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A novel facial emotion recognition scheme based on graph mining
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Recent years have seen an explosion in graph data from a variety of scientific, social and technological fields. From these fields, emotion recognition is an interesting research area because it finds many applications in real life such as in effective social robotics to increase the interactivity of the robot with human, driver safety during driving, pain monitoring during surgery etc. A novel facial emotion recognition based on graph mining has been proposed in this paper to make a paradigm shift in the way of representing the face region, where the face region is represented as a graph of nodes and edges and the gSpan frequent sub-graphs mining algorithm is used to find the frequent sub-structures in the graph database of each emotion. To reduce the number of generated sub-graphs, overlap ratio metric is utilized for this purpose. After encoding the final selected sub-graphs, binary classification is then applied to classify the emotion of the queried input facial image using six levels of classification. Binary cat swarm intelligence is applied within each level of classification to select proper sub-graphs that give the highest accuracy in that level. Different experiments have been conducted using Surrey Audio-Visual Expressed Emotion (SAVEE) database and the final system accuracy was 90.00%. The results show significant accuracy improvements (about 2%) by the proposed system in comparison to current published works in SAVEE database.

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Publication Date
Tue Mar 30 2021
Journal Name
Journal Of Economics And Administrative Sciences
Using Iterative Reweighting Algorithm and Genetic Algorithm to Calculate The Estimation of The Parameters Of The Maximum Likelihood of The Skew Normal Distribution
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Excessive skewness which occurs sometimes in the data is represented as an obstacle against normal distribution. So, recent studies have witnessed activity in studying the skew-normal distribution (SND) that matches the skewness data which is regarded as a special case of the normal distribution with additional skewness parameter (α), which gives more flexibility to the normal distribution. When estimating the parameters of (SND), we face the problem of the non-linear equation and by using the method of Maximum Likelihood estimation (ML) their solutions will be inaccurate and unreliable. To solve this problem, two methods can be used that are: the genetic algorithm (GA) and the iterative reweighting algorithm (IR) based on the M

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Publication Date
Sun Oct 01 2023
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science
Intelligence framework dust forecasting using regression algorithms models
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<span>Dust is a common cause of health risks and also a cause of climate change, one of the most threatening problems to humans. In the recent decade, climate change in Iraq, typified by increased droughts and deserts, has generated numerous environmental issues. This study forecasts dust in five central Iraqi districts using machine learning and five regression algorithm supervised learning system framework. It was assessed using an Iraqi meteorological organization and seismology (IMOS) dataset. Simulation results show that the gradient boosting regressor (GBR) has a mean square error of 8.345 and a total accuracy ratio of 91.65%. Moreover, the results show that the decision tree (DT), where the mean square error is 8.965, c

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Publication Date
Mon Jun 01 2020
Journal Name
Journal Of Planner And Development
The Quantitative Analysis To Assess The Efficiency Of The Transport Network In Sader City
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     This research examines the quantitative analysis to assess the efficiency of the transport network in Sadr City, where the study area suffers from a large traffic movement  for the variability of traffic flow and intensity at peak hours as a result of inside traffic and outside of it, especially in the neighborhoods of population with  economic concentration.                                                           &n

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Publication Date
Tue Dec 26 2017
Journal Name
Al-khwarizmi Engineering Journal
Determination of Welding Velocity and Arc Energy for Fusion MAG Welding Joint
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 Abstract

This paper is an experimental work to determinate the effect of welding velocity and formed arc energy for CO2-MAG fusion weld pool. The input parameters (arc voltage, wire feed speed and gas flow rate) were investigated to find their effects on the weld joint efficiency. Design of experiment with response surface methodology technique was used to build empirical mathematical models for welding velocity and arc energy in term of the input welding parameters. The predicted quadratic models were statistically checked for adequacy purpose by ANOVA analysis. Additionally, numerical optimization was conducted to obtain the optimum values for welding velocity and arc energy. A good agree

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Publication Date
Fri Jun 01 2018
Journal Name
Journal Of Engineering
Experimental Study of Optimum Chilled Water Distribution Configuration in Air Conditioning Terminal Unit Using RSM Technique
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The distribution of chilled water flow rate in terminal unit is an important factor used to evaluate the performance of central air conditioning unit. A prototype of A/C unit has been made, which contains three terminal units with a complete set of accessories (3-way valve, 2-way valve, and sensors) to study the effect of the main parameters, such as total water flow rate and chilled water supply temperature with variable valve opening. In this work, 40 tests were carried out. These tests were in two groups, 20 test for 3-way valve case and 20 test for 2-way valve case. These tests were performed at three levels of valve opening, total water flow rate and water supply temperature according to the design matrices establis

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Publication Date
Sun Dec 14 2014
Journal Name
Al-khwarizmi Engineering Journal
Determination of Optimum Welding Parameters for FSW AA2024-T351
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Abstract

Friction stir welding is a relatively new joining process, which involves the joining of metals without fusion or filler materials. In this study, the effect of welding parameters on the mechanical properties of aluminum alloys AA2024-T351 joints produced by FSW was investigated.

Different ranges of welding parameters, as input factors, such as welding speed (6 - 34 mm/min) and rotational speed (725 - 1235 rpm) were used to obtain their influences on the main responses, in terms of elongation, tensile strength, and maximum bending force. Experimental measurements of main responses were taken and analyzed using DESIGN EXPERT 8 experimental design software which was used to develop t

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Publication Date
Wed Nov 01 2017
Journal Name
Journal Of Engineering
Modelling and Optimization of Corrosion Inhibition of Mild Steel in Phosphoric Acid by Red Pomegranate Peels Aqueous Extract
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Taguchi experimental design (TED) is applied to find the optimum effectiveness of aqueous Red Pomegranate Peel (RPP) extract as a green inhibitor for the corrosion of mild steel in 2M H3PO4 solution. The Taguchi methodology has been used to study the effects of changing, temperature, RPP concentration and contact period, at three levels. Weight-loss measurements were designed by construction a L9 orthogonal arrangement of experiments.   Results of the efficiencies of inhibition were embraced for the signal to noise proportion & investigation of variance (ANOVA).  The results were further processed with a MINITAB-17 software package to find the optimal condition

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Publication Date
Thu Mar 31 2022
Journal Name
Iraqi Geological Journal
Development of Artificial Intelligence Models for Estimating Rate of Penetration in East Baghdad Field, Middle Iraq
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It is well known that the rate of penetration is a key function for drilling engineers since it is directly related to the final well cost, thus reducing the non-productive time is a target of interest for all oil companies by optimizing the drilling processes or drilling parameters. These drilling parameters include mechanical (RPM, WOB, flow rate, SPP, torque and hook load) and travel transit time. The big challenge prediction is the complex interconnection between the drilling parameters so artificial intelligence techniques have been conducted in this study to predict ROP using operational drilling parameters and formation characteristics. In the current study, three AI techniques have been used which are neural network, fuzzy i

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Publication Date
Wed Dec 01 2021
Journal Name
Baghdad Science Journal
Advanced Intelligent Data Hiding Using Video Stego and Convolutional Neural Networks
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Steganography is a technique of concealing secret data within other quotidian files of the same or different types. Hiding data has been essential to digital information security. This work aims to design a stego method that can effectively hide a message inside the images of the video file.  In this work, a video steganography model has been proposed through training a model to hiding video (or images) within another video using convolutional neural networks (CNN). By using a CNN in this approach, two main goals can be achieved for any steganographic methods which are, increasing security (hardness to observed and broken by used steganalysis program), this was achieved in this work as the weights and architecture are randomized. Thus,

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Publication Date
Sun Oct 01 2017
Journal Name
International Journal Of Science And Research (ij
Simulation of Chlorine Decay in Al-Gukook WaterDistribution Networks Using EPANET
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The approach of the research is to simulate residual chlorine decay through potable water distribution networks of Gukookcity. EPANET software was used for estimating and predicting chlorine concentration at different water network points . Data requiredas program inputs (pipe properties) were taken from the Baghdad Municipality, factors that affect residual chlorine concentrationincluding (pH ,Temperature, pressure ,flow rate) were measured .Twenty five samples were tested from November 2016 to July 2017.The residual chlorine values varied between ( 0.2-2mg/L) , and pH values varied between (7.6 -8.2) and the pressure was very weak inthis region. Statistical analyses were used to evaluated errors. The calculated concentrations by the calib

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