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Detecting Damaged Buildings on Post-Hurricane Satellite Imagery based on Transfer Learning
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In this article, Convolution Neural Network (CNN) is used to detect damage and no damage images form satellite imagery using different classifiers. These classifiers are well-known models that are used with CNN to detect and classify images using a specific dataset. The dataset used belongs to the Huston hurricane that caused several damages in the nearby areas. In addition, a transfer learning property is used to store the knowledge (weights) and reuse it in the next task. Moreover, each applied classifier is used to detect the images from the dataset after it is split into training, testing and validation. Keras library is used to apply the CNN algorithm with each selected classifier to detect the images. Furthermore, the performance measures are used as a criterion to decide which classifier is the best one to detect the images with high accuracy. Eventually, the simulation results show that each classifier detect the damage/no damage image with different performance measures and then makes it easy to select the best one.

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Publication Date
Sun Mar 04 2018
Journal Name
Iraqi Journal Of Science
Effect of maternal exposure of silver nanoparticles on the histogenesis of cerebellum in post-implantation of albino rats embryos
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The central nervous system is the most important system and is very sensitive to any accidental infection during ontogenesis; it includes brain and spinal cord. The cerebellum is the second largest part of the brain after cerebrum and it’s very sensitive to the abnormal changes during the embryological development. This study was designed to investigate the effect of the maternal exposure of selected concentrations of suspension of nanoparticles on the ontogenesis of the rat cerebellum after embryos implanted in uterus. A total of 60 female pregnant rats were divided in to three groups, each contains 20 females. Group1 (G1) was treated orally with 2mg/kg /body weight (b. wt) of suspension of silver nanoparticles (Ag NPs). While group 2 (G

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Publication Date
Sun Jan 01 2023
Journal Name
8th Engineering And 2nd International Conference For College Of Engineering – University Of Baghdad: Coec8-2021 Proceedings
Preliminary quality assurance of printgrammetry technique-3D modeling from Google Earth 3D imagery data
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Publication Date
Tue Jan 01 2019
Journal Name
Journal Of Southwest Jiaotong University
Multi -Focus Image Fusion Based on Stationary Wavelet Transform and PCA on YCBCR Color Space
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The multi-focus image fusion method can fuse more than one focused image to generate a single image with more accurate description. The purpose of image fusion is to generate one image by combining information from many source images of the same scene. In this paper, a multi-focus image fusion method is proposed with a hybrid pixel level obtained in the spatial and transform domains. The proposed method is implemented on multi-focus source images in YCbCr color space. As the first step two-level stationary wavelet transform was applied on the Y channel of two source images. The fused Y channel is implemented by using many fusion rule techniques. The Cb and Cr channels of the source images are fused using principal component analysis (PCA).

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Publication Date
Thu Dec 03 2015
Journal Name
Iraqi Journal Of Science
New multispectral images classification method based on MSR and Skewness implementing on various sensor scenes
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Publication Date
Wed Aug 28 2019
Journal Name
Journal Of Engineering
     Influent Flow Rate Effect On Sewage Pump Station Performance Based On Organic And Sediment Loading
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The performance of sewage pumps stations affected by many factors through its work time which produce undesired transportation efficiency. This paper is focus on the use of artificial neural network and multiple linear regression (MLR) models for prediction the major sewage pump station in Baghdad city. The data used in this work were obtained from Al-Habibia sewage pump station during specified records- three years in Al-Karkh district, Baghdad. Pumping capability of the stations was recognized by considering the influent input importance of discharge, total suspended solids (TSS) and biological oxygen demand (BOD).  In addition, the chemical oxygen demands (COD), pH and chloride (Cl). The proposed model performanc

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Publication Date
Tue May 23 2023
Journal Name
Journal Of Sensors
On-Board Digital Twin Based on Impedance and Model Predictive Control for Aerial Robot Grasping
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Aerial manipulation of objects has a number of advantages as it is not limited by the morphology of the terrain. One of the main problems of the aerial payload process is the lack of real-time prediction of the interaction between the gripper of the aerial robot and the payload. This paper introduces a digital twin (DT) approach based on impedance control of the aerial payload transmission process. The impedance control technique is implemented to develop the target impedance based on emerging the mass of the payload and the model of the gripper fingers. Tracking the position of the interactional point between the fingers of gripper and payload, inside the impedance control, is achieved using model predictive control (MPD) approach.

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Publication Date
Wed Jan 10 2024
Journal Name
The American Journal Of Interdisciplinary Innovation And Research
SUBJECT: REVIEW METHODS OF DETECTING SUGAR IN A SAMPLE
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Publication Date
Wed Aug 03 2022
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
The relationship of forensic accounting to detecting tax fraud
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Tax fraud is following different methods of tax evasion (bypassing the laws, instructions and regulations related to tax) by not showing the real taxable income by using laws, instructions and regulations improperly, and because of the weak basic role of forensic accounting in detecting and reducing tax fraud, the problem has become more influential on the state general tax income. The main objective of the research is to identify forensic accounting and the extent to how it can be applied in the General Tax Authority to assist forensic authorities in issuing judgments in fraud cases. To achieve the objectives of the research, the descriptive analytical approach was used to reach the topic of the research, and a questionnaire (co

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Publication Date
Thu May 28 2020
Journal Name
Applied Sciences
THz-TDS for Detecting Glycol Contamination in Engine Oil
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There continues to be a need for an in-situ sensor system to monitor the engine oil of internal combustion engines. Engine oil needs to be monitored for contaminants and depletion of additives. While various sensor systems have been designed and evaluated, there is still a need to develop and evaluate new sensing technologies. This study evaluated Terahertz time-domain spectroscopy (THz-TDS) for the identification and estimation of the glycol contamination of automotive engine oil. Glycol contamination is a result of a gasket or seal leak allowing coolant to enter an engine and mix with the engine oil. An engine oil intended for use in both diesel and gasoline engines was obtained. Fresh engine oil samples were contaminated with fou

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Publication Date
Fri Mar 01 2013
Journal Name
Journal Of Economics And Administrative Sciences
The Role of Forensic Accounting in Detecting Financial Fraud
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A Forensic Accounting is represent science that deals with the application of knowledge in the areas of accounting, finance, tax and audit for the analysis, investigation, inquiry, inspection and testing issues in the civil law and criminal law in an attempt to reach the truth through which enable the Forensic Accountant to provide his Expert opinion , forensic accounting plays a major role by providing a range of important services in the field of investigation for fraud and litigation support, As one of the most important legal and accounting functions is to investigate allegations of alleged by the related parties, especially those allegations related to the existence of fraud, since the goal of judicial accountant will depend

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