SnO_(2) has been extensively investigated as an anode material for sodium-ion batteries(SIBs)and potassium-ion batteries(PIBs)due to its high Na/K storage capacity,high abundance,and low toxicity.However,the sluggish ...SnO_(2) has been extensively investigated as an anode material for sodium-ion batteries(SIBs)and potassium-ion batteries(PIBs)due to its high Na/K storage capacity,high abundance,and low toxicity.However,the sluggish reaction kinetics,low electronic conductivity,and large volume changes during charge and discharge hinder the practical applications of SnO_(2)-based electrodes for SIBs and PIBs.Engineering rational structures with fast charge/ion transfer and robust stability is important to overcoming these challenges.Herein,S-doped SnO_(2)(S-SnO_(2))quantum dots(QDs)(≈3 nm)encapsulated in an N,S codoped carbon fiber networks(S-SnO_(2)-CFN)are rationally fabricated using a sequential freeze-drying,calcination,and S-doping strategy.Experimental analysis and density functional theory calculations reveal that the integration of S-SnO_(2) QDs with N,S codoped carbon fiber network remarkably decreases the adsorption energies of Na/K atoms in the interlayer of SnO_(2)-CFN,and the S doping can increase the conductivity of SnO_(2),thereby enhancing the ion transfer kinetics.The synergistic interaction between S-SnO_(2) QDs and N,S codoped carbon fiber network results in a composite with fast Na+/K+storage and extraordinary long-term cyclability.Specifically,the S-SnO_(2)-CFN delivers high rate capacities of 141.0 mAh g^(−1) at 20 A g^(−1) in SIBs and 102.8 mAh g^(−1) at 10 A g^(−1) in PIBs.Impressively,it delivers ultra-stable sodium storage up to 10,000 cycles at 5 A g^(−1) and potassium storage up to 5000 cycles at 2 A g^(−1).This study provides insights into constructing metal oxide-based carbon fiber network structures for high-performance electrochemical energy storage and conversion devices.展开更多
The fiber nonlinearity and phase noise(PN)are the focused impairments in the optical communication system,induced by high-capacity transmission and high laser input power.The channels include high-capacity transmissio...The fiber nonlinearity and phase noise(PN)are the focused impairments in the optical communication system,induced by high-capacity transmission and high laser input power.The channels include high-capacity transmissions that cannot be achieved at the end side without aliasing because of fiber nonlinearity and PN impairments.Thus,addressing of these distortions is the basic objective for the 5G mobile network.In this paper,the fiber nonlinearity and PN are investigated using the assembled methodology of millimeter-wave and radio over fiber(mmWave-RoF).The analytical model is designed in terms of outage probability for the proposed mmWave-RoF system.The performance of mmWave-RoF against fiber nonlinearity and PN is studied for input power,output power and length using peak to average power ratio(PAPR)and bit error rate(BER)measuring parameters.The simulation outcomes present that the impacts of fiber nonlinearity and PNcan be balanced for a huge capacity mmWave-RoF model applying input power carefully.展开更多
Al-Si alloy,a high temperature phase change material,has great potential in thermal management due to its advantages of high heat storage density and thermal conductivity.Microencapsulation of Al-Si alloy is one of th...Al-Si alloy,a high temperature phase change material,has great potential in thermal management due to its advantages of high heat storage density and thermal conductivity.Microencapsulation of Al-Si alloy is one of the effective techniques to solve high temperature leakage and corrosion.In this paper,commercial Al-10Si alloy micro powders were encapsulated with flexible ceramic shells whose total thickness is below 1μm by hydrothermal treatment and heat treatment in N_(2) atmosphere.The compositions and microstructures were characterized by XRD,SEM and TEM.The shell was composed of AlN fibers network structure embedded withα-Al_(2)O_(3)/AlN which prevented the alloy from leaking and oxidizing,as well as had excellent thermal stability.The latent heat of microcapsules was 351.8 J g^(-1)for absorption and 372.7 J g^(-1)for exothermic.The microcapsules showed near zero thermal performance loss with latent heat storage(LHS)/release(LHR)was 353.2/403.7 J g^(-1)after 3000 cycles.Compared with the published Al-Si alloy microcapsules,both high heat storage density and super thermal cycle stability were achieved,showing promising development prospects in high temperature thermal management.展开更多
Polyethylene oxide(PEO)-based solid-state electrolytes are considered ideal for electrolyte materials in solid-state lithium metal batteries(SSLMBs).However,practical applications are hindered by the lower conductivit...Polyethylene oxide(PEO)-based solid-state electrolytes are considered ideal for electrolyte materials in solid-state lithium metal batteries(SSLMBs).However,practical applications are hindered by the lower conductivity and poor interfacial stability.Here,we propose a strategy to construct a three-dimensional(3D)fiber network of metal-organic frameworks(MOFs).Composite solid electrolytes(CSEs)with continuous ion transport pathways were fabricated by filling a PEO polymer matrix in fibers containing interconnected MOFs.This 3D fiber network provides a fast Li+transport path and effectively improves the ionic conductivity(1.36×10^(-4) S·cm^(-1),30℃).In addition,the network of interconnected MOFs not only effectively traps the anions,but also provides sufficient mechanical strength to prevent the growth of Li dendrites.Benefiting from the advantages of structural design,the CSEs stabilize the Li/electrolyte interface and extend the cycle life of the Li-symmetric cells to 3000 h.The assembled SSLMBs exhibit excellent cycling performance at both room and high temperatures.In addition,the constructed pouch cells can provide an areal capacity of 0.62 mA·h·cm^(-2),which can still operate under extreme conditions.This work provides a new strategy for the design of CSEs with continuous structure and stable operation of SSLMBs.展开更多
Intelligent assembly of large-scale,complex structures using an intelligent manufacturing platform represents the future development direction for industrial manufacturing.During large-scale structural assembly proces...Intelligent assembly of large-scale,complex structures using an intelligent manufacturing platform represents the future development direction for industrial manufacturing.During large-scale structural assembly processes,several bottleneck problems occur in the existing auxiliary assembly technology.First,the traditional LiDARbased assembly technology is often limited by the openness of the manufacturing environment,in which there are blind spots,and continuous online assembly adjustment thus cannot be realized.Second,for assembly of large structures,a single-station LiDAR system cannot achieve complete coverage,which means that a multi-station combination method must be used to acquire the complete three-dimensional data;many more data errors are caused by the transfer between stations than by the measurement accuracy of a single station,which means that the overall system's measurement and adjustment errors are increased greatly.Third,because of the large numbers of structural components contained in a large assembly,the accumulated errors may lead to assembly interference,but the LiDAR-assisted assembly process does not have a feedback perception capability,and thus assembly component loss can easily be caused when assembly interference occurs.Therefore,this paper proposes to combine an optical fiber sensor network with digital twin technology,which will allow the test data from the assembly entity state in the real world to be applied to the"twin"model in the virtual world and thus solve the problems with test openness and data transfer.The problem of station and perception feedback is also addressed and represents the main innovation of this work.The system uses an optical fiber sensor network as a flexible sensing medium to monitor the strain field distribution within a complex area in real time,and then completes real-time parameter adjustment of the virtual assembly based on the distributed data.Complex areas include areas that are laser-unreachable,areas with complex contact surfaces,and areas with large-scale bending deformations.An assembly condition monitoring system is designed based on the optical fiber sensor network,and an assembly condition monitoring algorithm based on multiple physical quantities is proposed.The feasibility of use of the optical fiber sensor network as the real-state parameter acquisition module for the digital twin intelligent assembly system is discussed.The offset of any position in the test area is calculated using the convolutional neural network of a residual module to provide the compensation parameters required for the virtual model of the assembly structure.In the model optimization parameter module,a correction data table is obtained through iterative learning of the algorithm to realize state prediction from the test data.The experiment simulates a largescale structure assembly process,and performs virtual and real mapping for a variety of situations with different assembly errors to enable correction of the digital twin data stream for the assembly process through the optical fiber sensor network.In the plane strain field calibration experiment,the maximum error among the test values for this system is 0.032 mm,and the average error is 0.014 mm.The results show that use of visual calibration can correct the test error to within a very small range.This result is equally applicable to gradient curvature surfaces and freeform surfaces.Statistics show that the average measurement accuracy error for regular surfaces is better than 11.2%,and the average measurement accuracy error for irregular surfaces is better than 14.8%.During simulation of large-scale structure assembly experiments,the average position deviation accuracy is 0.043 mm,which is in line with the designed accuracy.展开更多
In this paper, we study the protection strategies of domestic optical fiber networks in Taiwan. Delay time experiment of two one-link failed cases are also reported and compared. We can get best protection strategy an...In this paper, we study the protection strategies of domestic optical fiber networks in Taiwan. Delay time experiment of two one-link failed cases are also reported and compared. We can get best protection strategy and bypass the optical transmission signal at shortest delay time.展开更多
The computation resources at a single node in Edge Computing(EC)are commonly limited,which cannot execute large scale computation tasks.To face the challenge,an Offloading scheme leveraging on NEighboring node Resourc...The computation resources at a single node in Edge Computing(EC)are commonly limited,which cannot execute large scale computation tasks.To face the challenge,an Offloading scheme leveraging on NEighboring node Resources(ONER)for EC over Fiber-Wireless(FiWi)access networks is proposed in this paper.In the ONER scheme,the FiWi network connects edge computing nodes with fiber and converges wireless and fiber connections seamlessly,so that it can support the offloading transmission with low delay and wide bandwidth.Based on the ONER scheme supported by FiWi networks,computation tasks can be offloaded to edge computing nodes in a wider range of area without increasing wireless hops(e.g.,just one wireless hop),which achieves low delay.Additionally,an efficient Computation Resource Scheduling(CRS)algorithm based on the ONER scheme is also proposed to make offloading decision.The results show that more offloading requests can be satisfied and the average completion time of computation tasks decreases significantly with the ONER scheme and the CRS algorithm.Therefore,the ONER scheme and the CRS algorithm can schedule computation resources at neighboring edge computing nodes for offloading to meet the challenge of large scale computation tasks.展开更多
While various kinds of fibers are used to improve the hot mix asphalt(HMA) performance, a few works have been undertaken on the hybrid fiber-reinforced HMA. Therefore, the fatigue life of modified HMA samples using po...While various kinds of fibers are used to improve the hot mix asphalt(HMA) performance, a few works have been undertaken on the hybrid fiber-reinforced HMA. Therefore, the fatigue life of modified HMA samples using polypropylene and polyester fibers was evaluated and two models namely regression and artificial neural network(ANN) were used to predict the fatigue life based on the fibers parameters. As ANN contains many parameters such as the number of hidden layers which directly influence the prediction accuracy, genetic algorithm(GA) was used to solve optimization problem for ANN. Moreover, the trial and error method was used to optimize the GA parameters such as the population size. The comparison of the results obtained from regression and optimized ANN with GA shows that the two-hidden-layer ANN with two and five neurons in the first and second hidden layers, respectively, can predict the fatigue life of fiber-reinforced HMA with high accuracy(correlation coefficient of 0.96).展开更多
To investigate wavelength response of the no core fiber（NCF）interference spectrum to concentration,a three-layer back propagation（BP）neural network model was established to optimize the concentration sensing data....To investigate wavelength response of the no core fiber（NCF）interference spectrum to concentration,a three-layer back propagation（BP）neural network model was established to optimize the concentration sensing data.In this method,the measured wavelength and the corresponding concentration were trained by a BP neural network,so that the accuracy of the measurement system was optimized.The wavelength was used as the training set and got into the input layer of the three layer BP network model which is used as the input value of the network,and the corresponding actual concentration value was used as the output value of the network,and the optimal network structure was trained.This paper discovers a preferable correlation between the predicted value and the actual value,where the former is approximately equal to the latter.The correlation coefficients of the measured and predicted values for a sucrose concentration were 1.000 89 and 1.003 94;similarly,correlations of0.999 51 and 1.018 8 for a glucose concentration were observed.The results demonstrate that the BP neural network can improve the prediction accuracy of the nonlinear relationship between the interference spectral data and the concentration in NCF sensing systems.展开更多
Nonlinear distortion is one of key limiting factors in radio over fiber (RoF) transmission systems. To suppress the nonlinear distortion, digital pre-distortion (DPD) has been investigated considerably. However, for m...Nonlinear distortion is one of key limiting factors in radio over fiber (RoF) transmission systems. To suppress the nonlinear distortion, digital pre-distortion (DPD) has been investigated considerably. However, for multi-band signals, DPD becomes very complex, which limits the applications. To reduce the complexity, many simplified DPDs have been proposed. In this work, a new multidimensional DPD is proposed, in which in-band and out-of-band distortion are separated and the out-of-band distortion is evaluated by sum and differences of all input signals instead of all individual input signals, thus complexity is reduced. An up to 6-band 64-QAM orthogonal frequency division multiplexing (OFDM) signal with each bandwidth of 200 MHz in simulations and a 5-band 20 MHz 64-QAM OFDM signal in experiments are used to validate the pro-posed DPD. The validation is illustrated in the means of power spectrum, AM/AM and AM/PM distortion, and error vector magnitude (EVM) of the received signal constellations. The average EVM improvement by simulation for 3-band, 4-band, 5-band and 6-band signals is 19.97 dB, 18.65 dB, 16.64 dB and 15.44 dB, respectively. The average EVM improvement by experiments for 5-band signals is 8.1 dB. Considering the ten times of bandwidth difference, experiments and simulation agree well.展开更多
The high-density population leads to crowded cities. The future city is envisaged to encompass a large-scale network with diverse applications and a massive number of interconnected heterogeneous wireless-enabled devi...The high-density population leads to crowded cities. The future city is envisaged to encompass a large-scale network with diverse applications and a massive number of interconnected heterogeneous wireless-enabled devices. Hence, green technology elements are crucial to design sustainable and future-proof network architectures. They are the solutions for spectrum scarcity, high latency, interference, energy efficiency, and scalability that occur in dense and heterogeneous wireless networks especially in the home area network （HAN）. Radio-over-fiber （ROF） is a technology candidate to provide a global view of HAN＇s activities that can be leveraged to allocate orthogonal channel communications for enabling wireless-enabled HAN devices transmission, with considering the clustered-frequency-reuse approach. Our proposed network architecture design is mainly focused on enhancing the network throughput and reducing the average network communications latency by proposing a data aggregation unit （DAU）. The performance shows that with the DAU, the average network communications latency reduces significantly while the network throughput is enhanced, compared with the existing ROF architecture without the DAU.展开更多
In the face of the increased global campaign to minimize the emission of greenhouse gases and the need for sustainability in manufacturing, there is a great deal of research focusing on environmentally benign and rene...In the face of the increased global campaign to minimize the emission of greenhouse gases and the need for sustainability in manufacturing, there is a great deal of research focusing on environmentally benign and renewable materials as a substitute for synthetic and petroleum-based products. Natural fiber-reinforced polymeric composites have recently been proposed as a viable alternative to synthetic materials. The current work investigates the suitability of coconut fiber-reinforced polypropylene as a structural material. The coconut fiber-reinforced polypropylene composites were developed. Samples of coconut fiber/polypropylene (PP) composites were prepared using Fused Filament Fabrication (FFF). Tests were then conducted on the mechanical properties of the composites for different proportions of coconut fibers. The results obtained indicate that the composites loaded with 2 wt% exhibited the highest tensile and flexural strength, while the ones loaded with 3 wt% had the highest compression strength. The ultimate tensile and flexural strength at 2 wt% were determined to be 34.13 MPa and 70.47 MPa respectively. The compression strength at 3 wt% was found to be 37.88 MPa. Compared to pure polypropylene, the addition of coconut fibers increased the tensile, flexural, and compression strength of the composite. In the study, an artificial neural network model was proposed to predict the mechanical properties of polymeric composites based on the proportion of fibers. The model was found to predict data with high accuracy.展开更多
基金National Natural Science Foundation of China,Grant/Award Number:51971065Innovation Program of Shanghai Municipal Education Commission,Grant/Award Number:2019-01-07-00-07-E00028。
文摘SnO_(2) has been extensively investigated as an anode material for sodium-ion batteries(SIBs)and potassium-ion batteries(PIBs)due to its high Na/K storage capacity,high abundance,and low toxicity.However,the sluggish reaction kinetics,low electronic conductivity,and large volume changes during charge and discharge hinder the practical applications of SnO_(2)-based electrodes for SIBs and PIBs.Engineering rational structures with fast charge/ion transfer and robust stability is important to overcoming these challenges.Herein,S-doped SnO_(2)(S-SnO_(2))quantum dots(QDs)(≈3 nm)encapsulated in an N,S codoped carbon fiber networks(S-SnO_(2)-CFN)are rationally fabricated using a sequential freeze-drying,calcination,and S-doping strategy.Experimental analysis and density functional theory calculations reveal that the integration of S-SnO_(2) QDs with N,S codoped carbon fiber network remarkably decreases the adsorption energies of Na/K atoms in the interlayer of SnO_(2)-CFN,and the S doping can increase the conductivity of SnO_(2),thereby enhancing the ion transfer kinetics.The synergistic interaction between S-SnO_(2) QDs and N,S codoped carbon fiber network results in a composite with fast Na+/K+storage and extraordinary long-term cyclability.Specifically,the S-SnO_(2)-CFN delivers high rate capacities of 141.0 mAh g^(−1) at 20 A g^(−1) in SIBs and 102.8 mAh g^(−1) at 10 A g^(−1) in PIBs.Impressively,it delivers ultra-stable sodium storage up to 10,000 cycles at 5 A g^(−1) and potassium storage up to 5000 cycles at 2 A g^(−1).This study provides insights into constructing metal oxide-based carbon fiber network structures for high-performance electrochemical energy storage and conversion devices.
基金The authors acknowledge the support from the Deanship of Scientific Research,Najran University.Kingdom of Saudi Arabia,for funding this work under the research groups funding program grant code number(NU/RG/SERC/11/3).
文摘The fiber nonlinearity and phase noise(PN)are the focused impairments in the optical communication system,induced by high-capacity transmission and high laser input power.The channels include high-capacity transmissions that cannot be achieved at the end side without aliasing because of fiber nonlinearity and PN impairments.Thus,addressing of these distortions is the basic objective for the 5G mobile network.In this paper,the fiber nonlinearity and PN are investigated using the assembled methodology of millimeter-wave and radio over fiber(mmWave-RoF).The analytical model is designed in terms of outage probability for the proposed mmWave-RoF system.The performance of mmWave-RoF against fiber nonlinearity and PN is studied for input power,output power and length using peak to average power ratio(PAPR)and bit error rate(BER)measuring parameters.The simulation outcomes present that the impacts of fiber nonlinearity and PNcan be balanced for a huge capacity mmWave-RoF model applying input power carefully.
基金financial support from the National Natural Science Foundation of China(No.52072276)Hubei Important Project on Science and Technology(No.2022BECO20).
文摘Al-Si alloy,a high temperature phase change material,has great potential in thermal management due to its advantages of high heat storage density and thermal conductivity.Microencapsulation of Al-Si alloy is one of the effective techniques to solve high temperature leakage and corrosion.In this paper,commercial Al-10Si alloy micro powders were encapsulated with flexible ceramic shells whose total thickness is below 1μm by hydrothermal treatment and heat treatment in N_(2) atmosphere.The compositions and microstructures were characterized by XRD,SEM and TEM.The shell was composed of AlN fibers network structure embedded withα-Al_(2)O_(3)/AlN which prevented the alloy from leaking and oxidizing,as well as had excellent thermal stability.The latent heat of microcapsules was 351.8 J g^(-1)for absorption and 372.7 J g^(-1)for exothermic.The microcapsules showed near zero thermal performance loss with latent heat storage(LHS)/release(LHR)was 353.2/403.7 J g^(-1)after 3000 cycles.Compared with the published Al-Si alloy microcapsules,both high heat storage density and super thermal cycle stability were achieved,showing promising development prospects in high temperature thermal management.
基金support from the China Postdoctoral Science Foundation(Nos.2022TQ0173 and 2023M731922).
文摘Polyethylene oxide(PEO)-based solid-state electrolytes are considered ideal for electrolyte materials in solid-state lithium metal batteries(SSLMBs).However,practical applications are hindered by the lower conductivity and poor interfacial stability.Here,we propose a strategy to construct a three-dimensional(3D)fiber network of metal-organic frameworks(MOFs).Composite solid electrolytes(CSEs)with continuous ion transport pathways were fabricated by filling a PEO polymer matrix in fibers containing interconnected MOFs.This 3D fiber network provides a fast Li+transport path and effectively improves the ionic conductivity(1.36×10^(-4) S·cm^(-1),30℃).In addition,the network of interconnected MOFs not only effectively traps the anions,but also provides sufficient mechanical strength to prevent the growth of Li dendrites.Benefiting from the advantages of structural design,the CSEs stabilize the Li/electrolyte interface and extend the cycle life of the Li-symmetric cells to 3000 h.The assembled SSLMBs exhibit excellent cycling performance at both room and high temperatures.In addition,the constructed pouch cells can provide an areal capacity of 0.62 mA·h·cm^(-2),which can still operate under extreme conditions.This work provides a new strategy for the design of CSEs with continuous structure and stable operation of SSLMBs.
基金supported by the National Science Foundation of China(Theoretical Model and Experimental Research on the Novel FBG Sensing System based on the Fusion Algorithm,No.61703056)the Jilin Province Science and Technology Development Plan Project(No.20190103154JH)。
文摘Intelligent assembly of large-scale,complex structures using an intelligent manufacturing platform represents the future development direction for industrial manufacturing.During large-scale structural assembly processes,several bottleneck problems occur in the existing auxiliary assembly technology.First,the traditional LiDARbased assembly technology is often limited by the openness of the manufacturing environment,in which there are blind spots,and continuous online assembly adjustment thus cannot be realized.Second,for assembly of large structures,a single-station LiDAR system cannot achieve complete coverage,which means that a multi-station combination method must be used to acquire the complete three-dimensional data;many more data errors are caused by the transfer between stations than by the measurement accuracy of a single station,which means that the overall system's measurement and adjustment errors are increased greatly.Third,because of the large numbers of structural components contained in a large assembly,the accumulated errors may lead to assembly interference,but the LiDAR-assisted assembly process does not have a feedback perception capability,and thus assembly component loss can easily be caused when assembly interference occurs.Therefore,this paper proposes to combine an optical fiber sensor network with digital twin technology,which will allow the test data from the assembly entity state in the real world to be applied to the"twin"model in the virtual world and thus solve the problems with test openness and data transfer.The problem of station and perception feedback is also addressed and represents the main innovation of this work.The system uses an optical fiber sensor network as a flexible sensing medium to monitor the strain field distribution within a complex area in real time,and then completes real-time parameter adjustment of the virtual assembly based on the distributed data.Complex areas include areas that are laser-unreachable,areas with complex contact surfaces,and areas with large-scale bending deformations.An assembly condition monitoring system is designed based on the optical fiber sensor network,and an assembly condition monitoring algorithm based on multiple physical quantities is proposed.The feasibility of use of the optical fiber sensor network as the real-state parameter acquisition module for the digital twin intelligent assembly system is discussed.The offset of any position in the test area is calculated using the convolutional neural network of a residual module to provide the compensation parameters required for the virtual model of the assembly structure.In the model optimization parameter module,a correction data table is obtained through iterative learning of the algorithm to realize state prediction from the test data.The experiment simulates a largescale structure assembly process,and performs virtual and real mapping for a variety of situations with different assembly errors to enable correction of the digital twin data stream for the assembly process through the optical fiber sensor network.In the plane strain field calibration experiment,the maximum error among the test values for this system is 0.032 mm,and the average error is 0.014 mm.The results show that use of visual calibration can correct the test error to within a very small range.This result is equally applicable to gradient curvature surfaces and freeform surfaces.Statistics show that the average measurement accuracy error for regular surfaces is better than 11.2%,and the average measurement accuracy error for irregular surfaces is better than 14.8%.During simulation of large-scale structure assembly experiments,the average position deviation accuracy is 0.043 mm,which is in line with the designed accuracy.
文摘In this paper, we study the protection strategies of domestic optical fiber networks in Taiwan. Delay time experiment of two one-link failed cases are also reported and compared. We can get best protection strategy and bypass the optical transmission signal at shortest delay time.
基金supported by National Natural Science Foundation of China(Grant No.61471053,61901052)Fundamental Research Funds for the Central Universities(Grant 2018RC03)Beijing Laboratory of Advanced Information Networks
文摘The computation resources at a single node in Edge Computing(EC)are commonly limited,which cannot execute large scale computation tasks.To face the challenge,an Offloading scheme leveraging on NEighboring node Resources(ONER)for EC over Fiber-Wireless(FiWi)access networks is proposed in this paper.In the ONER scheme,the FiWi network connects edge computing nodes with fiber and converges wireless and fiber connections seamlessly,so that it can support the offloading transmission with low delay and wide bandwidth.Based on the ONER scheme supported by FiWi networks,computation tasks can be offloaded to edge computing nodes in a wider range of area without increasing wireless hops(e.g.,just one wireless hop),which achieves low delay.Additionally,an efficient Computation Resource Scheduling(CRS)algorithm based on the ONER scheme is also proposed to make offloading decision.The results show that more offloading requests can be satisfied and the average completion time of computation tasks decreases significantly with the ONER scheme and the CRS algorithm.Therefore,the ONER scheme and the CRS algorithm can schedule computation resources at neighboring edge computing nodes for offloading to meet the challenge of large scale computation tasks.
文摘While various kinds of fibers are used to improve the hot mix asphalt(HMA) performance, a few works have been undertaken on the hybrid fiber-reinforced HMA. Therefore, the fatigue life of modified HMA samples using polypropylene and polyester fibers was evaluated and two models namely regression and artificial neural network(ANN) were used to predict the fatigue life based on the fibers parameters. As ANN contains many parameters such as the number of hidden layers which directly influence the prediction accuracy, genetic algorithm(GA) was used to solve optimization problem for ANN. Moreover, the trial and error method was used to optimize the GA parameters such as the population size. The comparison of the results obtained from regression and optimized ANN with GA shows that the two-hidden-layer ANN with two and five neurons in the first and second hidden layers, respectively, can predict the fatigue life of fiber-reinforced HMA with high accuracy(correlation coefficient of 0.96).
基金Supported by the National Natural Science Foundation of China(61307122)the University Science and Technology Innovation Team Support Project of Henan Province(13IRTTHN016)the Innovative and Training Project of Post Graduate Funding from the Henan Normal University(201310476046)
文摘To investigate wavelength response of the no core fiber（NCF）interference spectrum to concentration,a three-layer back propagation（BP）neural network model was established to optimize the concentration sensing data.In this method,the measured wavelength and the corresponding concentration were trained by a BP neural network,so that the accuracy of the measurement system was optimized.The wavelength was used as the training set and got into the input layer of the three layer BP network model which is used as the input value of the network,and the corresponding actual concentration value was used as the output value of the network,and the optimal network structure was trained.This paper discovers a preferable correlation between the predicted value and the actual value,where the former is approximately equal to the latter.The correlation coefficients of the measured and predicted values for a sucrose concentration were 1.000 89 and 1.003 94;similarly,correlations of0.999 51 and 1.018 8 for a glucose concentration were observed.The results demonstrate that the BP neural network can improve the prediction accuracy of the nonlinear relationship between the interference spectral data and the concentration in NCF sensing systems.
文摘Nonlinear distortion is one of key limiting factors in radio over fiber (RoF) transmission systems. To suppress the nonlinear distortion, digital pre-distortion (DPD) has been investigated considerably. However, for multi-band signals, DPD becomes very complex, which limits the applications. To reduce the complexity, many simplified DPDs have been proposed. In this work, a new multidimensional DPD is proposed, in which in-band and out-of-band distortion are separated and the out-of-band distortion is evaluated by sum and differences of all input signals instead of all individual input signals, thus complexity is reduced. An up to 6-band 64-QAM orthogonal frequency division multiplexing (OFDM) signal with each bandwidth of 200 MHz in simulations and a 5-band 20 MHz 64-QAM OFDM signal in experiments are used to validate the pro-posed DPD. The validation is illustrated in the means of power spectrum, AM/AM and AM/PM distortion, and error vector magnitude (EVM) of the received signal constellations. The average EVM improvement by simulation for 3-band, 4-band, 5-band and 6-band signals is 19.97 dB, 18.65 dB, 16.64 dB and 15.44 dB, respectively. The average EVM improvement by experiments for 5-band signals is 8.1 dB. Considering the ten times of bandwidth difference, experiments and simulation agree well.
基金supported by the Ministry of Higher Education,Malaysia under Scholarship of Hadiah Latihan Persekutuan under Grant No.KPT.B.600-19/3-791206065445
文摘The high-density population leads to crowded cities. The future city is envisaged to encompass a large-scale network with diverse applications and a massive number of interconnected heterogeneous wireless-enabled devices. Hence, green technology elements are crucial to design sustainable and future-proof network architectures. They are the solutions for spectrum scarcity, high latency, interference, energy efficiency, and scalability that occur in dense and heterogeneous wireless networks especially in the home area network （HAN）. Radio-over-fiber （ROF） is a technology candidate to provide a global view of HAN＇s activities that can be leveraged to allocate orthogonal channel communications for enabling wireless-enabled HAN devices transmission, with considering the clustered-frequency-reuse approach. Our proposed network architecture design is mainly focused on enhancing the network throughput and reducing the average network communications latency by proposing a data aggregation unit （DAU）. The performance shows that with the DAU, the average network communications latency reduces significantly while the network throughput is enhanced, compared with the existing ROF architecture without the DAU.
文摘In the face of the increased global campaign to minimize the emission of greenhouse gases and the need for sustainability in manufacturing, there is a great deal of research focusing on environmentally benign and renewable materials as a substitute for synthetic and petroleum-based products. Natural fiber-reinforced polymeric composites have recently been proposed as a viable alternative to synthetic materials. The current work investigates the suitability of coconut fiber-reinforced polypropylene as a structural material. The coconut fiber-reinforced polypropylene composites were developed. Samples of coconut fiber/polypropylene (PP) composites were prepared using Fused Filament Fabrication (FFF). Tests were then conducted on the mechanical properties of the composites for different proportions of coconut fibers. The results obtained indicate that the composites loaded with 2 wt% exhibited the highest tensile and flexural strength, while the ones loaded with 3 wt% had the highest compression strength. The ultimate tensile and flexural strength at 2 wt% were determined to be 34.13 MPa and 70.47 MPa respectively. The compression strength at 3 wt% was found to be 37.88 MPa. Compared to pure polypropylene, the addition of coconut fibers increased the tensile, flexural, and compression strength of the composite. In the study, an artificial neural network model was proposed to predict the mechanical properties of polymeric composites based on the proportion of fibers. The model was found to predict data with high accuracy.
