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: day, night, shadows, fog, and low light. It produced an accuracy of 98.10% in identifying the panel area and 98.14% in segmenting symbols, while the XOR algorithm gave the best result in recognizing 2,958 symbols with an accuracy of 99.93% in 2.4 ms per symbol. Another contribution of this system is that it has proven to be able to work in real time, processing 15–18 panels per second. These results confirm the efficiency of the proposed algorithm in dealing with distorted or low-quality images and stand out as a simplified and effective alternative to the traditional methods and old associative memory algorithms. Therefore, this research provides a practical and reliable framework for identifying Iraqi vehicle plates in security and traffic applications with high time requirements.
Background: EOS (encoded by the IKZF4 gene) is a member of the zinc finger transcription factor IKaros family, and plays a critical role in Treg suppressor functions, and maintaining Treg stability. IL-6 is a soluble mediator with a pleiotropic effect on inflammation, immune response, and hematopoiesis. Aim: To estimate serum IL-6 level and EOS gene expression in Iraqi patients with psoriasis. Method: Twenty-two patients with psoriasis (8 females, 14 males) with age ranged 18-72 years, were recruited from Baghdad Teaching Hospital, Dermatology Clinic, Baghdad, and 24 healthy donors. The serum levels of IL-6 by ELISA and the gene expression of IKZF4 (EOS gene) by RT-qPCR technique. Results: The results showed a non-significant diffe
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This paper presents a meta-heuristic swarm based optimization technique for solving robot path planning. The natural activities of actual ants inspire which named Ant Colony Optimization. (ACO) has been proposed in this work to find the shortest and safest path for a mobile robot in different static environments with different complexities. A nonzero size for the mobile robot has been considered in the project by taking a tolerance around the obstacle to account for the actual size of the mobile robot. A new concept was added to standard Ant Colony Optimization (ACO) for further modifications. Simulations results, which carried out using MATLAB 2015(a) environment, prove that the suggested algorithm outperforms the standard version of AC
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The aim of this research is to know how business organizations achieve competitive advantage ,and make it sustainable through constructing a green strategy ( friend to environment) which is reflected on sustaining their competitive advantages .The problem of this study is presented through trying to answer many thoughtful questions, the most important of them are:
1-Can business organizations today make green strategies supporting their competitive advantage?
2-Is there a framework or mechanism could be depended on by business organizations to manage strategic risks of losing their competit
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BACKGROUND: The humeral shaft fractures have a good rate of union, despite this fact, still there is a significant rate of nonunion after nonoperative treatment and more often after operative treatment. AIM: The aim of the study is to evaluate the autogenous onlay graft with compression plate for treatment of persistent humeral shaft non-union with failed previous surgery both radiological and functional outcome. MATERIALS AND METHODS: A prospective study on twenty patients having persistent aseptic non-union age between 20 and 60 years old, after failed surgical treatment of fractures humeral shaft in Al-Zahra teaching and Al-Kindy teaching hospitals, while infected nonunion, diabetes mellitus, secondary metastasis, smoking, a
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Software-defined networks (SDN) have a centralized control architecture that makes them a tempting target for cyber attackers. One of the major threats is distributed denial of service (DDoS) attacks. It aims to exhaust network resources to make its services unavailable to legitimate users. DDoS attack detection based on machine learning algorithms is considered one of the most used techniques in SDN security. In this paper, four machine learning techniques (Random Forest, K-nearest neighbors, Naive Bayes, and Logistic Regression) have been tested to detect DDoS attacks. Also, a mitigation technique has been used to eliminate the attack effect on SDN. RF and KNN were selected because of their high accuracy results. Three types of ne
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The problem of the research came through the following question (what is the effectiveness of active design in contemporary industrial products), and it emphasized the importance of research to make society with its members in a positive state of activity, and what can help the industrial product design to achieve this, but the goal of the study is (determining the characteristics and principles of design Active and its effectiveness in the industrial product), and the study was determined by industrial products related to daily, recreational and sports activity, The researcher relied on a form to determine the axes of analysis for the sample models, in order to reach the results of the research, the most important of which are: Realiz
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