The License Plate (LP), is a rectangular metal plate that contains numbers and letters. This plate is fixed onto the vehicle's body. It is used as a mean to identify the vehicle. The License Plate Recognition (LPR) system is a mean where a vehicle can be identified automatically using a computer system. The LPR has many applications, such as security applications for car tracking, or enforcing control on vehicles entering restricted areas (such as airports or governmental buildings). This paper is concerned with introducing a new method to recognize the Iraqi LPs using local vertical and horizontal projections, then testing its performance. The attained success rate reached 99.16%, with average recognition time around 0.012 second for recognizing a single alphanumeric symbol .
This study concluded detection of Toxoplasma gondii in milk, immunologically by using Elisa and nested PCR)nPCR (based on B1 gene, also to investigate the effect of toxoplasmosis, parity, breed and flock on some milk composition in the Iraqi local and Shami goats in the middle of Iraq. A total of 80 milk samples of the lactating goats were collected. Results of this study showed the prevalence of Toxoplasmosis was 21.25% and 28.75% by Elisa and nPCR respectively without significant differences. The sensitivity of Elisa was a low (30.43%) whereas the specificity was a high (82.45%). The degree of agreement estimated by Kappa coefficient revealed a slight agreement (0.14) between two methods. The results indicated that goats infected
... Show MoreIn this research, we propose to use two local search methods (LSM's); Particle Swarm Optimization (PSO) and the Bees Algorithm (BA) to solve Multi-Criteria Travelling Salesman Problem (MCTSP) to obtain the best efficient solutions. The generating process of the population of the proposed LSM's may be randomly obtained or by adding some initial solutions obtained from some efficient heuristic methods. The obtained solutions of the PSO and BA are compared with the solutions of the exact methods (complete enumeration and branch and bound methods) and some heuristic methods. The results proved the efficiency of PSO and BA methods for a large number of nodes ( ). The proposed LSM's give the best efficient solutions for the MCTSP for
... Show MoreBackground: To determine the DNA content in subfertile patients and to correlate it with seminal sperm concentration.
Design: Prospective observational study.
Setting: College of Medicine, Dept. of Physiological chemistry and Institute for embryo Research and infertility treatment-University of Baghdad.The study was conducted
through years 2004-2005.
Methods: A random sample of 61 subfertile male patients undergoing semen evaluation and aged from 20-45 years were studied. Semen samples were assessed for seminal sperm
concentration microscopically and were classified into 3 different groups according to count (million/ml).Then sperm D N A content (μg/ml) was estimated using a microchemical
spectropho
This research was designed to investigate the factors affecting the frequency of use of ride-hailing in a fast-growing metropolitan region in Southeast Asia, Kuala Lumpur. An intercept survey was used to conduct this study in three potential locations that were acknowledged by one of the most famous ride-hailing companies in Kuala Lumpur. This study used non-parametric and machine learning techniques to analyze the data, including the Pearson chi-square test and Bayesian Network. From 38 statements (input variables), the Pearson chi-square test identified 14 variables as the most important. These variables were used as predictors in developing a BN model that predicts the probability of weekly usage frequency of ride-hai
... Show MoreThe main aim of this paper is to study how the different estimators of the two unknown parameters (shape and scale parameter) of a generalized exponential distribution behave for different sample sizes and for different parameter values. In particular,
. Maximum Likelihood, Percentile and Ordinary Least Square estimators had been implemented for different sample sizes (small, medium, and large) and assumed several contrasts initial values for the two parameters. Two indicators of performance Mean Square Error and Mean Percentile Error were used and the comparisons were carried out between different methods of estimation by using monte carlo simulation technique .. It was obse
... Show MoreThe Assignment model is a mathematical model that aims to express a real problem facing factories and companies which is characterized by the guarantee of its activity in order to make the appropriate decision to get the best allocation of machines or jobs or workers on machines in order to increase efficiency or profits to the highest possible level or reduce costs or time To the extent possible, and in this research has been using the method of labeling to solve the problem of the fuzzy assignment of real data has been approved by the tire factory Diwaniya, where the data included two factors are the factors of efficiency and cost, and was solved manually by a number of iterations until reaching the optimization solution,
... Show MoreThe issues of journalists and media employees in general and photojournalists in particular have become important issues, especially as those issues are closely linked to the success or failure of the media process.
This research deals with (the issues of Iraqi photojournalists working in local and foreign institutions in Iraq - a case study in 2012), because of the ambiguity in identifying those issues, which focused on the issues of this research.
This was done through the research community of members of the Association of Iraqi photojournalists in Baghdad exclusively of (64) photographers and television photographers to identify the problems encountered in their work
... Show MoreIn this paper, a compact genetic algorithm (CGA) is enhanced by integrating its selection strategy with a steepest descent algorithm (SDA) as a local search method to give I-CGA-SDA. This system is an attempt to avoid the large CPU time and computational complexity of the standard genetic algorithm. Here, CGA dramatically reduces the number of bits required to store the population and has a faster convergence. Consequently, this integrated system is used to optimize the maximum likelihood function lnL(φ1, θ1) of the mixed model. Simulation results based on MSE were compared with those obtained from the SDA and showed that the hybrid genetic algorithm (HGA) and I-CGA-SDA can give a good estimator of (φ1, θ1) for the ARMA(1,1) model. Anot
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