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Gaining-Sharing Knowledge Based Algorithm for Solving Stochastic Programming Problems

Computers, Materials & Continua 2022年第5期71卷 2847-2868页

作者： Prachi Agrawal khalid Alnowibet Ali Wagdy mohamed Yogananda School of Artificial Intelligence Computers&Data ScienceShoolini UniversitySolan173229India Statistics and Operations Research Department College of ScienceKing Saud UniversityRiyadh11451Kingdom of Saudi Arabia Operations Research Department Faculty of Graduate Studies for Statistical ResearchCairo UniversityGiza12613Egypt Department of Mathematics and Actuarial Science School of Science and EngineeringThe American University in CairoEgypt

This paper presents a novel application of metaheuristic algorithmsfor solving stochastic programming problems using a recently developed gaining sharing knowledge based optimization (GSK) algorithm. The algorithmis based on human behavior in which people gain and share their knowledgewith others. Different types of stochastic fractional programming problemsare considered in this study. The augmented Lagrangian method (ALM)is used to handle these constrained optimization problems by convertingthem into unconstrained optimization problems. Three examples from theliterature are considered and transformed into their deterministic form usingthe chance-constrained technique. The transformed problems are solved usingGSK algorithm and the results are compared with eight other state-of-the-artmetaheuristic algorithms. The obtained results are also compared with theoptimal global solution and the results quoted in the literature. To investigatethe performance of the GSK algorithm on a real-world problem, a solidstochastic fixed charge transportation problem is examined, in which theparameters of the problem are considered as random variables. The obtainedresults show that the GSK algorithm outperforms other algorithms in termsof convergence, robustness, computational time, and quality of obtainedsolutions.

关键词： Gaining-sharing knowledge based algorithm metaheuristic algorithms stochastic programming stochastic transportation problem

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Digital Watermarking Scheme for Securing Textual Database Using Histogram Shifting Model

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Computers, Materials & Continua 2022年第6期71卷 5253-5270页

作者： khalid A.El Drandaly Walid Khedr Islam S.mohamed Ayman mohamed Mostafa Faculty of Computers and Informatics Zagazig UniversityZagazig44519Egypt College of Computer and Information Sciences Jouf UniversitySakaka72314Saudi Arabia

Information security is one of the most important methods of protecting the confidentiality and privacy of internet *** greater the volume of data,the more the need to increase the security methods for protecting data from *** task can be challenging for researchers in terms of managing enormous data and maintaining their safety and *** of digital content is a major issue in maintaining the privacy and secrecy of *** this end,digital watermarking is based on the concept of information security through the insertion and detection of an embedded watermark in an efficient *** methodologies in the research on digital watermarking result in data distortion after embedding the *** scenario can reduce the efficiency of detecting watermarks as well as violate data *** study adapts a robust reversible histogram shifting(HS)technique for textual data in relational ***,the study presents a digital watermarking scheme intended for document copyright protection and proof of *** major advantage of the proposed watermarking scheme is that it can protect digital data and preserve data *** the best of our knowledge,this research methodology is promising for use in the HS expansion model for watermarking data on nonnumeric *** addition,the results showed that despite exposing the database to an insertion attacks at 50%and 75%of the watermark,the proposed algorithm can recovermore than half of the embedded watermark in all addition and alteration attacks *** a result,the watermark information can be retained and restored completely.

关键词： Information security digital watermarking information hiding histogram shifting technique

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Hydrometallurgy two stage process for preparation of (Nd,La,Ce)_(2)O_(3) from end-of-life NiMH batteries

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Journal of Rare Earths 2024年第2期42卷 415-423,I0007页

作者： Karim Tanji khalid Ouzaouit mohamed Belghiti Isam Lamsayety Hakim Faqir Intissar Benzakour Centre de recherche REMINEX-Groupe MANAGEM MarrakechMorocco

The present work aims to investigate the recovery of light rare earth elements(LREEs) oxides from end-oflife NiMH batteries using a hydro metallurgical process followed by effective *** operational leaching parameters such as phosphoric acid concentration,temperature,and the solid-liquid ratio were first optimized by Box-Behnken *** results reveal that under optimum conditions([H_(3)PO_(4)]=2 mol/L,T=80℃,and S/L=1:10 g/mL) the leaching efficiencies of Ni,Co reach 98.1% and99.3%.While La,Ce,and Nd elements remain in the leaching residue as(La,Ce,Nd)PO_(4) with yields of 98.2%,98.6%,and 99.6% for La,Ce,and Nd,***,the(La,Ce,Nd)PO_(4) is leached with HCl acid,then the rare earth oxalate was precipitated using oxalic acid at a pH of 1.8 and then the product was calcined at 800℃ for 2 h in order to synthesize the(Nd,La,Ce)_(2)O_(3).The analysis using scanning electron microscopy(SEM) coupled with energy dispersive X-ray spectroscopy(EDX) confirms the homogeneity of(Nd,La,Ce)_(2)O_(3) particles that have two morphologies,i.e.,flower and sticks with a particle size between 3and 6 μ*** unit cell parameters of(Nd,La,Ce)_(2)O_(3) were calculated after Rietveld refinement of the XRD patterns,in the space group of Fm-3m are a=b=c=0.57921 nm and the volume equal to 0.194322 nm^(3).

关键词： NiMH batteries Hydrometallurgical process Leaching Phosphoric acid Box-Behnken Light rare earth oxides

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Managing Delivery of Safeguarding Substances as a Mitigation Against Outbreaks of Pandemics

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Computers, Materials & Continua 2021年第7期68卷 1161-1181页

作者： Said Ali Hassan khalid Alnowibet Prachi Agrawal Ali Wagdy mohamed Department of Operations Research and Decision Support Faculty of Computers and Articial IntelligenceCairo UniversityGiza12613Egypt Department of Statistics and Operations Research College of ScienceKing Saud UniversityRiyadhSaudi Arabia Trafc Safety Technologies Chair Vice Deanship of Scientic ResearchKing Saud UniversityRiyadhSaudi Arabia Department of Mathematics and Scientic Computing National Institute of TechnologyHamirpur177005India Operations Research Department Faculty of Graduate Studies for Statistical ResearchCairo UniversityGiza12613Egypt School of Engineering and Applied Sciences Wireless Intelligent Networks Center(WINC)Nile UniversityGizaEgypt

The optimum delivery of safeguarding substances is a major part of supply chain management and a crucial issue in the mitigation against the outbreak of pandemics.A problem arises for a decision maker who wants to optimally choose a subset of candidate consumers to maximize the distributed quantities of the needed safeguarding substances within a specic time period.A nonlinear binary mathematical programming model for the problem is *** decision variables are binary ones that represent whether to choose a specic consumer,and design constraints are formulated to keep track of the chosen *** better illustrate the problem,objective,and problem constraints,a real application case study is *** case study involves the optimum delivery of safeguarding substances to several hospitals in the Al-Gharbia Governorate in *** hospitals are selected to represent the consumers of safeguarding substances,as they are the rst crucial frontline for mitigation against a pandemic outbreak.A distribution truck is used to distribute the substances from the main store to the hospitals in specied required quantities during a given working *** objective function is formulated in order to maximize the total amount of delivered quantities during the specied time *** case study is solved using a novel Discrete Binary Gaining Sharing Knowledge-based Optimization algorithm(DBGSK),which involves two main stages:discrete binary junior and senior gaining and sharing *** has the ability of nding the solutions of the introduced problem,and the obtained results demonstrate robustness and convergence toward the optimal solutions.

关键词： Safeguarding substances mitigation against pandemic outbreaks supply chain management metaheuristic optimization

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Optimum Location of Field Hospitals for COVID-19: A Nonlinear Binary Metaheuristic Algorithm

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Computers, Materials & Continua 2021年第7期68卷 1183-1202页

作者： Said Ali Hassan khalid Alnowibet Prachi Agrawal Ali Wagdy mohamed Department of Operations Research and Decision Support Faculty of Computers and Artificial IntelligenceCairo UniversityGiza12613Egypt College of Science Department of Statistics and Operations ResearchKing Saud UniversityRiyadhSaudi Arabia Department of Mathematics and Scientific Computing National Institute of Technology HamirpurHimachal Pradesh177005India Department of Operations Research Faculty of Graduate Studies for Statistical ResearchCairo UniversityGiza12613Egypt Wireless Intelligent Networks Center(WINC) School of Engineering and Applied SciencesNile UniversityGizaEgypt

Determining the optimum location of facilities is critical in many fields,particularly in *** study proposes the application of a suitable location model for field hospitals during the novel coronavirus 2019(COVID-19)*** used model is the most appropriate among the three most common location models utilized to solve healthcare problems(the set covering model,the maximal covering model,and the P-median model).The proposed nonlinear binary constrained model is a slight modification of the maximal covering model with a set of nonlinear *** model is used to determine the optimum location of field hospitals for COVID-19 risk *** designed mathematical model and the solution method are used to deploy field hospitals in eight governorates in Upper *** this case study,a discrete binary gaining–sharing knowledge-based optimization(DBGSK)algorithm is *** DBGSK algorithm is based on how humans acquire and share knowledge throughout their *** DBGSK algorithm mainly depends on two junior and senior binary *** two stages enable DBGSK to explore and exploit the search space efficiently and effectively,and thus it can solve problems in binary space.

关键词： Facility location nonlinear binary model field hospitals for COVID-19 gaining-sharing knowledge-based metaheuristic algorithm

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Analysing Various Control Techniques for Manipulator Robotic System (Robogymnast)

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Computers, Materials & Continua 2023年第6期75卷 4681-4696页

作者： Mahmoud mohamed Bdereddin Abdul Samad Fatih Anayi Michael Packianather khalid Yahya School of Engineering Cardiff UniversityCardiffCF243AAUK Faculty of Engineering University of ZawiaZawia16418Libya Electrical and Electronic Department Azahra Higher Institution of Sciences and TechnologyAzahraLibya Department of Electrical and Electronics Engineering Nisantasi UniversityIstanbul34398Turkey

The Robogymnast is a highly complex,three-link system based on the triple-inverted pendulum and is modelled on the human example of a gymnast suspended by their hands from the high bar and executing larger and larger upswings to eventually rotate *** links of the Robogymnast correspond respectively to the arms,trunk,and lower limbs of the gymnast,and from its three joints,one is under passive operation,while the remaining two are *** passive top joint poses severe challenges in attaining the smooth movement control needed to operate the Robogymnast *** study assesses four types of controllers used for systems operation and identifies how far response stabilisation is achieved with *** system is simulated using MATLAB Simulink,with findings generated regarding rising and settling time,as well as *** research primarily seeks to exam-ine the application of a linear quadratic regulator controller,proportional-integral-derivative controller,fuzzy linear quadratic regulator controller and linear quadratic regulator-proportional-integral-derivative controller for this type of system and comparisons between the different controllers to demon-strate successful performance,which highlights the claimed advantages of the proposed system.

关键词： Robot gymnast(Robogymnast) proportional-integral-derivative(PID) linear quadratic regulator(LQR) fuzzy linear quadratic regulator(FLQR) Acrobat Robot(Acrobat)

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A method for real power transfer allocation using multivariable regression analysis

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Journal of Central South University 2012年第1期19卷 179-186页

作者： Hussain Shareef Azah mohamed Saifunizam Abd.khalid Mohd Wazir Mustafa Faculty of Electrical Engineering and Built Environment Universiti Kebangsaan Malaysia43600 BangiMalaysia Faculty of Electrical Engineering Universiti Teknologi Malaysia81310 JohorMalaysia

A multivariable regression(MVR) approach is proposed to identify the real power transfer between generators and *** on solved load flow results,it first uses modified nodal equation method(MNE) to determine real power contribution from each generator to ***,the results of MNE method and load flow information are utilized to determine suitable regression coefficients using MVR model to estimate the power *** 25-bus equivalent system of south Malaysia is utilized as a test system to illustrate the effectiveness of the MVR output compared to that of the MNE *** error of the estimate of MVR method ranges from 0.001 4 to 0.007 ***,when compared to MNE method,MVR method computes generator contribution to loads within 26.40 ms whereas the MNE method takes 360 ms for the calculation of same real power transfer ***,MVR method is more suitable for real time power transfer allocation.

关键词： power tracing multivariable regression power systems deregulation

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Deep Learning for Depression Detection Using Twitter Data

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Intelligent Automation & Soft Computing 2023年第5期36卷 1301-1313页

作者： Doaa Sami Khafaga Maheshwari Auvdaiappan KDeepa mohamed Abouhawwash Faten khalid Karim Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computational Intelligence SRM Institute of Science and TechnologyKattankulathurChennai603203India Department of Computer Science and Engineering M.Kumarasamy College of EngineeringKarur639113India Department of Mathematics Faculty of ScienceMansoura UniversityMansoura35516Egypt Department of Computational Mathematics Scienceand Engineering(CMSE)College of EngineeringMichigan State UniversityEast LansingMI48824USA

Today social media became a communication line among people to share their happiness,sadness,and anger with their *** is necessary to know people’s emotions are very important to identify depressed people from their *** depression detection helps to save people’s lives and other dangerous mental *** are many intelligent algorithms for predicting depression with high accuracy,but they lack the deﬁnition of such *** machine learning methods help to identify depressed *** the accuracy of existing methods was not *** overcome this issue,the deep learning method is used in the proposed method for depression *** this paper,a novel Deep Learning Multi-Aspect Depression Detection with Hierarchical Atten-tion Network(MDHAN)is used for classifying the depression ***,the Twitter data was preprocessed by tokenization,punctuation mark removal,stop word removal,stemming,and *** Adaptive Particle and grey Wolf optimization methods are used for feature *** MDHAN classiﬁes the Twitter data and predicts the depressed and non-depressed ***,the proposed method is compared with existing methods such as Convolutional Neur-al Network(CNN),Support Vector Machine(SVM),Minimum Description Length(MDL),and *** suggested MDH-PWO architecture gains 99.86%accuracy,more signiﬁcant than frequency-based deep learning models,with a lower false-positive *** experimental result shows that the proposed method achieves better accuracy,precision,recall,and *** also mini-mizes the execution time.

关键词： Depression detection twitter data tweets deep learning swarm intelligence multi-aspect depression detection prediction

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Does nuclear energy reduce carbon emissions despite using fuels and chemicals?Transition to clean energy and finance for green solutions

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Geoscience Frontiers 2024年第4期15卷 359-371页

作者： Muhammad Imran khalid Zaman Abdelmohsen A.Nassani Gheorghița Dinca Haroon ur Rashid Khan mohamed Haffar Department of Economics The University of HaripurHaripur Khyber Pakhtunkhwa 22620Pakistan Department of Management College of Business AdministrationKing Saud UniversityP.O.Box 71115Riyadh 11587Saudi Arabia Finance and Accounting Department Transilvania University of BrașovRomania Faculty of Business The University of Wollongong in DubaiDubai 20183United Arab Emirates Department of Management Birmingham Business SchoolUniversity of BirminghamBirminghamUnited Kingdom

Green power conversion is the shift away from traditional fuels towards clean energy sources such as nuclear power plants,hydroelectric dams,wind farms,and solar *** research examines the impact of clean energy demand and green financing on reducing carbon emissions in 29 economies in Europe and Asia from 2007 to *** study used a two-step differenced GMM estimator for the available data set spanning 2007 to *** study found that rising demand for nuclear power helps to achieve a carbon-neutral agenda,but insufficient funding for renewable energy leads to higher carbon *** research suggests increasing investment in nuclear energy and green financing can improve regional environmental *** study found a causal link between fuel imports,nuclear power and regional *** also determined that fuel imports,chemical use,green financing and the need for nuclear energy will likely impact regional environmental *** research recommends allocating more resources toward innovation to boost energy efficiency and expanding investment in renewable and nuclear energy production industries via green *** study also highlights the need to encourage the development of renewable energy sources to cut carbon emissions and establish a sustainable society.

关键词： Nuclear energy Renewable energy Green financing Fuel imports Chemical use Differenced GMM estimator

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Impact of soil compaction on the engineering properties of potato tubers

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International Journal of Agricultural and Biological Engineering 2020年第2期13卷 163-167页

作者： mohamed K.Edrris khalid A.Al-Gaadi Abdalhaleem A.Hassaballa ElKamil Tola khalid A.M.Ahmed Precision Agriculture Research Chair King Saud UniversityRiyadh 11451Saudi Arabia Department of Agricultural Engineering College of Food and Agriculture SciencesKing Saud UniversityRiyadh 11451Saudi Arabia Department of Agricultural&Biological Engineering Faculty of EngineeringKhartoum UniversityKhartoumSudan Chair of Dates Industry and Technology King Saud UniversityRiyadh 11451Saudi Arabia

A study on a 30 hm2 field was conducted to assess the variability in soil compaction and to investigate its effect on the engineering properties of potato tubers in terms of tuber shape and key dimensions(length,width and thickness)and resistance to penetration,rupture and shear *** soil compaction levels were spatially correlated with the engineering properties of potato tubers through linear regression and ANOVA *** three compaction levels included a low level(C1)ranging between 1.2-1.9 MPa,a medium level(C2)with compaction levels between 2.0-2.3 MPa and a high level(C3)ranging between 2.4-2.9 *** revealed that there were no significant changes in the key tuber dimensions corresponding to the variability in soil ***,inverse linear relationships were observed between soil compaction and the key tuber dimensions with R2 values of 77%,97%and 96%for length,width and thickness,***,the soil compaction was shown to have no effect on the tuber resistance to compression and shear *** contrast,the tuber resistance to penetration was significantly affected by soil compaction(p>F=0.0012).

关键词： compaction potato tubers precision agriculture potato engineering properties

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