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bsj-3494
Developing Arabic License Plate Recognition System Using Artificial Neural Network and Canny Edge Detection
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            In recent years, there has been expanding development in the vehicular part and the number of vehicles moving on the roads in all the sections of the country. Arabic 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 proposed system consists 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 identify and detect the vehicle license plate characters, and hence the results are displayed as a text on GUI. The proposed system successfully detects LP and recognizes multi-style Arabic characters with rates of 96% and 97.872% respectively under different conditions.

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Publication Date
Tue Sep 19 2017
Journal Name
Al-academy
Pen weight and diversity of Arabic calligraphy
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           This thesis study (pen weight and diversity of Arabic calligraphy), including the Arabic script went through multiple bodies, it came through the natural evolution of societies, and helped in the renovation and development of calligraphy after they gained a clear identity as a result of development that has occurred in the materials and writing instruments, especially industry pen that led to the diversity of Arabic calligraphy, and through the exploratory research and modeling study, which was obtained that the researcher could pose a problem discussed in the first chapter of his study follows by asking: is the pen is the weight of the role in the diversity of Arabic calligrap

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Publication Date
Mon Feb 04 2019
Journal Name
Journal Of The College Of Education For Women
Developing Faculty Performance Competencies and their Reflection on Achieving Total Quality in Higher Education Institutions
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Total Quality Assurance Concept have appeared in Higher Education Institutions as a result of the continuous criticism for the lower quality of the outputs of these institutions and their inappropriacy to the needs of the job market. The faculty, i.e. teaching staff member, is one of the most important output for his/her responsibility to achieve the stated goals in higher education. This represents a problem that may influence the construction of society which has to limit his tasks, responsibilities, and competencies that should be found in a faculty, and evaluating his teaching profession in light of the prerequisites of the century to become an input to achieve quality assurance in Higher Education. Therefore, the present study aims

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Publication Date
Mon Jun 05 2023
Journal Name
Al-khwarizmi Engineering Journal
Extraction of Bovine Serum Albumin by Aqueous Two-Phase System Using PEG4000/Sodium Citrate and PEG8000/Sodium Phosphate
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Aqueous Two Phase System (ATPS) or liquid-liquid extraction is used in biotechnology to recover valuable compounds from raw sources. In Aqueous Two-Phase Systems, many factors influence the Partition coefficient, K, (which is the ratio of protein concentration in the top phase to that in the bottom phase) and the Recovery percentage (Rec%). In this research, two systems of ATPS were used: first, polyethylene glycol (PEG) 4000/Sodium citrate (SC), and the second, PEG8000/ Sodium phosphate (SPH), for the extraction of Bovine Serum Albumin (BSA). The behavior of Rec% and K of pure (BSA) in ATPS has been investigated throughout the study by the effects of five parameters: temperature, concentration of polyethylene glycol (P

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Publication Date
Mon Dec 18 2017
Journal Name
Al-khwarizmi Engineering Journal
Using Smart Control System to Enhancement the Split Air Conditioning System Performance
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In IRAQ, the air conditioners are the principal cause of high electrical demand. In summer, the outer temperature sometimes exceeds 500C which significantly effects on the A/C system performance and power consumed. In the present work, the improvement in mechanical and electrical performance of split A/C system is investigated experimentally and analytically. In this paper, performance and energy saving enhancement of a split-A/C system was experimentally investigated to be efficiently compatible with elevated temperature weathers. This improvement is accomplished via Smart Control System integrate with Proportional-Integral- Differential PID algorithm. The PIC16F877A micro-controller has been programmed with the PID and PWM c

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Publication Date
Fri Jan 01 2021
Journal Name
International Journal Of Agricultural And Statistical Sciences
DYNAMIC MODELING FOR DISCRETE SURVIVAL DATA BY USING ARTIFICIAL NEURAL NETWORKS AND ITERATIVELY WEIGHTED KALMAN FILTER SMOOTHING WITH COMPARISON
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Survival analysis is widely applied in data describing for the life time of item until the occurrence of an event of interest such as death or another event of understudy . The purpose of this paper is to use the dynamic approach in the deep learning neural network method, where in this method a dynamic neural network that suits the nature of discrete survival data and time varying effect. This neural network is based on the Levenberg-Marquardt (L-M) algorithm in training, and the method is called Proposed Dynamic Artificial Neural Network (PDANN). Then a comparison was made with another method that depends entirely on the Bayes methodology is called Maximum A Posterior (MAP) method. This method was carried out using numerical algorithms re

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Publication Date
Tue Jul 01 2025
Journal Name
Ain Shams Engineering Journal
Deep neural networks for speech enhancement and speech recognition: A systematic review
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Publication Date
Tue Jul 01 2025
Journal Name
Ain Shams Engineering Journal
Deep neural networks for speech enhancement and speech recognition: A systematic review
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Publication Date
Thu Sep 01 2016
Journal Name
Journal Of Engineering
Application of Artificial Neural Network for Predicting Iron Concentration in the Location of Al-Wahda Water Treatment Plant in Baghdad City
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Iron is one of the abundant elements on earth that is an essential element for humans and may be a troublesome element in water supplies.  In this research an AAN model was developed to predict iron concentrations in the location of Al- Wahda water treatment plant in Baghdad city by water quality assessment of iron concentrations at seven WTPs up stream Tigris River. SPSS software was used to build the ANN model. The input data were iron concentrations in the raw water for the period 2004-2011. The results indicated the best model predicted Iron concentrations at Al-Wahda WTP with a coefficient of determination 0.9142. The model used one hidden layer with two nodes and the testing error was 0.834. The ANN model coul

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Publication Date
Sun Mar 01 2020
Journal Name
Sustainable Chemistry And Pharmacy
A sustainable approach to utilize olive pips for the sorption of lead ions: Numerical modeling with aid of artificial neural network
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Publication Date
Fri Aug 12 2022
Journal Name
Future Internet
Improved DDoS Detection Utilizing Deep Neural Networks and Feedforward Neural Networks as Autoencoder
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Software-defined networking (SDN) is an innovative network paradigm, offering substantial control of network operation through a network’s architecture. SDN is an ideal platform for implementing projects involving distributed applications, security solutions, and decentralized network administration in a multitenant data center environment due to its programmability. As its usage rapidly expands, network security threats are becoming more frequent, leading SDN security to be of significant concern. Machine-learning (ML) techniques for intrusion detection of DDoS attacks in SDN networks utilize standard datasets and fail to cover all classification aspects, resulting in under-coverage of attack diversity. This paper proposes a hybr

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