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An Open Platform for Processing IFC Model Versions

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Tsinghua Science and Technology 2008年第S1期13卷 126-131页

作者： mohamed nour Karl Beucke Informatik im Bauwesen Bauhaus-University Weimar

The IFC initiative from the International Alliance of Interoperability has been developing since the mid-nineties through several versions. This paper addresses the problem of binding the growing number of IFC versions and their EXPRESS definitions to programming environments (Java and .NET). The solution developed in this paper automates the process of generating early binding classes, whenever a new version of the IFC model is released. Furthermore, a runtime instantiation of the generated early binding classes takes place by importing IFC-STEP ISO 10303-P21 models. The user can navigate the IFC STEP model with relevance to the defining EXPRESS-schema, modify, delete, and create new instances. These functionalities are considered to be a basis for any IFC based implementation. It enables researchers to experiment the IFC model independently from any software application.

关键词： IFC EXPRESS STEP, bindings .NET Java

Privacy-preserved learning from non-i.i.d data in fog-assisted IoT:A federated learning approach

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Digital Communications and Networks 2024年第2期10卷 404-415页

作者： mohamed Abdel-Basset hossam hawash nour Moustafa Imran Razzak mohamed Abd Elfattah Faculty of Computers and Informatics Zagazig UniversityZagazigSharqiyah44519Egypt School of Engineering and Information Technology University of New South Wales@ADFACanberraACT2600Australia Deakin University Geelong Waurn Ponds CampusAustralia Computer Science Department Misr Higher Institute for Commerce and ComputersMansoura35511Egypt

With the prevalence of the Internet of Things(IoT)systems,smart cities comprise complex networks,including sensors,actuators,appliances,and cyber *** complexity and heterogeneity of smart cities have become vulnerable to sophisticated cyber-attacks,especially privacy-related attacks such as inference and data poisoning *** Learning(FL)has been regarded as a hopeful method to enable distributed learning with privacypreserved intelligence in IoT *** though the significance of developing privacy-preserving FL has drawn as a great research interest,the current research only concentrates on FL with independent identically distributed(i.i.d)data and few studies have addressed the non-i.i.d *** is known to be vulnerable to Generative Adversarial Network(GAN)attacks,where an adversary can presume to act as a contributor participating in the training process to acquire the private data of other *** paper proposes an innovative Privacy Protection-based Federated Deep Learning(PP-FDL)framework,which accomplishes data protection against privacy-related GAN attacks,along with high classification rates from non-i.i.d ***-FDL is designed to enable fog nodes to cooperate to train the FDL model in a way that ensures contributors have no access to the data of each other,where class probabilities are protected utilizing a private identifier generated for each *** PP-FDL framework is evaluated for image classification using simple convolutional networks which are trained using MNIST and CIFAR-10 *** empirical results have revealed that PF-DFL can achieve data protection and the framework outperforms the other three state-of-the-art models with 3%–8%as accuracy improvements.

关键词： Privacy preservation Federated learning Deep learning Fog computing Smart cities

Managing Software Testing Technical Debt Using Evolutionary Algorithms

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Computers, Materials & Continua 2022年第10期73卷 735-747页

作者： Muhammad Abid Jamil mohamed K.nour Department of Computer Science Umm Al-Qura UniversityMakkahSaudi Arabia

Technical debt(TD)happens when project teams carry out technical decisions in favor of a short-term goal(s)in their projects,whether deliberately or *** must be properly managed to guarantee that its negative implications do not outweigh its advantages.A lot of research has been conducted to show that TD has evolved into a common problem with considerable financial *** technical debt is the technical debt aspect of testing(or test debt).Test debt is a relatively new concept that has piqued the curiosity of the software industry in recent *** this article,we assume that the organization selects the testing artifacts at the start of every *** the latest features in consideration of expected business value and repaying technical debt are among candidate tasks in terms of the testing process(test cases increments).To gain the maximum benefit for the organization in terms of software testing optimization,there is a need to select the artifacts(i.e.,test cases)with maximum feature coverage within the available *** management of testing optimization for large projects is complicated and can also be treated as a multi-objective problem that entails a trade-off between the agile software’s short-term and long-term *** this article,we implement a multi-objective indicatorbased evolutionary algorithm(IBEA)for fixing such optimization *** capability of the algorithm is evidenced by adding it to a real case study of a university registration process.

关键词： Technical debt software testing optimization large scale agile projects evolutionary algorithms multiobjective optimization indicatorbased evolutionary algorithm(IBEA) pareto front

Potential generated by a massive inhomogeneous straight segment

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Research in Astronomy and Astrophysics 2011年第3期11卷 345-352页

作者： nour-Eddine Najid El haj Elourabi mohamed Zegoumou Equipe Mécanique Statistique et Astronomie-Laboratoire de Physique Théorique et Appliquée Université hassan Ⅱ Ain Chock-Faculté des Sciences Ain Chock BP 5366 Maarif Casablanca Morocco

The discoveries of binary asteroids have opened an important new field of research concerning the calculation of potential generated by irregular *** of them have an elongated shape.A simple model to describe the motion of a test particle in that kind of potential requires consideration of a finite homogeneous straight *** construct this model by adding an inhomogeneous distribution of mass. To be consistent with the geometrical shape of the asteroid,we explore a parabolic profile of the *** establish the closed analytical form of the potential generated by this inhomogeneous massive *** study of the dynamical behavior is fulfilled by the use of Lagrangian formulation,which allows us to calculate some two and three dimensional orbits.

关键词： asteroids—potential—inhomogeneous distribution

Sailfish Optimization with Deep Learning Based Oral Cancer Classification Model

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Computer Systems Science & Engineering 2023年第4期45卷 753-767页

作者： Mesfer Al Duhayyim Areej A.Malibari Sami Dhahbi mohamed K.nour Isra Al-Turaiki Marwa Obayya Abdullah.mohamed Department of Computer Science College of Sciences and Humanities-AflajPrince Sattam bin Abdulaziz UniversityAl-Kharj16278Saudi Arabia Department of Industrial and Systems Engineering College of EngineeringPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Computer Science College of Science&Art at MahayilKing Khalid UniversityAbha62529Saudi Arabia Department of Computer Science College of Computing and Information SystemUmm Al-Qura UniversityMecca24382Saudi Arabia Department of Information Technology College of Computer and Information SciencesKing Saud UniversityRiyadh4545Saudi Arabia Department of Biomedical Engineering College of EngineeringPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia Research Centre Future University in EgyptNew Cairo11845Egypt

Recently,computer aided diagnosis(CAD)model becomes an effective tool for decision making in healthcare *** advances in computer vision and artificial intelligence(AI)techniques have resulted in the effective design of CAD models,which enables to detection of the existence of diseases using various imaging *** cancer(OC)has commonly occurred in head and neck *** identification of OC enables to improve survival rate and reduce mortality ***,the design of CAD model for OC detection and classification becomes ***,this study introduces a novel Computer Aided Diagnosis for OC using Sailfish Optimization with Fusion based Classification(CADOC-SFOFC)*** proposed CADOC-SFOFC model determines the existence of OC on the medical *** accomplish this,a fusion based feature extraction process is carried out by the use of VGGNet-16 and Residual Network(ResNet)***,feature vectors are fused and passed into the extreme learning machine(ELM)model for classification ***,SFO algorithm is utilized for effective parameter selection of the ELM model,consequently resulting in enhanced *** experimental analysis of the CADOC-SFOFC model was tested on Kaggle dataset and the results reported the betterment of the CADOC-SFOFC model over the compared methods with maximum accuracy of 98.11%.Therefore,the CADOC-SFOFC model has maximum potential as an inexpensive and non-invasive tool which supports screening process and enhances the detection efficiency.

关键词： Oral cancer computer aided diagnosis deep learning fusion model seagull optimization classification

Maintain Optimal Configurations for Large Configurable Systems Using Multi-Objective Optimization

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Computers, Materials & Continua 2022年第11期73卷 4407-4422页

作者： Muhammad Abid Jamil Deafallah Alsadie mohamed K.nour Normi Sham Awang Abu Bakar Department of Computer Science Umm Al-Qura UniversityMakkahSaudi Arabia Kulliyyah of Information and Communication Technology International Islamic UniversityMalaysia

To improve the maintenance and quality of software product lines,efficient configurations techniques have been ***,due to the complexity of derived and configured products in a product line,the configuration process of the software product line(SPL)becomes timeconsuming and *** product line consists of a various number of feature models that need to be *** different approaches have been presented by Search-based software engineering(SBSE)to resolve the software engineering issues into computational solutions using some metaheuristic ***,multiobjective evolutionary algorithms help to optimize the configuration process of *** this paper,different multi-objective Evolutionary Algorithms like Non-Dominated Sorting Genetic algorithms II(NSGA-II)and NSGA-III and Indicator based Evolutionary Algorithm(IBEA)are applied to different feature models to generate optimal results for large *** proposed approach is also used to generate the optimized test suites with the help of different multi-objective Evolutionary Algorithms(MOEAs).

关键词： Software product line search-based software engineering metaheuristic multiobjective evolutionary algorithms feature model

General exact solution of the fin problem with variable thermal conductivity

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Propulsion and Power Research 2016年第1期5卷 63-69页

作者： Abass h.Abdel Kader mohamed S.Abdel Latif hamed M.nour Engineering Mathematics and Physics Department Faculty of EngineeringMansoura UniversityMansoura 35516Egypt

In this paper,Lie point symmetry method is used to obtain the general exact solution of the second order nonlinear ordinary differential equation which goveming heat transfer in rectangular fin with variable thermal *** new forms of thermal conductivity are introduced and the associated exact solution is obtained in each *** general relation among the fin efficiency,thermal conductivity and thermo-geometric parameter is obtained.

关键词： Exact solution Fin Thermal conductivity heat transfer Lie point symmetry

Water Wave Optimization with Deep Learning Driven Smart Grid Stability Prediction

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Computers, Materials & Continua 2022年第12期73卷 6019-6035页

作者： Anwer Mustafa hilal Aisha hassan Abdalla hashim heba G.mohamed Mohammad Alamgeer mohamed K.nour Anas Abdelrahman Abdelwahed Motwakel Department of Electrical and Computer Engineering International Islamic University MalaysiaKuala Lumpur53100Malaysia Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam Bin Abdulaziz UniversityAlKharjSaudi Arabia Department of Electrical Engineering College of EngineeringPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Information Systems College of Science&Art at MahayilKing Khalid UniversitySaudi Arabia Department of Computer Science and Bioinformatics Singhania UniversityPacheri BariJhnujhunuRajasthanIndia Department of Computer Sciences College of Computing and Information SystemUmm Al-Qura UniversitySaudi Arabia Department of Mechanical Engineering Faculty of Engineering&TechnologyFuture University in EgyptNew Cairo11835Egypt

Smart Grid(SG)technologies enable the acquisition of huge volumes of high dimension and multi-class data related to electric power grid operations through the integration of advanced metering infrastructures,control systems,and communication *** SGs,user demand data is gathered and examined over the present supply criteria whereas the expenses are then informed to the clients so that they can decide about electricity *** the entire procedure is valued on the basis of time,it is essential to perform adaptive estimation of the SG’s *** advancements inMachine Learning(ML)andDeep Learning(DL)models enable the designing of effective stability prediction models in *** this background,the current study introduces a novel Water Wave Optimization with Optimal Deep Learning Driven Smart Grid Stability Prediction(WWOODL-SGSP)*** aim of the presented WWOODL-SGSP model is to predict the stability level of SGs in a proficient *** attain this,the proposed WWOODL-SGSP model initially applies normalization process to scale the data to a uniform ***,WWO algorithm is applied to choose an optimal subset of features from the pre-processed ***,Deep Belief Network(DBN)model is followed to predict the stability level of ***,Slime Mold Algorithm(SMA)is exploited to fine tune the hyperparameters involved in DBN *** order to validate the enhanced performance of the proposedWWOODL-SGSP model,a wide range of experimental analyses was *** simulation results confirmthe enhanced predictive results of WWOODL-SGSP model over other recent approaches.

关键词： Smart grid stability prediction deep learning energy systems machine learning metaheursitics

In Vitro assessment of the nutritive value of expanded soybean meal for dairy cattle

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Journal of Animal Science and Biotechnology 2012年第2期3卷 93-99页

作者： Eman A Elwakeel Evan C Titgemeyer Zongjia J Cheng Abdelaziz M nour mohamed EA Nasser Department of Animal & Fish Production Faculty of Agriculture Alexandria University Department of Animal Sciences and Industry Kansas State University American Soybean Association-International Marketing

Little information is available about the nutritive value of expanded soybean meal, which is produced by expansion of soybeans prior to solvent extraction of the oil. During processing, expanded soybean meal is subjected to additional heat, which might increase the concentration of ruminally undegraded protein. Processing of soybeans with heat during oil extraction could affect lysine availability by increasing ruminally undegraded protein or by impairing intestinal digestion. Our objective was to compare solvent and expanded soybeans with regard to chemical composition and nutritive value for dairy cattle. Samples of expanded soybean meal （n = 14） and solventextracted soybean meal （n = 5） were obtained from People＇s Republic of China to study effects of the expansion process on nutritive value for dairy cattle. Solvent-extracted soybean meal （n = 2） and mechanically extracted （heated） soybean meal （n = 2） from the United States served as references for comparison. Samples were analyzed for crude fat, long-chain fatty acids, crude protein, amino acids, chemically available lysine, in situ ruminal protein degradation, and in vitro intestinal digestibility. No differences were found between solvent-extracted soybean meals from China and expanded soybean meals from China for crude fat, crude protein, amino acids, or chemically available lysine. In situ disappearance of nitrogen, ruminally undegraded protein content, and in vitro intestinal digestion of the ruminally undegraded protein were generally similar between solvent-extracted soybean meals made in China and expanded soybean meals made in China; variation among soybean meals was small. Results indicate that the additional heat from the expansion process was not great enough to affect the nutritive value of soybean meal protein for ruminants. Although expansion may improve the oil extraction process, the impact on the resulting soybean meal is minimal and does not require consideration when formulating ruminant di

关键词： Digestibility Escape Lysine Protein Rumen