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Comparative analysis of parameter estimation methods for Meixner process using wavelet packet transform
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The current research creates an overall relative analysis concerning the estimation of Meixner process parameters via the wavelet packet transform. Of noteworthy presentation relevance, it compares the moment method and the wavelet packet estimator for the four parameters of the Meixner process. In this paper, the research focuses on finding the best threshold value using the square root log and modified square root log methods with the wavelet packets in the presence of noise to enhance the efficiency and effectiveness of the denoising process for the financial asset market signal. In this regard, a simulation study compares the performance of moment estimation and wavelet packets for different sample sizes. The results show that wavelet packets are the best performers when associated with a robust threshold strategy for estimation. Illustrated below is the applicability of the proposed method by a real-world application from the foreign exchange market, emphasizing the use of wavelet packets for parameter estimation and the potential for improvement under stochastic modeling and analysis.

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Publication Date
Thu Nov 29 2018
Journal Name
Iraqi Journal Of Science
Application of WDR Technique with different Wavelet Codecs for Image Compression
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FG Mohammed, HM Al-Dabbas, Iraqi journal of science, 2018 - Cited by 6

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Publication Date
Wed Feb 01 2023
Journal Name
International Journal Of Electrical And Computer Engineering
Classification of COVID-19 from CT chest images using Convolutional Wavelet Neural Network
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<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol

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Publication Date
Sun Jun 01 2014
Journal Name
International Journal Of Advanced Research In Computer Science And Software Engineering
Medical Image Compression using Wavelet Quadrants of Polynomial Prediction Coding & Bit Plane Slicing
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Publication Date
Sun Sep 30 2018
Journal Name
Journal Of Theoretical And Applied Information Technology
FINGERPRINTS MATCHING USING THE ENERGY AND LOW ORDER MOMENT OF HAAR WAVELET SUBBANDS
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Fingerprint recognition is one among oldest procedures of identification. An important step in automatic fingerprint matching is to mechanically and dependably extract features. The quality of the input fingerprint image has a major impact on the performance of a feature extraction algorithm. The target of this paper is to present a fingerprint recognition technique that utilizes local features for fingerprint representation and matching. The adopted local features have determined: (i) the energy of Haar wavelet subbands, (ii) the normalized of Haar wavelet subbands. Experiments have been made on three completely different sets of features which are used when partitioning the fingerprint into overlapped blocks. Experiments are conducted on

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Publication Date
Wed Feb 01 2023
Journal Name
International Journal Of Electrical And Computer Engineering (ijece)
Classification of COVID-19 from CT chest images using Convolutional Wavelet Neural Network
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<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol

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Publication Date
Sun Dec 01 2013
Journal Name
Journal Of Economics And Administrative Sciences
Assess the Reality of the Process of Applying the strategic Innovation In Business organizations : A prospective Study of comparative analysis in anumber of business organizations the Iraqi Industrial
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Abstract :

      The research aims to Estimate the Strength of Strategic Innovation application in terms of application strength , and on the overall level in number of Iraqi Industrial business organizations . After wards determine whether their is differerences among those organizations in application process for the dimensions , and for the overall process .

      The Research revealed number of conclusions including that the process of strategic innovation is applied in a good Level , and demonstrates the desier of the industrial companies Leaders to Launch beyond the familiar products , and to provide new products that

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Publication Date
Wed Mar 29 2017
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Investigation and Comparative Study Among Various Methods of Contraception Used in Erbil City
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The objective of this study was to investigate and compare among five different methods of contraception including combined oral contraceptive pills (COC), Depot medroxyprogesterone acetate (DMPA), copper Intrauterine contraceptive device (IUCD), vaginal spermicides and male condom used in Hawler City through estimate of their effect, relative failure rate, percentage of use, adherence and compliance and adverse effects of each contraceptive method. In order to reach to these aims, a retrospective study was conducted in Hawler City in Azadi Health Care Center over a period of 6 months from 22th November, 2010 to 15th May, 2011 during which data collection and subjects follow up for 3 months had been achieved. A conv

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Publication Date
Wed Aug 30 2023
Journal Name
Baghdad Science Journal
Comparative Analysis of MFO, GWO and GSO for Classification of Covid-19 Chest X-Ray Images
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Medical images play a crucial role in the classification of various diseases and conditions. One of the imaging modalities is X-rays which provide valuable visual information that helps in the identification and characterization of various medical conditions. Chest radiograph (CXR) images have long been used to examine and monitor numerous lung disorders, such as tuberculosis, pneumonia, atelectasis, and hernia. COVID-19 detection can be accomplished using CXR images as well. COVID-19, a virus that causes infections in the lungs and the airways of the upper respiratory tract, was first discovered in 2019 in Wuhan Province, China, and has since been thought to cause substantial airway damage, badly impacting the lungs of affected persons.

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Publication Date
Tue Feb 01 2022
Journal Name
Baghdad Science Journal
An Enhanced Approach of Image Steganographic Using Discrete Shearlet Transform and Secret Sharing
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Recently, the internet has made the users able to transmit the digital media in the easiest manner. In spite of this facility of the internet, this may lead to several threats that are concerned with confidentiality of transferred media contents such as media authentication and integrity verification. For these reasons, data hiding methods and cryptography are used to protect the contents of digital media. In this paper, an enhanced method of image steganography combined with visual cryptography has been proposed. A secret logo (binary image) of size (128x128) is encrypted by applying (2 out 2 share) visual cryptography on it to generate two secret share. During the embedding process, a cover red, green, and blue (RGB) image of size (512

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Publication Date
Fri Nov 15 2024
Journal Name
Iraqi Journal Of Science
A Comparative Investigation of Different Ionospheric Models to Predict the MUF Parameter During Severe Geomagnetic Storm on 17th March 2015.
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The present work aimed to make a comparative investigation between three different ionospheric models: IRI-2020, ASAPS and VOACAP. The purpose of the comparative study is to investigate the compatibility of predicting the Maximum Usable Frequency parameter (MUF) over mid-latitude region during the severe geomagnetic storm on 17 March 2015. Three stations distributed in the mid-latitudes were selected for study; these are (Athens (23.50o E, 38.00o N), Jeju (124.53o E, 33.6o N) and Pt. Arguello (239.50o W, 34.80o N). The daily MUF outcomes were calculated using the tested models for the three adopted sites, for a span of five-day (the day of the event and two days preceding and following the event day). The calculated datasets were co

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