less computational complexity over its conventional counterparts. It can be a useful technique for use in chip design as it provides significant improvements. In this work, the performance of conventional convolutional coding with Viterbi decoding in AWGN channel, is studied and the results show the effectiveness of the work described here

    Speckle Noise Reduction in B-mode Ultrasound Imaging

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    Ultrasound is a widely used and safe medical diagnostic technique, due to low cost and capability of forming real time imaging. The usefulness of ultrasound imaging is degraded by the presence of signal dependant noise known as speckle. In this paper we make use of daubechies wavelet transformation, Wiener and employing an adaptive thresholding technique in order to improve the performance of this denosing approach the log transformed observation is separated into two images. The summation of these two images constructs the despeckled image

    Binary Wavelet Transform Based Histogram Feature for Content Based Image Retrieval

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    In this paper a new visual feature, binary wavelet transform based histogram (BWTH) is proposed for content based image retrieval. BWTH is facilitated with the color as well as texture properties. BWTH exhibits the advantages of binary wavelet transform and histogram. The performance of CBIR system with proposed feature is observed on Corel 1000 (DB1) and Corel 2450 (DB2) natural image database in color as well as gray space. The results analysis of DB1 database illustrates the better average precision and average recall of proposed method in RGB space (73.82%, 44.29%) compared to color histogram (70.85%, 42.16%), auto correlogram (66.15%, 39.52%) and discrete wavelet transform (60.83%, 38.25%). In case of gray space also performance of proposed method (66.69%, 40.77%) is better compared to auto correlogram (57.20%, 35.31%), discrete wavelet transform (52.70%, 32.98%) and wavelet correlogram (64.3%, 38.0%). It is verified that in case of DB2 database also average precision, average recall and average retrieval rate of proposed method are significantly better

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