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Evaluation of the Accuracy of Digital Elevation Model Produced from Different Open Source Data
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This study aims to estimate the accuracy of digital elevation models (DEM) which are created with exploitation of open source Google Earth data and comparing with the widely available DEM datasets, Shuttle Radar Topography Mission (SRTM), version 3, and Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Model (ASTER GDEM), version 2. The GPS technique is used in this study to produce digital elevation raster with a high level of accuracy, as reference raster, compared to the DEM datasets. Baghdad University, Al Jadriya campus, is selected as a study area. Besides, 151 reference points were created within the study area to evaluate the results based on the values of RMS.Furthermore, the Geographic Information System (GIS) was utilized to analyze, imagine and interpolate data in this study. The result of the statistical analysis revealed that RMSE of DEM related to the differences between the reference points and Google Earth, SRTM DEM and ASTER GDEM are 6.9, 5.5 and 4.8, respectively. What is more, a finding of this study shows convergence the level of accuracy for all open sources used in this study.

 

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Publication Date
Mon Aug 10 2020
Journal Name
Applied Optics
Liquid infiltration of monolithic open-access Fabry–Perot microcavities
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We describe a monolithic approach to fabricating large-scale arrays of high-finesse and low-mode-volume Fabry–Perot microcavities with open access to the air core. A stress-driven buckling self-assembly technique was used to form half-symmetric curved-mirror cavities, and a dry etching process was subsequently used to create micropores through the upper mirror. We show that the cavities retain excellent optical properties, with reflectance-limited finesse 2500

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Publication Date
Mon Feb 04 2019
Journal Name
Iraqi Journal Of Physics
Temperatture esttiimattiion off EXDRA and SSUMI dwarff Nova systtems from spectroscopic data
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The seasonal behavior of the light curve for selected star SS UMI and EXDRA during outburst cycle is studied. This behavior describes maximum temperature of outburst in dwarf nova. The raw data has been mathematically modeled by fitting Gaussian function based on the full width of the half maximum and the maximum value of the Gaussian. The results of this modeling describe the value of temperature of the dwarf novae star system leading to identify the type of elements that each dwarf nova consisted of.

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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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Publication Date
Tue Jan 01 2019
Journal Name
Ieee Access
Implementation of Univariate Paradigm for Streamflow Simulation Using Hybrid Data-Driven Model: Case Study in Tropical Region
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Publication Date
Fri Oct 31 2025
Journal Name
Mathematical Modelling Of Engineering Problems
Heterogeneous Traffic Management in SDN-Enabled Data Center Network Using Machine Learning-SPIKE Model
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Software-Defined Networking (SDN) has evolved network management by detaching the control plane from the data forwarding plane, resulting in unparalleled flexibility and efficiency in network administration. However, the heterogeneity of traffic in SDN presents issues in achieving Quality of Service (QoS) demands and efficiently managing network resources. SDN traffic flows are often divided into elephant flows (EFs) and mice flows (MFs). EFs, which are distinguished by their huge packet sizes and long durations, account for a small amount of total traffic but require disproportionate network resources, thus causing congestion and delays for smaller MFs. MFs, on the other hand, have a short lifetime and are latency-sensitive, but they accou

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Publication Date
Fri Aug 01 2014
Journal Name
Journal Of Economics And Administrative Sciences
Efficiency Measurement Model for Postgraduate Programs and Undergraduate Programs by Using Data Envelopment Analysis
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Measuring the efficiency of postgraduate and undergraduate programs is one of the essential elements in educational process. In this study, colleges of Baghdad University and data for the academic year (2011-2012) have been chosen to measure the relative efficiencies of postgraduate and undergraduate programs in terms of their inputs and outputs. A relevant method to conduct the analysis of this data is Data Envelopment Analysis (DEA). The effect of academic staff to the number of enrolled and alumni students to the postgraduate and undergraduate programs are the main focus of the study.

 

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Publication Date
Wed Jul 01 2020
Journal Name
Proceedings Of The Institution Of Mechanical Engineers, Part H: Journal Of Engineering In Medicine
Comparison study of classification methods of intramuscular electromyography data for non-human primate model of traumatic spinal cord injury
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Traumatic spinal cord injury is a serious neurological disorder. Patients experience a plethora of symptoms that can be attributed to the nerve fiber tracts that are compromised. This includes limb weakness, sensory impairment, and truncal instability, as well as a variety of autonomic abnormalities. This article will discuss how machine learning classification can be used to characterize the initial impairment and subsequent recovery of electromyography signals in an non-human primate model of traumatic spinal cord injury. The ultimate objective is to identify potential treatments for traumatic spinal cord injury. This work focuses specifically on finding a suitable classifier that differentiates between two distinct experimental

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Publication Date
Sun Apr 03 2016
Journal Name
Journal Of Educational And Psychological Researches
The Level of Computer Literacy of the Students at Al Quds Open University in Tulkarm Branch
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The purpose of this study is to assess the level of computer literacy of the students at AlQuds open university in Tulkarm Branch. The study investigates the effects of the variables of gender, specialization, academic level, owning a personal computer, internet communication, and own an email account on the level of computer literacy. A test of computer literacy was constructed by the researchers consisting of (37) multiple choice items with a reliability rate (0.85). The study population consisted of (4100) students, while the sample contained (352) students. The study revealed that the level of computer literacy of the students at AlQuds Open University in Tulkarm Branch was (66.2 %) which is educationally acceptable. It also

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Publication Date
Fri Jan 30 2026
Journal Name
Iraqi Journal Of Science
Producing Digital Models of Elevations (DEMs) using Surfer 16
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Digital Models of Elevations (DEMs) Using Surfer 16, which are interpolated to create three-dimensional controls for the entire terrain, are typically used in visualization of geospatial entities. The interpolation method used determines how accurate the resulting terrain model will be, hence it is necessary to compare the effectiveness of various approaches in this situation. Numerous generic interpolation techniques, using inverse distance to a power, triangulation as with linear interpolation, the nearest neighbor, and kriging, have been studied. These interpolation techniques produced DEMs. With the aid of SURFER software 16, the primary goal of this effort was to introduce the DEM using a spatial interpolation method and to pre

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Publication Date
Fri Apr 20 2018
Journal Name
Iaes International Journal Of Artificial Intelligence (ij-ai)
Optimization of Digital Histopathology Image Quality
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One of the biomedical image problems is the appearance of the bubbles in the slide that could occur when air passes through the slide during the preparation process. These bubbles may complicate the process of analysing the histopathological images. The objective of this study is to remove the bubble noise from the histopathology images, and then predict the tissues that underlie it using the fuzzy controller in cases of remote pathological diagnosis. Fuzzy logic uses the linguistic definition to recognize the relationship between the input and the activity, rather than using difficult numerical equation. Mainly there are five parts, starting with accepting the image, passing through removing the bubbles, and ending with predict the tissues

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