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bsj-7926
Building a Statistical Model to Detect Foreground Objects and using it in Video Steganography
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Video steganography has become a popular option for protecting secret data from hacking attempts and common attacks on the internet. However, when the whole video frame(s) are used to embed secret data, this may lead to visual distortion. This work is an attempt to hide sensitive secret image inside the moving objects in a video based on separating the object from the background of the frame, selecting and arranging them according to object's size for embedding secret image. The XOR technique is used with reverse bits between the secret image bits and the detected moving object bits for embedding. The proposed method provides more security and imperceptibility as the moving objects are used for embedding, so it is difficult to notice the changes in the moving objects instead of using background area for embedding in the video. The experimental results showed the better visual quality of the stego video with PSNR values exceeding 58 dB, this indicates that the proposed method works without causing much distortion in the original video and transmitted secret message.

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Publication Date
Sun Sep 06 2009
Journal Name
Baghdad Science Journal
Estimation of Immunoglobulins and complements and Using Enzyme linked Immuno sorbant Assay in Identification of Vulvovaginal candidiasis
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This study was conducted to determine the Immuno – globulins and complements quantitatively. The result revealed that the concentration of Immunoglobulin M(IgM) was increased significantly in patient group comparing with control group . The concentration of complement protein C4 was increased significantly in patient group comparing with control group.IgG of Candida albicans was detected by using ELISA Technique, the result indicated also that this antibody was found in 628% of the women who infected with Vulvovaginal Candidiasis. The sensitivity and specificity of the test were 63% and 89% respectively.

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Publication Date
Fri Jan 01 2021
Journal Name
International Journal Of Thermal Sciences
Experimental and numerical investigations of heat transfer enhancement in shell and helically microtube heat exchanger using nanofluids
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Publication Date
Wed Apr 01 2020
Journal Name
International Journal Of Psychosocial Rehabilitation,
The Effect of Using Resistance and Medical Ozone Training on Testosterone and Some Physiological Variables in Swimmers
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م.د. فاطمة حميد ،أ.م.د وفاء صباح محمد الخفاجي, International Journal of Psychosocial Rehabilitation,, 2020 - Cited by 1

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Publication Date
Fri Dec 01 2017
Journal Name
Rawaa Emad Jaloud And Fadia Falahfadia Falah
Isolation and Identification of Fungal Propagation in Iraqi Meat and Detection of Aflatoxin B1 Using ELISA Technique
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Publication Date
Wed Jan 01 2025
Journal Name
Journal Of The Indian Chemical Society
Inspection the impact of mixing and external resistance on the Microbial Desalination Cell for electricity generation and desalination efficiency by using Macroalgae as a bio-cathode
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Publication Date
Fri Aug 01 2008
Journal Name
2008 First International Conference On The Applications Of Digital Information And Web Technologies (icadiwt)
Hybrid canonical genetic algorithm and steepest descent algorithm for optimizing likelihood estimators of ARMA (1, 1) model
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This paper presents a hybrid genetic algorithm (hGA) for optimizing the maximum likelihood function ln(L(phi(1),theta(1)))of the mixed model ARMA(1,1). The presented hybrid genetic algorithm (hGA) couples two processes: the canonical genetic algorithm (cGA) composed of three main steps: selection, local recombination and mutation, with the local search algorithm represent by steepest descent algorithm (sDA) which is defined by three basic parameters: frequency, probability, and number of local search iterations. The experimental design is based on simulating the cGA, hGA, and sDA algorithms with different values of model parameters, and sample size(n). The study contains comparison among these algorithms depending on MSE value. One can conc

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Publication Date
Fri Jun 30 2017
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Adsorption Kinetic and Isotherms Studies of Thiophene Removal from Model Fuel on Activated Carbon Supported Copper Oxide
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In the present study, activated carbon supported metal oxides was prepared for thiophene removal from model fuel (Thiophene in n-hexane) using adsorptive desulfurization technique. Commercial activated carbon was loaded individually with copper oxide in the form of Cu2O/AC. A comparison of the kinetic and isotherm models of the sorption of thiophene from model fuel was made at different operating conditions including adsorbent dose, initial thiophene concentration and contact time. Various adsorption rate constants and isotherm parameters were calculated. Results indicated that the desulfurization was enhanced when copper was loaded onto activated carbon surface. The highest desulfurization percent for Cu2O/AC and o

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Publication Date
Thu Aug 08 2024
Journal Name
Computation
Evaluation of the Dynamics of Psychological Panic Factor, Glucose Risk and Estrogen Effects on Breast Cancer Model
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Contracting cancer typically induces a state of terror among the individuals who are affected. Exploring how glucose excess, estrogen excess, and anxiety work together to affect the speed at which breast cancer cells multiply and the immune system’s response model is necessary to conceive of ways to stop the spread of cancer. This paper proposes a mathematical model to investigate the impact of psychological panic, glucose excess, and estrogen excess on the interaction of cancer and immunity. The proposed model is precisely described. The focus of the model’s dynamic analysis is to identify the potential equilibrium locations. According to the analysis, it is possible to establish four equilibrium positions. The stability analys

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Publication Date
Mon Apr 03 2023
Journal Name
Journal Of Electronics,computer Networking And Applied Mathematics
Comparison of Some Estimator Methods of Regression Mixed Model for the Multilinearity Problem and High – Dimensional Data
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In order to obtain a mixed model with high significance and accurate alertness, it is necessary to search for the method that performs the task of selecting the most important variables to be included in the model, especially when the data under study suffers from the problem of multicollinearity as well as the problem of high dimensions. The research aims to compare some methods of choosing the explanatory variables and the estimation of the parameters of the regression model, which are Bayesian Ridge Regression (unbiased) and the adaptive Lasso regression model, using simulation. MSE was used to compare the methods.

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Publication Date
Thu Oct 29 2020
Journal Name
Complexity
Training and Testing Data Division Influence on Hybrid Machine Learning Model Process: Application of River Flow Forecasting
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The hydrological process has a dynamic nature characterised by randomness and complex phenomena. The application of machine learning (ML) models in forecasting river flow has grown rapidly. This is owing to their capacity to simulate the complex phenomena associated with hydrological and environmental processes. Four different ML models were developed for river flow forecasting located in semiarid region, Iraq. The effectiveness of data division influence on the ML models process was investigated. Three data division modeling scenarios were inspected including 70%–30%, 80%–20, and 90%–10%. Several statistical indicators are computed to verify the performance of the models. The results revealed the potential of the hybridized s

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