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Multi-Model Fusion Framework Using Deep Learning for Visual-Textual Sentiment Classification

Computers, Materials & Continua 2023年第8期76卷 2145-2177页

作者： israa k.salman al-tameemi Mohammad-Reza Feizi-Derakhshi Saeed Pashazadeh Mohammad Asadpour Computerized Intelligence Systems Laboratory Department of Computer EngineeringFaculty of Electrical and Computer EngineeringUniversity of TabrizTabriz51368Iran Department of Computer Engineering Faculty of Electrical and Computer EngineeringUniversity of TabrizTabriz51368Iran State Company for Engineering Rehabilitation and Testing Iraqi Ministry of Industry and MineralsBaghdad10011Iraq

Multimodal Sentiment Analysis(SA)is gaining popularity due to its broad application *** existing studies have focused on the SA of single modalities,such as texts or photos,posing challenges in effectively handling social media data with multiple ***,most multimodal research has concentrated on merely combining the two modalities rather than exploring their complex correlations,leading to unsatisfactory sentiment classification *** by this,we propose a new visualtextual sentiment classification model named Multi-Model Fusion(MMF),which uses a mixed fusion framework for SA to effectively capture the essential information and the intrinsic relationship between the visual and textual *** proposed model comprises three deep neural *** different neural networks are proposed to extract the most emotionally relevant aspects of image and text ***,more discriminative features are gathered for accurate sentiment ***,a multichannel joint fusion modelwith a self-attention technique is proposed to exploit the intrinsic correlation between visual and textual characteristics and obtain emotionally rich information for joint sentiment ***,the results of the three classifiers are integrated using a decision fusion scheme to improve the robustness and generalizability of the proposed *** interpretable visual-textual sentiment classification model is further developed using the Local Interpretable Model-agnostic Explanation model(LIME)to ensure the model’s explainability and *** proposed MMF model has been tested on four real-world sentiment datasets,achieving(99.78%)accuracy on Binary_Getty(BG),(99.12%)on Binary_iStock(BIS),(95.70%)on Twitter,and(79.06%)on the Multi-View Sentiment Analysis(MVSA)*** results demonstrate the superior performance of our MMF model compared to single-model approaches and current state-of-the-art techniques based on model evaluation cr

关键词： Sentiment analysis multimodal classification deep learning joint fusion decision fusion interpretability

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Shear Let Transform Residual Learning Approach for Single-Image Super-Resolution

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Computers, Materials & Continua 2024年第5期79卷 3193-3209页

作者： israa Ismail Ghada Eltaweel Mohamed Meselhy Eltoukhy Department of Computer Science Faculty of Computers and InformaticsSuez Canal UniversityIsmailia51422Egypt Department of Information Technology College of Computing and Information Technology at KhulaisUniversity of JeddahJeddahSaudi Arabia

Super-resolution techniques are employed to enhance image resolution by reconstructing high-resolution images from one or more low-resolution ***-resolution is of paramount importance in the context of remote sensing,satellite,aerial,security and surveillance ***-resolution remote sensing imagery is essential for surveillance and security purposes,enabling authorities to monitor remote or sensitive areas with greater *** study introduces a single-image super-resolution approach for remote sensing images,utilizing deep shearlet residual learning in the shearlet transform domain,and incorporating the Enhanced Deep Super-Resolution network(EDSR).Unlike conventional approaches that estimate residuals between high and low-resolution images,the proposed approach calculates the shearlet coefficients for the desired high-resolution image using the provided low-resolution image instead of estimating a residual image between the high-and low-resolution *** shearlet transform is chosen for its excellent sparse approximation ***,remote sensing images are transformed into the shearlet domain,which divides the input image into low and high *** shearlet coefficients are fed into the EDSR *** high-resolution image is subsequently reconstructed using the inverse shearlet *** incorporation of the EDSR network enhances training stability,leading to improved generated *** experimental results from the Deep Shearlet Residual Learning approach demonstrate its superior performance in remote sensing image recovery,effectively restoring both global topology and local edge detail information,thereby enhancing image *** to other networks,our proposed approach outperforms the state-of-the-art in terms of image quality,achieving an average peak signal-to-noise ratio of 35 and a structural similarity index measure of approximately 0.9.

关键词： Super-resolution shearlet transform shearlet coefficients enhanced deep super-resolution network

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Classification COVID-19 Based on Enhancement X-Ray Images and Low Complexity Model

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Computers, Materials & Continua 2022年第7期72卷 561-576页

作者： Aymen Saad israa Skamil Ahmed alsayat Ahmed Elaraby Department of Information Technology Technical College of ManagementKufaAl Furat Alawsat UniversityIraq Department of Medical Laboratory Techniques Al-Mustaqbal University CollegeHillaIraq Department of Computer Science College of Computer and Information SciencesJouf UniversitySaudi Arabia Department of Computer Science Faculty of Computers and InformationSouth Valley UniversityQenaEgypt

COVID-19 has been considered one of the recent epidemics that occurred at the last of 2019 and the beginning of 2020 that world *** spread of COVID-19 requires a fast technique for diagnosis to make the appropriate decision for the treatment.X-ray images are one of the most classifiable images that are used widely in diagnosing patients’data depending on radiographs due to their structures and tissues that could be *** Neural Networks(CNN)is the most accurate classification technique used to diagnose COVID-19 because of the ability to use a different number of convolutional layers and its high classification *** using CNNs techniques requires a large number of images to learn and obtain satisfactory *** this paper,we used SqueezNet with a modified output layer to classify X-ray images into three groups:COVID-19,normal,and *** this study,we propose a deep learning method with enhance the features of X-ray images collected from kaggle,Figshare to distinguish between COVID-19,Normal,and Pneumonia *** this regard,several techniques were used on the selected image samples which are Unsharp filter,Histogram equal,and Complement image to produce another view of the *** Squeeze Net CNN model has been tested in two scenarios using the 13,437 X-ray images that include 4479 for each type(COVID-19,Normal and Pneumonia).In the first scenario,the model has been tested without any enhancement on the *** achieved an accuracy of 91%.But,in the second scenario,the model was tested using the same previous images after being improved by several techniques and the performance was high at approximately 95%.The conclusion of this study is the used model gives higher accuracy results for enhanced images compared with the accuracy results for the original images.A comparison of the outcomes demonstrated the effectiveness of ourDLmethod for classifying COVID-19 based on enhanced X-ray images.

关键词： COVID-19 X-ray image enhancement classification CNN SqueezNet model

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Super-Resolution Based on Curvelet Transform and Sparse Representation

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Computer Systems Science & Engineering 2023年第4期45卷 167-181页

作者： israa Ismail Mohamed Meselhy Eltoukhy Ghada Eltaweel Department of Computer Science Faculty of Computers and InformaticsSuez Canal UniversityIsmailia51422Egypt Department of Information Technology University of JeddahCollege of Computing and Information Technology at KhulaisJeddahSaudi Arabia

Super-resolution techniques are used to reconstruct an image with a high resolution from one or more low-resolution image(s).In this paper,we proposed a single image super-resolution *** uses the nonlocal mean filter as a prior step to produce a denoised *** proposed algorithm is based on curvelet *** converts the denoised image into low and high frequencies(sub-bands).Then we applied a multi-dimensional interpolation called Lancozos interpolation over both *** parallel,we applied sparse representation with over complete dictionary for the denoised *** proposed algorithm then combines the dictionary learning in the sparse representation and the interpolated sub-bands using inverse curvelet transform to have an image with a higher *** experimental results of the proposed super-resolution algorithm show superior performance and obviously better-recovering images with enhanced *** comparison study shows that the proposed super-resolution algorithm outperforms the *** mean absolute error is 0.021±0.008 and the structural similarity index measure is 0.89±0.08.

关键词： Super-resolution Curvelet transform non-local means filter lancozos interpolation sparse representation

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A discrete event simulation model for waiting time management in an emergency department:A case study in an Egyptian hospital

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International Journal of Modeling, Simulation, and Scientific Computing 2021年第1期12卷 1-14页

作者： israa Mohamed Faculty of Computers and Informatics Zagazig University Ash-Sharkia 44519Egypt

This paper presents a discrete event simulation model to help improving healthcare service provided by an emergency department at a private hospital at Zagazig,*** construct a patient flow division model by dividing patients according to their severity *** patients division and routing have significant evidence in improving health service in terms of waiting times and Length of Stay(LoS),there is a lack in a detailed system evaluation and implementation under this *** on system observation and health care provider’s interviews,a comprehensive and clear picture of the system has been drawn along with a conceptual model showing different patient flows through the studied system.A discrete event simulation model of the Emergency Department is built using collected *** operational scenarios were tested against the baseline scenario to study the impact of patient flow division,including different staff capacities and different patient *** indicate that waiting times and length of patient stay can be significantly improved under the proposed7 system configuration.

关键词： Discrete event simulation healthcare simulation emergency departments patient flow analysis

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Internal friction behavior of Zr_(59)Fe_(18)al_(10)Ni_(10)Nb_(3)metallic glass under different aging temperatures

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Chinese Physics B 2021年第2期30卷 426-430页

作者： israa Faisal Ghazi israa Meften Hashim Aravindhan Surendar Nalbiy Salikhovich Tuguz Aseel Maljeboree Ayad Falkaim Nisith Geetha Department of Materials Engineering Engineering CollegeUniversity of Al-QadisiyahQadisiyyahIraq Nursing College University of Al-QadisiyahQadisiyyahIraq Department of Pharmacology Saveetha Dental College and HospitalSaveetha Institute of Medical and Technical SciencesChennaiIndia Department of Higher Mathematics Kuban State Agrarian UniversityKrasnodarRussian Federation College of Sciences for Women University of BabylonBabylonIraq Department of Electrical and Electronics Engineering Sengunthar College of EngineeringTiruchengodeIndia

We investigate the role of aging temperature on relaxation of internal friction in Zr_(59)Fe_(18)al_(10)Ni_(10)Nb_(3)metallic *** this purpose,dynamic mechanical analysis with different annealing temperatures and frequency values is *** results indicate that the aging process leads to decrease in the dissipated energy in the temperature range of glass *** is also found that the increase in applied frequency weakens the loss factor intensity in the metallic ***,the kohlrausch-Williams-Watts(kWW)equation is used to evaluate the evolution of internal friction during the aging *** to the results,higher annealing temperature will make the primary internal friction in the material increase;however,a sharp decline is observed with the *** drop in characteristic time of internal friction is also closely correlated to the rate of atomic rearrangement under the dynamic excitation so that at higher annealing temperatures,the driving force for the collaborative movement of atoms is easily provided and the mean relaxation time significantly decreases.

关键词： metallic glass internal friction relaxation dynamic analysis

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The Correlation of Miller Indices with the Conductivity Mechanism of Cu-Based High-Tc Superconductor

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Journal of Modern Physics 2017年第8期8卷 1143-1151页

作者： israa Maher Emad k. al-Shakarchi Physics Department College of Science Al-Nahrain University Baghdad Iraq

The high temperature superconductor of CuBa2Ca2Cu3O8+δ(Cu-1223) was synthesized experimentally by solid-state reaction. There were many pa-rameters affecting the preparation technique such as oxygen flow, sintering temperature, sintering time, and compacted pressure. The XRD-pattern exhibited a tetragonal phase for both Cu-1223, and Cu-1212. The resistivity measurement was considered the important experiment to show the predominant phase of superconductor if it was a high phase or low phase. The critical temperature (Tc) was about (128 k) for the high phase of Cu-1223, whereas the low phase of (Cu-1212) appeared at (Tc = 64 k). The correlation between the Miller indices and resistivity measurements was a good tool to predicate the expected mechanism of conductivity within the unit cell. It was clear that the arrangement of these planes was aligned in the a-c direction. That should make the motion of the charge to be simpler by a stepping plane toward c-axis.

关键词： Solid-State Reaction High-Tc Superconductor Resistivity Measurement XRD-Pattern SEM Analysis

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Analysis of Unsteady Flow over Offshore Wind Turbines in Combination with Different types of Foundations

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Journal of Marine Science and Application 2017年第2期16卷 199-207页

作者： israa alesbe Moustafa Abdel-Maksoud Sattar aljabair Institute for Fluid Dynamics and Ship Theory (M8) Hamburg University of Technology (TUHH) D-21073 Hamburg Germany Department of Mechanical Engineering University of Technology Baghdad 10066 Iraq

Environmental effects have an important influence on Offshore Wind Turbine (OWT) power generation efficiency and the structural stability of such turbines. In this study, we use an in-house Boundary Element (BEM)-panMARE code-to simulate the unsteady flow behavior of a full OWT with various combinations of aerodynamic and hydrodynamic loads in the time domain. This code is implemented to simulate potential flows for different applications and is based on a three-dimensional first-order panel method. Three different OWT configurations consisting of a generic 5 MW NREL rotor with three different types of foundations (Monopile, Tripod, and Jacket) are investigated. These three configurations are analyzed using the RANSE solver which is carried out using ANSYS CFX for validating the corresponding results. The simulations are performed under the same environmental atmospheric wind shear and rotor angular velocity, and the wave properties are wave height of 4 m and wave period of 7.16 s. In the present work, wave environmental effects were investigated firstly for the two solvers, and good agreement is achieved. Moreover, pressure distribution in each OWT case is presented, including detailed information about local flow fields. The time history of the forces at inflow direction and its moments around the mudline at each OWT part are presented in a dimensionless form with respect to the mean value of the last three loads and the moment amplitudes obtained from the BEM code, where the contribution of rotor force is lower in the tripod case and higher in the jacket case and the calculated hydrodynamic load that effect on jacket foundation type is lower than other two cases.

关键词： panel method time domain offshore wind turbine RANSE solver boundary element method unsteady flow

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An early discharge approach for managing hospital capacity

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International Journal of Modeling, Simulation, and Scientific Computing 2017年第1期8卷 83-95页

作者： israa Mohamed Ibrahim El-Henawy Ramadan Zean El-Din Department of Computing and Information Zagazig University 44519 ZagazigEgypt Institute of Statistical Studies and Research Cairo University 12613 GizaEgypt

The kidney and Oncology Departments at Zagazig University Hospital are suffering from increased demand and limited *** patients who find all beds occupied are simply turned away,i.e.,no waiting is *** paper investigates the impact of an early discharge approach that can be applied to patients that have been scheduled to discharge within 5 h.A discrete event simulation(DES)model is built using empirical distributions based on real *** model has been validated against real data and the results have shown that the proposed early discharge approach can reduce the number of turned away patients by 10%in the kidney Department,equivalent to 182 patients annually and by 11%in the Oncology Department,equivalent to 150 patients annually.

关键词： Simulation optimization discrete event simulation

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Effect of Carbon Dioxide Therapy on Diabetic Foot Ulcer

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Journal of Diabetes Mellitus 2015年第4期5卷 284-289页

作者： Naeem Shalan Abdulrahman al-Bazzaz israa al-Ani Fadi Najem Mohammad al-Masri Faculty of Pharmacy and Medical Sciences Al-Ahliyya Amman University Amman Jordan

Ulceration of diabetic foot represents one of the most concerning complications associated with uncontrolled blood sugar in diabetes mellitus. The aim of this study is to evaluate the condition of twenty-two diabetic patients with different degrees of ulceration in their feet after daily secessions of carbon dioxide therapy. Blood flow to the affected foot was measured by Doppler;also the size, color, degree of ulceration and sensation of the ulcerative area were all evaluated. Results showed improvement of blood flow to the affected foot as well as improvement in the sensation and color of the ulcerative area. It was concluded that carbon dioxide therapy of diabetic foot was promising and needed thorough investigation to be brought widely into application.

关键词： Diabetic Foot Ulcer Carbon Dioxide Therapy

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