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bsj-1301
An Embedded Data Using Slantlet Transform
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Data hiding is the process of encoding extra information in an image by making small modification to its pixels. To be practical, the hidden data must be perceptually invisible yet robust to common signal processing operations. This paper introduces a scheme for hiding a signature image that could be as much as 25% of the host image data and hence could be used both in digital watermarking as well as image/data hiding. The proposed algorithm uses orthogonal discrete wavelet transforms with two zero moments and with improved time localization called discrete slantlet transform for both host and signature image. A scaling factor ? in frequency domain control the quality of the watermarked images. Experimental results of signature image recovery after applying JPEG coding to the watermarking image are included.

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Publication Date
Wed Oct 17 2018
Journal Name
Iraqi Journal Of Laser
The Effect of using 940 nm Diode Laser in Comparison with Endoactivator on Radicular Dentin Permeability and Smear Layer Removal (An in Vitro Study)
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Abstract: The aim of this study is to assess the effectiveness of 940 nm diode laser in comparison to Endoactivator in elimination of smear layer in terms of radicular dentin permeability and ultra-structural changes of root canal walls by SEM evaluation. Twenty-eight single-rooted extracted lower premolars were instrumented up to size X4 (protaper Next, Dentsaply) and divided into two experimental groups according to the irrigation system, G1; activated by EndoActivator and G2; activated by Diode laser 940 nm, CW mode, 1.7 W. Afterward, the roots were made externally impermeable, filled with 2%methylene blue dye, divided horizontally into three segments representing the apical, middle, and coronal thirds then examined under stereo- micr

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Publication Date
Fri Sep 15 2023
Journal Name
Journal Of Baghdad College Of Dentistry
Reliability of the multipeg™ transducer in measuring dental implant stability by using a resonance frequency analysis device (Osstell®): An observational clinical study
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Background: Measuring implant stability is an important issue in predicting treatment success. Dental implant stability is usually measured through resonance frequency analysis (RFA). Osstell® RFA devices can be used with transducers (Smartpeg™) that correspond to the implants used as well as with transducers designed for application with Penguin® RFA devices (Multipeg™). Aims: This study aims to assess the reliability of a MultiPeg™ transducer with an Osstell® device in measuring dental implant stability. Materials and Methods: Sixteen healthy participants who required dental implant treatment were enrolled in this study. Implant stability was measured by using an Osstell® device with two transducers, namely, Smartpeg™ and M

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Publication Date
Thu Dec 28 2017
Journal Name
Al-khwarizmi Engineering Journal
An Autocorrelative Approach for EMG Time-Frequency Analysis
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As they are the smallest functional parts of the muscle, motor units (MUs) are considered as the basic building blocks of the neuromuscular system. Monitoring MU recruitment, de-recruitment, and firing rate (by either invasive or surface techniques) leads to the understanding of motor control strategies and of their pathological alterations. EMG signal decomposition is the process of identification and classification of individual motor unit action potentials (MUAPs) in the interference pattern detected with either intramuscular or surface electrodes. Signal processing techniques were used in EMG signal decomposition to understand fundamental and physiological issues. Many techniques have been developed to decompose intramuscularly detec

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Publication Date
Fri Mar 31 2017
Journal Name
Iraqi Journal Of Biotechnology
Reliable Reference Gene for Normalization of RT- qPCR Data in Human Cancer Cell Lines
Subjected to Gene Knockdown
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Quantitative real-time Polymerase Chain Reaction (RT-qPCR) has become a valuable molecular technique in biomedical research. The selection of suitable endogenous reference genes is necessary for normalization of target gene expression in RT-qPCR experiments. The aim of this study was to determine the suitability of each 18S rRNA and ACTB as internal control genes for normalization of RT-qPCR data in some human cell lines transfected with small interfering RNA (siRNA). Four cancer cell lines including MCF-7, T47D, MDA-MB-231 and Hela cells along with HEK293 representing an embryonic cell line were depleted of E2F6 using siRNA specific for E2F6 compared to negative control cells, which were transfected with siRNA not specific for any gene. Us

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Publication Date
Tue Jun 30 2020
Journal Name
Journal Of Economics And Administrative Sciences
Comparison of weighted estimated method and proposed method (BEMW) for estimation of semi-parametric model under incomplete data
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Generally, statistical methods are used in various fields of science, especially in the research field, in which Statistical analysis is carried out by adopting several techniques, according to the nature of the study and its objectives. One of these techniques is building statistical models, which is done through regression models. This technique is considered one of the most important statistical methods for studying the relationship between a dependent variable, also called (the response variable) and the other variables, called covariate variables. This research describes the estimation of the partial linear regression model, as well as the estimation of the “missing at random” values (MAR). Regarding the

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Publication Date
Fri Nov 29 2024
Journal Name
The Iraqi Geological Journal
Data Driven Approach for Predicting Pore Pressure of Oil and Gas Wells, Case Study of Iraq Southern Oilfields
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Precise forecasting of pore pressures is crucial for efficiently planning and drilling oil and gas wells. It reduces expenses and saves time while preventing drilling complications. Since direct measurement of pore pressure in wellbores is costly and time-intensive, the ability to estimate it using empirical or machine learning models is beneficial. The present study aims to predict pore pressure using artificial neural network. The building and testing of artificial neural network are based on the data from five oil fields and several formations. The artificial neural network model is built using a measured dataset consisting of 77 data points of Pore pressure obtained from the modular formation dynamics tester. The input variables

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Publication Date
Tue Aug 27 2024
Journal Name
Tem Journal
Preparing the Electrical Signal Data of the Heart by Performing Segmentation Based on the Neural Network U-Net
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Research on the automated extraction of essential data from an electrocardiography (ECG) recording has been a significant topic for a long time. The main focus of digital processing processes is to measure fiducial points that determine the beginning and end of the P, QRS, and T waves based on their waveform properties. The presence of unavoidable noise during ECG data collection and inherent physiological differences among individuals make it challenging to accurately identify these reference points, resulting in suboptimal performance. This is done through several primary stages that rely on the idea of preliminary processing of the ECG electrical signal through a set of steps (preparing raw data and converting them into files tha

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Publication Date
Tue Oct 01 2019
Journal Name
Journal Of Engineering
Evaluation of the Performance of Online GPS/GNSS Data Processing Services for Monitoring the Land Deformations and Movements
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In recent years, the Global Navigation Satellite Services (GNSS) technology has been frequently employed for monitoring the Earth crust deformation and movement. Such applications necessitate high positional accuracy that can be achieved through processing GPS/GNSS data with scientific software such as BERENSE, GAMIT, and GIPSY-OSIS. Nevertheless, these scientific softwares are sophisticated and have not been published as free open source software. Therefore, this study has been conducted to evaluate an alternative solution, GNSS online processing services, which may obtain this privilege freely. In this study, eight years of GNSS raw data for TEHN station, which located in Iran, have been downloaded from UNAVCO website

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Publication Date
Wed Apr 01 2015
Journal Name
Al–bahith Al–a'alami
Methods of US propaganda in Iraq- A Study of Coalition Provisional Authority and US Army Data after 2003
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with an organized propaganda campaign. This military campaign was helped to formulate its speech by many institutions, research centers, and knowledge and intelligence circles in order to mobilize public opinion gain supporters and face the opponents by different means depending on a variety of styles to achieve its required effects. 
          After the US occupation of Iraq, US media fighters sought to influence the Iraqi public opinion and making them convinced them of the important presence of US military forces in Iraq which necessitated finding its justification through the use of persuasive techniques in its intensive propaganda campaigns. 
  This research discusses the most important

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Publication Date
Fri Mar 01 2013
Journal Name
Journal Of Economics And Administrative Sciences
Robust Two-Step Estimation and Approximation Local Polynomial Kernel For Time-Varying Coefficient Model With Balance Longitudinal Data
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      In this research, the nonparametric technique has been presented to estimate the time-varying coefficients functions for the longitudinal balanced data that characterized by observations obtained through (n) from the independent subjects, each one of them is measured repeatedly by group of  specific time points (m). Although the measurements are independent among the different subjects; they are mostly connected within each subject and the applied techniques is the Local Linear kernel LLPK technique. To avoid the problems of dimensionality, and thick computation, the two-steps method has been used to estimate the coefficients functions by using the two former technique. Since, the two-

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