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International Journal of Ophthalmology(English edition) 2024年第1期17卷 61-65页

作者： Ahmed Mohamed Karara Zeinab el-Sanabary mostafa ali el-helw Tamer Ahmed Macky Mohamad Amr Salah Eddin Abdelhakim Department of Ophthalmology Kasr Al-Ainy HospitalCairo UniversityCairo 11431Egypt

AIM:To develop normative data for meibomian gland dysfunction(MGD)parameters,using non-contact meibography technique of Sirius Costruzione Strumenti Oftalmici(CSO)machine,in an Egyptian population ***:Observational,cross-sectional,analytic study,in which 104 Egyptian volunteers were *** upper lids were examined,using“Sirius CSO”*** eyelid was given a degree of meibomian gland loss(MGL),which was calculated by the software of the ***:Mean percentage MGL in right upper lid was of 30.9%±12.6%,and that of left upper lid was 32.6%±11.8%.Thirty-four volunteers(32.7%)had first-degree MGL in their right upper lid,and 67.3%had second-degree *** volunteer(1%)had zero-degree MGL in left upper lid,28(26.9%)had first-degree loss,and 75(72.1%)had second-degree *** of MGL in right upper eyelid was not related to age,but degree of MGL in left upper eyelid increased with *** was statistically significant difference between both genders for degree of MGL in right eye(P=0.036)and in left eye(P=0.027).CONCLUSION:Noncontact meibography is a useful non-invasive tool for diagnosing *** is diagnosed in 100%of apparently normal individuals;26.9%-32.7%of which have first-degree MGL,and 67.3%-72.1%have second-degree MGL.

关键词： Egyptian population meibomian gland dysfunction non-contact meibography standardization upper lid

MARIE:One-Stage Object Detection Mechanism for Real-Time Identifying of Firearms

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Computer Modeling in Engineering & Sciences 2025年第1期142卷 279-298页

作者： Diana Abi-Nader Hassan Harb ali Jaber ali Mansour Christophe Osswald Nour mostafa Chamseddine Zaki Computer Science Department Faculty of SciencesLebanese UniversityBeirut146404Lebanon College of Engineering and Technology American University of the Middle EastEgaila54200Kuwait Lab-STICC CNRS UMR 6285ENSTA-BretagneBrest29200France

Security and safety remain paramount concerns for both governments and individuals *** today’s context,the frequency of crimes and terrorist attacks is alarmingly increasing,becoming increasingly intolerable to ***,there is a pressing need for swift identification of potential threats to preemptively alert law enforcement and security forces,thereby preventing potential attacks or violent *** advancements in big data analytics and deep learning have significantly enhanced the capabilities of computer vision in object detection,particularly in identifying *** paper introduces a novel automatic firearm detection surveillance system,utilizing a one-stage detection approach named MARIE(Mechanism for Realtime Identification of Firearms).MARIE incorporates the Single Shot Multibox Detector(SSD)model,which has been specifically optimized to balance the speed-accuracy trade-off critical in firearm detection *** SSD model was further refined by integrating MobileNetV2 and InceptionV2 architectures for superior feature extraction *** experimental results demonstrate that this modified SSD configuration provides highly satisfactory performance,surpassing existing methods trained on the same dataset in terms of the critical speedaccuracy *** these innovations,MARIE sets a new standard in surveillance technology,offering a robust solution to enhance public safety effectively.

关键词： Firearm and gun detection single shot multi-box detector deep learning one-stage detector MobileNet inception convolutional neural network

Nonclassical Symmetries for Nonlinear Partial Differential Equations via Compatibility

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Communications in Theoretical Physics 2011年第10期56卷 611-616页

作者： mostafa F.el-Sabbagh Ahmad T.ali Mathematics Department Faculty of ScienceMinia UniversityMiniaEgypt King Abdul Aziz University Faculty of ScienceDepartment of MathematicsP.O.Box 80203Jeddah21589Saudi Arabia

The determining equations for the nonclassical symmetry reductions of nonlinear partial differential equations with arbitrary order can be obtained by requiring the compatibility between the original equations and the invariant surface conditions. The （2＋1）-dimensional shallow water wave equation, Boussinesq equation, and the dispersive wave equations in shallow water serve as examples i11ustrating how compatibility leads quickly and easily to the determining equations for their nonclassical symmetries.

关键词： nonclassical symmetriesm compatibility (2+ 1)-dimensional shallow water wave Boussinesq equa-tions and the dispersive wave equations in shallow water

Novel Framework of Segmentation 3D MRI of Brain Tumors

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Computers, Materials & Continua 2023年第2期74卷 3489-3502页

作者： Ibrahim Mahmoud el-Henawy mostafa elbaz Zainab H.ali Noha Sakr Department of Computer Science Faculty of Computers and InformaticsZagazig UniversityZagazigEgypt Department of Computer Science Faculty of Computers and InformaticsKafrelsheikh UniversityKafrelsheikhEgypt Department of Embedded Network Sys.and Tec. Faculty of Artificial IntelligenceKafrelsheikh UniversityKafrelsheikhEgypt Computers Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansouraEgypt

Medical image segmentation is a crucial process for computer-aided diagnosis and *** image segmentation refers to portioning the images into small,disjointed parts for simplifying the processes of analysis and *** and speckle noise are different types of noise in magnetic resonance imaging(MRI)that affect the accuracy of the segmentation process ***,image enhancement has a significant role in MRI *** paper proposes a novel framework that uses 3D MRI images from Kaggle and applies different diverse models to remove Rician and speckle noise using the best possible noise-free *** proposed techniques consider the values of Peak Signal to Noise Ratio(PSNR)and the level of noise as inputs to the attention-U-Net model for segmentation of the *** framework has been divided into three stages:removing speckle and Rician noise,the segmentation stage,and the feature extraction *** framework presents solutions for each problem at a different stage of the *** the first stage,the framework uses Vibrational Mode Decomposition(VMD)along with Block-matching and 3D filtering(Bm3D)algorithms to remove the ***,the most significant Rician noise-free images are passed to the three different methods:Deep Residual Network(DeRNet),Dilated Convolution Auto-encoder Denoising Network(Di-Conv-AE-Net),andDenoising Generative Adversarial Network(DGAN-Net)for removing the speckle *** Bm3D have achieved PSNR values for levels of noise(0,0.25,0.5,0.75)for reducing the Rician noise by(35.243,32.135,28.214,24.124)and(36.11,31.212,26.215,24.123)*** framework also achieved PSNR values for removing the speckle noise process for each level as follows:(34.146,30.313,28.125,24.001),(33.112,29.103,27.110,24.194),and(32.113,28.017,26.193,23.121)forDeRNet,Di-Conv-AE-Net,and DGAN-Net,*** experiments that have been conducted have proved the efficiency of the proposed framework a

关键词： MRI Rician noise speckle noise segmentation deep learning

Catalytic behaviors of Co-Mn/TiO_2 catalysts for Fischer-Tropsch synthesis

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燃料化学学报 2012年第12期40卷 1435-1443页

作者： mostafa Feyzi Faculty of Chemistry Razi UniversityKermanshahIran

The 15%(Co-Mn)/TiO2,(Co/Mn=1/6) catalyst was prepared using fusion procedure and studied for the conversion of synthesis gas to C2 ～ 4 *** effects of calcination conditions and operation conditions such as the H 2 / CO molar feed ratio at different temperatures,gas hourly space velocity(GHSV) and total reaction pressure on the catalytic performance of catalyst were *** stability of the catalyst during 150 h at optimal operation conditions(t = 250℃ H2 /CO= 2/1,GHSV=1 500 h-1 and p =0.3 MPa) has been *** is found that this catalyst is high stable for production C2 ～ 4 *** of both precursors and calcined catalysts by powder X-ray diffraction,scanning electron microscopy(SEM),Brunauer-Emmett-Teller(BET) specific surface area measurement and thermal analysis methods such as thermal gravimetric analysis(TGA) and differential scanning calorimetry(DSC) show that the different preparation method influences the catalyst precursor structure and morphology.

关键词：气化理论燃料化学研究发展

Design of on-board calibration methods for a digital sun sensor based on Levenberg–Marquardt algorithm and Kalman filters

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Chinese Journal of Aeronautics 2020年第1期33卷 339-351页

作者： ali RAHDAN Hossein BOLANDI mostafa ABEDI Department of electrical Engineering Iran University of Science&TechnologyTehran ***Iran Department of electrical Engineering Shahid Beheshti UniversityTehran ***Iran

Digital sun sensor is one of the most important sensors used in the Attitude Determination System(ADS)of the *** to the harsh environmental conditions that exist in the space,various distortions may occur in the sun sensor optical system that lead to the reduced accuracy of this ***,it is necessary to recalibrate the optical parameters of the aforementioned *** this purpose,first a novel attitude independent error model is proposed for the SS-411 sun sensor that includes the central point of the CCD array,installation error,filter thickness and sensor ***,the mutual interfaces between the sensor parameters are considered in the developed *** order to extract the sensor parameters,a nonlinear optimization technique called the Levenberg–Marquardt is applied to the developed model as a batch *** addition,the Extended Kalman Filter(EKF)and the Unscented Kalman Filter(UKF)have been utilized as sequential *** will be shown that by considering a worst case of variation amount for sensor parameters,an accuracy improvement of about 17°is achieved by the developed calibration *** between the developed algorithms represents that UKF has higher accuracy,shorter time convergence but higher computational load.

关键词： Digital sun sensor Extended Kalman filter Levenberg–Marquardt On-board calibration Unscented Kalman filter

Residual Attention Deep SVDD for COVID-19 Diagnosis Using CT Scans

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Computers, Materials & Continua 2023年第2期74卷 3333-3350页

作者： Akram ali Alhadad Omar Tarawneh Reham R.mostafa Hazem M.el-Bakry Information Systems Department Faculty of Computers and InformationMansoura UniversityMansoura35511Egypt Computer Science Department Ibb UniversityIbbYemen SE Department Faculty of Computer Sciences and InformaticsAmman Arab UniversityAmman11953Jordan

COVID-19 is the common name of the disease caused by the novel coronavirus(2019-nCoV)that appeared in Wuhan,China in *** the infected people is the most important factor in the fight against the *** gold-standard test to diagnose COVID-19 is polymerase chain reaction(PCR),but it takes 5–6 h and,in the early stages of infection,may produce false-negative *** Computed Tomography(CT)images to diagnose patients infected with COVID-19 has become an urgent *** this study,we propose a residual attention deep support vector data description SVDD(RADSVDD)approach to diagnose *** is a novel approach combining residual attention with deep support vector data description(DSVDD)to classify the CT *** the best of our knowledge,we are the first to combine residual attention with DSVDD in general,and specifically in the diagnosis of *** attention with DSVDD naively may cause model *** in the proposed RADSVDD guides the network during training and enables quick learning,residual connectivity prevents vanishing *** approach consists of three models,each model is devoted to recognizing one certain disease and classifying other diseases as *** models learn in an end-to-end *** proposed approach attained high performance in classifying CT images into intact,COVID-19,and non-COVID-19 *** evaluate the proposed approach,we created a dataset from published datasets and had it assessed by an experienced *** proposed approach achieved high performance,with the normal model attained sensitivity(0.96–0.98),specificity(0.97–0.99),F1-score(0.97–0.98),and area under the receiver operator curve(AUC)0.99;the COVID-19 model attained sensitivity(0.97–0.98),specificity(0.97–0.99),F1-score(0.97–0.99),and AUC 0.99;and the non-COVID pneumoniamodel attained sensitivity(0.97–1),specificity(0.98–0.99),F1-score(0.97–0.99),and AUC 0.99.

关键词： Deep learning deep SVDD residual attention anomaly detection COVID-19 Coronavirus

Experimental investigation of flow and distortion mitigation by mechanical vortex generators in a coupled serpentine inlet-turbofan engine system

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Chinese Journal of Aeronautics 2020年第5期33卷 1375-1391页

作者： Iman MAGHSOUDI Mohammad ali VAZIRY mostafa MAHMOODI Department of Aerospace Malek-Ashtar University of TechnologyTehran 158751774Iran Department of Aerospace Malek-Ashtar University of TechnologyIsfahanShahinshahr 115/83145Iran

The performance of compact,aggressive ducts in advanced propulsion systems is limited by the internal flow separation coupled with the formation of secondary counter-rotating vortices that give rise to intensive flow distortions at the duct *** experimental investigation was conducted to study the flow field and passive suppression of flow separation and Aerodynamic Interface Plane (AIP) distortion in a serpentine air inlet *** were performed by a turbofan engine at several Engine Operating Points (EOPs) from 56%(idle) to 100%(max).A large total pressure deficit region arose at the upper part of the AIP,which was associated with the upper surface flow *** the new mechanical S-type vortex generators in two longitudinal positions (VGl and VG2),separation and loss were diminished at the upper part of the duct and *** VG2 arrangement attained the maximum reductions in distortion coefficients which were 73.72%,60.7% and 37.8% in DC(90°),DC(60°) and△P_C/P metrics,*** the next step of the study,some unsteady aspects of the flow field were analyzed inside the *** separation onset and reattachment points were determined by the standard deviation of static pressure on the upper *** AIP spectral distribution showed that the boundary of low pressure and high pressure recovery regions was dominated by the maximum ***,the PSD diagram of several probes at AIP revealed the vortex shedding frequency and its higher harmonics at separation *** energy content of distinct unsteady spectral features in the bare configuration was significantly reduced using VGs,which showed the improvement of flow at the duct exit.

关键词： Distortion coefficient Power spectral density Serpentine inlet Total pressure Vortex generators

Performance and characterization of iron-nickel catalysts for light olefin production

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Journal of Natural Gas Chemistry 2010年第4期19卷 422-430页

作者： mostafa Feyzi ali Akbar Mirzaei Department of Chemistry Faculty of SciencesUniversity of Sistan & Baluchestan

A series of x （Fe,Ni）/Al2O3 catalysts （x = 2-12 wt%） were prepared using incipient wetness method and studied for the conversion of synthesis gas to light olefins.6 wt%（Fe,Ni）/Al2O3 catalyst was found to be the optimal catalyst for the production of C2-C4 *** effects of calcination behaviors and operational conditions on the catalytic performance of the optimal catalyst were *** best operational conditions were molar feed ratio H2/CO = 2/1,T = 260 ℃,gas hourly space velocity （GHSV） = 2600 h^-1 and the pressure of 3 ***-izations of both precursors and catalysts were carried out using X-ray diffraction （XRD）,temperature-programmed reduction （TPR）,scanning electron microscopy （SEM）,N2-adsorption-desorption measurement,thermal gravimetric analysis （TGA） and differential scanning calorimetry （DSC）.

关键词： calcination behaviors operational conditions catalytic performance characterization

Correlating thermal conductivity of pure hydrocarbons and aromatics via perceptron artificial neural network (PANN) method

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Chinese Journal of Chemical Engineering 2017年第5期25卷 547-554页

作者： mostafa Lashkarbolooki ali Zeinolabedini Hezave Mahdi Bayat School of Chemical Engineering Babol University of Technology Islamic Azad University Dashtestan Branch Department of Chemical Engineering Faculty of EngineeringUniversity of Bojnord

Accurate estimation of liquid thermal conductivity is highly necessary to appropriately design equipments in different industries. Respect to this necessity, in the current investigation a feed-forward artificial neural network(ANN) model is examined to correlate the liquid thermal conductivity of normal and aromatic hydrocarbons at the temperatures range of 257–338 K and atmospheric pressure. For this purpose, 956 experimental thermal conductivities for normal and aromatic hydrocarbons are collected from different previously published *** the modeling stage, to discriminate different substances, critical temperature(Tc), critical pressure(Pc)and acentric factor(ω) are utilized as the network inputs besides the temperature. During the examination, effects of different transfer functions and number of neurons in hidden layer are investigated to find the optimum network architecture. Besides, statistical error analysis considering the results obtained from available correlations and group contribution methods and proposed neural network is performed to reliably check the feasibility and accuracy of the proposed method. Respect to the obtained results, it can be concluded that the proposed neural network consisted of three layers namely, input, hidden and output layers with 22 neurons in hidden layer was the optimum ANN model. Generally, the proposed model enables to correlate the thermal conductivity of normal and aromatic hydrocarbons with absolute average relative deviation percent(AARD), mean square error(MSE), and correlation coefficient(R^2) of lower than 0.2%, 1.05 × 10^(-7) and 0.9994, respectively.

关键词： Thermal conductivity Artificial neural network Critical properties Hydrocarbons Aromatics