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| 1 | Analysis of Unsteady Flow over Offshore Wind Turbines in Combination with Different types of Foundations显示文摘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. | Israa Alesbe Moustafa Abdel-Maksoud Sattar Aljabair | 2017 | Journal of Marine Science and Application2017，16，2： | 3 |
| 2 | Fuzzy Logic Control of a Robotic Manipulator for Obstacles Avoidance显示文摘 | Nabeel Kadim Abid Al-Sahib Israa Rafie Shareef | 2012 | Journal of Mechanics Engineering and Automation2012，2，1： | 1 |
| 3 | Problem-based learning (PBL): Assessing students’ learning preferences using vark显示文摘 | Israa M. Alkhasawneh Majd T. Mrayyan Charles Docherty Safaa Alashram Hamzeh Y. Yousef | 2007 | Nurse Education Today2007，，5： | 1 |
| 4 | En-hanced remediation of hydrocarbon contaminated desert soilfertilized with organic carbons显示文摘 | Radwan S S Al-Mailem Dina El-Nemr Israa | 2000 | International Biodeterio-ration&Biodegradation2000，46，2： | 1 |
| 5 | A Survey of Classical Methods and New Trends in Pansharpening of Multis-pectral Images显示文摘 | Israa Amro Javier Mateos Miguel Vega | 2011 | Journal on Advances in Signal Processing2011，1，79： | 1 |
| 6 | Methods for extracellular vesicle isolation from cancer cells显示文摘Cells are known to release different types of vesicles such as small extracellular vesicles(sEVs)and large extracellular vesicles(LEVs).sEVs and LEVs play important roles in intercellular communication,pre-metastatic niche formation,and disease progression;both can be detected cell culture media and biological fluids.sEVs and LEVs contain a variety of protein and RNA cargo,and they are believed to impact many biological functions of the recipient cells upon their internalization or binding to cell surface proteins.It has recently been established that standard isolation techniques,such as differential ultracentrifugation,yield a mixed population of EVs.However,density gradient ultracentrifugation has been reported to allow the isolation of sEVs without cellular debris.Here,we describe the most common methods used to isolate sEVs from cell culture medium,mouse and human plasma,and a new technique for isolating sEVs from tissues as well.This article also provides detailed procedures to isolate LEVs. | Israa Salem Nicole M.Naranjo Amrita Singh Rachel DeRita Shiv Ram Krishn Luca S.Sirman Fabio Quaglia Alexander Duffy Nicholas Bowler Aejaz Sayeed Lucia R.Languino | 2020 | Cancer Drug Resistance2020，3，3： | 0 |
| 7 | Amiodarone Improper Rapid Intravenous Injection Can Be Ended with Serious Complications and Even Death显示文摘 | Hasan Ali Farhan Israa Fadhil Yaseen | 2015 | Journal of Pharmacy and Pharmacology2015，3，4： | 0 |
| 8 | Multi-Model Fusion Framework Using Deep Learning for Visual-Textual Sentiment Classification显示文摘Multimodal Sentiment Analysis(SA)is gaining popularity due to its broad application potential.The 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 modalities.Moreover,most multimodal research has concentrated on merely combining the two modalities rather than exploring their complex correlations,leading to unsatisfactory sentiment classification results.Motivated 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 content.The proposed model comprises three deep neural networks.Two different neural networks are proposed to extract the most emotionally relevant aspects of image and text data.Thus,more discriminative features are gathered for accurate sentiment classification.Then,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 classification.Finally,the results of the three classifiers are integrated using a decision fusion scheme to improve the robustness and generalizability of the proposed model.An 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 resilience.The 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)dataset.These 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 criteria. | Israa K.Salman Al-Tameemi Mohammad-Reza Feizi-Derakhshi Saeed Pashazadeh Mohammad Asadpour | 2023 | Computers, Materials & Continua2023，76，8： | 0 |
| 9 | An early discharge approach for managing hospital capacity显示文摘The Kidney and Oncology Departments at Zagazig University Hospital are suffering from increased demand and limited capacity.Arrival patients who find all beds occupied are simply turned away,i.e.,no waiting is allowed.This 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 data.The 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. | Israa Mohamed Ibrahim El-Henawy Ramadan Zean El-Din | 2017 | International Journal of Modeling, Simulation, and Scientific Computing2017，8，1： | 0 |
| 10 | Classification COVID-19 Based on Enhancement X-Ray Images and Low Complexity Model显示文摘COVID-19 has been considered one of the recent epidemics that occurred at the last of 2019 and the beginning of 2020 that world widespread.This 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 classified.Convolutional 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 accuracy.Classification using CNNs techniques requires a large number of images to learn and obtain satisfactory results.In this paper,we used SqueezNet with a modified output layer to classify X-ray images into three groups:COVID-19,normal,and pneumonia.In 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 infection.In 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 dataset.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 datasets.It 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. | Aymen Saad Israa SKamil Ahmed Alsayat Ahmed Elaraby | 2022 | Computers, Materials & Continua2022，，7： | 0 |
| 11 | Super-Resolution Based on Curvelet Transform and Sparse Representation显示文摘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 algorithm.It uses the nonlocal mean filter as a prior step to produce a denoised image.The proposed algorithm is based on curvelet transform.It converts the denoised image into low and high frequencies(sub-bands).Then we applied a multi-dimensional interpolation called Lancozos interpolation over both sub-bands.In parallel,we applied sparse representation with over complete dictionary for the denoised image.The 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 resolution.The experimental results of the proposed super-resolution algorithm show superior performance and obviously better-recovering images with enhanced edges.The comparison study shows that the proposed super-resolution algorithm outperforms the state-of-the-art.The mean absolute error is 0.021±0.008 and the structural similarity index measure is 0.89±0.08. | Israa Ismail Mohamed Meselhy Eltoukhy Ghada Eltaweel | 2023 | Computer Systems Science & Engineering2023，45，4： | 0 |
| 12 | Internal friction behavior of Zr_(59)Fe_(18)Al_(10)Ni_(10)Nb_(3)metallic glass under different aging temperatures显示文摘We investigate the role of aging temperature on relaxation of internal friction in Zr_(59)Fe_(18)Al_(10)Ni_(10)Nb_(3)metallic glass.For this purpose,dynamic mechanical analysis with different annealing temperatures and frequency values is applied.The results indicate that the aging process leads to decrease in the dissipated energy in the temperature range of glass transition.It is also found that the increase in applied frequency weakens the loss factor intensity in the metallic glass.Moreover,the Kohlrausch-Williams-Watts(KWW)equation is used to evaluate the evolution of internal friction during the aging process.According to the results,higher annealing temperature will make the primary internal friction in the material increase;however,a sharp decline is observed with the time.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. | Israa Faisal Ghazi Israa Meften Hashim Aravindhan Surendar Nalbiy Salikhovich Tuguz Aseel MAljeboree Ayad FAlkaim Nisith Geetha | 2021 | Chinese Physics B2021，30，2： | 0 |
| 13 | Preparation, Characterization and Release Study of Microspheres Loaded with Mychophenolic Acid Using Different Ratios of Two Molecular Weight PLGA显示文摘 | Israa Al-Ani Alaa Abdulrasool Jabar Faraj | 2013 | 材料科学与工程(中英文A版)2013，3，12： | 0 |
| 14 | A discrete event simulation model for waiting time management in an emergency department:A case study in an Egyptian hospital显示文摘This paper presents a discrete event simulation model to help improving healthcare service provided by an emergency department at a private hospital at Zagazig,Egypt.We construct a patient flow division model by dividing patients according to their severity level.Although 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 configuration.Based 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 data.Different operational scenarios were tested against the baseline scenario to study the impact of patient flow division,including different staff capacities and different patient magnitudes.Results indicate that waiting times and length of patient stay can be significantly improved under the proposed7 system configuration. | Israa Mohamed | 2021 | International Journal of Modeling, Simulation, and Scientific Computing2021，12，1： | 0 |
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