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Optimizing Optical Fiber Faults Detection:A Comparative Analysis of Advanced Machine Learning Approaches

Computers, Materials & Continua 2024年第5期79卷 2697-2721页

作者： Kamlesh Kumar Soothar Yuanxiang Chen Arif hussain Magsi Cong Hu hussain shah School of Electronics Engineering Beijing University of Posts and TelecommunicationsBeijing100876China State Key Laboratory of Integrated Services Networks Xidian UniversityXi’an710071China State Key Laboratory ofNetworking and Switching Technology Beijing University of Posts and TelecommunicationsBeijing100876China

Efficient optical network management poses significant importance in backhaul and access network communicationfor preventing service disruptions and ensuring Quality of Service(QoS)satisfaction.The emerging faultsin optical networks introduce challenges that can jeopardize the network with a variety of faults.The existingliterature witnessed various partial or inadequate solutions.On the other hand,Machine Learning(ML)hasrevolutionized as a promising technique for fault detection and prevention.Unlike traditional fault managementsystems,this research has three-fold contributions.First,this research leverages the ML and Deep Learning(DL)multi-classification system and evaluates their accuracy in detecting six distinct fault types,including fiber cut,fibereavesdropping,splicing,bad connector,bending,and PC connector.Secondly,this paper assesses the classificationdelay of each classification algorithm.Finally,this work proposes a fiber optics fault prevention algorithm thatdetermines to mitigate the faults accordingly.This work utilized a publicly available fiber optics dataset namedOTDR_Data and applied different ML classifiers,such as Gaussian Naive Bayes(GNB),Logistic Regression(LR),Support Vector Machine(SVM),K-Nearest Neighbor(KNN),Random Forest(RF),and Decision Tree(DT).Moreover,Ensemble Learning(EL)techniques are applied to evaluate the accuracy of various classifiers.In addition,this work evaluated the performance of DL-based Convolutional Neural Network and Long-Short Term Memory(CNN-LSTM)hybrid classifier.The findings reveal that the CNN-LSTM hybrid technique achieved the highestaccuracy of 99%with a delay of 360 s.On the other hand,EL techniques improved the accuracy in detecting fiberoptic faults.Thus,this research comprehensively assesses accuracy and delay metrics for various classifiers andproposes the most efficient attack detection system in fiber optics.

关键词： Fiber optics fault detection multiclassification machine learning ensemble learning

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Toward a comprehensive hypothesis of oxygen-evolution reaction in the presence of iron and gold

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Journal of Energy Chemistry 2024年第2期89卷 172-183,I0005页

作者： Negah Hashemi Jafar hussain shah Cejun Hu Subhajit Nandy Pavlo Aleshkevych Sumbal Farid Keun Hwa Chae Wei Xie Taifeng Liu Junhu Wang Mohammad Mahdi Najafpour Department of Chemistry Institute for Advanced Studies in Basic Sciences(IASBS)Zanjan 45137-66731Iran Center for Advanced Mössbauer Spectroscopy Mössbauer Effect Data CenterDalian Institute of Chemical PhysicsChinese Academy of SciencesDalian 116023LiaoningChina Key Lab of Advanced Energy Materials Chemistry(Ministry of Education) Renewable Energy Conversion and Storage CenterCollege of ChemistryNankai UniversityTianjin 300071China Advanced Analysis Center Korea Institute of Science and TechnologySeoul 02792Republic of Korea Institute of Physics Polish Academy of SciencesWarsaw 02-668Poland National and Local Joint Engineering Research Center for Applied Technology of Hybrid Nanomaterials Henan UniversityKaifeng 475004HenanChina Center of Climate Change and Global Warming Institute for Advanced Studies in Basic Sciences(IASBS)Zanjan 45137-66731Iran Research Center for Basic Sciences&Modern Technologies(RBST) Institute for Advanced Studies in Basic Sciences(IASBS)Zanjan 45137-66731Iran

This study investigates the effects of Fe on the oxygen-evolution reaction(OER)in the presence of Au.Two distinct areas of OER were identified:the first associated with Fe sites at low overpotential(~330 mV),and the second with Au sites at high overpotential(~870 mV).Various factors such as surface Fe concentration,electrochemical method,scan rate,potential range,concentration,method of adding K_(2)Fe O_(4),nature of Fe,and temperature were varied to observe diverse behaviors during OER for Fe O_(x)H_(y)/Au.Trace amounts of Fe ions had a significant impact on OER,reaching a saturation point where the activity did not increase further.Strong electronic interaction between Fe and Au ions was indicated by X-ray photoelectron spectroscopy(XPS)and electron paramagnetic resonance(EPR)analyses.In situ visible spectroscopy confirmed the formation of Fe O_(4)^(2-)during OER.In situ Mossbauer and surfaceenhanced Raman spectroscopy(SERS)analyses suggest the involvement of Fe-based species as intermediates during the rate-determining step of OER.A lattice OER mechanism based on Fe O_(x)H_(y)was proposed for operation at low overpotentials.Density functional theory(DFT)calculations revealed that Fe oxide,Fe-oxide clusters,and Fe doping on the Au foil exhibited different activities and stabilities during OER.The study provides insights into the interplay between Fe and Au in OER,advancing the understanding of OER mechanisms and offering implications for the design of efficient electrocatalytic systems.

关键词： DFT calculation Fe/Au electrocatalysis Mechanism Oxygen evolution Water oxidation

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Attitude-adjusting dynamical behavior of cubic rover on low-gravity testbed

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Astrodynamics 2024年第1期8卷 149-159页

作者： Bowen Jiang Muhammad Talha hussain Xiangyuan Zeng School of Automation Beijing Institute of TechnologyBeijing100081China

Cubic rovers that traverse by hopping systems are promising in low-gravity environments.Although several analyses of the control methods and mobility of the cubic rover are available,investigations of its attitude-adjusting behavior are still limited.This study derives the dynamic equations of the two attitude-adjusting modes of the cubic rover,referred to as walking and twisting.The relationships between the speed threshold and rotation angle of the cubic rover were investigated in both rigid and regolith environments using a self-designed low-gravity testbed.Comparative studies were conducted by considering the experimental and simulated outputs.The results of this study can be interesting for roving mission planning when exploring planetary moons and small celestial bodies.

关键词： low-gravitytestbed attitude-adjusting motion cubic rover experimental study

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Accelerated Particle Swarm Optimization Algorithm for Efficient Cluster Head Selection in WSN

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Computers, Materials & Continua 2024年第6期79卷 3585-3629页

作者： Imtiaz Ahmad Tariq hussain Babar shah Altaf hussain Iqtidar Ali Farman Ali Institute of Computer Sciences and Information Technology The University of AgriculturePeshawarPakistan School of Computer Science and Technology Zhejiang Gongshang UniversityHangzhouChina College of Technological Innovation Zayed UniversityDubaiUnited Arab Emirates School of Computer Science and Technology Chongqing University of Posts and TelecommunicationsChongqing400065China Department of Applied AI School of ConvergenceCollege of Computing and InformaticsSungkyunkwan UniversitySeoul03063South Korea

Numerous wireless networks have emerged that can be used for short communication ranges where the infrastructure-based networks may fail because of their installation and cost.One of them is a sensor network with embedded sensors working as the primary nodes,termed Wireless Sensor Networks(WSNs),in which numerous sensors are connected to at least one Base Station(BS).These sensors gather information from the environment and transmit it to a BS or gathering location.WSNs have several challenges,including throughput,energy usage,and network lifetime concerns.Different strategies have been applied to get over these restrictions.Clustering may,therefore,be thought of as the best way to solve such issues.Consequently,it is crucial to analyze effective Cluster Head(CH)selection to maximize efficiency throughput,extend the network lifetime,and minimize energy consumption.This paper proposed an Accelerated Particle Swarm Optimization(APSO)algorithm based on the Low Energy Adaptive Clustering Hierarchy(LEACH),Neighboring Based Energy Efficient Routing(NBEER),Cooperative Energy Efficient Routing(CEER),and Cooperative Relay Neighboring Based Energy Efficient Routing(CR-NBEER)techniques.With the help of APSO in the implementation of the WSN,the main methodology of this article has taken place.The simulation findings in this study demonstrated that the suggested approach uses less energy,with respective energy consumption ranges of 0.1441 to 0.013 for 5 CH,1.003 to 0.0521 for 10 CH,and 0.1734 to 0.0911 for 15 CH.The sending packets ratio was also raised for all three CH selection scenarios,increasing from 659 to 1730.The number of dead nodes likewise dropped for the given combination,falling between 71 and 66.The network lifetime was deemed to have risen based on the results found.A hybrid with a few valuable parameters can further improve the suggested APSO-based protocol.Similar to underwater,WSN can make use of the proposed protocol.The overall results have been evaluated and compared with the existing approaches of sensor

关键词： Wireless sensor network cluster head selection low energy adaptive clustering hierarchy accelerated particle swarm optimization

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Deep Learning for Financial Time Series Prediction:A State-of-the-Art Review of Standalone and HybridModels

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Computer Modeling in Engineering & Sciences 2024年第4期139卷 187-224页

作者： Weisi Chen Walayat hussain Francesco Cauteruccio Xu Zhang School of Software Engineering Xiamen University of TechnologyXiamen361024China Peter Faber Business School Australian Catholic UniversityNorth Sydney2060Australia Department of Information Engineering Polytechnic University of MarcheAncona60121Italy

Financial time series prediction,whether for classification or regression,has been a heated research topic over the last decade.While traditional machine learning algorithms have experienced mediocre results,deep learning has largely contributed to the elevation of the prediction performance.Currently,the most up-to-date review of advanced machine learning techniques for financial time series prediction is still lacking,making it challenging for finance domain experts and relevant practitioners to determine which model potentially performs better,what techniques and components are involved,and how themodel can be designed and implemented.This review article provides an overview of techniques,components and frameworks for financial time series prediction,with an emphasis on state-of-the-art deep learning models in the literature from2015 to 2023,including standalonemodels like convolutional neural networks(CNN)that are capable of extracting spatial dependencies within data,and long short-term memory(LSTM)that is designed for handling temporal dependencies;and hybrid models integrating CNN,LSTM,attention mechanism(AM)and other techniques.For illustration and comparison purposes,models proposed in recent studies are mapped to relevant elements of a generalized framework comprised of input,output,feature extraction,prediction,and related processes.Among the state-of-the-artmodels,hybrid models like CNNLSTMand CNN-LSTM-AM in general have been reported superior in performance to stand-alone models like the CNN-only model.Some remaining challenges have been discussed,including non-friendliness for finance domain experts,delayed prediction,domain knowledge negligence,lack of standards,and inability of real-time and highfrequency predictions.The principal contributions of this paper are to provide a one-stop guide for both academia and industry to review,compare and summarize technologies and recent advances in this area,to facilitate smooth and informed implementation,and to highlight future research directions.

关键词： Financial time series prediction convolutional neural network long short-term memory deep learning attention mechanism finance

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Appropriate Combination of Crossover Operator and Mutation Operator in Genetic Algorithms for the Travelling Salesman Problem

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Computers, Materials & Continua 2024年第5期79卷 2399-2425页

作者： Zakir hussain Ahmed Habibollah Haron Abdullah Al-Tameem Department of Mathematics and Statistics College of ScienceImam Mohammad Ibn Saud Islamic University(IMSIU)Riyadh11432Kingdom of Saudi Arabia Faculty of Computing Universiti Teknologi MalaysiaJohor Bahru81310Malaysia College of Computer and Information Sciences Imam Mohammad Ibn Saud Islamic University(IMSIU)Riyadh11432Kingdom of Saudi Arabia

Genetic algorithms(GAs)are very good metaheuristic algorithms that are suitable for solving NP-hard combinatorial optimization problems.AsimpleGAbeginswith a set of solutions represented by a population of chromosomes and then uses the idea of survival of the fittest in the selection process to select some fitter chromosomes.It uses a crossover operator to create better offspring chromosomes and thus,converges the population.Also,it uses a mutation operator to explore the unexplored areas by the crossover operator,and thus,diversifies the GA search space.A combination of crossover and mutation operators makes the GA search strong enough to reach the optimal solution.However,appropriate selection and combination of crossover operator and mutation operator can lead to a very good GA for solving an optimization problem.In this present paper,we aim to study the benchmark traveling salesman problem(TSP).We developed several genetic algorithms using seven crossover operators and six mutation operators for the TSP and then compared them to some benchmark TSPLIB instances.The experimental studies show the effectiveness of the combination of a comprehensive sequential constructive crossover operator and insertion mutation operator for the problem.The GA using the comprehensive sequential constructive crossover with insertion mutation could find average solutions whose average percentage of excesses from the best-known solutions are between 0.22 and 14.94 for our experimented problem instances.

关键词： Travelling salesman problem genetic algorithms crossover operator mutation operator comprehensive sequential constructive crossover insertion mutation

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PdCu alloy anchored defective titania for photocatalytic conversion of carbon dioxide into methane with 100% selectivity

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Journal of Energy Chemistry 2024年第4期91卷 254-265页

作者： Lina Zhang Sajjad hussain Qiuye Li Jianjun Yang National&Local Joint Engineering Research Center for Applied Technology of Hybrid Nanomaterials Henan UniversityKaifeng 475004HenanChina

The photoreduction of CO_(2)into CH_(4)with simultaneous high activity and selectivity is a promising strategy to increase energy supply and alleviate global warming.However,the absence of the active sites that is responsible for the adsorption and activation of CO_(2)and the generation of CO and H2via side reactions often lead to poor efficiency and low selectivity of the catalyst.Herein,Cu,Pd,and PdCu metal clusters cocatalyst-anchored defective TiO_(2)nanotubes(Cu/TiO_(2)-SBO,Pd/TiO_(2)-SBO,and Pd1Cu1/TiO_(2)-SBO)were designed via a simple solution impregnation reduction and applied for photocatalytic conversion of CO_(2)to CH_(4).The Pd1Cu1/TiO_(2)-SBO photocatalyst exhibits excellent catalytic performance among the other catalysts for photoreduction of CO_(2)into CH_(4).More interestingly,the product selectivity of CH_(4)reaches up to 100%with a rate of 25μmol g^(-1)h^(-1).In-situ diffuse reflectance infrared Fourier transform spectroscopy(DRIFTS)and density functional theory(DFT)simulations indicate that the main reasons for the high selectivity of CH_(4)are attributed to the PdCu alloy and oxygen vacancies,which jointly enhance the photoinduced carrier separation and lower energy barriers of key intermediates.Moreover,due to the tunable d-band center of the Cu site in the PdCu alloy,the generated intermediates can be well prevented from poisoning and promoted to participate in further reactions.Hopefully,the current study will provide insight into the development of new,highly selective photocatalysts for the visible light-catalytic reduction of CO_(2)into CH_(4).

关键词： PdCu alloy Defective TiO_(2) Photoreduction of CO_(2) Photocatalytic mechanism

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Experimental Study on Heat Storage Properties Comparison of Paraffin/Metal Foams Phase Change Material Composites

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Journal of Thermal Science 2024年第2期33卷 469-478页

作者： Waqar AHMED Abid hussain Hanzla shahID Imran ALI Hafiz Muhammad ALI Department of Mechanical Engineering University of Engineering and TechnologyTaxila47080Pakistan Department of Mechanical Engineering Institute of Space TechnologyIslamabadPakistan Department of Mechanical Mechatronics and Manufacturing EngineeringUniversity of Engineering and Technology LahoreFaisalabad CampusPunjabPakistan Mechanical Engineering Department King Fahd University of Petroleum and MineralsDhahran31261Saudi Arabia Interdisciplinary Research Center for Renewable Energy and Power Systems(IRC-REPS) King Fahd University of Petroleum and MineralsDhahran31261Saudi Arabia

Heat storage properties of phase change materials(PCMs) are essential characteristics that perform a key role in thermal heat energy storage systems.The thermal properties of PCMs can be improved by developing metal foam/PCM composites.The addition of metal foam in PCMs has a significant effect on the thermal characteristics of PCMs.In this paper,the heat storage properties of two different metal foam/PCM composites were experimentally examined.The behavior of paraffin in metal foam(copper and iron-nickel)/paraffin composites concerning pure paraffin at a constant heat flux of 1000 W/m^(2) in three directions simultaneously(x,y,and z) was studied.Paraffin was infiltrated into copper and iron-nickel foams to develop composite materials which resulted in enhancing the thermal conductivity of the paraffin.A comparative analysis is made on the heat storage properties of paraffin in copper and iron-nickel foams/paraffin composites.Inner temperature distribution during the phase transition process is experimentally evaluated.This comparison indicates that temperature uniformity in copper foam/paraffin composite is better than in iron-nickel foam/paraffin composite and pure paraffin at the same heat flux.Experimental results show that at heat flux of 1000 W/m^(2),the heat storage time for copper foam/paraffin composite is 20.63% of that of iron-nickel foam/paraffin composite.

关键词： heat storage capacity paraffin/metal foam composite temperature uniformity heat storage rate phase transition process

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Knowledge and discriminatory attitudes towards HIV/AIDS among the women of reproductive age group of Pakistan using the Multiple Indicator Cluster Survey(MICS)

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Global Health Journal 2024年第2期8卷 74-82页

作者： Remsha hussain Russell Kabir School of Allied Health Faculty of HealthMedicine and Social CareAnglia Ruskin UniversityUnited Kingdom

Background Human immunodeficiency virus/acquired immunodeficiency syndrome(HIV/AIDS)has become a major worldwide public health issue,with a focus on developing nations.Despite having a very low HIV prevalence,South Asia faces serious issues with stigma and false information because of a lack of awareness.This stigma highlights significant gaps in popular awareness while also sustaining unfavorable attitudes towards those living with HIV/AIDS.Pakistan is ranked second in South Asia for the rapidly increasing AIDS epidemic.Thorough information and optimistic outlooks are essential for successful HIV/AIDS prevention,control,and treatment.But false beliefs about how HIV/AIDS spreads lead to negative perceptions,which highlights the need to look into how women’s knowledge and attitudes about HIV/AIDS in Pakistan are influenced by sociodemographic traits and autonomy.Methods The purpose of this study is to evaluate Pakistani women’s discriminatory attitudes and level of awareness on HIV/AIDS.This study used data(the women in reproductive age 15-49 years’dataset)from the Pakistan Multiple Indicator Cluster Survey to conduct an analytical cross-sectional analysis.To represent the respondents’attitudes and knowledge towards people living with HIV(PLHIV),two composite variables were developed and composite scored.Binary logistics regression was used to identify predictor variables and chi-square was used for bivariate analysis.Results The findings reveal that almost 90%of Pakistani women have poor knowledge and attitude with HIV/AIDS.In Punjab,72.8%of rural residents have low knowledge,whereas only 20.6%of young individuals(15-<25 years old)show the least amount of ignorance.Education is shown to be crucial,and“Higher”education is associated with superior knowledge.Urban dwellers in Khyber Pakhtunkhwa typically have more expertise.Knowledge of HIV is positively correlated with education;those with higher education levels know a lot more(odds ratio[OR]=5.419).Similarly,quintiles with greater incomes show a higher likelihood

关键词： HIV/AIDS PLHIV Knowledge Attitudes Women Pakistan

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Fine Sand and Clay Sediment Acoustic Properties of the Novel Sediment Sample from the Arabian Sea:Experimental Investigations and Biot−Stoll Model Validation

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China Ocean Engineering 2024年第1期38卷 169-180页

作者： shahabuddin SHAIKH HUANG Yi-wang ZHANG Ze-chuan Habib hussain ZUBERI National Key Laboratory of Underwater Acoustic Technology and College of Underwater Acoustic Engineering Harbin Engineering UniversityHarbin 150001China

The present study explores the physical and acoustic characteristics of fine sand and clay in novel seabed marine sediments from of Pakistan coastline of the Arabian Sea.The measured physical parameters included mean grain size,mass density,bulk density,salinity,porosity,permeability,pore size and mineralogical composition.Acoustic properties,including sound speed and attenuation,in the high frequency range of 90-170 kHz were analyzed.A controlled laboratory setup with the acoustic transmission method and Fourier transform techniques was utilized to examine the sound propagation and absorption of novel seabed sediments.The standard deviation of mean sound speed in fresh water was 0.75 m/s,and attenuation was observed in the range of 0.43 to 0.61 dB/m.The mean sound velocity in sand and clay varied from 1706 to 1709 m/s and 1602 to 1608 m/s,respectively.Corresponding average attenuation was observed at 80 to 93 dB/m in sandy sediments and from 31.8 to 38.6 dB/m in clayey sediments.Sound velocity variation within sandy sediment is low,consistent with expected results,and smaller than the predicted uncertainty.However,clay sediment exhibited a positive linear correlation and low sound speed variation.Attenuation increased linearly with frequency for both sediments.Finally,the laboratory results were validated by using the Biot−Stoll model.The dispersion of sound speed in sandy and clayey sediments was consistent with the predictions of the Biot−Stoll model.Measured attenuation aligned more with Biot−Stoll model predictions due to improved permeability,tortuosity and pore size parameter fitting.

关键词： physical and acoustic characteristics marine sediments sound speed attenuation Biot−Stoll model

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