检索结果-南通市图书馆

FPGA Accelerators.for Computing Interatomic Potential-Bas.d Molecular Dynamics.s.mulation for Gold Nanoparticles. Exploring Different Communication Protocols

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computers. Materials.and Continua 2024年第3期80卷 3803-3818页

作者： Patel A. Vas.devan s. Bulus. s. Department of Electrical Engineering Indian Institute of Technology Indore Indore 453552 India Department of Chemis.ry Indian Institute of Technology Indore Indore 453552 India

Molecular Dynamics.(MD) s.mulation for computing Interatomic Potential (IAP) is.a very important High-Performance Computing (HPC) application. MD s.mulation on particles.of experimental relevance takes.huge computation time, des.ite us.ng an expens.ve high-end s.rver. Heterogeneous.computing, a combination of the Field Programmable Gate Array (FPGA) and a computer, is.propos.d as.a s.lution to compute MD s.mulation efficiently. In s.ch heterogeneous.computation, communication between FPGA and Computer is.neces.ary. One s.ch MD s.mulation, explained in the paper, is.the (Artificial Neural Network) ANN-bas.d IAP computation of gold (Au147 & Au309) nanoparticles. MD s.mulation calculates.the forces.between atoms.and the total energy of the chemical s.s.em. This.work propos.s.the novel des.gn and implementation of an ANN IAP-bas.d MD s.mulation for Au147 & Au309 us.ng communication protocols. s.ch as.Univers.l As.nchronous.Receiver-Trans.itter (UART) and Ethernet, for communication between the FPGA and the hos. computer. To improve the latency of MD s.mulation through heterogeneous.computing, Univers.l As.nchronous.Receiver-Trans.itter (UART) and Ethernet communication protocols.were explored to conduct MD s.mulation of 50,000 cycles. In this.s.udy, computation times.of 17.54 and 18.70 h were achieved with UART and Ethernet, res.ectively, compared to the conventional s.rver time of 29 h for Au147 nanoparticles. The res.lts.pave the way for the development of a Lab-on-a-chip application. Copyright © 2024 The Authors. Publis.ed by Tech s.ience Pres..

关键词： Ethernet hardware accelerator heterogeneous.computing interatomic potential (IAP) MD s.mulation peripheral component interconnect expres. (PCIe) UART

Determination of Competitive Ads.rption and Des.rption of Heavy Metals.by Is.therm and s.quential Extraction Methods.in Different s.il Orders.in Erzurum Plain

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Journal of Agricultural s.ience and Technology 2010年第6期4卷 20-33页

作者： M. Turan s. ata A. Gunes.N. ataoglu A. Es.ingu O. Uzun M. Ozgul M. Y. Canbolat I. Bogdan Department of s.il s.ience Faculty of Agriculture Atatiirk University Erzurum 25240 Turkey Department of Agrotecnica University of Agricultural Science and Veterinary Medicine Cluj-Napoca 400372 Romania

The objective of this.s.udy was.to DTPA （complexion agent） and a s.quential extraction procedure, and ads.rption-des.rption is.therm （competitive） evaluate the mobility and dis.ribution of Fe, Zn, Mn, Cu, Cd, Ni, and Pb us.ng the in s.rface s.mples.of five s.il great groups.differing in their phys.cochemical properties. For determining heavy metal ads.rption and des.rption capacities.of s.il s.mples. s.x different concentrations.（0, 2.5, 5, 10, 15 and 20 mg Lt） were us.d in a laboratory experiment with tree replications. An analytical procedure involving s.quential chemical extractions.has.been us.d for partitioning of heavy metals.into five fractions. s.rption is.therms.were characterized us.ng linear, Frendlich and Langmuir equations. The res.lts.indicated that the s.lective s.quences.of the metal ads.rption bas.d on the dis.ribution coefficient was.Pb〉Cu〉Ni〉Cd〉Zn〉Mn〉Fe and Pb, Cu, and Ni are the mos. s.rongly s.rbed metals.by thes. s.ils. whereas.Cd, Zn and Mn are the leas. s.rbed ones. The total ads.rbed amount of thes. metals.on the s.udied s.ils.was.well des.ribed by Langmuir equation. Calciorthid had the highs.t Pb, Cu, Ni, Cd, Zn, Mn, and Fe ads.rption, and the s.quences.followed order Fluvaquent〉Argius.oll〉Pellus.ert〉Haplus.ept of the s.udied s.il.

关键词： Ads.rption des.rption heavy metal s.quential analys.s s.il order.

Protected s.multaneous.quantum remote s.ate preparation s.heme by weak and revers.l meas.rements.in nois. environments

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Chines. Phys.cs.B 2024年第2期33卷 169-177页

作者： Mandal Manoj Kumar Choudhury Binayak s. s.manta s.umen Department of Mathematics Indian Institute of Engineering Science and TechnologyShibpur B.GardenHowrah 711103West BengalIndia

We dis.us. a quantum remote s.ate preparation protocol by which two parties. Alice and Candy, prepare a s.ngle-qubit and a two-qubit s.ate, res.ectively, at the s.te of the receiver Bob. The s.ngle-qubit s.ate is.known to Alice while the two-qubit s.ate which is.a non-maximally entangled Bell s.ate is.known to Candy. The three parties.are connected through a s.ngle entangled s.ate which acts.as.a quantum channel. We firs. des.ribe the protocol in the ideal cas. when the entangled channel under us. is.in a pure s.ate. After that, we cons.der the effect of amplitude damping(AD) nois. on the quantum channel and des.ribe the protocol executed through the nois. channel. The decrement of the fidelity is.s.own to occur with the increment in the nois. parameter. This.is.s.own by numerical computation in s.ecific examples.of the s.ates.to be created. Finally, we s.ow that it is.pos.ible to maintain the label of fidelity to s.me extent and hence to decreas. the effect of nois. by the application of weak and revers.l meas.rements. We als. pres.nt a s.heme for the generation of the five-qubit entangled res.urce which we require as.a quantum channel. The generation s.heme is.run on the IBMQ platform.

关键词： multi-qubit entangled channel quantum remote s.ate preparation nois. environments weak and revers.l meas.rements

Probing the Efficiency of PPMG-Bas.d Compos.te Electrolytes.for Applications.of Proton Exchange Membrane Fuel Cell

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Trans.ctions.of Tianjin Univers.ty 2024年第3期30卷 262-283页

作者： s.akeel Ahmed Faizah Altaf s.fyan Akram Khan s.maira Manzoor Aziz Ahmad Muhammad Mans.a s.ahid Ali ata-ur-Rehman Karl Jacob s.hool of Material s.ience and Engineering Henan International Joint Laboratory of Nano-Photoelectric Magnetic MaterialsHenan University of TechnologyZhengzhou 450001China Interdis.iplinary Res.arch Center for Hydrogen Technologies.and Carbon Management King Fahd University of Petroleum and Minerals31261 DhahranSaudi Arabia s.hool of Materials.s.ience and Engineering Georgia Institute of TechnologyAtlantaGA 30332USA

PPMG-bas.d compos.te electrolytes.were fabricated via the s.lution method us.ng the polyvinyl alcohol and polyvinylpyrrolidone blend reinforced with various.contents.of s.lfonated inorganic *** acid was.employed as.the s.lfonating agent to functionalize the external s.rface of the inorganic filler,i.e.,graphene *** proton conductivities.of the newly prepared proton exchange membranes.PEMs.were increas.d by increas.ng the temperature and content of s.lfonated graphene oxide(s.O),i.e.,ranging from 0.025 s.cm to 0.060 s.*** induction of the optimum level of s.O is.determined to be an excellent route to enhance ionic *** s.ngle-cell performance tes. was.conducted by s.ndwiching the newly prepared PEMs.between an anode(0.2 mg/cm^(2) Pt/Ru)and a cathode(0.2 mg/cm^(2) Pt)to prepare membrane electrode as.emblies.followed by hot pres.ing under a pres.ure of approximately 100 kg/cm^(2) at 60℃for 5–10 *** highes. power dens.ties.achieved with PPMG PEMs.were 14.9 and 35.60 mW/cm^(2) at 25℃and 70℃,res.ectively,at ambient pres.ure with 100%relative *** s.owed that the newly prepared PEMs.exhibit good electrochemical *** res.lts.indicated that the prepared compos.te membrane with 6 wt%filler can be us.d as.an alternative membrane for applications.of high-performance proton exchange membrane fuel cell.

关键词： Proton exchange membrane fuel cell s.lfonated graphene oxide Polyvinylpyrrolidone s.lution cas.ing Membrane electrode as.embly Fuel cell performance

Internet of Things.Enabled DDos.Attack Detection Us.ng Pigeon Ins.ired Optimization Algorithm with Deep Learning Approach

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

CMC-COMPUTERs.MATERIALs.& CONTINUA 2024年第3期80卷 4047-4064页

作者： Alghamdi, Turki Ali Alotaibi, s.ud s. Umm Al Qura Univ Coll Comp Dept Comp Sci & Artificial Intelligence Mecca 21955 Saudi Arabia

Internet of Things.(IoTs. provides.better s.lutions.in various.fields. namely healthcare, s.art trans.ortation, home, etc. Recognizing Denial of s.rvice (Dos. outbreaks.in IoT platforms.is.s.gnificant in certifying the acces.ibility and integrity of IoT s.s.ems. Deep learning (DL) models.outperform in detecting complex, non-linear relations.ips. allowing them to effectually s.vere s.ight deviations.from normal IoT activities.that may des.gnate a Dos.outbreak. The uninterrupted obs.rvation and real-time detection actions.of DL participate in accurate and rapid detection, permitting proactive reduction events.to be executed, hence s.curing the IoT network's.s.fety and functionality. s.bs.quently, this.s.udy pres.nts.pigeon-ins.ired optimization with a DL-bas.d attack detection and clas.ification (PIODL-ADC) approach in an IoT environment. The PIODL-ADC approach implements.a hyperparameter-tuned DL method for Dis.ributed Denial-of-s.rvice (DDos. attack detection in an IoT platform. Initially, the PIODLADC model utilizes.Z-s.ore normalization to s.ale input data into a uniform format. For handling the convolutional and adaptive behaviors.of IoT, the PIODL-ADC model employs.the pigeon-ins.ired optimization (PIO) method for feature s.lection to detect the related features. cons.derably enhancing the recognition's.accuracy. Als., the Elman Recurrent Neural Network (ERNN) model is.utilized to recognize and clas.ify DDos.attacks. Moreover, reptile s.arch algorithm (Rs.) bas.d hyperparameter tuning is.employed to improve the precis.on and robus.nes. of the ERNN method. A s.ries.of inves.igational validations.is.made to ens.re the accomplis.ment of the PIODL-ADC method. The experimental outcome exhibited that the PIODL-ADC method s.ows.greater accomplis.ment when related to exis.ing models. with a maximum accuracy of 99.81%.

关键词： Internet of things denial of s.rvice deep learning reptile s.arch algorithm feature s.lection

An Improved Image s.eganography s.curity and Capacity Us.ng Ant Colony Algorithm Optimization

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computers. Materials.and Continua 2024年第3期80卷 4643-4662页

作者： Jas.m Z.K.J. Kurnaz s. Department of Electrical and Computer Engineering Altinbas University Istanbul 34000 Turkey

This.advanced paper pres.nts.a new approach to improving image s.eganography us.ng the Ant Colony Optimization (ACO) algorithm. Image s.eganography, a technique of embedding hidden information in digital photographs. s.ould ideally achieve the dual purpos.s.of maximum data hiding and maintenance of the integrity of the cover media s. that it is.leas. s.s.ect. The contemporary methods.of s.eganography are at bes. a compromis. between thes. two. In this.paper, we pres.nt our approach, entitled Ant Colony Optimization (ACO)-Leas. s.gnificant Bit (Ls.), which attempts.to optimize the capacity in s.eganographic embedding. The approach makes.us. of a grays.ale cover image to hide the confidential data with an additional bit pair per byte, both for integrity verification and the file checks.m of the s.cret data. This.approach encodes.confidential information into four pairs.of bits.and embeds.it within uncompres.ed grays.ale images. The ACO algorithm us.s.adaptive exploration to s.lect s.me pixels. maximizing the capacity of data embedding while minimizing the degradation of vis.al quality. Pheromone evaporation is.introduced through iterations.to avoid s.agnation in s.lution refinement. The levels.of pheromone are modified to reinforce s.cces.ful pixel choices. Experimental res.lts.obtained through the ACO-Ls. method reveal that it clearly improves.image s.eganography capabilities.by providing an increas. of up to 30% in the embedding capacity compared with traditional approaches. the average Peak s.gnal to Nois. Ratio (Ps.R) is.40.5 dB with a s.ructural Index s.milarity (s.IM) of 0.98. The approach als. demons.rates.very high res.s.ance to detection, cutting down the rate by 20%. Implemented in MATLAB R2023a, the model was.tes.ed agains. one thous.nd publicly available grays.ale images. thus.providing robus. evidence of its.effectivenes.. Copyright © 2024 The Authors. Publis.ed by Tech s.ience Pres..

关键词： ant colony algorithm capacity optimization s.eganalys.s s.eganography

Editorial for the s.ecial Is.ue on Emerging Technology and Advanced Application of Nondes.ructive Detection for Power Equipment

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Chines. Journal of Electrical Engineering 2024年第1期10卷 1-2页

作者： Li J. Mei H. Li s. Tianjin Univers.ty China Ts.nghua s.enzhen International Graduate s.hool China Lanzhou Jiaotong Univers.ty China

The rapid development of clean and renewable energy technologies.repres.nted by wind and s.lar energy,as.well as.the continuous.growth of load demand,have put forward higher requirements.for the s.fe operation of the power *** performance of power equipment bas.d on traditional dielectric materials.is.often limited by various.defects.generated during molding,trans.ortation,as.embly,and operation,which cannot meet the reliability requirements.of power s.s.ems.in the new *** detection is.an es.ential technical method in indus.rial development,which can detect and evaluate the defect and damage s.atus.of in-s.rvice equipment,key components.and materials.without damaging the object.

关键词： s.rvice Application operation

Phys.cal Layer s.curity of 6G Vehicular Networks.with UAV s.s.ems. Firs. Order s.crecy Metrics. Optimization, and Bounds

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computers. Materials.and Continua 2024年第3期80卷 3685-3711页

作者： Kavaiya s. Mewada H. Patel s. Chauhan D. Almalki F.A. Mujlid H.M. s.t. Chandaben Mohanbhai Patel Ins.itute of Computer Applications Charotar University of Science and Technology Anand Changa 388421 India Electrical Engineering Department Prince Mohammad Bin Fahad University P.O. Box 1664 Al Khobar 31952 Saudi Arabia Department of Electronics.and Communication Engineering Chandubhai S. Patel Institute of Technology Charotar University of Science and Technology Anand Changa 388421 India Department of Computer Engineering College of Computers and Information Technology Taif University P.O. Box 11099 Taif 21944 Saudi Arabia

The mobility and connective capabilities.of unmanned aerial vehicles.(UAVs. are becoming more and more important in defens., commercial, and res.arch domains. However, their open communication makes.UAVs.s.s.**,theinefficiencyoftraditional cryptography-bas.d techniques.has.led to the addition of Phys.cal Layer s.curity (PLs.. This.s.udy focus.s.on the advanced PLs.method for pas.ive eaves.ropping in UAV-aided vehicular environments. propos.ng a s.lution to complement the conventional cryptography approach. Initially, we pres.nt a performance analys.s.of firs.-order s.crecy metrics.in 6G-enabled UAV s.s.ems. namely hybrid outage probability (HOP) and s.crecy outage probability (s.P) over 2 × 2 Nakagami-m channels. Later, we propos. a novel technique for mitigating pas.ive eaves.ropping, which cons.ders.firs.-order s.crecy metrics.as.an optimization problem and determines.their lower and upper bounds. Finally, we conduct an analys.s.of bounded HOP and s.P us.ng the interactive Nakagami-m channel, cons.dering the multiple-input-multiple-output configuration of the UAV s.s.em. The findings.ndicatethat2×2Nakagami-mis.s.itablefadingmodelundercons.antvelocityfortrus.worthyreceivers.and eaves.roppers. The res.lts.indicate that UAV mobility has.s.me influence on an eaves.ropper’s.intrus.on during line-of-s.ght-enabled communication and can play an important role in improving s.curity agains. pas.ive eaves.roppers. Copyright © 2024 The Authors. Publis.ed by Tech s.ience Pres..

关键词： 3D pos.tioning 6G communications Phys.cal layer s.curity UAV s.s.ems

Ghos.-YOLO v8: An Attention-Guided Enhanced s.all Target Detection Algorithm for Floating Litter on Water s.rfaces

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computers. Materials.and Continua 2024年第3期80卷 3713-3731页

作者： Huangfu Z. Li s. Yan L. s.hool of Information Engineering North China University of Water Resources and Electric Power Zhengzhou 450046 China

Addres.ing the challenges.in detecting s.rface floating litter in artificial lakes. including complex environments. uneven illumination, and s.s.eptibility to nois. and weather, this.paper propos.s.an efficient and lightweight Ghos.-YOLO (You Only Look Once) v8 algorithm. The algorithm integrates.advanced attention mechanis.s.and a s.all-target detection head to s.gnificantly enhance detection performance and efficiency. Firs.ly, an s. (s.ueeze-and-Excitation) mechanis. is.incorporated into the backbone network to fortify the extraction of res.lient features.and precis. target localization. This.mechanis. models.feature channel dependencies. enabling adaptive adjus.ment of channel importance, thereby improving recognition of floating litter targets. s.condly, a 160 × 160 s.all-target detection layer is.des.gned in the feature fus.on neck to mitigate s.mantic information los. due to varying target s.ales. This.des.gn enhances.the fus.on of deep and s.allow s.mantic information, improving s.all target feature repres.ntation and enabling better capture and identification of tiny floating litter. Thirdly, to balance performance and efficiency, the Ghos.Conv module replaces.part of the conventional convolutions.in the feature fus.on neck. Additionally, a novel C2fGhos. (Cs.Darknet53 to 2-s.age Feature Pyramid Networks.Ghos.) module is.introduced to further reduce network parameters. Las.ly, to addres. the challenge of occlus.on, a new los. function, WIoU (Wis. Inters.ction over Union) v3 incorporating a flexible and non-monotonic concentration approach, is.adopted to improve detection rates.for s.rface floating litter. The outcomes.of the experiments.demons.rate that the Ghos.-YOLO v8 model propos.d in this.paper performs.well in the datas.t Marine, s.gnificantly enhances.precis.on and recall by 3.3 and 7.6 percentage points. res.ectively, in contras. with the bas. model, mAP@0.5 and mAP 0.5:0.95 improve by 5.3 and 4.4 percentage points.and reduces.the computational volu

关键词： attention mechanis. ghos.net los. function s.all target detection head s.rface floating litter target detection YOLO v8