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.
Building a system to identify individuals through their speech recording can find its application in diverse areas, such as telephone shopping, voice mail and security control. However, building such systems is a tricky task because of the vast range of differences in the human voice. Thus, selecting strong features becomes very crucial for the recognition system. Therefore, a speaker recognition system based on new spin-image descriptors (SISR) is proposed in this paper. In the proposed system, circular windows (spins) are extracted from the frequency domain of the spectrogram image of the sound, and then a run length matrix is built for each spin, to work as a base for feature extraction tasks. Five different descriptors are generated fro
... Show MoreResearchers are increasingly using multimodal biometrics to strengthen the security of biometric applications. In this study, a strong multimodal human identification model was developed to address the growing problem of spoofing attacks in biometric security systems. Through the use of metaheuristic optimization methods, such as the Genetic Algorithm(GA), Ant Colony Optimization(ACO), and Particle Swarm Optimization (PSO) for feature selection, this unique model incorporates three biometric modalities: face, iris, and fingerprint. Image pre-processing, feature extraction, critical image feature selection, and multibiometric recognition are the four main steps in the workflow of the system. To determine its performance, the model wa
... Show MoreGlaucoma is a visual disorder, which is one of the significant driving reason for visual impairment. Glaucoma leads to frustrate the visual information transmission to the brain. Dissimilar to other eye illness such as myopia and cataracts. The impact of glaucoma can’t be cured; The Disc Damage Likelihood Scale (DDLS) can be used to assess the Glaucoma. The proposed methodology suggested simple method to extract Neuroretinal rim (NRM) region then dividing the region into four sectors after that calculate the width for each sector and select the minimum value to use it in DDLS factor. The feature was fed to the SVM classification algorithm, the DDLS successfully classified Glaucoma d
Mouth ulcers are common oral lesions. Although several topical treatments are commercially available, their limited residence time requires frequent application, which remains a significant drawback. This study aimed to develop a novel mucoadhesive, thermosensitive, in situ gel-forming spray for local delivery of betamethasone sodium phosphate, thereby reducing systemic exposure. Formulations were optimized using the design of experiment approach to investigate the effects of thermosensitive polymers (Poloxamer 407 and Poloxamer 188), mucoadhesive polymer (hyaluronic acid), and drug incorporation on gelation temperature and time. The optimized formulation gelled at 33.3 ± 0.7 °C within 14.79 ± 1.87 s and showed a spray angle of 4
... Show MoreMany academics have concentrated on applying machine learning to retrieve information from databases to enable researchers to perform better. A difficult issue in prediction models is the selection of practical strategies that yield satisfactory forecast accuracy. Traditional software testing techniques have been extended to testing machine learning systems; however, they are insufficient for the latter because of the diversity of problems that machine learning systems create. Hence, the proposed methodologies were used to predict flight prices. A variety of artificial intelligence algorithms are used to attain the required, such as Bayesian modeling techniques such as Stochastic Gradient Descent (SGD), Adaptive boosting (ADA), Decision Tre
... Show MoreMany academics have concentrated on applying machine learning to retrieve information from databases to enable researchers to perform better. A difficult issue in prediction models is the selection of practical strategies that yield satisfactory forecast accuracy. Traditional software testing techniques have been extended to testing machine learning systems; however, they are insufficient for the latter because of the diversity of problems that machine learning systems create. Hence, the proposed methodologies were used to predict flight prices. A variety of artificial intelligence algorithms are used to attain the required, such as Bayesian modeling techniques such as Stochastic Gradient Descent (SGD), Adaptive boosting (ADA), Deci
... Show MoreIn this paper, an algorithm is suggested to train a single layer feedforward neural network to function as a heteroassociative memory. This algorithm enhances the ability of the memory to recall the stored patterns when partially described noisy inputs patterns are presented. The algorithm relies on adapting the standard delta rule by introducing new terms, first order term and second order term to it. Results show that the heteroassociative neural network trained with this algorithm perfectly recalls the desired stored pattern when 1.6% and 3.2% special partially described noisy inputs patterns are presented.
The study aimed to find out the relationship between the dimensions of internal control systems and the availability of an effective governance framework in the Sudanese banks. The study used descriptive and analytical method for collecting and analyzing the study data using SPSS program. The questionnaire was used as an analysis tool. The target sample of Sudanese bank employees, the study found several results, including that the bank avoids methods that lead to the rational use of available resources, and identifies and separation of tasks among employees, in addition to rapid response to reports The study found several recommendations, including the need for a list of banks that are sufficiently flexible and comp
... Show MoreBegan the process of re-engineering processes in the private sector as a way to assist organizations in re-thinking how to run the business in order to improve production processes and reduce operational cost, to get to compete on a global level. That was a major restructuring by further evolution in the use of technology to support innovative operations.
Entered the technology in all areas of life and different regulations, This led to use as a change in all aspects The companies achieved success and progress today through the use of resources so as to ensure the wishes of the customers and their needs, and the requirements of the market primarily, Which is reflected on the basis of building strate
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