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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 has been developed for clustering purpose. Mainly, the purpose of using modified K-means clustering technique is to group the similar features into (K) templates in order to simulate the differences in the ways that human express each emotion. To evaluate the proposed system, a subset from Cohen-Kanade (CK) dataset have been used, it consists of 870 facial images samples for the seven basic emotions (angry, disgust, fear, happy, normal, sad, and surprise). The conducted test results indicated that SVM classifier can lead to higher performance in comparison with the results of other proposed methods due to its desirable characteristics (such as large-margin separation, good generalization performance, etc.).

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Publication Date
Mon Aug 17 2020
Journal Name
International Journal Of Applied Mechanics And Engineering
Analysis of structural concrete bar members based on secant stiffness methods
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In this paper, the behavior of structural concrete linear bar members was studied using numerical model implemented in a computer program written in MATLAB. The numerical model is based on the modified version of the procedure developed by Oukaili. The model is based on real stress-strain diagrams of concrete and steel and their secant modulus of elasticity at different loading stages. The behavior presented by normal force-axial strain and bending moment-curvature relationships is studied by calculating the secant sectional stiffness of the member. Based on secant methods, this methodology can be easily implemented using an iterative procedure to solve non-linear equations. A comparison between numerical and experimental data, illustrated

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Publication Date
Mon Aug 17 2020
Journal Name
International Journal Of Applied Mechanics And Engineering
Analysis of Structural Concrete Bar Members Based on Secant Stiffness Methods
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Abstract<p>In this paper, the behavior of structural concrete linear bar members was studied using numerical model implemented in a computer program written in MATLAB. The numerical model is based on the modified version of the procedure developed by Oukaili. The model is based on real stress-strain diagrams of concrete and steel and their secant modulus of elasticity at different loading stages. The behavior presented by normal force-axial strain and bending moment-curvature relationships is studied by calculating the secant sectional stiffness of the member. Based on secant methods, this methodology can be easily implemented using an iterative procedure to solve non-linear equations. A compari</p> ... Show More
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Publication Date
Tue Dec 05 2023
Journal Name
Baghdad Science Journal
AlexNet-Based Feature Extraction for Cassava Classification: A Machine Learning Approach
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Cassava, a significant crop in Africa, Asia, and South America, is a staple food for millions. However, classifying cassava species using conventional color, texture, and shape features is inefficient, as cassava leaves exhibit similarities across different types, including toxic and non-toxic varieties. This research aims to overcome the limitations of traditional classification methods by employing deep learning techniques with pre-trained AlexNet as the feature extractor to accurately classify four types of cassava: Gajah, Manggu, Kapok, and Beracun. The dataset was collected from local farms in Lamongan Indonesia. To collect images with agricultural research experts, the dataset consists of 1,400 images, and each type of cassava has

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Publication Date
Fri Dec 01 2017
Journal Name
British Journal Of Oral And Maxillofacial Surgery
A novel approach for the three-dimensional evaluation of facial asymmetry of unilateral cleft lip and palate patients (UCLP)
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Publication Date
Wed Sep 16 2020
Journal Name
Al-kindy College Medical Journal
The importance of anatomical zonal classification in the early management of penetrating neck injuries
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Background: Penetrating neck injuries are common problem in our country due to increasing violence, terrorist bombing and military operations.
These injuries are potentially life threating and need great attention and proper management.
Objective: The aim of this study is to focus on the importance of anatomical zonal classification of the neck in the management of penetrating injuries of the visceral compartment of the Neck.
Methods :70 patients with various injuries who were managed at causality unit and Otolaryngology department in Al-Kindy Teaching Hospital during aperiod from January 1st 2015 to October 31st 2015.
The study carried on those patient depending on proper clinical examination and their urgent management.

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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
Thu Feb 07 2019
Journal Name
Journal Of The College Of Education For Women
SPEECH RECOGNITION OF ARABIC WORDS USING ARTIFICIAL NEURAL NETWORKS
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The speech recognition system has been widely used by many researchers using different
methods to fulfill a fast and accurate system. Speech signal recognition is a typical
classification problem, which generally includes two main parts: feature extraction and
classification. In this paper, a new approach to achieve speech recognition task is proposed by
using transformation techniques for feature extraction methods; namely, slantlet transform
(SLT), discrete wavelet transforms (DWT) type Daubechies Db1 and Db4. Furthermore, a
modified artificial neural network (ANN) with dynamic time warping (DTW) algorithm is
developed to train a speech recognition system to be used for classification and recognition
purposes. T

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Publication Date
Wed Feb 25 2026
Journal Name
Journal Of Studies And Researches Of Sport Education
The effectiveness of the use of yoga exercises and its impact on the reactions of the two Alvesologih nervous and respiratory systems in the correction of antenna pistol shooting accuracy
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Publication Date
Mon Jan 01 2024
Journal Name
Bio Web Of Conferences
An overview of machine learning classification techniques
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Machine learning (ML) is a key component within the broader field of artificial intelligence (AI) that employs statistical methods to empower computers with the ability to learn and make decisions autonomously, without the need for explicit programming. It is founded on the concept that computers can acquire knowledge from data, identify patterns, and draw conclusions with minimal human intervention. The main categories of ML include supervised learning, unsupervised learning, semisupervised learning, and reinforcement learning. Supervised learning involves training models using labelled datasets and comprises two primary forms: classification and regression. Regression is used for continuous output, while classification is employed

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Publication Date
Wed Feb 14 2024
Journal Name
Aip Conference Proceedings
Segmentation Moon Images Using Different Segmentation Methods and Isolate the Lunar Craters
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Segmentation is the process of partition digital images into different parts depending on texture, color, or intensity, and can be used in different fields in order to segment and isolate the area to be partitioned. In this work images of the Moon obtained through observations in Astronomy and space dep. College of science university of Baghdad by ( Toward space telescopes and widespread used of a CCD camera) . Different segmentation methods were used to segment lunar craters. Different celestial objects cause craters when they crash into the surface of the Moon like asteroids and meteorites. Thousands of craters appears on the Moon's surface with ranges in size from meter to many kilometers, it provide insights into the age and ge

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