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Symmetric- Based Steganography Technique Using Spiral-Searching Method for HSV Color Images
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Steganography is defined as hiding confidential information in some other chosen media without leaving any clear evidence of changing the media's features. Most traditional hiding methods hide the message directly in the covered media like (text, image, audio, and video). Some hiding techniques leave a negative effect on the cover image, so sometimes the change in the carrier medium can be detected by human and machine. The purpose of suggesting hiding information is to make this change undetectable. The current research focuses on using complex method to prevent the detection of hiding information by human and machine based on spiral search method, the Structural Similarity Index Metrics measures are used to get the accuracy and quality of the retrieved image and to improve its perceived quality.

The values of information measures are calculated through practical experiments of (perceptibility, robustness, capacity) by using interpolation technique and structural similarity measures. Experimental results show that the use of these measures (PSNR, MSE, and SSIM) has improved the image quality by 87% and has produced values of PSNR (38-41 dB), MSE = 0.6537 and SSIM= 0.8255. The results also demonstrate a remarkable progress in the field of hiding information and the increasing difficulty of detecting it by humans and machines.

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Publication Date
Fri Apr 22 2022
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Developing models to predicting the effect of crises on construction projects using MLR technique
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Publication Date
Sat Dec 01 2018
Journal Name
Al-khwarizmi Engineering Journal
Analysis the Surface Morphology of the Porous Media by using Atomic Force Microscope technique
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An atomic force microscope (AFM) technique is utilized to investigate the polystyrene (PS) impact upon the morphological properties of the outer as well as inner surface of poly vinyl chloride (PVC) porous fibers. Noticeable a new shape of the nodules at the outer and inner surfaces, namely "Crater nodules", has been observed. The fibers surface images have seen to be regular nodular texture at the skin of the inner and outer surfaces at low PS content. At PS content of 6 wt.%, the nodules structure was varied from Crater shape to stripe. While with increasing of PS content, the pore density reduces as a result of increasing the size of the pore at the fiber surface. Moreover, the test of 3D-AFM images shows that the roughness of both su

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Publication Date
Sat Aug 31 2019
Journal Name
Iraqi Journal Of Physics
Manufacturing Zener diode using ZnO-CuO-ZnO/Si structures deposited laser induced plasma technique
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        In this paper Zener diode was manufactured using ZnO-CuO-ZnO/Si heterojunction structure that used laser induced plasma technique to prepare the nanofilms. Six samples were prepared with a different number of laser pulses, started with 200 to 600 pulses on ZnO tablet with fixed the number of laser pulses on CuO tablet at 300 pulses. The pulse energy of laser deposited was 900mJ using ZnO tablet and 600mJ using CuO tablet. All prepared films shown good behavior as Zener diode when using porous silicon as substrate.

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Publication Date
Mon Oct 01 2018
Journal Name
Iraqi Journal Of Science
Theoretical Study of The Electromagnetic Structure of Boron Isotopes Using Local Scale Transformation Technique
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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Simplified Novel Approach for Accurate Employee Churn Categorization using MCDM, De-Pareto Principle Approach, and Machine Learning
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Churning of employees from organizations is a serious problem. Turnover or churn of employees within an organization needs to be solved since it has negative impact on the organization. Manual detection of employee churn is quite difficult, so machine learning (ML) algorithms have been frequently used for employee churn detection as well as employee categorization according to turnover. Using Machine learning, only one study looks into the categorization of employees up to date.  A novel multi-criterion decision-making approach (MCDM) coupled with DE-PARETO principle has been proposed to categorize employees. This is referred to as SNEC scheme. An AHP-TOPSIS DE-PARETO PRINCIPLE model (AHPTOPDE) has been designed that uses 2-stage MCDM s

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Publication Date
Sat Dec 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
(Estimation and Analysis of the Cobb-Duglas Production Function for the Rail Transport Sector in Iraq for the Period 1990-2016 using the ARDL Model)
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Abstract:

Since the railway transport sector is very important in many countries of the world, we have tried through this research to study the production function of this sector and to indicate the level of productivity under which it operates.

It was found through the estimation and analysis of the production function Kub - Duglas that the railway transport sector in Iraq suffers from a decline in the level of productivity, which was reflected in the deterioration of the level of services provided for the transport of passengers and goods. This led to the loss of the sector of importance in supporting the national economy and the reluctance of most passengers an

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Publication Date
Thu Jan 01 2015
Journal Name
Journal Of Theoretical And Applied Information Technology
Graph based text representation for document clustering
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Advances in digital technology and the World Wide Web has led to the increase of digital documents that are used for various purposes such as publishing and digital library. This phenomenon raises awareness for the requirement of effective techniques that can help during the search and retrieval of text. One of the most needed tasks is clustering, which categorizes documents automatically into meaningful groups. Clustering is an important task in data mining and machine learning. The accuracy of clustering depends tightly on the selection of the text representation method. Traditional methods of text representation model documents as bags of words using term-frequency index document frequency (TFIDF). This method ignores the relationship an

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Publication Date
Thu Oct 21 2021
Journal Name
The 3rd Al-noor International Conference Of Science And Technology 2021 Muscat-oman
Gama Platform Survey for Agent-Based Modelling
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The agent-based modeling is currently utilized extensively to analyze complex systems. It supported such growth, because it was able to convey distinct levels of interaction in a complex detailed environment. Meanwhile, agent-based models incline to be progressively complex. Thus, powerful modeling and simulation techniques are needed to address this rise in complexity. In recent years, a number of platforms for developing agent-based models have been developed. Actually, in most of the agents, often discrete representation of the environment, and one level of interaction are presented, where two or three are regarded hardly in various agent-based models. The key issue is that modellers work in these areas is not assisted by simulation plat

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Publication Date
Mon Dec 21 2020
Journal Name
Bulletin Of The Iraq Natural History Museum (p-issn: 1017-8678 , E-issn: 2311-9799)
MONITORING OF THE WILD MAMMAL FAUNA IN BAMO MOUNTAIN IN NORTHERN IRAQ (KURDISTAN) FOR THE FIRST TIME USING CAMERA TRAP METHOD AND RAISING AWARENESS FOR ITS CONSERVATION
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Mammals are under threat worldwide due to deforestation, hunting, and other human activities. In Iraq, a total of 93 species of wild mammals have been recorded including species with global conservation concern. Bamo Mountain is situated within the Zagros Mountains in northern Iraq which is a suitable habitat for wild mammals. Due to scarcity of the field survey efforts and cryptic behavior, monitoring of the wild mammals fauna in Zagros Mountain seems challenging. Therefore, we used a camera trap which seems to be an ideal way to determine species diversity of wild mammals in Bamo Mountain. Moreover, interviews with local villagers were performed. The mammalian diversity of Bamo Mountain is not fully explored but seemed threatened by lo

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Early Diagnose Alzheimer's Disease by Convolution Neural Network-based Histogram Features Extracting and Canny Edge
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Alzheimer's disease (AD) increasingly affects the elderly and is a major killer of those 65 and over. Different deep-learning methods are used for automatic diagnosis, yet they have some limitations. Deep Learning is one of the modern methods that were used to detect and classify a medical image because of the ability of deep Learning to extract the features of images automatically. However, there are still limitations to using deep learning to accurately classify medical images because extracting the fine edges of medical images is sometimes considered difficult, and some distortion in the images. Therefore, this research aims to develop A Computer-Aided Brain Diagnosis (CABD) system that can tell if a brain scan exhibits indications of

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