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Fourier Transform Coding-based Techniques for Lossless Iris Image Compression
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     Today, the use of iris recognition is expanding globally as the most accurate and reliable biometric feature in terms of uniqueness and robustness. The motivation for the reduction or compression of the large databases of iris images becomes an urgent requirement. In general, image compression is the process to remove the insignificant or redundant information from the image details, that implicitly makes efficient use of redundancy embedded within the image itself. In addition, it may exploit human vision or perception limitations to reduce the imperceptible information.
     This paper deals with reducing the size of image, namely reducing the number of bits required in representing the image. This was performed by exploiting the transforms-based coding techniques of lossless base compression system. In these techniques, the first part looked at the traditional Fourier transform coding technique while the second part aimed at enhancing the performance of the traditional transformation techniques. This was achieved once by overcoming the inherited problems of this technique that suffers from the complex nature base, then latter by incorporating the double base coding techniques of hierarchal scheme, as  mixing of both discrete wavelet transform and zipper coding techniques.

     The test results indicated that the proposed scheme produced high compression ratio with identically preserving the quality of the compressed (decoded) image.

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Publication Date
Tue Feb 13 2024
Journal Name
Iraqi Journal Of Science
Parameters Estimation for Modified Weibull Distribution Based on Type One Censored Samplest
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The three parameters distribution called modified weibull distribution (MWD) was introduced first by Sarhan and Zaindin (2009)[1]. In theis paper, we deal with interval estimation to estimate the parameters of modified weibull distribution based on singly type one censored data, using Maximum likelihood method and fisher information to obtain the estimates of the parameters for modified weibull distribution, after that applying this technique to asset of real data which taken for Leukemia disease in the hospital of central child teaching .

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Publication Date
Thu Nov 17 2022
Journal Name
Journal Of Information And Optimization Sciences
Hybrid deep learning model for Arabic text classification based on mutual information
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Publication Date
Sat Mar 31 2018
Journal Name
Journal Of Engineering
Estimation of Minimum Miscibility Pressure for 〖CO〗_2 Flood Based on EOS
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CO2 Gas is considered one of the unfavorable gases and it causes great air pollution. It’s possible to decrease this pollution by injecting  gas in the oil reservoirs to provide a good miscibility and to increase the oil recovery factor. MMP was estimated by Peng Robinson equation of state (PR-EOS). South Rumila-63 (SULIAY) is involved for which the miscible displacement by  is achievable based on the standard criteria for success EOR processes. A PVT report was available for the reservoir under study. It contains deferential liberation (DL) and constant composition expansion (CCE) tests.  PVTi software is one of the (Eclipse V.2010) software’s packages, it has been used to achieve the goal.

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Publication Date
Sat Feb 27 2021
Journal Name
Iraqi Journal Of Science
Design and Implementation of an IoT-based Transactional System for Quality Management
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The spread of Coronavirus has forced populations around the globe to adopt strict measures such as lockdown, home quarantine, and home office. Moreover, in the current development of network communications, people can exploit internet and intranet features in many systems that need to be faster, more efficient, and available on time. Furthermore, with the benefits of using internet-of-things (IoT), through which things are generated, gained, discovered, and proposed without interference, the user could receive the last status without exertion and direct contact (i.e., in a contactless manner). These specifications can be used in a transaction system. This paper proposes an electronic transaction system (ETS) as a replacement for the curr

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Publication Date
Wed Apr 15 2020
Journal Name
Al-mustansiriyah Journal Of Science
Adaptation Proposed Methods for Handling Imbalanced Datasets based on Over-Sampling Technique
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Classification of imbalanced data is an important issue. Many algorithms have been developed for classification, such as Back Propagation (BP) neural networks, decision tree, Bayesian networks etc., and have been used repeatedly in many fields. These algorithms speak of the problem of imbalanced data, where there are situations that belong to more classes than others. Imbalanced data result in poor performance and bias to a class without other classes. In this paper, we proposed three techniques based on the Over-Sampling (O.S.) technique for processing imbalanced dataset and redistributing it and converting it into balanced dataset. These techniques are (Improved Synthetic Minority Over-Sampling Technique (Improved SMOTE),  Border

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Publication Date
Mon Apr 26 2021
Journal Name
Journal Of Electrical Engineering & Technology
ANFIS Based Reinforcement Learning Strategy for Control A Nonlinear Coupled Tanks System
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Publication Date
Mon Dec 01 2014
Journal Name
2014 Ieee Student Conference On Research And Development
Feature extraction for co-occurrence-based cosine similarity score of text documents
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Publication Date
Sun Jun 20 2021
Journal Name
Baghdad Science Journal
PDCNN: FRAMEWORK for Potato Diseases Classification Based on Feed Foreword Neural Network
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         The economy is exceptionally reliant on agricultural productivity. Therefore, in domain of agriculture, plant infection discovery is a vital job because it gives promising advance towards the development of agricultural production. In this work, a framework for potato diseases classification based on feed foreword neural network is proposed. The objective of this work  is presenting a system that can detect and classify four kinds of potato tubers diseases; black dot, common scab, potato virus Y and early blight based on their images. The presented PDCNN framework comprises three levels: the pre-processing is first level, which is based on K-means clustering algorithm to detect the infected area from potato image. The s

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Publication Date
Mon Jan 28 2013
Journal Name
Spie Proceedings
Enhancement of security for free space optics based on reconfigurable chaotic technique
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Free Space Optical (FSO) technology offers highly directional, high bandwidth communication channels. This technology can provide fiber-like data rate over short distances. In order to improve security associated with data transmission in FSO networks, a secure communication method based on chaotic technique is presented. In this paper, we have turned our focus on a specific class of piece wise linear one-dimensional chaotic maps. Simulation results indicate that this approach has the advantage of possessing excellent correlation property. In this paper we examine the security vulnerabilities of single FSO links and propose a solution to this problem by implementing the chaotic signal generator “reconfigurable tent map”. As synchronizat

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Publication Date
Wed Jul 01 2020
Journal Name
Journal Of Engineering
Bat Algorithm Based an Adaptive PID Controller Design for Buck Converter Model
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The aim of this paper is to design a PID controller based on an on-line tuning bat optimization algorithm for the step-down DC/DC buck converter system which is used in the battery operation of the mobile applications. In this paper, the bat optimization algorithm has been utilized to obtain the optimal parameters of the PID controller as a simple and fast on-line tuning technique to get the best control action for the system. The simulation results using (Matlab Package) show the robustness and the effectiveness of the proposed control system in terms of obtaining a suitable voltage control action as a smooth and unsaturated state of the buck converter input voltage of ( ) volt that will stabilize the buck converter sys

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