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作者： ESHAQ mohammed ADNAN ahmed 湖南大学

学位级别：硕士

本文通过对安曼阿拉伯大学与湖南大学的比较性分析研究,旨在衡量工商管理研究生的创业特征及其对创业能力的影响。我们设计并分发了一份调查问卷,对（115）名男女学生进行分层抽样,其调查对象为该学年（2018-2019）的硕士和博士学位课... 详细信息

本文通过对安曼阿拉伯大学与湖南大学的比较性分析研究,旨在衡量工商管理研究生的创业特征及其对创业能力的影响。我们设计并分发了一份调查问卷,对（115）名男女学生进行分层抽样,其调查对象为该学年（2018-2019）的硕士和博士学位课程。问卷中使用了很多分析、描述和推理方法。此项研究的主要结论如下:安曼阿拉伯大学和湖南大学工商管理研究生的创业特征与创业能力之间存在正相关关系,皮尔逊相关系数为（.460）。这一趋势的力度表明,创业特征每增加一个单位,将导致创业能力增加33%。安曼阿拉伯大学和湖南大学工商管理研究生创业特征在显著性水平（0.05）上对创业能力有统计意义上的影响,为22.1%,对创业行为的影响占21.9%,对创业意愿的影响占8.7%。安曼阿拉伯大学和湖南大学工商管理研究生的创业能力和创业行为存在统计学意义上的显著差异,但其创业意愿无显著差异这项研究的主要建议如下:建议工商管理研究生课程和工商经济学院的教师将重点放在创业相关的学术课程,并在提供企业孵化器和适当的教学方法上,运用模拟实战的方法和手段,发现学生的创业特征,为创业做好准备

关键词：工商管理专业研究生创业特征学术课程

Design & Implement of Smart Office Control based on RS-485 Protocol

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Design & Implement of Smart Office Control based on RS-485 P...

作者： Abdulrahman mohammed ahmed Alshaikh 湖南大学

学位级别：硕士

本文介绍了基于RS-485通信协议的远程智能办公控制系统的基本原理。该系统主要包括个人计算机、接口工具和收发装置。利用PC串行端口和ART电缆在PC遥控器和微控制器之间建立通信,当数据信号转换为RS-485信号后,可以远距离(高达4000英尺... 详细信息

本文介绍了基于RS-485通信协议的远程智能办公控制系统的基本原理。该系统主要包括个人计算机、接口工具和收发装置。利用PC串行端口和ART电缆在PC遥控器和微控制器之间建立通信,当数据信号转换为RS-485信号后,可以远距离(高达4000英尺)发送和接收数据,实现信号长距离传输。本文借助Visual Basic平台,利用C语言对微控制器(pic16f960)进行程,利用RS-232实现PC远程控制器和微控制器(pic16f960)之间实现串行连接。基于上述方法,用户可以轻松读取驱动程序在LCD模块上发送的数据。此外,本文利用RS-485的操作原理将RS-232信号转换成RS-485信号,以便其长距离传输。接收器则将RS-485信号转换回原始信号,供单片机使用,进而实现用户远程控制办公设备的开启与关闭。本文研究了RS-485使用的双绞线电缆的电气性能,与其他电缆相比,双绞线电缆抗干扰能力强,价格相对便宜。通过对该系统样机的测试,验证了该系统理论的可行性。

关键词：微控制器 RS-485通信协议智能办公控制系统 C语言电器设备

IOT Based Smart Parking System Using Ensemble Learning

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Intelligent Automation & Soft Computing 2023年第6期36卷 3637-3656页

作者： Walaa H.Elashmawi Ahmad Akram mohammed Yasser Menna Hisham Manar mohammed Noha Ihab ahmed Ali Department of Computer Science Faculty of Computers and InformaticsSuez Canal University4.5 Km the Ring RoadIsmailiaIsmailia41522Egypt Department of Computer Engineering and Software Systems Faculty of EngineeringAin Shams UniversityAl-Abbaseya4543070Egypt Department of Computer Science Faculty of Computer ScienceMisr International University28 KM Cairo–Ismailia RoadCairo44971Egypt College of Computer Engineering and Sciences Prince Sattam Bin Abdulaziz UniversityAl-Kharj11942Saudi Arabia Higher Future Institute for Specialized Technological Studies Cairo3044Egypt

Parking space is usually very limited in major cities,especially Cairo,leading to traffic congestion,air pollution,and driver *** car parking systems tend to tackle parking issues in a non-digitized *** systems require the drivers to search for an empty parking space with no guaran-tee of finding any wasting time,resources,and causing unnecessary *** address these issues,this paper proposes a digitized parking system with a proof-of-concept implementation that combines multiple technological concepts into one solution with the advantages of using IoT for real-time tracking of park-ing *** authentication and automated payments are handled using a quick response(QR)code on entry and *** experiments were done on real data collected for six different locations in Cairo via a live popular times *** machine learning models were investigated in order to estimate the occu-pancy rate of certain ***,a clear analysis of the differences in per-formance is illustrated with the final model deployed being *** has achieved the most efficient results with a R^(2) score of 85.7%.

关键词： IoT XGBoost linear regression random forest ensemble learning isolation forest

Analogue Modelling of Fold-and-Thrust Belts Controlled by Multiple Detachment Layers: An Example from the Eastern Sichuan Basin

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Analogue Modelling of Fold-and-Thrust Belts Controlled by Mu...

作者： mohammed Saleh ahmed Gaghman 中国石油大学(华东)

学位级别：硕士

四川盆地位于中国西南部,经历了复杂的构造演化过程,也是中国油气资源最为丰富的盆地之一。四川盆地东部褶皱带(简称“川东褶皱带”)以发育隔档式褶皱为主要构造特征,构造变形较为复杂。同时,在川东褶皱带,发现了三套塑性滑脱层分别为... 详细信息

四川盆地位于中国西南部,经历了复杂的构造演化过程,也是中国油气资源最为丰富的盆地之一。四川盆地东部褶皱带(简称“川东褶皱带”)以发育隔档式褶皱为主要构造特征,构造变形较为复杂。同时,在川东褶皱带,发现了三套塑性滑脱层分别为中下寒武统膏盐岩、志留系泥岩、中下三叠统膏盐岩。以这三套滑脱层为界可将川东地层划分为三套构造层:深部寒武系-奥陶系构造层(以中下寒武统膏盐岩滑脱层为底界),中部石炭系-二叠系构造层(以志留系泥岩滑脱层为底界)和浅部中生界构造层(以中下三叠统膏盐岩滑脱层为底界)。三套滑脱层将川东地区垂向上划分为上中、下三套构造层,各构造层之间的构造变形具有显著差异。尽管前人已经针对川东褶皱带开展了大量的研究工作并取得了一定的认识,然而关于这三套滑脱层对川东褶皱带构造变形过程所起到的控制作用尚待明确。本文在地震解译和构造平衡恢复的基础之上,结合多滑脱层砂箱物理模拟实验开展研究,重点探讨川东地区多套滑脱层对川东褶皱带构造变形的控制作用。首先,通过地震解译和构造平衡恢复(Midland Valley),刻画出川东褶皱带的构造特征,其构造平衡恢复结果表明:川东褶皱带最大缩短量为26.13km(缩短率约为20.34%),最大缩短速率为0.090 mm/a。在此基础上,根据川东褶皱带地层发育特点和构造特征,设置了五组构造物理模拟实验,通过控制滑脱层数量、滑脱层厚度、缩短量与缩短速率等参数,模拟和研究川东褶皱带构造变形的运动学过程,并定量评价了构造变形的过程。实验结果表明,滑脱层配置(数量、垂向分布等)和变形速率对川东多套滑脱层发育区的构造变形样式及构造演化过程具有重要的控制作用:(1)深部滑脱层的拆离效果显著强于浅部滑脱层,导致垂向上深部构造层内的构造变形差异性高于浅部构造层(2)缩短速率减小时,滑脱层的拆离效果明显增加,各构造层变形样式的差异性也随之增强。结合地震资料和砂箱模拟实验结果分析,推测川东地区在早期弱挤压变形阶段(缩短速率较低),其三套滑脱层的拆离作用明显,以发育滑脱褶皱及小型调节断层为主要构造变形特征,同时各构造层变形特征产生了明显的垂向差异性;在后期强烈挤压变形阶段(缩短速率快速提升),缩短速率限制了各滑脱层的拆离作用,各构造层以发育高陡逆冲断层和反冲断层为主,变形特征趋于一致。

关键词：四川盆地褶皱冲断带多滑脱层构造平衡恢复构造物理模拟

Intelligent Firefly Algorithm Deep Transfer Learning Based COVID-19 Monitoring System

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Computers, Materials & Continua 2023年第2期74卷 2889-2903页

作者： Mahmoud Ragab mohammed W.Al-Rabia Sami Saeed Binyamin ahmed A.Aldarmahi Information Technology Department Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah 21589Saudi Arabia Centre for Artificial Intelligence in Precision Medicines King Abdulaziz UniversityJeddah 21589Saudi Arabia Mathematics Department Faculty of ScienceAl-Azhar UniversityNaser City 11884CairoEgypt Department of Medical Microbiology and Parasitology Faculty of MedicineKing Abdulaziz UniversityJeddah 21589Saudi Arabia Health Promotion Center King Abdulaziz UniversityJeddah 21589Saudi Arabia Computer and Information Technology Department The Applied CollegeKing Abdulaziz UniversityJeddah 21589Saudi Arabia Basic Science Department College of Science and Health ProfessionsKing Saud Bin Abdulaziz University for Health SciencesJeddah 21423Saudi Arabia King Abdullah International Medical Research Center Ministry of National Guard-Health AffairsJeddah 21423Saudi Arabia

With the increasing and rapid growth rate of COVID-19 cases,the healthcare scheme of several developed countries have reached the point of *** important and critical steps in fighting against COVID-19 is powerful screening of diseased patients,in such a way that positive patient can be treated and isolated.A chest radiology image-based diagnosis scheme might have several benefits over traditional *** accomplishment of artificial intelligence(AI)based techniques in automated diagnoses in the healthcare sector and rapid increase in COVID-19 cases have demanded the requirement of AI based automated diagnosis and recognition *** study develops an Intelligent Firefly Algorithm Deep Transfer Learning Based COVID-19Monitoring System(IFFA-DTLMS).The proposed IFFADTLMSmodelmajorly aims at identifying and categorizing the occurrence of COVID19 on chest *** attain this,the presented IFFA-DTLMS model primarily applies densely connected networks(DenseNet121)model to generate a collection of feature *** addition,the firefly algorithm(FFA)is applied for the hyper parameter optimization of DenseNet121 ***,autoencoder-long short term memory(AE-LSTM)model is exploited for the classification and identification of *** ensuring the enhanced performance of the IFFA-DTLMS model,a wide-ranging experiments were performed and the results are reviewed under distinctive *** experimental value reports the betterment of IFFA-DTLMS model over recent approaches.

关键词： COVID-19 artificial intelligence intelligent systems deep learning decision making

A Novel Cryptocurrency Prediction Method Using Optimum CNN

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Computers, Materials & Continua 2022年第4期71卷 1051-1063页

作者： Syed H.Hasan Syeda Huyam Hasan mohammed Salih ahmed Syed Hamid Hasan Iowa State University AmesUSA University of Texas at Arlington USA Department of Computer Engineering College of Computer Science and Information TechnologyImam Abdulrahman Bin Faisal UniversityDammamSaudi Arabia Department of Information Systems Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddahSaudi Arabia

In recent years,cryptocurrency has become gradually more significant in economic regions *** cryptocurrencies,records are stored using a cryptographic *** main aim of this research was to develop an optimal solution for predicting the price of cryptocurrencies based on user opinions from social *** is used as a marketing tool for cryptoanalysis owing to the unrestricted conversations on cryptocurrencies that take place on social media ***,this work focuses on extracting Tweets and gathering data from different sources to classify them into positive,negative,and neutral categories,and further examining the correlations between cryptocurrency movements and Tweet *** paper proposes an optimized method using a deep learning algorithm and convolution neural network for cryptocurrency prediction;this method is used to predict the prices of four cryptocurrencies,namely,Litecoin,Monero,Bitcoin,and *** results of analyses demonstrate that the proposed method forecasts prices with a high accuracy of about 98.75%.The method is validated by comparison with existing methods using visualization tools.

关键词： Cryptocurrency litecoin monero bitcoin ethereum twitter optimal CNN price prediction sentiment analysis

Falkner-Skan aspects of a radiating(50%ethylene glycol D 50%water)-based hybrid nanofluid when Joule heating as well as Darcy-Forchheimer and Lorentz forces affect significantly

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Propulsion and Power Research 2023年第3期12卷 428-442页

作者： Ghulam Rasool A.Wakif Xinhua Wang ahmed Alshehri Abdulkafi mohammed Saeed Institute of Intelligent Machinery Faculty of Materials and ManufacturingBeijing University of TechnologyBeijing 100124China Department of Mechanical Engineering Lebanese American UniversityBeirutLebanon Laboratory of Mechanics Faculty of Sciences Aïn ChockHassan II UniversityCasablancaMorocco Department of Mathematics Faculty of SciencesKing Abdulaziz UniversityJeddah 21589Saudi Arabia Department of Mathematics College of ScienceQassim UniversityBuraydah 51452Saudi Arabia

Falkner-Skan aspects are revealed numerically for a non-homogeneous hybrid mixture of 50%ethylene glycol-50%water,silver nanomaterials Ag,and molybdenum disul-fide nanoparticles MoS2 during its motion over a static wedge surface in a DarcyForchheimer porous medium by employing the modified Buongiorno *** Brownian and thermophoresis mechanisms are included implicitly along with the thermophysical properties of each phase via the mixture theory and some efficient phenomenological *** present simulation also accounts for the impacts of nonlinear radiative heat flux,magnetic forces,and Joule ***,the generalized differential quadrature method and Newton-Raphson technique are applied successfully for solving the resulting nonlinear boundary layer *** a limiting case,the obtained findings are validated accurately with the existing literature *** behaviors of velocity,temperature,and nanoparticles volume fraction are discussed comprehensively against various governing *** crucial results,it is revealed that the temperature is enhanced due to magnetic field,linear porosity,radiative heat flux,Brownian motion,thermophoresis,and Joule heating ***,it is depicted that the hybrid nanoliquids present a higher heat flux rate than the monotype nanoliquids and liquids ***,the surface frictional impact is minimized via the linear porosity ***,the surface heat transfer rate receives a prominent improvement due to the radiative heat flux inclusion.

关键词： Ethylene glycol-water hybrid fluid Hybrid nanofluid Falkner-Skan flow Nonlinear radiation Modified Buongiorno nanofluid model

Early Detection of Alzheimer’s Disease Based on Laplacian Re-Decomposition and XGBoosting

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Computer Systems Science & Engineering 2023年第9期46卷 2773-2795页

作者： Hala ahmed Hassan Soliman Shaker El-Sappagh Tamer Abuhmed mohammed Elmogy Information Technology Department Faculty of Computers and InformationMansoura UniversityMansoura35511Egypt Faculty of Computer Science and Engineering Galala UniversitySuez435611Egypt Faculty of Computers and Artificial Intelligence Benha UniversityBanha13518Egypt College of Computing and Informatics Sungkyunkwan UniversitySuwonKorea

The precise diagnosis of Alzheimer’s disease is critical for patient treatment,especially at the early stage,because awareness of the severity and progression risks lets patients take preventative actions before irreversible brain damage *** is possible to gain a holistic view of Alzheimer’s disease staging by combining multiple data modalities,known as image *** this paper,the study proposes the early detection of Alzheimer’s disease using different modalities of Alzheimer’s disease brain ***,the preprocessing was performed on the ***,the data augmentation techniques are used to handle ***,the skull is removed to lead to good *** the second phase,two fusion stages are used:pixel level(early fusion)and feature level(late fusion).We fused magnetic resonance imaging and positron emission tomography images using early fusion(Laplacian Re-Decomposition)and late fusion(Canonical Correlation Analysis).The proposed system used magnetic resonance imaging and positron emission tomography to take advantage of *** resonance imaging system’s primary benefits are providing images with excellent spatial resolution and structural information for specific *** emission tomography images can provide functional information and the metabolisms of particular *** characteristic helps clinicians detect diseases and tumor progression at an early ***,the feature extraction of fused images is extracted using a convolutional neural *** the case of late fusion,the features are extracted first and then ***,the proposed system performs XGB to classify Alzheimer’s *** system’s performance was evaluated using accuracy,specificity,and *** medical data were retrieved in the 2D format of 256×256 *** classifiers were optimized to achieve the final results:for the decision tree,the maximum depth of a tree was *** best number of trees for the random forest was 60;for

关键词： Alzheimer’s disease(AD) machine learning(ML) image fusion Laplacian Re-decomposition(LRD) XGBoosting

Recognition of Urdu Handwritten Alphabet Using Convolutional Neural Network (CNN)

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Computers, Materials & Continua 2022年第11期73卷 2967-2984页

作者： Gulzar ahmed Tahir Alyas Muhammad Waseem Iqbal Muhammad Usman Ashraf ahmed mohammed Alghamdi Adel A.Bahaddad Khalid Ali Almarhabi Department of Computer Science University of South AsiaLahore54000Pakistan Department of Computer Science Lahore Garrison UniversityLahore54000Pakistan Department of Software Engineering Superior UniversityLahore54000Pakistan Department of Computer Science GC Women UniversitySialkot53310Pakistan Department of Software Engineering College of Computer Science and EngineeringUniversity of Jeddah21493Saudi Arabia Department of Information System Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Computer Science College of Computing in Al-QunfudahUmm Al-Qura UniversityMakkah24381Saudi Arabia

Handwritten character recognition systems are used in every field of life nowadays,including shopping malls,banks,educational institutes,*** is the national language of Pakistan,and it is the fourth spoken language in the ***,it is still challenging to recognize Urdu handwritten characters owing to their cursive *** paper presents a Convolutional Neural Networks(CNN)model to recognize Urdu handwritten alphabet recognition(UHAR)offline and online *** research contributes an Urdu handwritten dataset(aka UHDS)to empower future works in this *** offline systems,optical readers are used for extracting the alphabets,while diagonal-based extraction methods are implemented in online ***,our research tackled the issue concerning the lack of comprehensive and standard Urdu alphabet datasets to empower research activities in the area of Urdu text *** this end,we collected 1000 handwritten samples for each alphabet and a total of 38000 samples from 12 to 25 age groups to train our CNN model using online and offline ***,we carried out detailed experiments for character recognition,as detailed in the *** proposed CNN model outperformed as compared to previously published approaches.

关键词： Urdu handwritten text recognition handwritten dataset convolutional neural network artificial intelligence machine learning deep learning

A New Generative Mathematical Model for Coverless Steganography System Based on Image Generation

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Computers, Materials & Continua 2023年第3期74卷 5087-5103页

作者： Al-Hussien Seddik mohammed Salah Gamal Behery ahmed El-harby ahmed Ismail Ebada Sokea Teng Yunyoung Nam Mohamed Abouhawwash Department of Computer Science Faculty of ScienceMinia UniversityMiniaEgypt Department of Computer Science Faculty of Computers and Artificial IntelligenceDamietta UniversityNew DamiettaEgypt Department of ICT Convergence Soonchunhyang UniversityAsan31538Korea Department of Mathematics Faculty of ScienceMansoura UniversityMansoura35516Egypt Department of Computational Mathematics Scienceand Engineering(CMSE)Michigan State UniversityEast Lansing48824MIUSA

The ability of any steganography system to correctly retrieve the secret message is the primary criterion for measuring its ***,researchers have tried to generate a new natural image driven from only the secret message bits rather than using a cover to embed the secret message within it;this is called the stego *** paper proposes a new secured coverless steganography system using a generative mathematical model based on semi Quick Response(QR)code and maze game image *** system consists of two *** first component contains two processes,encryption process,and hiding *** encryption process encrypts secret message bits in the form of a semi-QR code image whereas the hiding process conceals the pregenerated semi-QR code in the generated maze game *** the other hand,the second component contains two processes,extraction and decryption,which are responsible for extracting the semi-QR code from the maze game image and then retrieving the original secret message from the extracted semi-QR code image,*** results were obtained using the bit error rate(BER)*** results confirmed that the system achieved high hiding capacity,good performance,and a high level of robustness against attackers compared with other coverless steganography methods.

关键词： Coverless steganography data hiding information security QR code maze game