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Research on Emotion Classification Based on Multi-modal Fusion
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Nowadays, people's expression on the Internet is no longer limited to text, especially with the rise of the short video boom, leading to the emergence of a large number of modal data such as text, pictures, audio, and video. Compared to single mode data ,the multi-modal data always contains massive information. The mining process of multi-modal information can help computers to better understand human emotional characteristics. However, because the multi-modal data show obvious dynamic time series features, it is necessary to solve the dynamic correlation problem within a single mode and between different modes in the same application scene during the fusion process. To solve this problem, in this paper, a feature extraction framework of the three-dimensional dynamic expansion is established based on the common multi-modal data, for example video , sound ,text.Based on the framework, a multi-modal fusion-matched framework based on spatial and temporal feature enhancement, respectively to solve the dynamic correlation within and between modes, and then model the short and long term dynamic correlation information between different modes based on the proposed framework. Multiple group experiments performed on MOSI datasets show that the emotion recognition model constructed based on the framework proposed here in this paper can better utilize the more complex complementary information between different modal data. Compared with other multi-modal data fusion models, the spatial-temporal attention-based multimodal data fusion framework proposed in this paper significantly improves the emotion recognition rate and accuracy when applied to multi-modal emotion analysis, so it is more feasible and effective.

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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
Wed Sep 01 2021
Journal Name
Expert Systems With Applications
A long short-term recurrent spatial-temporal fusion for myoelectric pattern recognition
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Publication Date
Wed May 10 2023
Journal Name
Diagnostics
A Deep Feature Fusion of Improved Suspected Keratoconus Detection with Deep Learning
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Detection of early clinical keratoconus (KCN) is a challenging task, even for expert clinicians. In this study, we propose a deep learning (DL) model to address this challenge. We first used Xception and InceptionResNetV2 DL architectures to extract features from three different corneal maps collected from 1371 eyes examined in an eye clinic in Egypt. We then fused features using Xception and InceptionResNetV2 to detect subclinical forms of KCN more accurately and robustly. We obtained an area under the receiver operating characteristic curves (AUC) of 0.99 and an accuracy range of 97–100% to distinguish normal eyes from eyes with subclinical and established KCN. We further validated the model based on an independent dataset with

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Publication Date
Mon Jun 19 2023
Journal Name
Journal Of Engineering
Data Classification using Quantum Neural Network
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In this paper, integrated quantum neural network (QNN), which is a class of feedforward

neural networks (FFNN’s), is performed through emerging quantum computing (QC) with artificial neural network(ANN) classifier. It is used in data classification technique, and here iris flower data is used as a classification signals. For this purpose independent component analysis (ICA) is used as a feature extraction technique after normalization of these signals, the architecture of (QNN’s) has inherently built in fuzzy, hidden units of these networks (QNN’s) to develop quantized representations of sample information provided by the training data set in various graded levels of certainty. Experimental results presented here show that

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Publication Date
Wed Sep 30 2020
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
The effect of the law of amending the unified pension law No. (26) of 2019 on the size of tax revenues An applied research on a sample of Iraqi public universities: أثر تطبيق قانون التقاعد الموحد رقم (26) لسنة 2019 على حجم الايرادات الضريبية
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The contribution rate of tax revenues in the federal budget is very small compared to the rate of contribution of oil revenues and this leads to negative repercussions on the Iraqi economy and the budget becomes a prisoner of high and low oil prices, and this is a problem that needs to be studied to know the extent of the impact of economic and political decisions on the size of tax revenue and The research goal is determined in studying the effect of amending the Unified Law No (26) of 2019 on the size of annual tax revenues .                                   &

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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
Mon Feb 25 2019
Journal Name
Iraqi Journal Of Physics
Effects of multi- Deposition on the structural and optical properties of CdS nanocrystalline thin film prepared by CBD technique.
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Cadmium sulfide (CdS) nanocrystalline thin films have been prepared by chemical bath deposition (CBD) technique on commercial glass substrates at 70ºC temperature. Cadmium chloride (CdCl2) as a source of cadmium (Cd), thiourea (CS(NH2)2) as a source of sulfur and ammonia solution (NH4OH) were added to maintain the pH value of the solution at 10. The characterization of thin films was carried out through the structural and optical properties by X-ray diffraction (XRD) and UV-VIS spectroscopy. A UV-VIS optical spectroscopy study was carried out to determine the band gap of the nanocrystalline CdS thin film and it showed a blue shift with respect to the bulk value (from 3.9 - 2.4eV). In present w

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Publication Date
Tue Mar 08 2022
Journal Name
Multimedia Tools And Applications
Comparison study on the performance of the multi classifiers with hybrid optimal features selection method for medical data diagnosis
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Publication Date
Sun Mar 01 2020
Journal Name
Baghdad Science Journal
A Comparative Study on the Double Prior for Reliability Kumaraswamy Distribution with Numerical Solution
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This work, deals with Kumaraswamy distribution. Kumaraswamy (1976, 1978) showed well known probability distribution functions such as the normal, beta and log-normal but in (1980) Kumaraswamy developed a more general probability density function for double bounded random processes, which is known as Kumaraswamy’s distribution. Classical maximum likelihood and Bayes methods estimator are used to estimate the unknown shape parameter (b). Reliability function are obtained using symmetric loss functions by using three types of informative priors two single priors and one double prior. In addition, a comparison is made for the performance of these estimators with respect to the numerical solution which are found using expansion method. The

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Publication Date
Sun Dec 01 2019
Journal Name
Baghdad Science Journal
Adsorption of Some Alephatic Dicarboxylic Acids on Zinc Oxide: A kinetic and Thermodynamic Study
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The adsorption of Malonic acid, Succinic acid, Adipic acid, and Azelaic acid from their aqueous solutions on zinc oxide surface were investigated. The adsorption efficiency was investigated using various factors such as adsorbent amount, contact time, initial concentration, and temperature. Optimum conditions for acids removal from its aqueous solutions were found to be adsorbent dose (0.2 g), equilibrium contact time (40 minutes), initial acids concentration (0.005 M). Variation of temperature as a function of adsorption efficiency showed that increasing the temperature would result in decreasing the adsorption ability. Kinetic modeling by applying the pseudo-second order model can provide a better fit of the data with a greater correla

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