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Optical Mark Recognition using Modify Bi-directional Associative Memory
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Optical Mark Recognition (OMR) is an important technology for applications that require speedy, high-accuracy processing of a huge volume of hand-filled forms. The aim of this technology is to reduce manual work, human effort, high accuracy in assessment, and minimize time for evaluation answer sheets. This paper proposed OMR by using Modify Bidirectional Associative Memory (MBAM), MBAM has two phases (learning and analysis phases), it will learn on the answer sheets that contain the correct answers by giving its own code that represents the number of correct answers, then detection marks from answer sheets by using analysis phase. This proposal will be able to detect no selection or select more than one choice, in addition, using MBAM make it timeless because it will deal with a complete answer sheet, it no need to extract the answer boxes from the answers sheet. The proposed OMR exhibits accuracy is 99.998% in the recognition of marked and non-marked.    

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Publication Date
Wed Dec 29 2021
Journal Name
Al-khwarizmi Engineering Journal
Analysis of Magnetorheological Normally Close Directional Control Valve: Magnetorheological normally close directional control valve
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This valve is intended for use in valves for steering movement, using the qualities of the Magneto-rheological (MR) fluid to regulate the fluid, direct contact without the utilization of moving parts like a spool, a connection between electric flux, and fluid power was made, The simulation was done to employ the" finite element method of magnetism (FEMM)" to arrive at the best design. This software is used for magnetic resonance valve finite element analysis. The valve's best performance was obtained by using a closed directional control valve in the normal state normally closed (NC) MR valve, with simulation results revealing the optimum magnetic flux density in the absence of a current and the shedding condition, as well as the optimum

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Publication Date
Sat Jan 01 2022
Journal Name
International Journal Of Nonlinear Analysis And Applications
Human recognition by utilizing voice recognition and visual recognition
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Audio-visual detection and recognition system is thought to become the most promising methods for many applications includes surveillance, speech recognition, eavesdropping devices, intelligence operations, etc. In the recent field of human recognition, the majority of the research be- coming performed presently is focused on the reidentification of various body images taken by several cameras or its focuses on recognized audio-only. However, in some cases these traditional methods can- not be useful when used alone such as in indoor surveillance systems, that are installed close to the ceiling and capture images right from above in a downwards direction and in some cases people don't look straight the cameras or it cannot be added in some

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Publication Date
Thu Nov 01 2018
Journal Name
2018 1st Annual International Conference On Information And Sciences (aicis)
Speech Emotion Recognition Using Minimum Extracted Features
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Recognizing speech emotions is an important subject in pattern recognition. This work is about studying the effect of extracting the minimum possible number of features on the speech emotion recognition (SER) system. In this paper, three experiments performed to reach the best way that gives good accuracy. The first one extracting only three features: zero crossing rate (ZCR), mean, and standard deviation (SD) from emotional speech samples, the second one extracting only the first 12 Mel frequency cepstral coefficient (MFCC) features, and the last experiment applying feature fusion between the mentioned features. In all experiments, the features are classified using five types of classification techniques, which are the Random Forest (RF),

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Publication Date
Sat Dec 02 2017
Journal Name
Al-khwarizmi Engineering Journal
Human Face Recognition Using Wavelet Network
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            This paper presents a study of wavelet self-organizing maps (WSOM) for face recognition. The WSOM is a feed forward network that estimates optimized wavelet based for the discrete wavelet transform (DWT) on the basis of the distribution of the input data, where wavelet basis transforms are used as activation function.

 

 

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Publication Date
Sat May 21 2011
Journal Name
The International Journal Of Advanced Manufacturing Technology
Magneto-rheological directional control valve
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The main part in hydraulic system is directional control valve. Directional control valve has complex construction such as moving spool to control the direction of actuator for required speed. Magneto-rheological (MR) fluid is one of controllable fluids. Utilizing the MR fluid properties, direct interface can be realized between magnetic field and fluid power without the need for moving parts like spool in directional control valves. This study proposes the design of four ways/three position MR proportional directional control valve (4/3 MR valve). The construction of valve and the principle of work are presented. Analysis for magnetic circuit and simulation for valve performance were done. The experiment was conducted to show the principle

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Publication Date
Sun Nov 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
Face Recognition and Emotion Recognition from Facial Expression Using Deep Learning Neural Network
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Abstract<p>Face recognition, emotion recognition represent the important bases for the human machine interaction. To recognize the person’s emotion and face, different algorithms are developed and tested. In this paper, an enhancement face and emotion recognition algorithm is implemented based on deep learning neural networks. Universal database and personal image had been used to test the proposed algorithm. Python language programming had been used to implement the proposed algorithm.</p>
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Publication Date
Tue Apr 01 2025
Journal Name
Materials Today Communications
Engineered Composition and Morphology: Unveiling 2D Bi₂(W₁₋ₓMox)O₆ Nanosheets for Enhanced Optical and Ionizing Protection Applications
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Publication Date
Sun Jun 01 2014
Journal Name
Baghdad Science Journal
Computer aided photographic memory enhancement and speed reading (case study)
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This work aimed to design and testing of a computer program – based eyeQ improvement, photographic memory enhancement, and speed reading to match the reading speed 150 – 250 word per minute (WPM) with the mind ability of processing and eye snap shooting 5000WPM . The package designed based on Visual Basic 6. The efficiency of the designed program was tested on a 10 persons with different levels of education and ages and the results show an increase in their reading speed of approximately 25% in the first month of training with noticeable enhancement in the memory as well as an increase in the ability to read for longer time without feeling nerves or boring, a nonlinear continuously increase in reading speed is assured after the first mo

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Publication Date
Sun Sep 24 2023
Journal Name
Journal Of Al-qadisiyah For Computer Science And Mathematics
Human Recognition Using Ear Features: A Review
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Over the past few years, ear biometrics has attracted a lot of attention. It is a trusted biometric for the identification and recognition of humans due to its consistent shape and rich texture variation. The ear presents an attractive solution since it is visible, ear images are easily captured, and the ear structure remains relatively stable over time.  In this paper, a comprehensive review of prior research was conducted to establish the efficacy of utilizing ear features for individual identification through the employment of both manually-crafted features and deep-learning approaches. The objective of this model is to present the accuracy rate of person identification systems based on either manually-crafted features such as D

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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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