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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) for classification purpose. The results obtained from the different groups are then fused using Naïve Bayes classifier to make the final decision regards the emotion class. Different tests were performed using Surrey Audio-Visual Expressed Emotion (SAVEE) database and the achieved results showed that the system gives the desired accuracy (100%) when fusion decisions of the facial groups. The achieved result outperforms state-of-the-art results on the same database.

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Publication Date
Tue Dec 12 2017
Journal Name
Al-khwarizmi Engineering Journal
Model Reference Adaptive Control based on a Self-Recurrent Wavelet Neural Network Utilizing Micro Artificial Immune Systems
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Abstract 

This paper presents an intelligent model reference adaptive control (MRAC) utilizing a self-recurrent wavelet neural network (SRWNN) to control nonlinear systems. The proposed SRWNN is an improved version of a previously reported wavelet neural network (WNN). In particular, this improvement was achieved by adopting two modifications to the original WNN structure. These modifications include, firstly, the utilization of a specific initialization phase to improve the convergence to the optimal weight values, and secondly, the inclusion of self-feedback weights to the wavelons of the wavelet layer. Furthermore, an on-line training procedure was proposed to enhance the control per

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Publication Date
Sun Feb 02 2025
Journal Name
Engineering, Technology & Applied Science Research
An Enhanced Document Source Identification System for Printer Forensic Applications based on the Boosted Quantum KNN Classifier
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Document source identification in printer forensics involves determining the origin of a printed document based on characteristics such as the printer model, serial number, defects, or unique printing artifacts. This process is crucial in forensic investigations, particularly in cases involving counterfeit documents or unauthorized printing. However, consistent pattern identification across various printer types remains challenging, especially when efforts are made to alter printer-generated artifacts. Machine learning models are often used in these tasks, but selecting discriminative features while minimizing noise is essential. Traditional KNN classifiers require a careful selection of distance metrics to capture relevant printing

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Publication Date
Tue Oct 01 2013
Journal Name
Radioelectronics And Communications Systems
BER performance enhancement for secure wireless communication systems based on DCSK-MIMO techniques under Rayleigh fading channel
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There has been a growing interest in the use of chaotic techniques for enabling secure communication in recent years. This need has been motivated by the emergence of a number of wireless services which require the channel to provide very low bit error rates (BER) along with information security. As more and more information is transacted over wireless media, there has been increasing criminal activity directed against such systems. This paper investigates the feasibility of using chaotic communications over Multiple-Input-Multiple-Output (MIMO) channels. We have studied the performance of differential chaos shift keying (DCSK) with 2×2 Alamouti scheme and 2×1 Alamouti scheme for different chaotic maps over additive white Gaussian noise (

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Publication Date
Tue Jan 27 2026
Journal Name
Journal Of Baghdad College Of Dentistry
Dental arches dimensions, forms and its association to facial types in a sample of Iraqi adults with skeletal and dental class II-division 1 and class III malocclusion(A cross sectional study)
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Background: The association between facial types and dental arches forms has considerable implications in orthodontic diagnosis and treatment planning. The aim was to establish the maxillary and mandibular dental arches width and length in skeletal and dental class II division 1 and class III malocclusion groups, find out the most frequent dental arch form and facial type and the association between them and to check the gender differences. Materials and Methods: Frontal and lateral facial photographs and maxillary and mandibular occlussal photographs for 90 iraqi subjects with age 18-25 years old (45 males and 45 females) divided equally into three groups, the 1st group with class II division 1malocclusion (overjet more than 3mm but less t

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Publication Date
Sat Dec 02 2017
Journal Name
Al-khwarizmi Engineering Journal
Design of a Programmable System for Failure Modes and Effect Analysis of Steam-Power Plant Based on the Fault Tree Analysis
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In this paper, the system of the power plant has been investigated as a special type of industrial systems, which has a significant role in improving societies since the electrical energy has entered all kinds of industries, and it is considered as the artery of modern life.

   The aim of this research is to construct a programming system, which could be used to identify the most important failure modes that are occur in a steam type of power plants. Also the effects and reasons of each failure mode could be analyzed through the usage of this programming system reaching to the basic events (main reasons) that causing each failure mode. The construction of this system for FMEA is dependi

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Publication Date
Fri Mar 31 2017
Journal Name
Al-khwarizmi Engineering Journal
Design of Nonlinear PID Neural Controller for the Speed Control of a Permanent Magnet DC Motor Model based on Optimization Algorithm
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In this paper, the speed control of the real DC motor is experimentally investigated using nonlinear PID neural network controller. As a simple and fast tuning algorithm, two optimization techniques are used; trial and error method and particle swarm optimization PSO algorithm in order to tune the nonlinear PID neural controller's parameters and to find best speed response of the DC motor. To save time in the real system, a Matlab simulation package is used to carry out these algorithms to tune and find the best values of the nonlinear PID parameters. Then these parameters are used in the designed real time nonlinear PID controller system based on LabVIEW package. Simulation and experimental results are compared with each other and showe

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Publication Date
Mon Nov 18 2024
Journal Name
Molecular Crystals And Liquid Crystals
Synthesis and liquid crystal properties of a new class of calamitic mesogens based on twin 1,3,4-thiadiazole derivatives with imine linkage
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Publication Date
Wed May 01 2024
Journal Name
Journal Of Drug Delivery Science And Technology
Antibacterial and wound healing performance of a novel electrospun nanofibers based on polymethyl-methacrylate/gelatin impregnated with different content of propolis
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Publication Date
Fri Jun 18 2021
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Quadtree partitioning scheme of color image based
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Publication Date
Thu May 31 2018
On the Use of 6th-Order Tunable Complementary Metal-Oxide-Semiconductor Varactor based Filter in Ultra-Wideband Low Noise Amplifier
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Background:

The plethora of the emerged radio frequency applications makes the frequency spectrum crowded by many applications and hence the ability to detect specific application’s frequency without distortion is a difficult task to achieve.

Objective:

The goal is to achieve a method to mitigate the highest interferer power in the frequency spectrum in order to eliminate the distortion.

Method:

This paper presents the application of the proposed tunable 6th-order notch filter on Ultra-Wideband (UWB) Complementary Metal-Oxide-Semiconductor (CMOS) Low Noise

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