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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
Fri Aug 03 2012
Journal Name
مجلة دراسات الترجمة
Assessing EFL Students` Recognition and Production of Subordinate Clauses
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This study deals with the grammatical processing ability of English Subordinate Clauses which can account for variance in word recognition and production skills. The study aims at: A) Assessing whether the students can recognize correct usage and comprehension of different types of Subordinate Clauses English grammar sentences by using appropriate word. B) Showing if the students can produce the correct type of Subordinate Clauses that should be used in English grammar sentences. To achieve these aims, a test has been conducted and distributed on 50 students at third stage at the College of Education (Ibn-Rushd) for the academic year 2012-2013. A test is exposed to a jury of experts for the purpose of ascertaining their validity. The spli

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Publication Date
Fri Jun 11 2021
Journal Name
Journal Of Computing And Information Technology
A Survey on Emotion Recognition for Human Robot Interaction
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With the recent developments of technology and the advances in artificial intelligent and machine learning techniques, it becomes possible for the robot to acquire and show the emotions as a part of Human-Robot Interaction (HRI). An emotional robot can recognize the emotional states of humans so that it will be able to interact more naturally with its human counterpart in different environments. In this article, a survey on emotion recognition for HRI systems has been presented. The survey aims to achieve two objectives. Firstly, it aims to discuss the main challenges that face researchers when building emotional HRI systems. Secondly, it seeks to identify sensing channels that can be used to detect emotions and provides a literature review

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Publication Date
Mon Jan 01 2024
Journal Name
Ieee Transactions On Emerging Topics In Computational Intelligence
Reservoir Network With Structural Plasticity for Human Activity Recognition
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Publication Date
Wed Dec 01 2021
Journal Name
Baghdad Science Journal
Biological Evaluation and Theoretical Study of Bi-dentate Ligand for Amoxicillin Derivative with Some Metal Ions
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               In this paper, the complexes of Shiff base of Methyl -6-[2-(diphenylmethylene)amino)-2-(4-hydroxyphenyl)acetamido]-2,2-dimethyl-5-oxo-1-thia-4-azabicyclo[3.2.0]heptane-3-carboxylate (L) with Cobalt(II), Nickel(II), Cupper(II) and Zinc(II) have been prepared. The compounds have been characterized by different means such as FT-IR, UV-Vis, magnetic moment, elemental microanalyses (C.H.N), atomic absorption, and molar conductance. It is obvious when looking at the spectral study that the overall complexes obtained as monomeric structure as well as the metals center moieties are two-coordinated with octahedral geometry excepting Co complexes that existed as a tetrahedral geometry. Hyper Chem-8.0.7

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Publication Date
Fri Jan 01 2016
Journal Name
Applied And Computational Mathematics
Memory Effects Due to Fractional Time Derivative and Integral Space in Diffusion Like Equation Via Haar Wavelets
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Publication Date
Thu Jun 01 2023
Journal Name
Baghdad Science Journal
Some Subclasses of Univalent and Bi-Univalent Functions Related to K-Fibonacci Numbers and Modified Sigmoid Function
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            This paper is interested in certain  subclasses of univalent and bi-univalent functions concerning  to shell- like curves connected with k-Fibonacci numbers involving modified Sigmoid activation function θ(t)=2/(1+e^(-t) ) ,t ≥0 in unit disk |z|<1 . For estimating of the initial coefficients |c_2 | , |c_3 |, Fekete-Szego ̈ inequality and the  second Hankel determinant have been investigated for the functions in our classes. 

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Publication Date
Mon Aug 01 2022
Journal Name
Telkomnika (telecommunication Computing Electronics And Control)
Dorsal hand veins features extraction and recognition by correlation coefficient
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Publication Date
Mon Sep 21 2020
Journal Name
Iraqi Journal For Electrical And Electronic Engineering
Emotion Recognition Based on Mining Sub-Graphs of Facial Components
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Facial emotion recognition finds many real applications in the daily life like human robot interaction, eLearning, healthcare, customer services etc. The task of facial emotion recognition is not easy due to the difficulty in determining the effective feature set that can recognize the emotion conveyed within the facial expression accurately. Graph mining techniques are exploited in this paper to solve facial emotion recognition problem. After determining positions of facial landmarks in face region, twelve different graphs are constructed using four facial components to serve as a source for sub-graphs mining stage using gSpan algorithm. In each group, the discriminative set of sub-graphs are selected and fed to Deep Belief Network (DBN) f

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Publication Date
Sun Jan 10 2016
Journal Name
British Journal Of Applied Science &amp; 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
Fri Jul 01 2011
Journal Name
Engineering And Technology Journal
Off-Line Arabic Signature Recognition Based on Invariant Moments Properties
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