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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
Fri Jan 01 2021
Journal Name
Ieee Access
Microwave Nondestructive Testing for Defect Detection in Composites Based on K-Means Clustering Algorithm
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Publication Date
Fri Jul 19 2024
Journal Name
An International Journal Of Optimization And Control: Theories & Applications (ijocta)
Design optimal neural network based on new LM training algorithm for solving 3D - PDEs
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In this article, we design an optimal neural network based on new LM training algorithm. The traditional algorithm of LM required high memory, storage and computational overhead because of it required the updated of Hessian approximations in each iteration. The suggested design implemented to converts the original problem into a minimization problem using feed forward type to solve non-linear 3D - PDEs. Also, optimal design is obtained by computing the parameters of learning with highly precise. Examples are provided to portray the efficiency and applicability of this technique. Comparisons with other designs are also conducted to demonstrate the accuracy of the proposed design.

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Publication Date
Tue Jun 01 2021
Journal Name
Bulletin Of Electrical Engineering And Informatics
A new pseudorandom bits generator based on a 2D-chaotic system and diffusion property
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A remarkable correlation between chaotic systems and cryptography has been established with sensitivity to initial states, unpredictability, and complex behaviors. In one development, stages of a chaotic stream cipher are applied to a discrete chaotic dynamic system for the generation of pseudorandom bits. Some of these generators are based on 1D chaotic map and others on 2D ones. In the current study, a pseudorandom bit generator (PRBG) based on a new 2D chaotic logistic map is proposed that runs side-by-side and commences from random independent initial states. The structure of the proposed model consists of the three components of a mouse input device, the proposed 2D chaotic system, and an initial permutation (IP) table. Statist

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Publication Date
Mon Oct 02 2023
Journal Name
Journal Of Engineering
Microgrid Integration Based on Deep Learning NARMA-L2 Controller for Maximum Power Point Tracking
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This paper presents a hybrid energy resources (HER) system consisting of solar PV, storage, and utility grid. It is a challenge in real time to extract maximum power point (MPP) from the PV solar under variations of the irradiance strength.  This work addresses challenges in identifying global MPP, dynamic algorithm behavior, tracking speed, adaptability to changing conditions, and accuracy. Shallow Neural Networks using the deep learning NARMA-L2 controller have been proposed. It is modeled to predict the reference voltage under different irradiance. The dynamic PV solar and nonlinearity have been trained to track the maximum power drawn from the PV solar systems in real time.

Moreover, the proposed controller i

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Publication Date
Mon Jan 01 2024
Journal Name
Lecture Notes In Mechanical Engineering
Development and Validation of a Free Piston Engine Linear Generator Simulation Model Including Cycle-To-Cycle Variation and Ignition Timing Sub-Models
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Publication Date
Tue Sep 08 2020
Journal Name
Baghdad Science Journal
Modified BFGS Update (H-Version) Based on the Determinant Property of Inverse of Hessian Matrix for Unconstrained Optimization
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The study presents the modification of the Broyden-Flecher-Goldfarb-Shanno (BFGS) update (H-Version) based on the determinant property of inverse of Hessian matrix (second derivative of the objective function), via updating of the vector s ( the difference between the next solution and the current solution), such that the determinant of the next inverse of Hessian matrix is equal to the determinant of the current inverse of Hessian matrix at every iteration. Moreover, the sequence of inverse of Hessian matrix generated by the method would never  approach a near-singular matrix, such that the program would never break before the minimum value of the objective function is obtained. Moreover, the new modification of BFGS update (H-vers

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Publication Date
Sun Oct 31 2021
Journal Name
Iraqi Geological Journal
Estimate Gas Initially in Place of Tight Gas Reservoirs Based on Developed Methodology of Dynamic Material Balance Technique
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With growing global demand for hydrocarbons and decreasing conventional reserves, the gas industry is shifting its focus in the direction of unconventional reservoirs. Tight gas reservoirs have typically been deemed uneconomical due to their low permeability which is understood to be below 0.1mD, requiring advanced drilling techniques and stimulation to enhance hydrocarbons. However, the first step in determining the economic viability of the reservoir is to see how much gas is initially in place. Numerical simulation has been regarded across the industry as the most accurate form of gas estimation, however, is extremely costly and time consuming. The aim of this study is to provide a framework for a simple analytical method to esti

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Publication Date
Mon Apr 20 2026
Journal Name
Nauchforum
TRANSLATION STRATEGIES OF PHRASEOLOGICAL UNITS FROM ITALIAN INTO RUSSIAN: BASED ON V. ARDONE’S NOVEL THE TRAIN OF CHILDREN
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The translation of phraseological units is among the most challenging tasks in literary translation, as fixed expressions convey denotative, connotative, and cultural meanings that resist full equivalence. This study classifies the strategies employed in the Russian translation of Viola Ardone’s The Train of Children, drawing on the frameworks of Vinay and Darbelnet, Newmark, and Koller. Analysis of 37 idioms reveals five strategies, with phraseological equivalence prevailing, while compensation—though less frequent—emerges as stylistically most significant.

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Publication Date
Sun Nov 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
SDN-RA: An Optimized Reschedule Algorithm of SDN Load Balancer for Data Center Networks Based on QoS
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Abstract<p>With the development of cloud computing during the latest years, data center networks have become a great topic in both industrial and academic societies. Nevertheless, traditional methods based on manual and hardware devices are burdensome, expensive, and cannot completely utilize the ability of physical network infrastructure. Thus, Software-Defined Networking (SDN) has been hyped as one of the best encouraging solutions for future Internet performance. SDN notable by two features; the separation of control plane from the data plane, and providing the network development by programmable capabilities instead of hardware solutions. Current paper introduces an SDN-based optimized Resch</p> ... Show More
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Publication Date
Thu Nov 02 2017
Journal Name
Iraqi Journal Of Laser
Enhancement the Sensitivity of Humidity Sensor Based on an Agarose Coating Transmission-Type Photonic Crystal Fiber Interferometer
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Photonic Crystal Fiber Interferometers (PCFIs) are widely used for sensing applications. This work presents the fabrication and the characterization of a relative humidity sensor based on a polymer-coated photonic crystal fiber that operates in a Mach- Zehnder Interferometer (MZI) transmission mode. The fabrication of the sensor involved splicing a short (1 cm) length of Photonic Crystal Fiber (PCF) between two single-mode fibers (SMF). It was then coated with a layer of agarose solution. Experimental results showed that a high humidity sensitivity of 29.37 pm/%RH was achieved within a measurement range of 27–95%RH. The sensor also showed good repeatability, small size, measurement accuracy and wide humidity range. The RH sensitivity o

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