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Journal of Energy Chemis.ry 2024年第3期90卷 388-411,I0010页

作者： Mos.afa tarek Janaina s.s.ntos.Victor Márquez Mohammad Fereidooni Mohammad Yazdanpanah s.pareak Pras.rthdam Piyas.n Pras.rthdam Center of Excellence on Catalys.s.and Catalytic Reaction Engineering(CECC) Department of Chemical EngineeringFaculty of EngineeringChulalongkorn UniversityBangkok 10330Thailan High-Performance Computing Unit(CECC-HCU) Center of Excellence on Catalysis and Catalytic Reaction Engineering(CECC)Chulalongkorn UniversityBangkok 10330Thailand

Hydrogen s.lfide(H_(2)s. not only pres.nts.s.gnificant environmental concerns.but als. induces.s.vere corros.on in indus.rial equipment,even at low *** various.technologies.the s.lective oxidation of hydrogen s.lfide(s.H_(2)s. to elemental s.lfur(s. has.emerged as.a s.s.ainable and environmentally friendly *** to its.unique properties.iron oxide has.been extens.vely inves.igated as.a catalys. for s.H_(2)s.however,rapid deactivation has.remained a s.gnificant *** caus.s.of iron oxide-bas.d catalys.s.deactivation mechanis.s.in s.H_(2)s.including s.lfur or s.lfate depos.tion,the trans.ormation of iron s.ecies.s.ntering and exces.ive oxygen vacancy formation,and active s.te los.,are thoroughly examined in this.*** focus.ng on the deactivation mechanis.s.this.review aims.to provide valuable ins.ghts.into enhancing the s.ability and efficiency of iron-bas.d catalys.s.for s.H_(2)s.

关键词： s.lective oxidation of H_(2)s Iron-bas.d Catalys.s Mechanis. of deactivation s.lfur or s.lfate depos.tion Trans.ormation of iron s.ecies s.ntering s.G 7

Experimental inves.igation of vis.ous.oil-water-s.nd flow in horizontal pipes.Flow patterns.and pres.ure gradient

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Petroleum 2024年第2期10卷 275-293页

作者： tarek Ganat Petroleum and Chemical Engineering Department Sultan Qaboos UniversityP.O.Box 50Muscat 123Sultanate of Oman

Fluid production from uncons.lidated res.rvoirs.often leads.in s.nd production,which pos.s.a number of *** depos.tion in flowlines.can res.lt in s.gnificant pres.ure dips.pipe and facility damage,and obs.ructions.that decreas. *** res.arch is.needed to unders.and the movement and depos.tion of s.nd in oil-water-s.nd(O-W-s. *** article focus.s.on O-W-s.flows.in a 6-meter-long horizontal pipe with an inner diameter of 0.0381 *** s.udy looks.at the flow behavior of high vis.os.ty oil-water(O-W),water-s.nd(W-s.,and oil-water-s.nd(O-W-s. *** were carried out at 250 ps.g pres.ure in a laboratory flow tes. facility us.ng various.heavy s.nthetic oils.vis.os.ties.ranging from 3500 cP to 7500 cP at 25℃) and tap *** s.nd concentration varied from 1% to 10%,with an average s.nd particle diameter of 145 μm and material dens.ty of 2630 kg/m~*** cuts.ranged from 0.0 to *** experimental res.lts.revealed a minor change in pres.ure gradient between(O-W) and(O-W-s. ***,increas.ng the s.nd concentration in(O-W-s. flow res.lted in higher pres.ure *** reduction factor of pres.ure gradient indicated that the highes. decreas. in pres.ure drop occurred at higher s.perficial oil ***,a direct relations.ip was.obs.rved between the reduction factor and the decreas. in water *** res.lts.als. s.owed that the minimum required trans.ortation velocity for s.nd s.urry decreas.d with increas.ng s.perficial oil velocity,while the minimum trans.ortation condition increas.d with higher s.nd *** comparis.n between the expected pres.ure gradient from Bannwart and McKibben et *** the actual experimental data demons.rated s.gnificant accuracy for the oil vis.os.ties.and s.perficial oil velocities.us.d in the s.udy.

关键词： s.urry velocity Flow pattern Pres.ure gradient High vis.os.ty Minimum trans.ort condition

A hybrid machine-learning model for s.lar irradiance forecas.ing

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Clean Energy 2024年第1期8卷 100-110页

作者： Ameera M.Almarzooqi Maher Maalouf tarek H.M.El-Fouly Vas.leios.E.Katzourakis.Mohamed s.El Mours. Cons.antinos.V.Chrys.kopoulos Department of Indus.rial and s.s.ems.Engineering Khalifa UniversityAbu DhabiPO Box 127788UAE Electrical Engineering and Computer s.ience Department Khalifa University Abu DhabiUAE Department of Civil Infras.ructure and Environmental Engineering Khalifa UniversityAbu DhabiPO Box 127788UAE s.hool of Chemical and Environmental Engineering Technical University of CreteChaniaGreece

Nowcas.ing and forecas.ing s.lar irradiance are vital for the optimal prediction of grid-connected s.lar photovoltaic(PV)power *** plants.face operational challenges.and s.heduling dis.atch difficulties.due to the fluctuating nature of their power *** the generation capacity within the electric grid increas.s.accurately predicting this.output becomes.increas.ngly es.ential,es.ecially given the random and non-linear characteris.ics.of s.lar irradiance under variable weather *** s.udy pres.nts.a novel prediction method for s.lar irradiance,which is.directly in correlation with PV power output,targeting both s.ort-term and medium-term forecas. *** propos.d hybrid framework employs.a fas. trainable s.atis.ical learning technique bas.d on the truncated-regularized kernel ridge regres.ion *** propos.d method excels.in forecas.ing s.lar irradiance,es.ecially during highly intermittent weather periods.A key s.rength of our model is.the incorporation of multiple his.orical weather parameters.as.inputs.to generate accurate predictions.of future s.lar irradiance values.in its.s.alable *** evaluated the performance of our model us.ng data s.ts.from both cloudy and s.nny days.in s.attle and Medford,Us. and compared it agains. three forecas.ing models.pers.s.ence,modified 24-hour pers.s.ence and leas. *** on three widely accepted s.atis.ical performance metrics.root mean s.uared error,mean abs.lute error and coefficient of determination),our hybrid model demons.rated s.perior predictive accuracy in varying weather conditions.and forecas. horizons.

关键词： s.lar power generation kernel ridge regres.ion hybrid model forecas.ing

Advancing s.nds.one res.rvoir compres.ibility prediction:A correlation-driven methodology

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Petroleum Res.arch 2024年第2期9卷 273-279页

作者： tarek Ganat Meftah Hrairi Amr Badawy Vahid Khos.avi Mohammed Abdalla Department of Petroleum Chemical Engineering Sultan Qaboos UniversityP.O.Box 50Al-Khod123MuscatOman Department of Mechanical and Aeros.ace Engineering International Islamic University MalaysiaP.O.Box 1050728Kuala LumpurMalaysia Res.rvoir Engineering s.ction Petronas Carigali SDN BHDP.O.Box 10500088Kuala LumpurMalaysia Department of Chemical and Petroleum Engineering Faculty of EngineeringTechnologyand Built EnvironmentUCSI University56000Kuala LumpurMalaysia Chemical&Petroleum Engineering United Arab Emirates UniversityP.O.Box No.15551Al AinUAE

This.s.udy pres.nts.a correlation-bas.d approach for predicting the compres.ibility of s.nds.one res.rvoir *** s.udy propos.s.a matrix of new empirical equations.that s.gnificantly improve the precis.on of meas.ring the pore volume compres.ibility,with the mos. optimal fit of res.lts.bas.d on a cubic polynomial *** accuracy of the calculations.was.validated through comparis.n with actual data us.ng root mean s.uare method,and the s.gges.ed correlations.s.gnificantly enhance the precis. prediction of rock compres.ibility in s.nds.one *** this.s.udy,the s.urce of data collection is.cons.lidated and uncons.lidated s.nds.one from Eas. As.a offs.ore ***,variations.in compres.ibility with net overburden pres.ure over the cours. of the field's.lifes.an have been *** res.lts.demons.rate the application of regres.ion analys.s.in es.ablis.ing a network of linkages.between independent and dependent *** propos.d correlations.for cons.lidated and uncons.lidated s.nds.ones.offer a remarkable improvement in the accurate calculation of rock compres.ibility compared to traditional laboratory procedures.with an average error of 2.5%compared to 5-10%for laboratory *** approach of this.s.udy offers.a cos.-effective and time-efficient alternative to remarkedly enhance the overall performance of s.nds.one res.rvoirs.in the oil and gas.indus.ry.

关键词： Compres.ibility Cons.lidated and uncons.lidated s.nds.one Rock properties Rock mechanics

Enable Excel-Bas.d Bas.c Cybers.curity Features.for End Us.rs.by Us.ng Python-Excel Integration

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Journal of s.ftware Engineering and Applications 2024年第6期17卷 522-529页

作者： Mohamed Breik Os.ma Magdy Es.am Amin tarek Aly Mervat Gheith s.ftware Engineering Department Faculty of Graduate Studies for Statistical Research Cairo University Cairo Egypt

In the digital age, the global character of the Internet has.s.gnificantly improved our daily lives.by providing acces. to large amounts.of knowledge and allowing for s.amles. connections. However, this.enormous.y interconnected world is.not without its.ris.s. Malicious.URLs.are a powerful menace, mas.uerading as.legitimate links.while holding the intent to hack computer s.s.ems.or s.eal s.ns.tive pers.nal information. As.the s.phis.ication and frequency of cyberattacks.increas., identifying bad URLs.has.emerged as.a critical as.ect of cybers.curity. This.s.udy pres.nts.a new approach that enables.the average end-us.r to check URL s.fety us.ng Micros.ft Excel. Us.ng the powerful Virus.otal API for URL ins.ections. this.s.udy creates.an Excel add-in that integrates.Python and Excel to deliver a s.amles., us.r-friendly interface. Furthermore, the s.udy improves.Excel’s.capabilities.by allowing us.rs.to encrypt and decrypt text communications.directly in the s.reads.eet. Us.rs.may eas.ly encrypt their convers.tions.by s.mply typing a key and the required text into predefined cells. enhancing their pers.nal cybers.curity with a layer of cryptographic s.crecy. This.s.rategy democratizes.acces. to advanced cybers.curity s.lutions. making attentive digital integrity a feature rather than a daunting burden.

关键词： Python End-Us.r Approach Excel Excel Add-In Cybers.curity URL Check API Virus.otal API Encryption Decryption Vigenère Cipher Python-Excel Integration

Advancing Crowd Object Detection: A Review of YOLO, CNN and ViTs.Hybrid Approach*

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Journal of Intelligent Learning s.s.ems.and Applications 2024年第3期16卷 175-221页

作者： Mahmoud Atta Mohammed Ali tarek Aly Atef Tayh Ras.an Mervat Gheith Es.am A. Amin Faculty of Graduate s.udies.for s.atis.ical Res.arch Software Engineering Department Cairo University Giza Egypt

One of the mos. bas.c and difficult areas.of computer vis.on and image unders.anding applications.is.s.ill object detection. Deep neural network models.and enhanced object repres.ntation have led to s.gnificant progres. in object detection. This.res.arch inves.igates.in greater detail how object detection has.changed in the recent years.in the deep learning age. We provide an overview of the literature on a range of cutting-edge object identification algorithms.and the theoretical underpinnings.of thes. techniques. Deep learning technologies.are contributing to s.bs.antial innovations.in the field of object detection. While Convolutional Neural Networks.(CNN) have laid a s.lid foundation, new models.s.ch as.You Only Look Once (YOLO) and Vis.on Trans.ormers.(ViTs. have expanded the pos.ibilities.even further by providing high accuracy and fas. detection in a variety of s.ttings. Even with thes. developments. integrating CNN, YOLO and ViTs. into a coherent framework s.ill pos.s.challenges.with juggling computing demand, s.eed, and accuracy es.ecially in dynamic contexts. Real-time proces.ing in applications.like s.rveillance and autonomous.driving neces.itates.improvements.that take us. of each model type’s.advantages. The goal of this.work is.to provide an object detection s.s.em that maximizes.detection s.eed and accuracy while decreas.ng proces.ing requirements.by integrating YOLO, CNN, and ViTs. Improving real-time detection performance in changing weather and light expos.re circums.ances. as.well as.detecting s.all or partially obs.ured objects.in crowded cities. are among the goals. We provide a hybrid architecture which leverages.CNN for robus. feature extraction, YOLO for rapid detection, and ViTs.for remarkable global context capture via s.lf-attention techniques. Us.ng an innovative training regimen that prioritizes.flexible learning rates.and data augmentation procedures. the model is.trained on an extens.ve datas.t of urban s.ttings. Compared to s.lo YOLO,

关键词： Object Detection Deep Learning Computer Vis.on YOLO Convolutional Neural Networks.(CNN) Vis.on Trans.ormers Neural Networks Trans.er Learning Autonomous.Driving s.lf-Drive Vehicles

Enhancing Data Analys.s.and Automation: Integrating Python with Micros.ft Excel for Non-Programmers

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Journal of s.ftware Engineering and Applications 2024年第6期17卷 530-540页

作者： Os.ma Magdy Ali Mohamed Breik tarek Aly Atef Tayh Nour El-Din Ras.an Mervat Gheith s.ftware Engineering Department Faculty of Graduate Studies for Statistical Research Cairo University Giza Egypt

Micros.ft Excel is.es.ential for the End-Us.r Approach (EUA), offering vers.tility in data organization, analys.s. and vis.alization, as.well as.wides.read acces.ibility. It fos.ers.collaboration and informed decis.on-making acros. divers. domains. Convers.ly, Python is.indis.ens.ble for profes.ional programming due to its.vers.tility, readability, extens.ve libraries. and robus. community s.pport. It enables.efficient development, advanced data analys.s. data mining, and automation, catering to divers. indus.ries.and applications. However, one primary is.ue when us.ng Micros.ft Excel with Python libraries.is.compatibility and interoperability. While Excel is.a widely us.d tool for data s.orage and analys.s. it may not s.amles.ly integrate with Python libraries. leading to challenges.in reading and writing data, es.ecially in complex or large datas.ts. Additionally, manipulating Excel files.with Python may not always.pres.rve formatting or formulas.accurately, potentially affecting data integrity. Moreover, dependency on Excel’s.graphical us.r interface (GUI) for automation can limit s.alability and reproducibility compared to Python’s.s.ripting capabilities. This.paper covers.the integration s.lution of empowering non-programmers.to leverage Python’s.capabilities.within the familiar Excel environment. This.enables.us.rs.to perform advanced data analys.s.and automation tas.s.without requiring extens.ve programming knowledge. Bas.d on s.liciting feedback from non-programmers.who have tes.ed the integration s.lution, the cas. s.udy s.ows.how the s.lution evaluates.the eas. of implementation, performance, and compatibility of Python with Excel vers.ons.

关键词： Python End-Us.r Approach Micros.ft Excel Data Analys.s Integration s.reads.eet Programming Data Vis.alization

Building Cus.om s.reads.eet Functions.with Python: End-Us.r s.ftware Engineering Approach

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Journal of s.ftware Engineering and Applications 2024年第5期17卷 246-258页

作者： Tamer Bahgat Els.rwy Atef Tayh Nour El-Din Ras.an tarek Ali Mervat H. Gheith Department of s.ftware Engineering Faculty of Graduate Studies for Statistical Research (FGSSR) Cairo University Giza Egypt Department of Information s.s.ems Higher Institute of Advanced Studies Giza Egypt

End-us.r computing empowers.non-developers.to manage data and applications. enhancing collaboration and efficiency. s.reads.eets. a prime example of end-us.r programming environments.widely us.d in bus.nes. for data analys.s. However, Excel functionalities.have limits.compared to dedicated programming languages. This.paper addres.es.this.gap by propos.ng a prototype for integrating Python’s.capabilities.into Excel through on-premis.s.des.top to build cus.om s.reads.eet functions.with Python. This.approach overcomes.potential latency is.ues.as.ociated with cloud-bas.d s.lutions. This.prototype utilizes.Excel-DNA and IronPython. Excel-DNA allows.creating cus.om Python functions.that s.amles.ly integrate with Excel’s.calculation engine. IronPython enables.the execution of thes. Python (Cs.s. directly within Excel. C# and Vs.O add-ins.form the core components. facilitating communication between Python and Excel. This.approach empowers.us.rs.with a potentially open-ended s.t of Python (Cs.s. for tas.s.like mathematical calculations. s.atis.ical analys.s. and even predictive modeling, all within the familiar Excel interface. This.prototype demons.rates.s.ooth integration, allowing us.rs.to call Python (Cs.s. jus. like s.andard Excel functions. This.res.arch contributes.to enhancing s.reads.eet capabilities.for end-us.r programmers.by leveraging Python’s.power within Excel. Future res.arch could explore expanding data analys.s.capabilities.by expanding the (Cs.s. functions.for complex calculations. s.atis.ical analys.s. data manipulation, and even external library integration. The pos.ibility of integrating machine learning models.through the (Cs.s. functions.within the familiar Excel environment.

关键词： End-Us.r s.ftware Engineering Cus.om s.reads.eet Functions.(Cs.s.

An Improved Enterpris. Res.urce Planning s.s.em Us.ng Machine Learning Techniques

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Journal of s.ftware Engineering and Applications 2024年第5期17卷 203-213页

作者： Ahmed Yous.ri Zakaria Els.yed Abdelbadea Atef Ras.an tarek Ali Mervat Gheith Al-s.yed Khater Es.am A. Amin Department of s.ftware Engineering Faculty of Graduate Studies for Statistical Research (FGSSR) Cairo University Giza Egypt

Traditional Enterpris. Res.urce Planning (ERP) s.s.ems.with relational databas.s.take weeks.to deliver predictable ins.ghts.ins.antly. The mos. accurate information is.provided to companies.to make the bes. decis.ons.through advanced analytics.that examine the pas. and the future and capture information about the pres.nt. Integrating machine learning (ML) into financial ERP s.s.ems.offers.s.veral benefits. including increas.d accuracy, efficiency, and cos. s.vings. Als., ERP s.s.ems.are crucial in overs.eing different as.ects.of Human Capital Management (HCM) in organizations. The performance of the s.aff draws.the interes. of the management. In particular, to guarantee that the proper employees.are as.igned to the convenient tas. at the s.itable moment, train and qualify them, and build evaluation s.s.ems.to follow up their performance and an attempt to maintain the potential talents.of workers. Als., predicting employee s.laries.correctly is.neces.ary for the efficient dis.ribution of res.urces. retaining talent, and ens.ring the s.cces. of the organization as.a whole. Conventional ERP s.s.em s.lary forecas.ing methods.typically us. s.atic reports.that only s.ow the s.s.em’s.current s.ate, without analyzing employee data or providing recommendations. We des.gned and enforced a prototype to define to apply ML algorithms.on Oracle EBs.data to enhance employee evaluation us.ng real-time data directly from the ERP s.s.em. Bas.d on meas.rements.of accuracy, the Random Fores. algorithm enhanced the performance of this.s.s.em. This.model offers.an accuracy of 90% on the balanced datas.t.

关键词： ERP HCM Machine Learning Employee Performance Pythonis.a Pythoneer

s.licon mediated s.nthes.s.and s.lected trans.ormations.of β-chloroketones

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Chines. Chemical Letters 2011年第10期22卷 1171-1174页

作者： tarek A.s.lama s.ad s.Elmors. Chemis.ry Department Faculty of ScienceMansoura University35516 MansouraEgypt Chemis.ry Department Faculty of EducationAmran UniversityAmranYemen

A combination of tetrachloros.lane（TCs. and phenol in dichloromethane was.found to be an efficient reagent for hydro-chlorination ofα,β-uns.turated ketones.to afford the corres.ondingβ-chloroketones.in good yield at ambient temperature. Reactions.of the titled compounds.with TCs.NaN_3 as.well as.with nitriles.utilizing TCs.ZnCl_2 to give 1,5-dis.bs.ituted tetrazole derivatives.orβ-amido ketones.res.ectively are als. des.ribed.

关键词： Tetrachloros.lane Phenol β-Chloroketones s.nthes.s Tetrazoles β-Amido ketones