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HandWritten Numerals Recognition System
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  Recognition is one of the basic characteristics of human brain, and also for the living   creatures. It is possible to recognize images, persons, or patterns according to their characteristics. This recognition could be done using eyes or dedicated proposed methods. There are numerous applications for pattern recognition such as recognition of printed or handwritten letters, for example reading post addresses automatically and reading documents or check reading in bank.

      One of the challenges which faces researchers in character recognition field is the recognition of digits, which are written by hand. This paper describes a classification method for on-line handwritten digits and off-line handwritten digits in same time using Genetic Algorithm.

      Genetic Algorithms (GAs), are search procedures that use the mechanics of natural selection and natural genetics, have been used in this paper to solve numbers recognition problem. The genetic algorithm treats numbers as a binary string of [6 x 10] pixels and by the process of mating and mutating; the input string is matched to the closest existing character in a database. The proposed method is tested on a sample of 500 digits written by 10 different persons and found to perform satisfactorily most of the time; this paper realized a high percentage of 85%.

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Publication Date
Thu Dec 01 2022
Journal Name
Journal Of Education For Pure Science- University Of Thi-qar
Dorsal Hand Vein Image Recognition: A Review
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Subcutaneous vascularization has become a new solution for identification management over the past few years. Systems based on dorsal hand veins are particularly promising for high-security settings. The dorsal hand vein recognition system comprises the following steps: acquiring images from the database and preprocessing them, locating the region of interest, and extracting and recognizing information from the dorsal hand vein pattern. This paper reviewed several techniques for obtaining the dorsal hand vein area and identifying a person. Therefore, this study just provides a comprehensive review of existing previous theories. This model aims to offer the improvement in the accuracy rate of the system that was shown in previous studies and

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Publication Date
Mon Jun 05 2023
Journal Name
Journal Of Engineering
Isolated Word Speech Recognition Using Mixed Transform
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Methods of speech recognition have been the subject of several studies over the past decade. Speech recognition has been one of the most exciting areas of the signal processing. Mixed transform is a useful tool for speech signal processing; it is developed for its abilities of improvement in feature extraction. Speech recognition includes three important stages, preprocessing, feature extraction, and classification. Recognition accuracy is so affected by the features extraction stage; therefore different models of mixed transform for feature extraction were proposed. The properties of the recorded isolated word will be 1-D, which achieve the conversion of each 1-D word into a 2-D form. The second step of the word recognizer requires, the

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Publication Date
Tue Dec 05 2023
Journal Name
Baghdad Science Journal
A Novel System for Confidential Medical Data Storage Using Chaskey Encryption and Blockchain Technology
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Secure storage of confidential medical information is critical to healthcare organizations seeking to protect patient's privacy and comply with regulatory requirements. This paper presents a new scheme for secure storage of medical data using Chaskey cryptography and blockchain technology. The system uses Chaskey encryption to ensure integrity and confidentiality of medical data, blockchain technology to provide a scalable and decentralized storage solution. The system also uses Bflow segmentation and vertical segmentation technologies to enhance scalability and manage the stored data. In addition, the system uses smart contracts to enforce access control policies and other security measures. The description of the system detailing and p

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Publication Date
Thu Sep 06 2018
Journal Name
Al-khwarizmi Engineering Journal
Performance Augmenting of a Vertical Axis Wind Turbine using Adaptable Convergent Ducting System
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Developments are carried out to enhance the performance of vertical axis wind turbines (VAWT). This paper studies the performance of the ducted wind turbine with convergent duct (DAWT). Basically, the duct technique is utilized to provide the desired wind velocity facing the turbine. Methodology was developed to estimate the decisive performance parameter and to present the effect of the convergent duct with different inlet angles. The ducted wind turbine was analyzed and simulated using MATLAB software and numerically using ANSYS-Fluent 17.2. Result of both approaches were presented and showed good closeness for the two cases of covering angles 12  and 20 respectively. Results also showed that the convergent duct with an inlet angl

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Publication Date
Sun Jun 20 2021
Journal Name
Baghdad Science Journal
Performance Evaluation of Intrusion Detection System using Selected Features and Machine Learning Classifiers
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Some of the main challenges in developing an effective network-based intrusion detection system (IDS) include analyzing large network traffic volumes and realizing the decision boundaries between normal and abnormal behaviors. Deploying feature selection together with efficient classifiers in the detection system can overcome these problems.  Feature selection finds the most relevant features, thus reduces the dimensionality and complexity to analyze the network traffic.  Moreover, using the most relevant features to build the predictive model, reduces the complexity of the developed model, thus reducing the building classifier model time and consequently improves the detection performance.  In this study, two different sets of select

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Publication Date
Sun Jan 10 2016
Journal Name
British Journal Of Applied Science & Technology
The Effect of Classification Methods on Facial Emotion Recognition ‎Accuracy
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The interests toward developing accurate automatic face emotion recognition methodologies are growing vastly, and it is still one of an ever growing research field in the region of computer vision, artificial intelligent and automation. However, there is a challenge to build an automated system which equals human ability to recognize facial emotion because of the lack of an effective facial feature descriptor and the difficulty of choosing proper classification method. In this paper, a geometric based feature vector has been proposed. For the classification purpose, three different types of classification methods are tested: statistical, artificial neural network (NN) and Support Vector Machine (SVM). A modified K-Means clustering algorithm

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Publication Date
Wed Aug 01 2018
Journal Name
Engineering And Technology Journal
A Proposed Method for the Sound Recognition Process
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Publication Date
Sat Nov 02 2019
Journal Name
Advances In Intelligent Systems And Computing
Spin-Image Descriptors for Text-Independent Speaker Recognition
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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

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Publication Date
Wed Dec 01 2021
Journal Name
Journal Of Physics: Conference Series
Disc damage likelihood scale recognition for Glaucoma detection
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Abstract<p>Glaucoma 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</p> ... Show More
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Publication Date
Tue Oct 08 2002
Journal Name
Iraqi Journal Of Laser
Laser Detection and Tracking System Using an Array of Photodiodes with Fuzzy Logic controller
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In this work laser detection and tracking system (LDTS) is designed and implemented using a fuzzy logic controller (FLC). A 5 mW He-Ne laser system and an array of nine PN photodiodes are used in the detection system. The FLC is simulated using MATLAB package and the result is stored in a lock up table to use it in the real time operation of the system. The results give a good system response in the target detection and tracking in the real time operation.

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