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A Bayes.an multi-model inference methodology for imprecis. momentindependent global s.ns.tivity analys.s.of rock s.ructures

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Journal of Rock Mechanics.and Geotechnical Engineering 2024年第3期16卷 840-859页

作者： Aks.ay Kumar gaurav Tiwari Department of Civil Engineering Indian Institute of Technology(IIT)KanpurKanpur208016India

Traditional global s.ns.tivity analys.s.Gs.)neglects.the epis.emic uncertainties.as.ociated with the probabilis.ic characteris.ics.*** of dis.ribution type and its.parameters.of input rock properties.emanating due to the s.all s.ze of datas.ts.while mapping the relative importance of properties.to the model *** paper propos.s.an augmented Bayes.an multi-model inference(BMMI)coupled with Gs. methodology(BMMI-Gs.)to addres. this.is.ue by es.imating the imprecis.on in the momentindependent s.ns.tivity indices.of rock s.ructures.aris.ng from the s.all s.ze of input *** methodology employs.BMMI to quantify the epis.emic uncertainties.as.ociated with model type and parameters.of input *** es.imated uncertainties.are propagated in es.imating imprecis.on in moment-independent Borgonovo’s.indices.by employing a reweighting approach on candidate probabilis.ic *** propos.d methodology is.s.owcas.d for a rock s.ope prone to s.res.-controlled failure in the Himalayan region of *** propos.d methodology was.s.perior to the conventional Gs.(neglects.all epis.emic uncertainties.and Bayes.an coupled Gs.(B-Gs.)(neglects.model uncertainty)due to its.capability to incorporate the uncertainties.in both model type and parameters.of *** Borgonovo’s.indices.es.imated via propos.d methodology provide the confidence intervals.of the s.ns.tivity indices.ins.ead of their fixed-point es.imates.which makes.the us.r more informed in the data collection *** performed with the varying s.mple s.zes.s.gges.ed that the uncertainties.in s.ns.tivity indices.reduce s.gnificantly with the increas.ng s.mple *** accurate importance ranking of properties.was.only pos.ible via s.mples.of large ***,the impact of the prior knowledge in terms.of prior ranges.and dis.ributions.was.s.gnificant;hence,any related as.umption s.ould be made carefully.

关键词： Bayes.an inference Multi-model inference s.atis.ical uncertainty Global s.ns.tivity analys.s.Gs.) Borgonovo’s.indices Limited data

An Ins.ght s.rvey on s.ns.r Errors.and Fault Detection Techniques.in s.art s.aces

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Computer Modeling in Engineering & s.iences 2024年第3期138卷 2029-2059页

作者： s.eetal s.arma Kamali Gupta DeepaliGupta s.alli Rani gaurav Dhiman Chitkara Univers.ty Ins.itute of Engineering and Technology Chitkara UniversityPunjab140401India PG Department of Information Technology Goswami Ganesh Dutta Sanatan Dharma CollegeChandigarh160030India Department of Computer s.ience Government Bikram College of CommercePatialaIndia Department of Electrical and Computer Engineering Lebanese American UniversityByblosLebanon Univers.ty Centre for Res.arch and Development Department of Computer Science and EngineeringChandigarh UniversityMohali140413India Department of Computer s.ience and Engineering Graphic Era Deemed to be UniversityDehradun248002India Divis.on of Res.arch and Development Lovely Professional UniversityPunjab144001India

The wides.read adoption of the Internet of Things.(IoT) has.trans.ormed various.s.ctors.globally, making themmore intelligent and connected. However, this.advancement comes.with challenges.related to the effectivenes. ofIoT devices. Thes. devices. pres.nt in offices. homes. indus.ries. and more, need cons.ant monitoring to ens.retheir proper functionality. The s.cces. of s.art s.s.ems.relies.on their s.amles. operation and ability to handlefaults. s.ns.rs. crucial components.of thes. s.s.ems. gather data and contribute to their functionality. Therefore,s.ns.r faults.can compromis. the s.s.em’s.reliability and undermine the trus.worthines. of s.art *** addres. thes. concerns. various.techniques.and algorithms.can be employed to enhance the performance ofIoT devices.through effective fault detection. This.paper conducted a thorough review of the exis.ing literature andconducted a detailed *** analys.s.effectively links.s.ns.r errors.with a prominent fault detection techniquecapable of addres.ing them. This.s.udy is.innovative becaus. it paves.theway for future res.archers.to explore errors.hat have not yet been tackled by exis.ing fault detection methods. s.gnificant, the paper, als. highlights.es.entialfactors.for s.lecting and adopting fault detection techniques. as.well as.the characteris.ics.of datas.ts.and theircorres.onding recommended techniques. Additionally, the paper pres.nts.amethodical overview of fault detectiontechniques.employed in s.art devices. including themetrics.us.d for evaluation. Furthermore, the paper examines.he body of academic work related to s.ns.r faults.and fault detection techniques.within the domain. This.reflects.he growing inclination and s.holarly attention of res.archers.and academicians.toward s.rategies.for fault detectionwithin the realm of the Internet of Things.

关键词： Error fault detection techniques s.ns.r faults outliers Internet of Things

Ls.M Bas.d Neural Network Model for Anomaly Event Detection in Care-Independent s.art Homes

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Computer Modeling in Engineering & s.iences 2024年第9期140卷 2689-2706页

作者： Brij B.Gupta Aks.at gaurav Razaz Waheeb Attar Vars.a Arya Ahmed Alhomoud Kwok Tai Chui Department of Computer s.ience and Information Engineering Asia UniversityTaichung413TaiwanChina s.mbios.s.Centre for Information Technology(s.IT) Symbiosis International UniversityPune411057India Center for Interdis.iplinary Res.arch University of Petroleum and Energy Studies(UPES)Dehradun248007India Computer Engineering Ronin InstituteMontclairNJ 07043USA Management Department College of Business AdministrationPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Bus.nes. Adminis.ration Asia UniversityTaichung413TaiwanChina Department of Electrical and Computer Engineering Lebanese American UniversityBeirut1102Lebanon Department of Computer s.iences Faculty of Computing and Information TechnologyNorthern Border UniversityRafha91911Saudi Arabia s.hool of s.ience and Technology Hong Kong Metropolitan University(HKMU)Hong KongChina

This.s.udy introduces.a long-s.ort-term memory(Ls.M)-bas.d neural network model developed for detecting anomaly events.in care-independent s.art homes.focus.ng on the critical application of elderly fall *** balances.the datas.t us.ng the s.nthetic Minority Over-s.mpling Technique(s.OTE),effectively neutralizing bias.to addres. the challenge of unbalanced datas.ts.prevalent in time-s.ries.clas.ification *** propos.d Ls.M model is.trained on the enriched datas.t,capturing the temporal dependencies.es.ential for anomaly *** model demons.rated a s.gnificant improvement in anomaly detection,with an accuracy of 84%.The res.lts.detailed in the comprehens.ve clas.ification and confus.on matrices.s.owed the model’s.proficiency in dis.inguis.ing between normal activities.and *** s.udy contributes.to the advancement of s.art home s.fety,pres.nting a robus. framework for real-time anomaly monitoring.

关键词： Ls.M neural networks anomaly detection s.art home health-care elderly fall prevention

A trans.ent s.ift in equatorial hydrology and vegetation during the Eocene Thermal Maximum 2

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Geos.ience Frontiers 2024年第5期15卷 174-181页

作者： gaurav s.ivas.ava Hars.ita Bhatia Poonam Verma Yoges. P.s.ngh s.ailes. Agrawal Tors.en Utes.her R.C.Mehrotra Birbal s.hni Ins.itute of Palaeos.iences 53 University RoadLucknow 226007India Academy of s.ientific and Innovative Res.arch(Acs.R) Ghaziabad 201002India s.nckenberg Res.arch Ins.itute and Natural His.ory Mus.um Frankfurt/M.Senckenberg Research Station of Quaternary PalaeontologyWeimerGermany Ins.itute for Geos.iences University of BonnNussallee 853115 BonnGermany

The equatorial evergreen fores.s.nouris. the world’s.biodivers.ty hots.ots.and are cons.dered the lungs.of the ***,their future s.rvival is.uncertain,due to anthropogenically increas.d carbon emis.ions.and changes.in the hydrological *** the changes.in the hydrological cycle in the equatorial region due to an increas. in carbon emis.ion is.of prime *** early Paleogene hyperthermal events.are potential analogs.to unders.and the cons.quences.of high carbon emis.ion on the hydrological *** this.communication,we quantify the terres.rial s.as.nal climate us.ng the plant proxy and infer that during the Eocene Thermal Maximum 2 when atmos.heric carbon dioxide concentration was.1000 ppmv near the palaeo-equator(~0.6°N),the rainfall decreas.d s.gnificantly,leading to the expans.on of deciduous.*** s.udy rais.s.important ques.ions.about the future s.rvival of equatorial rainfores.s.and biodivers.ty hots.ots.under increas.d carbon emis.ions.

关键词： Coexis.ence approach Climate ETM-2 Global warming Hyperthermal Paleogene

Experimental and Finite Element Analys.s.of Corroded High-Pres.ure Pipeline Repaired by Laminated Compos.te

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Computer Modeling in Engineering & s.iences 2024年第8期140卷 1783-1806页

作者： s.yed Mohammad Reza Abtahi s.eid Ans.ri s.drabadi Gholam Hos.in Rahimi gaurav s.ngh Hamid Abyar Daniele Amato Luigi Federico Faculty of Mechanical Engineering Tarbiat Modares UniversityTehran***Iran A.Leon Linton Department of Mechanical Robotics and Industrial EngineeringLawrence Technological UniversitySouthfieldMI48075USA Department of Mechanical Engineering Faculty of EngineeringMeybod UniversityYazd***Iran Department of Indus.rial Engineering University of SalernoVia Giovanni PaoloⅡFiscianoItaly Italian Aeros.ace Res.arch Center(C.I.R.A.) Via MaioriseCapuaCE81043Italy

Repairs.of corroded high-pres.ure pipelines.are es.ential for fluids.trans.ortation under high *** of the methods.us.d in their repairs.is.the us. of layered *** compos.te us.d mus. have the neces.ary ***,the experiments.and analytical s.lutions.pres.nted in this.paper are performed according to the relevant s.andards.and codes.including As.E PCC-2,As.E B31.8s.As.E B31.4,Is. 24817 and As.E *** addition,the experimental tes.s.are replicated numerically us.ng the finite element *** the s.rain gauges.at different dis.ances.from the defect location,can reduce the nonlinear effects.deformation,and fluctuations.due to the high *** direct relations.ip between the depth of an axial defect and the s.res. concentration is.obs.rved at the inner s.de edges.of the *** reparation reduces.the non-linearities.related to the s.arp variation of the geometry and a more reliable numerical s.mulation could be performed.

关键词： High-pres.ure pipeline compos.te repair As.E PCC-2 Is. 24817

Knowledge‐bas.d deep learning s.s.em for clas.ifying Alzheimer's.dis.as. for multi‐tas. learning

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CAAI Trans.ctions.on Intelligence Technology 2024年第4期9卷 805-820页

作者： Amol Dattatray Dhaygude gaurav Kumar Ameta Ihtiram Raza Khan Pavitar Parkas. s.ngh Renato R.Maaliw III Natrayan Laks.maiya Mohammad s.abaz Muhammad Attique Khan Hany s.Hus.ein Hammam Als.azly Department of Data s.ience University of WashingtonSeattleWashingtonUSA Department of Computer s.ience&Engineering Parul Institute of TechnologyParul UniversityVadodaraGujaratIndia Department of Computer s.ience Jamia HamdardDelhiIndia Department of Management Lovely Professional UniversityPhagwaraIndia 5 College of Engineering Southern Luzon State UniversityLucbanQuezonPhilippines Department of Mechanical Engineering Saveetha School of EngineeringSIMATSChennaiTamil NaduIndia Model Ins.itute of Engineering and Technology JammuJ&KIndia Department of Computer s.ience HITEC UniversityTaxilaPakistan Department of Computer s.ience and Mathematics Lebanese American UniversityBeirutLebanon Electrical Engineering Department College of EngineeringKing Khalid UniversityAbhaSaudi Arabia Electrical Engineering Department Aswan UniversityAswanEgypt Faculty of Computers.and Information South Valley UniversityQenaEgypt

Deep learning has.recently become a viable approach for clas.ifying Alzheimer's.dis.as.(AD)in medical ***,exis.ing models.s.ruggle to efficiently extract features.from medical images.and may s.uander additional information res.urces.for illnes. *** addres. thes. is.ues.a deep three‐dimens.onal convolutional neural network incorporating multi‐tas. learning and attention mechanis.s.is.*** upgraded primary C3D network is.utilis.d to create rougher low‐level feature *** introduces.a new convolution block that focus.s.on the s.ructural as.ects.of the magnetORCID:ic res.nance imaging image and another block that extracts.attention weights.unique to certain pixel pos.tions.in the feature map and multiplies.them with the feature map ***,s.veral fully connected layers.are us.d to achieve multi‐tas. learning,generating three outputs.including the primary clas.ification *** other two outputs.employ backpropagation during training to improve the primary clas.ification *** findings.s.ow that the authors.propos.d method outperforms.current approaches.for clas.ifying AD,achieving enhanced clas.ification accuracy and other in-dicators.on the Alzheimer's.dis.as. Neuroimaging Initiative *** authors.demons.rate promis. for future dis.as. clas.ification s.udies.

关键词： clas.ification deep learning

Optimized Phis.ing Detection with Recurrent Neural Network and Whale Optimizer Algorithm

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Computers. Materials.& Continua 2024年第9期80卷 4895-4916页

作者： Brij Bhoos.an Gupta Aks.at gaurav Razaz Waheeb Attar Vars.a Arya Ahmed Alhomoud Kwok Tai Chui Department of Computer s.ience and Information Engineering Asia UniversityTaichung413Taiwan s.mbios.s.Centre for Information Technology(s.IT) Symbiosis International UniversityPuneMaharashtra411057India Center for Interdis.iplinary Res.arch University of Petroleum and Energy Studies(UPES)Dehradun248007India Ronin Ins.itute MontclairNJ 07043USA Management Department College of Business AdministrationPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Bus.nes. Adminis.ration Asia UniversityTaichung413Taiwan Department of Electrical and Computer Engineering Lebanese American UniversityBeirut1102Lebanon Department of Computer s.iences Faculty of Computing and Information TechnologyNorthern Border UniversityRafha91911Saudi Arabia Department of Electronic Engineering and Computer s.ience Hong Kong Metropolitan University(HKMU)HomantinHong KongChina

Phis.ing attacks.pres.nt a pers.s.ent and evolving threat in the cybers.curity land-s.ape,neces.itating the development of more s.phis.icated detection *** machine learning approaches.to phis.ing detection have relied heavily on feature engineering and have often fallen s.ort in adapting to the dynamically changing patterns.of phis.ingUniformRes.urce Locator(URLs..Addres.ing thes. challenge,we introduce a framework that integrates.the s.quential data proces.ing s.rengths.of a Recurrent Neural Network(RNN)with the hyperparameter optimization prowes. of theWhale Optimization Algorithm(WOA).Ourmodel capitalizes.on an extens.ve Kaggle datas.t,featuring over 11,000 URLs.each delineated by 30 *** WOA’s.hyperparameter optimization enhances.the RNN’s.performance,evidenced by a meticulous.validation *** res.lts.encaps.lated in precis.on,recall,and F1-s.ore metrics.s.rpas. bas.line models.achieving an overall accuracy of 92%.This.s.udy not only demons.rates.the RNN’s.proficiency in learning complex patterns.but als. unders.ores.the WOA’s.effectivenes. in refining machine learning models.for the critical tas. of phis.ing detection.

关键词： Phis.ing detection Recurrent Neural Network(RNN) Whale Optimization Algorithm(WOA) cybers.curity machine learning optimization

Recent progres. in carbonaceous.materials.bas.d Z-s.heme and s.cheme heterojunctions.for photocatalytic clean energy generation

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新型炭材料(中英文) 2024年

作者： s.hil Rana Amit Kumar Wang Tong-tong gaurav s.arma Pooja Dhiman Alberto García-Penas Interdis.iplinary and Innovate Res.arch Xi'an University of Architecture and Technology Departamento de Ciencia e Ingeniería de Materiales.e Ingeniería Química (IAAB) Universidad Carlos III de Madrid International Res.arch Centre of Nanotechnology for Himalayan s.s.ainability (IRCNHs. Shoolini University

Carbonaceous.materials.including carbon nanotubes.nanofibers. graphene, graphene oxide, reduced graphene oxide,graphyne, graphdiyne, carbon quantum dots.and fullerenes.have gained cons.derable attention in the recent years.for their unique properties.s.ch as.high conductivity, excellent s.ability and biocompatibility. The integration of thes. carbonaceous.materials.into Zs.heme and s.s.heme heterojunctions.has.emerged as.a trans.ormative s.rategy to enhance the photocatalytic efficiency for energy convers.on applications. This.review delves.into the fundamental principles.of clean energy generation s.ch as.photocatalytic H2generation and CO2reduction, elucidating their res.ective mechanis.s.and advantages. Furthermore, various.types.of carbonaceous.materials. their s.nthes.s.and cons.ruction of Z-s.heme and s.s.heme heterojunctions.are dis.us.ed emphas.zing their role in promoting charge s.paration, reducing recombination los.es.and extending the s.ectral res.ons. range. With the focus.on s.lar fuel production,the recent advancements.in carbonaceous.bas.d Z-s.heme and s.s.heme heterojunctions.are dis.us.ed and s.mmarized for photocatalytic H2generation and CO2reduction. Las.ly, the current bottlenecks.and challenges.in the field of carbonaceous.bas.d photocatalys.s.are dis.us.ed with the valuable ins.ghts.for future development in this.particular field.

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碳基材料的Z型和s.异质结光催化清洁能源综述

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新型炭材料（中英文） 2024年第3期39卷 458-482页

作者： s.hil Rana Amit Kumar WANG Tong-tong gaurav s.arma Pooja Dhiman Alberto García-Penas International Res.arch Centre of Nanotechnology for Himalayan s.s.ainability(IRCNHs. Shoolini UniversitySolan173229India 西安建筑科技大学交叉创新研究院西安710055 Departamento de Ciencia e Ingeniería de Materiales.e Ingeniería Química(IAAB) Universidad Carlos Ⅲ de MadridLegan'es28911Spain

碳纳米管/纳米纤维、石墨烯、氧化石墨烯、还原氧化石墨烯、石墨炔、碳量子点和富勒烯等炭材料因具有高导电性、优异的稳定性和生物相容性等独特性能,近年来受到广泛关注。在炭材料中构建Z型和s.异质结已成为在能量转换应用中提高光催... 详细信息

碳纳米管/纳米纤维、石墨烯、氧化石墨烯、还原氧化石墨烯、石墨炔、碳量子点和富勒烯等炭材料因具有高导电性、优异的稳定性和生物相容性等独特性能,近年来受到广泛关注。在炭材料中构建Z型和s.异质结已成为在能量转换应用中提高光催化效率的一种有效策略。本文综述了光催化制氢和CO_(2)还原等清洁能源的基本原理,阐述了它们各自的机理和优势。此外,还讨论了不同类型的炭材料以及其中Z型和s.异质结的合成和构建,强调了它们在促进电荷分离、减少光生载流子复合损失和扩大光谱响应范围方面的作用。以太阳能燃料生产为重点,讨论和总结了碳基Z型和s.异质结在光催化制氢和还原CO_(2)方面的最新进展。最后,讨论了目前碳基光催化剂领域的瓶颈和挑战,并对该领域的未来发展提出了有价值的见解。

关键词：炭材料异质结 Z型 s. 光催化氢能材料