This project presents an enhanced Iraqi vehicle plate identification system, incorporating digital processing technologies and the XOR Auto-Associative Memory advanced associative memory algorithm, towards a fast and efficient performance under diverse conditions of imagery. The system consists of three major stages: identification of the panel area, or localization, using edge transformations and morphological operations; symbol segmentation, or segmentation, based on horizontal and vertical projections for the exact extraction of numbers and letters; and finally, recognition use of XOR operations and a binary distance criterion known as Hamming Distance. The model was tested on 420 images of panels in different scenarios of lighting

Krawtchouk polynomials (KPs) and their moments are promising techniques for applications of information theory, coding theory, and signal processing. This is due to the special capabilities of KPs in feature extraction and classification processes. The main challenge in existing KPs recurrence algorithms is that of numerical errors, which occur during the computation of the coefficients in large polynomial sizes, particularly when the KP parameter (p) values deviate away from 0.5 to 0 and 1. To this end, this paper proposes a new recurrence relation in order to compute the coefficients of KPs in high orders. In particular, this paper discusses the development of a new algorithm and presents a new mathematical model for computing the

The using of the parametric models and the subsequent estimation methods require the presence of many of the primary conditions to be met by those models to represent the population under study adequately, these prompting researchers to search for more flexible parametric models and these models were nonparametric, many researchers, are interested in the study of the function of permanence and its estimation methods, one of these non-parametric methods.

For work of purpose statistical inference parameters around the statistical distribution for life times which censored data , on the experimental section of this thesis has been the comparison of non-parametric methods of permanence function, the existence

Visual analytics becomes an important approach for discovering patterns in big data. As visualization struggles from high dimensionality of data, issues like concept hierarchy on each dimension add more difficulty and make visualization a prohibitive task. Data cube offers multi-perspective aggregated views of large data sets and has important applications in business and many other areas. It has high dimensionality, concept hierarchy, vast number of cells, and comes with special exploration operations such as roll-up, drill-down, slicing and dicing. All these issues make data cubes very difficult to visually explore. Most existing approaches visualize a data cube in 2D space and require preprocessing steps. In this paper, we propose a visu

Analysis the economic and financial phenomena and other requires to build the appropriate model, which represents the causal relations between factors. The operation building of the model depends on Imaging conditions and factors surrounding an in mathematical formula and the Researchers target to build that formula appropriately. Classical linear regression models are an important statistical tool, but used in a limited way, where is assumed that the relationship between the variables illustrations and response variables identifiable. To expand the representation of relationships between variables that represent the phenomenon under discussion we used Varying Coefficient Models

Abstract

Robust controller design requires a proper definition of uncertainty bounds. These uncertainty bounds are commonly selected randomly and conservatively for certain stability, without regard for controller performance.  This issue becomes critically important for multivariable systems with high nonlinearities, as in Active Magnetic Bearings (AMB) System. Flexibility and advanced learning abilities of intelligent techniques make them appealing for uncertainty estimation. The aim of this paper is to describe the development of robust H₂/H_∞ controller for AMB based on intelligent estimation of uncertainty bounds using Adaptive Neuro Fuzzy Inference System (ANFIS).  Simulatio

In this work; Silicon dioxide (SiO2) were fabricated by pulsed
laser ablation (PLA). The electron temperature was calculated by
reading the data of I-V curve of Langmuir probe which was
employed as a diagnostic technique for measuring plasma properties.
Pulsed Nd:YA Glaser was used for measuring the electron
temperature of SiO2 plasma plume under vacuum environment with
varying both pressure and axial distance from the target surface. The
electron temperature has been measured experimentally and the
effects of each of pressure and Langmuir probe distance from the
target were studied. An inverse relationship between electron
temperature and both pressure and axial distance was observed.

This Research Tries To Investigate The Problem Of Estimating The Reliability Of Two Parameter Weibull Distribution,By Using Maximum Likelihood Method, And White Method. The Comparison Is done Through Simulation Process Depending On Three Choices Of Models (?=0.8 , ß=0.9) , (?=1.2 , ß=1.5) and (?=2.5 , ß=2). And Sample Size n=10 , 70, 150 We Use the Statistical Criterion Based On the Mean Square Error (MSE) For Comparison Amongst The Methods.

Project management are still depending on manual exchange of information based on paper documents. Where design drawings drafting by computer-aided design (CAD), but the data needed by project management software can not be extracted directly from CAD, and must be manually entered by the user. The process of calculation and collection of information from drawings and enter in the project management software needs effort and time with the possibility of errors in the transfer and enter of information. This research presents an integrated computer system for building projects where the extraction and import quantities, through the interpretation of AutoCAD drawing with MS Access database of unit costs and productivities for the pricing and

          This paper deals with studying the effect of hole inclination angle on computing slip velocity and consequently its effect on lifting capacity. The study concentrates on selected vertical wells in Rumaila field, Southern Iraq. Different methods were used to calculate lifting capacity. Lifting capacity is the most important factor for successful drilling and which reflex on preventing hole problems and reduces drilling costs. Many factors affect computing lifting capacity, so hence the effect of hole inclination angle on lifting capacity will be shown in this study. A statistical approach was used to study the lifting capacity values which deal with the effect of hole