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Development of Iraqi License Plate Recognition System based on Canny Edge Detection Method
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In recent years, there has been expanding development in the vehicular part and the number of vehicles moving on the road in all the sections of the country. Vehicle number plate identification based on image processing is a dynamic area of this work; this technique is used for security purposes such as tracking of stolen cars and access control to restricted areas. The License Plate Recognition System (LPRS) exploits a digital camera to capture vehicle plate numbers is used as input to the proposed recognition system. Basically, the developing system is consist of three phases, vehicle license plate localization, character segmentation, and character recognition, the License Plate (LP) detection is presented using canny Edge detection algorithm, Connect Component Analysis (CCA) have been exploited for segmenting characters. Finally, a Multi-Layer Perceptron Artificial Neural Network (MLPANN) model is utilized to recognize and detect the vehicle license plate characters, and hence the results are displayed as a text on GUI. The proposed system successfully identified and recognized multi_style Iraqi license plates using different image situations and it was evaluated based on different metrics performance, achieving an overall system performance of 91.99%. This results shows the effectiveness of the proposed method compared with other existing methods, whose average recognition rate is 86% and the average processing time of one image is 0.242s which proves the practicality of the proposed method.

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Publication Date
Fri Jul 01 2022
Journal Name
Arabian Journal Of Geosciences
Effect of well scheduling and pattern on project development management in unconventional tight gas reservoirs
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The advancements in horizontal drilling combined with hydraulic fracturing have been historically proven as the most viable technologies in the exploitation of unconventional resources (e.g., shale and tight gas reservoirs). However, the number of fractures, well timing, and arrangement pattern can have a significant impact on the project economy. Therefore, such design and operating parameters need to be efficiently optimized for obtaining the best production performance from unconventional gas reservoirs. In this study, the process of selecting the optimal number of fractures was conducted on a section of a tight gas reservoir model (based on data from the Whicher Range (WR) tight gas field in Western Australia). Then, the optimal number

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Publication Date
Tue Oct 01 2019
Journal Name
Journal Of Economics And Administrative Sciences
Stock Exchange and its Impact on Economic Development In the Kingdom of Saudi Arabia (KSA)
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this research paper aims at measuring and analyzing the influence of the stock exchange on the economic development in the Kingdom. This is done through comparing the Gross Domestic Product (GDP) as a changeable factor affiliated with some independent variables in the KSA stock exchange. These variables are (All Share Index {TASI}, Market Value, Trade Volume Index, number of companies and number of shares). The study covers the period from 2003 to 2017 and adapts the measuring method in analyzing this relation using the Multiple Linear Regression (Stepwise) and (SPSS). The study affirmed the validity of the

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Publication Date
Sat Jun 01 2013
Journal Name
Journal Of Economics And Administrative Sciences
The Impact of Students Dropout on Human Development in Iraq For Period ( 2001 ــ 2011 )
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Abstraet

Students dropout from the Education has a negative phenomena on individual and society and even on different aspects of life especially on the economic aspect , Thus our research tries studying and analyzing the relation between the size of dropout and human development level in Iraq and as (research sample) the first decade of this century as a studying period, the study includes the dropout in Secondary schools and depending the formal records as a main source to evaluate the size of this problem in Iraq , which shows an increase in the size of dropout in this period in comparison with the last decades of the twentieth century, this produces a negative effect on human developme

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Publication Date
Thu Mar 12 2020
Journal Name
Al-khwarizmi Engineering Journal
Optimization the Effect of Electrode Material Change on EDM Process Performance Using Taguchi Method
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Electrical Discharge Machining (EDM) is a widespread Nontraditional Machining (NTM) processes for manufacturing of a complicated geometry or very hard metals parts that are difficult to machine by traditional machining operations. Electrical discharge machining is a material removal (MR) process characterized by using electrical discharge erosion. This paper discusses the optimal parameters of EDM on high-speed steel (HSS) AISI M2 as a workpiece using copper and brass as an electrode. The input parameters used for experimental work are current (10, 24 and 42 A), pulse on time (100, 150 and 200 µs), and pulse off time (4, 12 and 25 µs) that have effect on the material removal rate (MRR), electrode wear rate (EWR) and wear ratio (WR). A

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Publication Date
Wed Feb 10 2016
Journal Name
Scientific Reports
Experimental demonstration on the deterministic quantum key distribution based on entangled photons
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As an important resource, entanglement light source has been used in developing quantum information technologies, such as quantum key distribution(QKD). There are few experiments implementing entanglement-based deterministic QKD protocols since the security of existing protocols may be compromised in lossy channels. In this work, we report on a loss-tolerant deterministic QKD experiment which follows a modified “Ping-Pong”(PP) protocol. The experiment results demonstrate for the first time that a secure deterministic QKD session can be fulfilled in a channel with an optical loss of 9 dB, based on a telecom-band entangled photon source. This exhibits a conceivable prospect of ultilizing entanglement light source in real-life fiber-based

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Publication Date
Fri Feb 04 2022
Journal Name
Neuroquantology
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 performa

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Publication Date
Tue May 01 2018
Journal Name
Journal Of Physics: Conference Series
Performance of Case-Based Reasoning Retrieval Using Classification Based on Associations versus Jcolibri and FreeCBR: A Further Validation Study
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Publication Date
Tue Nov 29 2022
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
A proposed form for the Combined Assurance report and its impact In achieving sustainable development in the Iraqi economic units
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Despite the importance of sustainable development and its dimensions in developing performance and supporting competitive advantage in economic units, there is a gap and lack of coordination between Combined Assurance  providers (management, internal audit, external audit) to report on sustainable development, and the research aims to propose a model for the Combined Assurance report to achieve development sustainable development in the Iraqi economic units, especially the Baghdad Municipality, enables assurance providers to coordinate efforts that lead to the achievement of Combined Assurance, The research found the proposed model for the Combined Assurance report in achieving sustainable development in the Iraqi economic units, es

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Publication Date
Fri Sep 27 2024
Journal Name
Journal Of Applied Mathematics And Computational Mechanics
Fruit classification by assessing slice hardness based on RGB imaging. Case study: apple slices
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Correct grading of apple slices can help ensure quality and improve the marketability of the final product, which can impact the overall development of the apple slice industry post-harvest. The study intends to employ the convolutional neural network (CNN) architectures of ResNet-18 and DenseNet-201 and classical machine learning (ML) classifiers such as Wide Neural Networks (WNN), Naïve Bayes (NB), and two kernels of support vector machines (SVM) to classify apple slices into different hardness classes based on their RGB values. Our research data showed that the DenseNet-201 features classified by the SVM-Cubic kernel had the highest accuracy and lowest standard deviation (SD) among all the methods we tested, at 89.51 %  1.66 %. This

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Publication Date
Fri Jun 17 2022
Journal Name
International Journal Of Health Sciences
Molecular detection of biofilm coding genes in Staphylococcus aureus
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In accordance with epidemic COVID-19, the elevated infection rates, disinfectant overuse and antibiotic misuse what led to immune suppression in most of the population in addition to genotypic and phenotypic alterations in the microorganisms, so a great need to reevaluate the genetic determinants that responsible for bacterial community (biofilm) has been raised. A total of 250 clinical specimens were obtained from patients in Baghdad hospitals and streaked on Mannitol salt agar medium. The results revealed that 156 isolates appeared as round yellow colonies, indicating that they were mostly identified as Staphylococcus aureus from 250 specimens. The antibiotic resistance pattern of the isolates for methicillin 37.17% (n=58), Amoxic

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