The conventional zenith tropospheric delay(ZTD)model(known as the Saastamoinen model)does not consider seasonal variations affecting the delay,giving it low accuracy and stability.This may be improved with adjustments...The conventional zenith tropospheric delay(ZTD)model(known as the Saastamoinen model)does not consider seasonal variations affecting the delay,giving it low accuracy and stability.This may be improved with adjustments to account for annual and semi-annual variations.This method uses ZTD data provided by the Global Geodetic Observing System to analyze seasonal variations in the bias of the Saastamoinen model in Asia,and then constructs a model with seasonal variation corrections,denoted as SSA.To overcome the dependence of the model on in-situ meteorological parameters,the SSA+GPT3 model is formed by combining the SSA and GPT3(global pressure-temperature)models.The results show that the introduction of annual and semi-annual variations can substantially improve the Saastamoinen model,yielding small and time-stable variations in bias and root mean square(RMS).In summer and autumn,the bias and RMS are noticeably smaller than those from the Saastamoinen model.In addition,the SSA model performs better in low-latitude and low-altitude areas,and bias and RMS decease with the increase of latitude or altitude.The prediction accuracy of the SSA model is also evaluated for external consistency.The results show that the accuracy of the SSA model(bias:-0.38 cm,RMS:4.43 cm)is better than that of the Saastamoinen model(bias:1.45 cm,RMS:5.16 cm).The proposed method has strong applicability and can therefore be used for predictive ZTD correction across Asia.展开更多
An analytical solution is presented for the electromagnetic scattering from an infinite-length metallic carbon nanotube and a carbon nanotube bundle.The scattering field and scattering cross section are predicted usin...An analytical solution is presented for the electromagnetic scattering from an infinite-length metallic carbon nanotube and a carbon nanotube bundle.The scattering field and scattering cross section are predicted using a modal technique based on a Bessel and Hankel function for the electric line source and a quantum conductance function for the carbon nanotube.For the particular case of an isolated armchair (10,10) carbon nanotube,the scattered field predicted from this technique is in excellent agreement with the measured result.Furthermore,the analysis indicates that the scattering pattern of an isolated carbon nanotube differs from that of the carbon nanotube bundle of identical index (m,n) metallic carbon nanotubes.展开更多
We report the generation of high energy 2μm picosecond pulses from a thulium-doped fiber master oscillator power amplifier system.The all-fiber configuration was realized by a flexible large-mode area photonic crysta...We report the generation of high energy 2μm picosecond pulses from a thulium-doped fiber master oscillator power amplifier system.The all-fiber configuration was realized by a flexible large-mode area photonic crystal fiber(LMA-PCF).The amplifier output is a linearly-polarized 1.5 ns,100 kHz pulse train with a pulse energy of up to 250μJ.Pulse compression was achieved with(2+2)-pass chirped volume Bragg grating(CVBG)to obtain a 2.8 ps pulse width with a total pulse energy of 46μJ.The overall system compactness was enabled by the all-fiber amplifier design and the multi-pass CVBG-based compressor.The laser output was then used to demonstrate high-speed direct-writing capability on a temperature-sensitive biomaterial to change its topography(i.e.fabricate microchannels,foams and pores).The topographical modifications of biomaterials are known to influence cell behavior and fate which is potentially useful in many cell and tissue engineering applications.展开更多
TiO2 thin films were deposited on quartz substrates by DC reactive magnetron sputtering of a pure Ti target in Ar/O2 plasma at room temperature. The TiO2 films were annealed at different temperatures ranging from 300 ...TiO2 thin films were deposited on quartz substrates by DC reactive magnetron sputtering of a pure Ti target in Ar/O2 plasma at room temperature. The TiO2 films were annealed at different temperatures ranging from 300 to 800 °C in a tube furnace under flowing oxygen gas for half an hour each. The effect of annealing temperatures on the structure, optical properties, and morphologies were presented and discussed by using X-ray diffraction, optical absorption spectrum, and atomic force microscope. The films show the presence of diffraction peaks from the (101), (004), (200) and (105) lattice planes of the anatase TiO2 lattice. The direct band gap of the annealed films decreases with the increase of annealing temperature. While, the roughness of the films increases with the increases of annealing temperature, and some significant roughness changes of the TiO2 film surfaces were observed after the annealing temperature reached 800 °C. Moreover, the influences of annealing on the microstructures of the TiO2 film were investigated also by in situ observation in transmission electron microscope.展开更多
Grid-connected reactive-load compensation and harmonic control are becoming a central topic as photovoltaic(PV)grid-connected systems diversified.This research aims to produce a high-performance inverter with a fast d...Grid-connected reactive-load compensation and harmonic control are becoming a central topic as photovoltaic(PV)grid-connected systems diversified.This research aims to produce a high-performance inverter with a fast dynamic response for accurate reference tracking and a low total har-monic distortion(THD)even under nonlinear load applications by improving its control scheme.The proposed system is expected to operate in both stand-alone mode and grid-connected mode.In stand-alone mode,the proposed controller supplies power to critical loads,alternatively during grid-connected mode provide excess energy to the utility.A modified variable step incremental conductance(VS-InCond)algorithm is designed to extract maximum power from PV.Whereas the proposed inverter controller is achieved by using a modified PQ theory with double-band hysteresis current controller(PQ-DBHCC)to produce a reference current based on a decomposition of a single-phase load current.The nonlinear rectifier loads often create significant distortion in the output voltage of single-phase inverters,due to excessive current harmonics in the grid.Therefore,the proposed method generates a close-loop reference current for the switching scheme,hence,minimizing the inverter voltage distortion caused by the excessive grid current harmonics.The simulation findings suggest the proposed control technique can effectively yield more than 97%of power conversion efficiency while suppressing the grid current THD by less than 2%and maintaining the unity power factor at the grid side.The efficacy of the proposed controller is simulated using MATLAB/Simulink.展开更多
We propose to perform an image-based framework for electrical energy meter reading.Our aim is to extract the image region that depicts the digits and then recognize them to record the consumed units.Combining the read...We propose to perform an image-based framework for electrical energy meter reading.Our aim is to extract the image region that depicts the digits and then recognize them to record the consumed units.Combining the readings of serial numbers and energy meter units,an automatic billing system using the Internet of Things and a graphical user interface is deployable in a real-time setup.However,such region extraction and character recognition become challenging due to image variations caused by several factors such as partial occlusion due to dust on the meter display,orientation and scale variations caused by camera positioning,and non-uniform illumination caused by shades.To this end,our work evaluates and compares the stateof-the art deep learning algorithm You Only Look Once(YOLO)along with traditional handcrafted features for text extraction and recognition.Our image dataset contains 10,000 images of electrical energymeters and is further expanded by data augmentation such as in-plane rotation and scaling tomake the deep learning algorithms robust to these image variations.For training and evaluation,the image dataset is annotated to produce the ground truth of all the images.Consequently,YOLO achieves superior performance over the traditional handcrafted features with an average recognition rate of 98%for all the digits.It proves to be robust against the mentioned image variations compared with the traditional handcrafted features.Our proposed method can be highly instrumental in reducing the time and effort involved in the currentmeter reading,where workers visit door to door,take images ofmeters and manually extract readings from these images.展开更多
This paper presents a novel approach for tire-pattern classification,aimed at conducting forensic analysis on tire marks discovered at crime scenes.The classification model proposed in this study accounts for the intr...This paper presents a novel approach for tire-pattern classification,aimed at conducting forensic analysis on tire marks discovered at crime scenes.The classification model proposed in this study accounts for the intricate and dynamic nature of tire prints found in real-world scenarios,including accident sites.To address this complexity,the classifier model was developed to harness the meta-learning capabilities of few-shot learning algorithms(learning-to-learn).The model is meticulously designed and optimized to effectively classify both tire patterns exhibited on wheels and tire-indentation marks visible on surfaces due to friction.This is achieved by employing a semantic segmentation model to extract the tire pattern marks within the image.These marks are subsequently used as a mask channel,combined with the original image,and fed into the classifier to perform classification.Overall,The proposed model follows a three-step process:(i)the Bilateral Segmentation Network is employed to derive the semantic segmentation of the tire pattern within a given image.(ii)utilizing the semantic image in conjunction with the original image,the model learns and clusters groups to generate vectors that define the relative position of the image in the test set.(iii)the model performs predictions based on these learned features.Empirical verification demonstrates usage of semantic model to extract the tire patterns before performing classification increases the overall accuracy of classification by∼4%.展开更多
The development of Vehicular Ad-hoc Network(VANET)technology is helping Intelligent Transportation System(ITS)services to become a reality.Vehicles can use VANETs to communicate safety messages on the road(while drivi...The development of Vehicular Ad-hoc Network(VANET)technology is helping Intelligent Transportation System(ITS)services to become a reality.Vehicles can use VANETs to communicate safety messages on the road(while driving)and can inform their location and share road condition information in real-time.However,intentional and unintentional(e.g.,packet/frame collision)wireless signal jamming can occur,which will degrade the quality of communication over the channel,preventing the reception of safety messages,and thereby posing a safety hazard to the vehicle’s passengers.In this paper,VANET jamming detection applying Support Vector Machine(SVM)machine learning technology is used to classify jamming and non-jamming situations.The analysis is based on two cases which include normal traffic and heavy traffic conditions,where the results show that the probability of packet dropping will increase when many vehicles are using the wireless channel simultaneously.When using SVM classification,the most appropriate feature set applied in determining a jamming situation shows an accuracy of 98%or higher.Furthermore,more advanced jamming attacks need to be considered for preparation of more reliable and safer autonomous ITS services.Such research can use vehicular communication transmission and reception data based on selected published datasets.In this paper,an additional adversarial defense algorithm using the Density-Based Spatial Clustering of Applications with Noise(DBSCAN)method is proposed,which assumes that evolutionary attacks of the jammer will attempt to confuse the trained classifier.The simulation results show that applying DBSCAN can improve the accuracy by elimination of outliers before conducting classification testing.展开更多
As a representative of chain-based protocol in Wireless Sensor Networks (WSNs), EEPB is an elegant solution on energy efficiency. However, in the latter part of the operation of the network, there is still a big probl...As a representative of chain-based protocol in Wireless Sensor Networks (WSNs), EEPB is an elegant solution on energy efficiency. However, in the latter part of the operation of the network, there is still a big problem: reserving energy of the node frequently presents the incapacity of directly communicating with the base station, at the same time capacity of data acquisition and transmission as normal nodes. If these nodes were selected as LEADER nodes, that will accelerate the death process and unevenness of energy consumption distribution among nodes.This paper proposed a chain routing algorithm based ontraffic prediction model (CRTP).The novel algorithmdesigns a threshold judgment method through introducing the traffic prediction model in the process of election of LEADER node. The process can be dynamically adjusted according to the flow forecasting. Therefore, this algorithm lets the energy consumption tend-ing to keep at same level. Simulation results show that CRTP has superior performance over EEPB in terms of balanced network energy consumption and the prolonged network life.展开更多
HVDC auxiliary power control can significantly improve the transient stability of AC/DC power grid.An HVDC adaptive emergency power support method based on unbalanced power on line estimation is proposed in this paper...HVDC auxiliary power control can significantly improve the transient stability of AC/DC power grid.An HVDC adaptive emergency power support method based on unbalanced power on line estimation is proposed in this paper.By establishing the extended state equation of the system,the on line dynamic estimation of unbalanced power of the system was realized.On this basis,power support was realized based on the principle of the ladder increment.The optimal DC was selected by the power support factor,and the emergency power support controller was installed on the DC.This emergency power support method can realize dynamic optimal power support with minimized control cost.The three infeed HVDC system was built on PSCAD.The simulation results show the effectiveness of the proposed method.展开更多
A single-channel electroencephalography(EEG)device,despite being widely accepted due to convenience,ease of deployment and suitability for use in complex environments,typically poses a great challenge for reactive bra...A single-channel electroencephalography(EEG)device,despite being widely accepted due to convenience,ease of deployment and suitability for use in complex environments,typically poses a great challenge for reactive brain-computer interface(BCI)applications particularly when a continuous command from users is desired to run a motorized actuator with different speed profiles.In this study,a combination of an inconspicuous visual stimulus and voluntary eyeblinks along with a machine learning-based decoder is considered as a new reactive BCI paradigm to increase the degree of freedom and minimize mismatches between the intended dynamic command and transmitted control signal.The proposed decoder is constructed based on Gaussian Process model(GPM)which is a nonparametric Bayesian approach that has the advantages of being able to operate on small datasets and providing measurements of uncertainty on predictions.To evaluate the effectiveness of the proposed method,the GPM is compared against other competitive techniques which include k-Nearest Neighbors,linear discriminant analysis,support vector machine,ensemble learning and neural network.Results demonstrate that a significant improvement can be achieved via the GPM approach with average accuracy reaching over 96%and mean absolute error of no greater than 0.8 cm/s.In addition,the analysis reveals that while the performances of other existing methods deteriorate with a certain type of stimulus due to signal drifts resulting from the voluntary eyeblinks,the proposed GPM exhibits consistent performance across all stimuli considered,thereby manifesting its generalization capability and making it a more suitable option for dynamic commands with a single-channel EEG-controlled actuator.展开更多
A novel numerical algorithm for fault location estimation of single-phase-to-earth fault on EHV transmission lines is presented in this paper. The method is based on one-terminal voltage and current data and is used i...A novel numerical algorithm for fault location estimation of single-phase-to-earth fault on EHV transmission lines is presented in this paper. The method is based on one-terminal voltage and current data and is used in a procedure that provides the automatic determination of faulted types and phases, rather than requires engineer to specify them. The loop and nodal equations comparing the faulted phase to non-faulted phases of multi-parallel lines are introduced in the fault location estimation models, in which source impedance of remote end is not involved. Precise algorithms of locating fault are derived. The effect of load flow and fault resistance,on the location accuracy, are effectively eliminated. The algorithms are demonstrated by digital computer simulations.展开更多
The paper proposes an Indoor Localization System(ILS)which uses only one fixed Base Station(BS)with simple non-reconfigurable antennas.The proposed algorithm measures Received Signal Strength(RSS)and maps it to the lo...The paper proposes an Indoor Localization System(ILS)which uses only one fixed Base Station(BS)with simple non-reconfigurable antennas.The proposed algorithm measures Received Signal Strength(RSS)and maps it to the location in the room by estimating signal strength of a direct line of sight(LOS)signal and signal of the first order reflection from the wall.The algorithm is evaluated through both simulations and empirical measurements in a furnished open space office,sampling 21 different locations in the room.It is demonstrated the system can identify user’s real-time location with a maximum estimation error below 0.7 m for 80%confidence Cumulative Distribution Function(CDF)user level,demonstrating the ability to accurately estimate the receiver’s location within the room.The system is intended as a cost-efficient indoor localization technique,offering simplicity and easy integration with existing wireless communication systems.Unlike comparable single base station localization techniques,the proposed system does not require beam scanning,offering stable communication capacity while performing the localization process.展开更多
With the growing adoption of Electrical Vehicles(EVs),it is expected that a large number of on-board Li-ion batteries will be retired from EVs in the near future.Retired batteries will typically retain 80%of their ini...With the growing adoption of Electrical Vehicles(EVs),it is expected that a large number of on-board Li-ion batteries will be retired from EVs in the near future.Retired batteries will typically retain 80%of their initial capacities and can be recycled as second life batteries(SLBs).Although the capital costs of SLBs are much cheaper,their operational reliability is an important concern since used batteries may suffer from a higher failure rate.This paper aggregates brand new batteries and SLBs together to improve power system’s operating performance with renewable energy resources.In the context of a day-ahead and intra-day dispatch framework,a two-stage coordinated optimal scheduling method is proposed.Specifically,the energy cost of brand-new batteries and SLBs is calculated based on detailed battery degradation model,and the reliability of batteries is modeled based on the Weibull distribution.Moreover,Conditional value at risk(CVaR)criterion is applied to evaluate the risk induced by intermittent renewable power output,load demand variation and SLBs failure probability.Simulation tests demonstrate the effectiveness of the proposed method.展开更多
The accelerated arriving of 5G era has brought a new round of intelligent transformation which will completely emancipate smart terminal devices.While the subsequent deleterious effect of electromagnetic wave on elect...The accelerated arriving of 5G era has brought a new round of intelligent transformation which will completely emancipate smart terminal devices.While the subsequent deleterious effect of electromagnetic wave on electronic devices is increasingly serious,driving the growth of next-generation electromagnetic wave absorbents.As a tactful combination of components and structures,three-dimensional(3D)macroscopic absorbents with fascinating synergy afford exceptional electromagnetic wave absorption,and tremendous efforts have been devoted to this investigation.However,in terms of macroscopic absorbents and their synergistic effect,few reviews are proposed to comb the latest achievements and detailed synergy.This review article focuses on the synergistic effect of macro-architectured absorbents mainly including structure-induced synergy,structure-components synergy,and multiple-components induced synergy.And then the potential construction principles and strategies of macroscopic absorbents are combed.Significantly,the key information for structures and components manipulation including nano-micro design and components regulation is further dissected by critically selected cutting-edge 3D macroscopic absorbents.Moreover,a brief summary of multifunctional electromagnetic wave absorbents(EWAs)-based macroscopic structures is presented.Finally,the development prospects and challenges of these materials are discussed.展开更多
To overcome the shortcomings of model-driven state estimation methods, this paper proposes a data-driven robust state estimation (DDSE) method through off-line learning and on-line matching. At the off-line learning s...To overcome the shortcomings of model-driven state estimation methods, this paper proposes a data-driven robust state estimation (DDSE) method through off-line learning and on-line matching. At the off-line learning stage, a linear regression equation is presented by clustering historical data from supervisory control and data acquisition (SCADA), which provides a guarantee for solving the over-learning problem of the existing DDSE methods;then a novel robust state estimation method that can be transformed into quadratic programming (QP) models is proposed to obtain the mapping relationship between the measurements and the state variables (MRBMS). The proposed QP models can well solve the problem of collinearity in historical data. Furthermore, the off-line learning stage is greatly accelerated from three aspects including reducing historical categories, constructing tree retrieval structure for known topologies, and using sensitivity analysis when solving QP models. At the on-line matching stage, by quickly matching the current snapshot with the historical ones, the corresponding MRBMS can be obtained, and then the estimation values of the state variables can be obtained. Simulations demonstrate that the proposed DDSE method has obvious advantages in terms of suppressing over-learning problems, dealing with collinearity problems, robustness, and computation efficiency.展开更多
The fabrication of high-performance electromagnetic(EM)wave absorption(EMA)materials is an effective strategy to deal with ever-increasing EM pollution.In this work,a series of manganese oxides/porous carbon(Mn_(x)O_(...The fabrication of high-performance electromagnetic(EM)wave absorption(EMA)materials is an effective strategy to deal with ever-increasing EM pollution.In this work,a series of manganese oxides/porous carbon(Mn_(x)O_(y)@C)hybrid composites are obtained by a two-step process.It is revealed that different manganese oxides play various influence on the dielectric properties of absorbers.Owing to the moderate complex permittivity of MnO@C hybrid composites,the optimal reflection loss could reach as high as-76.0 dB at the matching thickness of 2.0 mm with 5.2 GHz of effective absorption bandwidth at thickness of 2.1 mm.We demonstrated that the addition of porous carbon is vital for enhancing EMA performance of composites,which not only coordinates impedance matching allowing more EM waves enter the absorber,but also provides the path for electron movement,thus profiting conductive loss.Besides,different heterogeneous interfaces including porous carbon,manganese oxide and so on,are conducive to contribution of interface polarization.The most noteworthy is ingenious design of composite materials and systematic research of EM energy attenuation mechanism in this work will provide the possibility to realize high-performance EMA.展开更多
We present a simple and customizable microneedle mold fabrication technique using a low-cost desktop SLA 3D printer.As opposed to conventional microneedle fabrication methods,this technique neither requires complex an...We present a simple and customizable microneedle mold fabrication technique using a low-cost desktop SLA 3D printer.As opposed to conventional microneedle fabrication methods,this technique neither requires complex and expensive manufacturing facilities nor expertise in microfabrication.While most low-cost 3D-printed microneedles to date display low aspect ratios and poor tip sharpness,we show that by introducing a two-step“Print&Fill”mold fabrication method,it is possible to obtain high-aspect ratio sharp needles that are capable of penetrating tissue.Studying first the effect of varying design input parameters and print settings,it is shown that printed needles are always shorter than specified.With decreasing input height,needles also begin displaying an increasingly greater than specified needle base diameter.Both factors contribute to low aspect ratio needles when attempting to print submillimeter height needles.By setting input height tall enough,it is possible to print needles with high-aspect ratios and tip radii of 20–40μm.This tip sharpness is smaller than the specified printer resolution.Consequently,high-aspect ratio sharp needle arrays are printed in basins which are backfilled and cured in a second step,leaving sub-millimeter microneedles exposed resulting microneedle arrays which can be used as male masters.Silicone female master molds are then formed from the fabricated microneedle arrays.Using the molds,both carboxymethyl cellulose loaded with rhodamine B as well as polylactic acid microneedle arrays are produced and their quality examined.A skin insertion study is performed to demonstrate the functional capabilities of arrays made from the fabricated molds.This method can be easily adopted by the microneedle research community for in-house master mold fabrication and parametric optimization of microneedle arrays.展开更多
Pantograph‐catenary arc fault is the primary factor threatening the stability of the power transmission for high‐speed railway.The motion characteristics of the pantograph‐catenary arc under low air pressure and st...Pantograph‐catenary arc fault is the primary factor threatening the stability of the power transmission for high‐speed railway.The motion characteristics of the pantograph‐catenary arc under low air pressure and strong airflow is significantly different from the case under atmospheric pressure.In this paper,an experimental platform of panto-graph‐catenary arc was built to investigate arc root position‐time and arc column lon-gitudinal drift height‐time characteristic curves under different air pressures and airflow velocites.Via analysing the corresponding results,it can be found that there are different arc root-arc column traction mechanisms at different stages of arc development.The arcing time and arc root stagnation time under low air pressure are significantly longer than the case under atmospheric pressure,resulting in more serious electrode ablation.The arc column longitudinal drift velocity and height are greater with the increase of airflow velocity.Two typical irregular arc motion phenomena-arc root jumping and arc reignition are observed.To clarify the internal mechanism of the above phenomenon,a magnetohydrodynamics(MHD)model of the pantograph‐catenary arc was lauched,the influence mechanism of the pantograph‐catenary arc temperature and voltage are studied,and the physical process of arc temperature oscillation is analysed.The research results provide theoretical support for arc protection in high‐altitude areas.展开更多
基金This work was supported by the Basic Science Research Program of Shaanxi Province(2023-JC-YB-057 and 2022JM-031).
文摘The conventional zenith tropospheric delay(ZTD)model(known as the Saastamoinen model)does not consider seasonal variations affecting the delay,giving it low accuracy and stability.This may be improved with adjustments to account for annual and semi-annual variations.This method uses ZTD data provided by the Global Geodetic Observing System to analyze seasonal variations in the bias of the Saastamoinen model in Asia,and then constructs a model with seasonal variation corrections,denoted as SSA.To overcome the dependence of the model on in-situ meteorological parameters,the SSA+GPT3 model is formed by combining the SSA and GPT3(global pressure-temperature)models.The results show that the introduction of annual and semi-annual variations can substantially improve the Saastamoinen model,yielding small and time-stable variations in bias and root mean square(RMS).In summer and autumn,the bias and RMS are noticeably smaller than those from the Saastamoinen model.In addition,the SSA model performs better in low-latitude and low-altitude areas,and bias and RMS decease with the increase of latitude or altitude.The prediction accuracy of the SSA model is also evaluated for external consistency.The results show that the accuracy of the SSA model(bias:-0.38 cm,RMS:4.43 cm)is better than that of the Saastamoinen model(bias:1.45 cm,RMS:5.16 cm).The proposed method has strong applicability and can therefore be used for predictive ZTD correction across Asia.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.60871073,60971064,and 51005001)the Open Program of the State Key Laboratory of Millimeter Wave of China(Grant No.K201006)+1 种基金the Special Funds for the Technological and Innovative Talent of Harbin City,China(Grant No.2010RFXXG010)the Youth Foundation of Harbin University of Science and Technology,China(Grant Nos.2009YF025 and 2009YF024)
文摘An analytical solution is presented for the electromagnetic scattering from an infinite-length metallic carbon nanotube and a carbon nanotube bundle.The scattering field and scattering cross section are predicted using a modal technique based on a Bessel and Hankel function for the electric line source and a quantum conductance function for the carbon nanotube.For the particular case of an isolated armchair (10,10) carbon nanotube,the scattered field predicted from this technique is in excellent agreement with the measured result.Furthermore,the analysis indicates that the scattering pattern of an isolated carbon nanotube differs from that of the carbon nanotube bundle of identical index (m,n) metallic carbon nanotubes.
基金Agency for Science,Technology and Research(A^*STAR)Singapore through the X-ray Photonics Programme(1426500052)A^*STAR Graduate Academy through the A^*STAR Graduate Scholarship.
文摘We report the generation of high energy 2μm picosecond pulses from a thulium-doped fiber master oscillator power amplifier system.The all-fiber configuration was realized by a flexible large-mode area photonic crystal fiber(LMA-PCF).The amplifier output is a linearly-polarized 1.5 ns,100 kHz pulse train with a pulse energy of up to 250μJ.Pulse compression was achieved with(2+2)-pass chirped volume Bragg grating(CVBG)to obtain a 2.8 ps pulse width with a total pulse energy of 46μJ.The overall system compactness was enabled by the all-fiber amplifier design and the multi-pass CVBG-based compressor.The laser output was then used to demonstrate high-speed direct-writing capability on a temperature-sensitive biomaterial to change its topography(i.e.fabricate microchannels,foams and pores).The topographical modifications of biomaterials are known to influence cell behavior and fate which is potentially useful in many cell and tissue engineering applications.
基金Funded by the National Basic Research Program of China (973 Program, 2009CB939704)the NSFC (No. 10905043, 11005082, 11004052)+4 种基金the Specialized Research Fund for the Doctoral Program of Higher Education (20100141120042, 20110141130004)the Foundations from Chinese Ministry of Education (311003)the Open Research Fund of State Key Laboratory of Electronic Thin Films and Integrated Devices (UESTC) (KFJJ201004)Young Chenguang Project of Wuhan City (201050231055)the Fundamental Research Funds for the Central Universities, Hubei Provincial Natural Science Foundation(2011CDB270)
文摘TiO2 thin films were deposited on quartz substrates by DC reactive magnetron sputtering of a pure Ti target in Ar/O2 plasma at room temperature. The TiO2 films were annealed at different temperatures ranging from 300 to 800 °C in a tube furnace under flowing oxygen gas for half an hour each. The effect of annealing temperatures on the structure, optical properties, and morphologies were presented and discussed by using X-ray diffraction, optical absorption spectrum, and atomic force microscope. The films show the presence of diffraction peaks from the (101), (004), (200) and (105) lattice planes of the anatase TiO2 lattice. The direct band gap of the annealed films decreases with the increase of annealing temperature. While, the roughness of the films increases with the increases of annealing temperature, and some significant roughness changes of the TiO2 film surfaces were observed after the annealing temperature reached 800 °C. Moreover, the influences of annealing on the microstructures of the TiO2 film were investigated also by in situ observation in transmission electron microscope.
基金funded by Geran Galakan Penyelidik Muda GGPM-2020-004 Universiti Kebangsaan Malaysia.
文摘Grid-connected reactive-load compensation and harmonic control are becoming a central topic as photovoltaic(PV)grid-connected systems diversified.This research aims to produce a high-performance inverter with a fast dynamic response for accurate reference tracking and a low total har-monic distortion(THD)even under nonlinear load applications by improving its control scheme.The proposed system is expected to operate in both stand-alone mode and grid-connected mode.In stand-alone mode,the proposed controller supplies power to critical loads,alternatively during grid-connected mode provide excess energy to the utility.A modified variable step incremental conductance(VS-InCond)algorithm is designed to extract maximum power from PV.Whereas the proposed inverter controller is achieved by using a modified PQ theory with double-band hysteresis current controller(PQ-DBHCC)to produce a reference current based on a decomposition of a single-phase load current.The nonlinear rectifier loads often create significant distortion in the output voltage of single-phase inverters,due to excessive current harmonics in the grid.Therefore,the proposed method generates a close-loop reference current for the switching scheme,hence,minimizing the inverter voltage distortion caused by the excessive grid current harmonics.The simulation findings suggest the proposed control technique can effectively yield more than 97%of power conversion efficiency while suppressing the grid current THD by less than 2%and maintaining the unity power factor at the grid side.The efficacy of the proposed controller is simulated using MATLAB/Simulink.
文摘We propose to perform an image-based framework for electrical energy meter reading.Our aim is to extract the image region that depicts the digits and then recognize them to record the consumed units.Combining the readings of serial numbers and energy meter units,an automatic billing system using the Internet of Things and a graphical user interface is deployable in a real-time setup.However,such region extraction and character recognition become challenging due to image variations caused by several factors such as partial occlusion due to dust on the meter display,orientation and scale variations caused by camera positioning,and non-uniform illumination caused by shades.To this end,our work evaluates and compares the stateof-the art deep learning algorithm You Only Look Once(YOLO)along with traditional handcrafted features for text extraction and recognition.Our image dataset contains 10,000 images of electrical energymeters and is further expanded by data augmentation such as in-plane rotation and scaling tomake the deep learning algorithms robust to these image variations.For training and evaluation,the image dataset is annotated to produce the ground truth of all the images.Consequently,YOLO achieves superior performance over the traditional handcrafted features with an average recognition rate of 98%for all the digits.It proves to be robust against the mentioned image variations compared with the traditional handcrafted features.Our proposed method can be highly instrumental in reducing the time and effort involved in the currentmeter reading,where workers visit door to door,take images ofmeters and manually extract readings from these images.
文摘This paper presents a novel approach for tire-pattern classification,aimed at conducting forensic analysis on tire marks discovered at crime scenes.The classification model proposed in this study accounts for the intricate and dynamic nature of tire prints found in real-world scenarios,including accident sites.To address this complexity,the classifier model was developed to harness the meta-learning capabilities of few-shot learning algorithms(learning-to-learn).The model is meticulously designed and optimized to effectively classify both tire patterns exhibited on wheels and tire-indentation marks visible on surfaces due to friction.This is achieved by employing a semantic segmentation model to extract the tire pattern marks within the image.These marks are subsequently used as a mask channel,combined with the original image,and fed into the classifier to perform classification.Overall,The proposed model follows a three-step process:(i)the Bilateral Segmentation Network is employed to derive the semantic segmentation of the tire pattern within a given image.(ii)utilizing the semantic image in conjunction with the original image,the model learns and clusters groups to generate vectors that define the relative position of the image in the test set.(iii)the model performs predictions based on these learned features.Empirical verification demonstrates usage of semantic model to extract the tire patterns before performing classification increases the overall accuracy of classification by∼4%.
文摘The development of Vehicular Ad-hoc Network(VANET)technology is helping Intelligent Transportation System(ITS)services to become a reality.Vehicles can use VANETs to communicate safety messages on the road(while driving)and can inform their location and share road condition information in real-time.However,intentional and unintentional(e.g.,packet/frame collision)wireless signal jamming can occur,which will degrade the quality of communication over the channel,preventing the reception of safety messages,and thereby posing a safety hazard to the vehicle’s passengers.In this paper,VANET jamming detection applying Support Vector Machine(SVM)machine learning technology is used to classify jamming and non-jamming situations.The analysis is based on two cases which include normal traffic and heavy traffic conditions,where the results show that the probability of packet dropping will increase when many vehicles are using the wireless channel simultaneously.When using SVM classification,the most appropriate feature set applied in determining a jamming situation shows an accuracy of 98%or higher.Furthermore,more advanced jamming attacks need to be considered for preparation of more reliable and safer autonomous ITS services.Such research can use vehicular communication transmission and reception data based on selected published datasets.In this paper,an additional adversarial defense algorithm using the Density-Based Spatial Clustering of Applications with Noise(DBSCAN)method is proposed,which assumes that evolutionary attacks of the jammer will attempt to confuse the trained classifier.The simulation results show that applying DBSCAN can improve the accuracy by elimination of outliers before conducting classification testing.
文摘As a representative of chain-based protocol in Wireless Sensor Networks (WSNs), EEPB is an elegant solution on energy efficiency. However, in the latter part of the operation of the network, there is still a big problem: reserving energy of the node frequently presents the incapacity of directly communicating with the base station, at the same time capacity of data acquisition and transmission as normal nodes. If these nodes were selected as LEADER nodes, that will accelerate the death process and unevenness of energy consumption distribution among nodes.This paper proposed a chain routing algorithm based ontraffic prediction model (CRTP).The novel algorithmdesigns a threshold judgment method through introducing the traffic prediction model in the process of election of LEADER node. The process can be dynamically adjusted according to the flow forecasting. Therefore, this algorithm lets the energy consumption tend-ing to keep at same level. Simulation results show that CRTP has superior performance over EEPB in terms of balanced network energy consumption and the prolonged network life.
基金the National Natural Science Foundation of China(Grant No.51607158)the Key Scientific Technological Project in Henan Province(Grant No.192102210075)。
文摘HVDC auxiliary power control can significantly improve the transient stability of AC/DC power grid.An HVDC adaptive emergency power support method based on unbalanced power on line estimation is proposed in this paper.By establishing the extended state equation of the system,the on line dynamic estimation of unbalanced power of the system was realized.On this basis,power support was realized based on the principle of the ladder increment.The optimal DC was selected by the power support factor,and the emergency power support controller was installed on the DC.This emergency power support method can realize dynamic optimal power support with minimized control cost.The three infeed HVDC system was built on PSCAD.The simulation results show the effectiveness of the proposed method.
基金This work was supported by the Ministry of Higher Education Malaysia for Fundamental Research Grant Scheme with Project Code:FRGS/1/2021/TK0/USM/02/18.
文摘A single-channel electroencephalography(EEG)device,despite being widely accepted due to convenience,ease of deployment and suitability for use in complex environments,typically poses a great challenge for reactive brain-computer interface(BCI)applications particularly when a continuous command from users is desired to run a motorized actuator with different speed profiles.In this study,a combination of an inconspicuous visual stimulus and voluntary eyeblinks along with a machine learning-based decoder is considered as a new reactive BCI paradigm to increase the degree of freedom and minimize mismatches between the intended dynamic command and transmitted control signal.The proposed decoder is constructed based on Gaussian Process model(GPM)which is a nonparametric Bayesian approach that has the advantages of being able to operate on small datasets and providing measurements of uncertainty on predictions.To evaluate the effectiveness of the proposed method,the GPM is compared against other competitive techniques which include k-Nearest Neighbors,linear discriminant analysis,support vector machine,ensemble learning and neural network.Results demonstrate that a significant improvement can be achieved via the GPM approach with average accuracy reaching over 96%and mean absolute error of no greater than 0.8 cm/s.In addition,the analysis reveals that while the performances of other existing methods deteriorate with a certain type of stimulus due to signal drifts resulting from the voluntary eyeblinks,the proposed GPM exhibits consistent performance across all stimuli considered,thereby manifesting its generalization capability and making it a more suitable option for dynamic commands with a single-channel EEG-controlled actuator.
基金Sponsored by the Key Science Fund of Tianjin (Grant No. 023801211)
文摘A novel numerical algorithm for fault location estimation of single-phase-to-earth fault on EHV transmission lines is presented in this paper. The method is based on one-terminal voltage and current data and is used in a procedure that provides the automatic determination of faulted types and phases, rather than requires engineer to specify them. The loop and nodal equations comparing the faulted phase to non-faulted phases of multi-parallel lines are introduced in the fault location estimation models, in which source impedance of remote end is not involved. Precise algorithms of locating fault are derived. The effect of load flow and fault resistance,on the location accuracy, are effectively eliminated. The algorithms are demonstrated by digital computer simulations.
基金This work is supported by Climate Change Institute,Universiti Kebangsaan Malaysia.
文摘The paper proposes an Indoor Localization System(ILS)which uses only one fixed Base Station(BS)with simple non-reconfigurable antennas.The proposed algorithm measures Received Signal Strength(RSS)and maps it to the location in the room by estimating signal strength of a direct line of sight(LOS)signal and signal of the first order reflection from the wall.The algorithm is evaluated through both simulations and empirical measurements in a furnished open space office,sampling 21 different locations in the room.It is demonstrated the system can identify user’s real-time location with a maximum estimation error below 0.7 m for 80%confidence Cumulative Distribution Function(CDF)user level,demonstrating the ability to accurately estimate the receiver’s location within the room.The system is intended as a cost-efficient indoor localization technique,offering simplicity and easy integration with existing wireless communication systems.Unlike comparable single base station localization techniques,the proposed system does not require beam scanning,offering stable communication capacity while performing the localization process.
基金supported in part by the National Natural Science Foundation of China (NO.52278003 and NO.72171026)in part by the National Natural Science Foundation of Hunan province (NO.21A0217)。
文摘With the growing adoption of Electrical Vehicles(EVs),it is expected that a large number of on-board Li-ion batteries will be retired from EVs in the near future.Retired batteries will typically retain 80%of their initial capacities and can be recycled as second life batteries(SLBs).Although the capital costs of SLBs are much cheaper,their operational reliability is an important concern since used batteries may suffer from a higher failure rate.This paper aggregates brand new batteries and SLBs together to improve power system’s operating performance with renewable energy resources.In the context of a day-ahead and intra-day dispatch framework,a two-stage coordinated optimal scheduling method is proposed.Specifically,the energy cost of brand-new batteries and SLBs is calculated based on detailed battery degradation model,and the reliability of batteries is modeled based on the Weibull distribution.Moreover,Conditional value at risk(CVaR)criterion is applied to evaluate the risk induced by intermittent renewable power output,load demand variation and SLBs failure probability.Simulation tests demonstrate the effectiveness of the proposed method.
基金supported by the National Natural Science Foundation of China(No.52274362)the Doctorial Foundation of Henan University of Technology(Nos.2021BS030 and 2020BS030)+5 种基金the Key R&D projects of Henan Province(No.221111230800)the Innovative Funds Plan of Henan University of Technology(No.2021ZKCJ05)the Key Scientific and Technological Research Projects in Henan Province(No.222102240091)the Natural Science Foundation from the Department of Science and Technology of Henan Province(No.232300420309)the Taishan Scholars and Young Experts Program of Shandong Province(No.tsqn202103057)the Key Laboratory of Engineering Dielectrics and Its Application(Harbin University of Science and Technology),Ministry of Education.
文摘The accelerated arriving of 5G era has brought a new round of intelligent transformation which will completely emancipate smart terminal devices.While the subsequent deleterious effect of electromagnetic wave on electronic devices is increasingly serious,driving the growth of next-generation electromagnetic wave absorbents.As a tactful combination of components and structures,three-dimensional(3D)macroscopic absorbents with fascinating synergy afford exceptional electromagnetic wave absorption,and tremendous efforts have been devoted to this investigation.However,in terms of macroscopic absorbents and their synergistic effect,few reviews are proposed to comb the latest achievements and detailed synergy.This review article focuses on the synergistic effect of macro-architectured absorbents mainly including structure-induced synergy,structure-components synergy,and multiple-components induced synergy.And then the potential construction principles and strategies of macroscopic absorbents are combed.Significantly,the key information for structures and components manipulation including nano-micro design and components regulation is further dissected by critically selected cutting-edge 3D macroscopic absorbents.Moreover,a brief summary of multifunctional electromagnetic wave absorbents(EWAs)-based macroscopic structures is presented.Finally,the development prospects and challenges of these materials are discussed.
基金This work was supported in part by National Natural Science Foundation of China(No.52077076)in part by the State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources(No.LAPS2021-18).
文摘To overcome the shortcomings of model-driven state estimation methods, this paper proposes a data-driven robust state estimation (DDSE) method through off-line learning and on-line matching. At the off-line learning stage, a linear regression equation is presented by clustering historical data from supervisory control and data acquisition (SCADA), which provides a guarantee for solving the over-learning problem of the existing DDSE methods;then a novel robust state estimation method that can be transformed into quadratic programming (QP) models is proposed to obtain the mapping relationship between the measurements and the state variables (MRBMS). The proposed QP models can well solve the problem of collinearity in historical data. Furthermore, the off-line learning stage is greatly accelerated from three aspects including reducing historical categories, constructing tree retrieval structure for known topologies, and using sensitivity analysis when solving QP models. At the on-line matching stage, by quickly matching the current snapshot with the historical ones, the corresponding MRBMS can be obtained, and then the estimation values of the state variables can be obtained. Simulations demonstrate that the proposed DDSE method has obvious advantages in terms of suppressing over-learning problems, dealing with collinearity problems, robustness, and computation efficiency.
基金financially supported by the National Natural Science Foundation of China(No.51407134)Natural Science Foundation of Shandong Province(No.ZR2019YQ24)+9 种基金Taishan Scholars and Young Experts Program of Shandong Province(No.tsqn202103057)China Postdoctoral Science Foundation(No.2016M590619)Natural Science Foundation of Heilongjiang Province(ZD2020E009)Key Laboratory of Engineering Dielectrics and Its Application(Harbin University of Science and Technology),Ministry of Education(No.KFZ1803)the Qingchuang Talents Induction Program of Shandong Higher Education Institution(Research and Innovation Team of Structural-Functional Polymer Composites)the support from The Thousand Talents PlanThe World-Class University and DisciplineThe Taishan Scholar’s AdvantageousDistinctive Discipline Program of Shandong ProvinceThe World-Class Discipline Program of Shandong Province。
文摘The fabrication of high-performance electromagnetic(EM)wave absorption(EMA)materials is an effective strategy to deal with ever-increasing EM pollution.In this work,a series of manganese oxides/porous carbon(Mn_(x)O_(y)@C)hybrid composites are obtained by a two-step process.It is revealed that different manganese oxides play various influence on the dielectric properties of absorbers.Owing to the moderate complex permittivity of MnO@C hybrid composites,the optimal reflection loss could reach as high as-76.0 dB at the matching thickness of 2.0 mm with 5.2 GHz of effective absorption bandwidth at thickness of 2.1 mm.We demonstrated that the addition of porous carbon is vital for enhancing EMA performance of composites,which not only coordinates impedance matching allowing more EM waves enter the absorber,but also provides the path for electron movement,thus profiting conductive loss.Besides,different heterogeneous interfaces including porous carbon,manganese oxide and so on,are conducive to contribution of interface polarization.The most noteworthy is ingenious design of composite materials and systematic research of EM energy attenuation mechanism in this work will provide the possibility to realize high-performance EMA.
基金This work has been funded through an Irish Research Council Postgraduate Scholarship,a National University of Ireland Travel Studentship,a Marie-Skłodowska-Curie Fellowship(H2020-MSCA-IF-2014/658761)Science Foundation Ireland and the European Regional Development Fund(grant agreement number:13/RC/2073).
文摘We present a simple and customizable microneedle mold fabrication technique using a low-cost desktop SLA 3D printer.As opposed to conventional microneedle fabrication methods,this technique neither requires complex and expensive manufacturing facilities nor expertise in microfabrication.While most low-cost 3D-printed microneedles to date display low aspect ratios and poor tip sharpness,we show that by introducing a two-step“Print&Fill”mold fabrication method,it is possible to obtain high-aspect ratio sharp needles that are capable of penetrating tissue.Studying first the effect of varying design input parameters and print settings,it is shown that printed needles are always shorter than specified.With decreasing input height,needles also begin displaying an increasingly greater than specified needle base diameter.Both factors contribute to low aspect ratio needles when attempting to print submillimeter height needles.By setting input height tall enough,it is possible to print needles with high-aspect ratios and tip radii of 20–40μm.This tip sharpness is smaller than the specified printer resolution.Consequently,high-aspect ratio sharp needle arrays are printed in basins which are backfilled and cured in a second step,leaving sub-millimeter microneedles exposed resulting microneedle arrays which can be used as male masters.Silicone female master molds are then formed from the fabricated microneedle arrays.Using the molds,both carboxymethyl cellulose loaded with rhodamine B as well as polylactic acid microneedle arrays are produced and their quality examined.A skin insertion study is performed to demonstrate the functional capabilities of arrays made from the fabricated molds.This method can be easily adopted by the microneedle research community for in-house master mold fabrication and parametric optimization of microneedle arrays.
文摘Pantograph‐catenary arc fault is the primary factor threatening the stability of the power transmission for high‐speed railway.The motion characteristics of the pantograph‐catenary arc under low air pressure and strong airflow is significantly different from the case under atmospheric pressure.In this paper,an experimental platform of panto-graph‐catenary arc was built to investigate arc root position‐time and arc column lon-gitudinal drift height‐time characteristic curves under different air pressures and airflow velocites.Via analysing the corresponding results,it can be found that there are different arc root-arc column traction mechanisms at different stages of arc development.The arcing time and arc root stagnation time under low air pressure are significantly longer than the case under atmospheric pressure,resulting in more serious electrode ablation.The arc column longitudinal drift velocity and height are greater with the increase of airflow velocity.Two typical irregular arc motion phenomena-arc root jumping and arc reignition are observed.To clarify the internal mechanism of the above phenomenon,a magnetohydrodynamics(MHD)model of the pantograph‐catenary arc was lauched,the influence mechanism of the pantograph‐catenary arc temperature and voltage are studied,and the physical process of arc temperature oscillation is analysed.The research results provide theoretical support for arc protection in high‐altitude areas.
