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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 Aug 30 2023
Journal Name
Iraqi Journal Of Science
Efficient Cloud-Based Resource Sharing Through Multi-Tenancy and Load Balancing: An Exploration of Higher Education and Digital Libraries
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      Cloud computing has gained considerable attention in academia and industry in recent years. The cloud facilitates data sharing and enables cost efficiency, thus playing a vital role today as well as for the foreseeable future. In this paper, a brief discussion the application of multi-tenant and load-balancing technologies to cloud-based digital resource sharing suitable for academic and digital libraries is presented. As a new paradigm for digital resource sharing, a proposal of improving the current user service model with private cloud storage for other sectors, including the medical and financial fields is offered. This paper gives a summary of cloud computing and its possible applications, combined with digital data optim

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Publication Date
Tue Dec 27 2022
Journal Name
2022 3rd Information Technology To Enhance E-learning And Other Application (it-ela)
Diabetes Prediction Using Machine Learning
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Diabetes is one of the increasing chronic diseases, affecting millions of people around the earth. Diabetes diagnosis, its prediction, proper cure, and management are compulsory. Machine learning-based prediction techniques for diabetes data analysis can help in the early detection and prediction of the disease and its consequences such as hypo/hyperglycemia. In this paper, we explored the diabetes dataset collected from the medical records of one thousand Iraqi patients. We applied three classifiers, the multilayer perceptron, the KNN and the Random Forest. We involved two experiments: the first experiment used all 12 features of the dataset. The Random Forest outperforms others with 98.8% accuracy. The second experiment used only five att

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Publication Date
Fri Jul 01 2022
Journal Name
Iraqi Journal Of Science
Application of the Elevation and Residual Static Correction methods on a selected Seismic data of West Luhais area in the South of Iraq
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The present study deals with processing of one seismic line (2WL2) with a length of (37km) for (2D) seismic data of west Luhais area that is located within the administrative borders of the province of Muthanna in south of Iraq. The quality of the recorded data of this line is in general weak due to the effect of noise mainly. The study was made up in oil Exploration Company by utilizing OMEGA software which consists of a great number of the processing programs. The elevation static correction and residual static correction were applied on the studied line and the final section were resulted after completing the treatment processes that proceed followed of the static correction process and the result of elevation static correcting was go

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Publication Date
Thu Sep 30 2021
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Development a Statistical Relationship between Compressional Wave Velocity and Petrophysical Properties from Logs Data for JERIBE Formation ASMARI Reservoir in FAUQI Oil Field
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   The Compressional-wave (Vp) data are useful for reservoir exploration, drilling operations, stimulation, hydraulic fracturing employment, and development plans for a specific reservoir. Due to the different nature and behavior of the influencing parameters, more complex nonlinearity exists for Vp modeling purposes. In this study, a statistical relationship between compressional wave velocity and petrophysical parameters was developed from wireline log data for Jeribe formation in Fauqi oil field south Est Iraq, which is studied using single and multiple linear regressions. The model concentrated on predicting compressional wave velocity from petrophysical parameters and any pair of shear waves velocity, porosity, density, a

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Publication Date
Thu Sep 30 2021
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Development a Statistical Relationship between Compressional Wave Velocity and Petrophysical Properties from Logs Data for JERIBE Formation ASMARI Reservoir in FAUQI Oil Field
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   The Compressional-wave (Vp) data are useful for reservoir exploration, drilling operations, stimulation, hydraulic fracturing employment, and development plans for a specific reservoir. Due to the different nature and behavior of the influencing parameters, more complex nonlinearity exists for Vp modeling purposes. In this study, a statistical relationship between compressional wave velocity and petrophysical parameters was developed from wireline log data for Jeribe formation in Fauqi oil field south Est Iraq, which is studied using single and multiple linear regressions. The model concentrated on predicting compressional wave velocity from petrophysical parameters and any pair of shear waves velocity, porosity, density, and

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Publication Date
Tue Jan 19 2021
Journal Name
Isprs International Journal Of Geo-information
The Potential of LiDAR and UAV-Photogrammetric Data Analysis to Interpret Archaeological Sites: A Case Study of Chun Castle in South-West England
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With the increasing demands to use remote sensing approaches, such as aerial photography, satellite imagery, and LiDAR in archaeological applications, there is still a limited number of studies assessing the differences between remote sensing methods in extracting new archaeological finds. Therefore, this work aims to critically compare two types of fine-scale remotely sensed data: LiDAR and an Unmanned Aerial Vehicle (UAV) derived Structure from Motion (SfM) photogrammetry. To achieve this, aerial imagery and airborne LiDAR datasets of Chun Castle were acquired, processed, analyzed, and interpreted. Chun Castle is one of the most remarkable ancient sites in Cornwall County (Southwest England) that had not been surveyed and explored

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Publication Date
Sat Feb 27 2021
Journal Name
Iraqi Journal Of Science
Integration of Remotely Sensed Digital Elevation Model Data and Geographic Information System Facilities to Estimate Net Solar Radiation Variances in Iraq (1987-2017)
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The calculation of potential earth's surface solar radiation is imperative for analyzing the atmosphere-vegetation-soil interaction process. Therefore, many schemes were introduced with  direct (using net radiometer) or indirect (using air temperature or air plus soil temperatures) formulas. Three combinations of factors are known to control the Rn value; the astronomical based factors which determine the general spatial distribution of Rn values, the climatological factors which determine the assigned spatial variation of those values, and the topographical factors that influence climatological factors rates ( i.e. have indirect effects on Rn values).

     For Iraq, the ecosystem in

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Publication Date
Wed Mar 27 2019
Journal Name
Iraqi Journal Of Science
Application of Source Parameter Imaging (SPI) Technique to Gravity and Magnetic Data to Estimate the Basement Depth in Diyala Area, Eastern Central Iraq
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The Bouguer gravity and magnetic RTP data were used to detect the depth of basement rocks in middle and south Diyala Province, east Iraq. The depth of the basement rocks was calculated by using the Source Parameter Imaging (SPI) method. New attempt is achieved to applied the SPI technique to the gravity values to estimate the depth of basement rocks. The depths of basement map derived from gravity data range 8-14 km, the depth of basement map derived from magnetic data range 9-13.5 km and the basement depth prepared by C.G.G, 1974 range 9-11 km. The derived maps from SPI method and that prepared by C.G.G, 1974 show good matching in the distribution of the depths of the study area. This study showed that basement’s depth range from

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Publication Date
Sat Jul 31 2021
Journal Name
Iraqi Journal Of Science
Interpretation of 3D Seismic Reflection Data to Reveal Stratigraphic Setting of the Reservoir of Mishrif Formation in Dujaila Oil Field, Southeast of Iraq
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     This research is an attempt to solve the ambiguity associated with the stratigraphic setting of the main reservoir (late Cretaceous) of Mishrif Formation in Dujaila oil field. This was achieved by studying a 3D seismic reflection post-stack data for an area of ​​602.62 Km2 in Maysan Governorate, southeast of Iraq. Seismic analysis of the true amplitude reflections, time maps, and 3D depositional models showed a sufficient seismic evidence that the Mishrif Formation produces oil from a stratigraphic trap of isolated reef carbonate buildups that were grown on the shelf edge of the carbonate platform, located in the area around the productive well Dujaila-1. The low-frequency attribute illustrated tha

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Publication Date
Fri Aug 01 2014
Journal Name
Int. J. Mod. Eng. Res
Exact solutions for MHD flow of a viscoelastic fluid with the fractional Burgers’ model in an annular pipe
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This paper presents an analytical study for the magnetohydrodynamic (MHD) flow of a generalized Burgers’ fluid in an annular pipe. Closed from solutions for velocity is obtained by using finite Hankel transform and discrete Laplace transform of the sequential fractional derivatives. Finally, the figures are plotted to show the effects of different parameters on the velocity profile.

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