Weather forecasts from numerical weather prediction models play a central role in solar energy forecasting,where a cascade of physics-based models is used in a model chain approach to convert forecasts of solar irradi...Weather forecasts from numerical weather prediction models play a central role in solar energy forecasting,where a cascade of physics-based models is used in a model chain approach to convert forecasts of solar irradiance to solar power production.Ensemble simulations from such weather models aim to quantify uncertainty in the future development of the weather,and can be used to propagate this uncertainty through the model chain to generate probabilistic solar energy predictions.However,ensemble prediction systems are known to exhibit systematic errors,and thus require post-processing to obtain accurate and reliable probabilistic forecasts.The overarching aim of our study is to systematically evaluate different strategies to apply post-processing in model chain approaches with a specific focus on solar energy:not applying any post-processing at all;post-processing only the irradiance predictions before the conversion;post-processing only the solar power predictions obtained from the model chain;or applying post-processing in both steps.In a case study based on a benchmark dataset for the Jacumba solar plant in the U.S.,we develop statistical and machine learning methods for postprocessing ensemble predictions of global horizontal irradiance(GHI)and solar power generation.Further,we propose a neural-network-based model for direct solar power forecasting that bypasses the model chain.Our results indicate that postprocessing substantially improves the solar power generation forecasts,in particular when post-processing is applied to the power predictions.The machine learning methods for post-processing slightly outperform the statistical methods,and the direct forecasting approach performs comparably to the post-processing strategies.展开更多
In the present computational fluid dynamics （CFD） community, post-processing is regarded as a procedure to view parameter distribution, detect characteristic structure and reveal physical mechanism of fluid flow bas...In the present computational fluid dynamics （CFD） community, post-processing is regarded as a procedure to view parameter distribution, detect characteristic structure and reveal physical mechanism of fluid flow based on computational or experimental results. Field plots by contours, iso-surfaces, streamlines, vectors and others are traditional post-processing techniques. While the shock wave, as one important and critical flow structure in many aerodynamic problems, can hardly be detected or distinguished in a direct way using these traditional methods, due to possible confusions with other similar discontinuous flow structures like slip line, contact discontinuity, etc. Therefore, method for automatic detection of shock wave in post-processing is of great importance for both academic research and engineering applications. In this paper, the current status of methodologies developed for shock wave detection and implementations in post-processing platform are reviewed, as well as discussions on advantages and limitations of the existing methods and proposals for further studies of shock wave detection method. We also develop an advanced post-processing software, with improved shock detection.展开更多
Quantum random number generators adopting single negligible dead time of avalanche photodiodes （APDs） photon detection have been restricted due to the non- We propose a new approach based on an APD array to improve...Quantum random number generators adopting single negligible dead time of avalanche photodiodes （APDs） photon detection have been restricted due to the non- We propose a new approach based on an APD array to improve the generation rate of random numbers significantly. This method compares the detectors＇ responses to consecutive optical pulses and generates the random sequence. We implement a demonstration experiment to show its simplicity, compactness and scalability. The generated numbers are proved to be unbiased, post-processing free, ready to use, and their randomness is verified by using the national institute of standard technology statistical test suite. The random bit generation efficiency is as high as 32.8% and the potential generation rate adopting the 32× 32 APD array is up to tens of Gbits/s.展开更多
To improve the ability of detecting underwater targets under strong wideband interference environment,an efficient method of line spectrum extraction is proposed,which fully utilizes the feature of the target spectrum...To improve the ability of detecting underwater targets under strong wideband interference environment,an efficient method of line spectrum extraction is proposed,which fully utilizes the feature of the target spectrum that the high intense and stable line spectrum is superimposed on the wide continuous spectrum.This method modifies the traditional beam forming algorithm by calculating and fusing the beam forming results at multi-frequency band and multi-azimuth interval,showing an excellent way to extract the line spectrum when the interference and the target are not in the same azimuth interval simultaneously.Statistical efficiency of the estimated azimuth variance and corresponding power of the line spectrum band depends on the line spectra ratio(LSR)of the line spectrum.The change laws of the output signal to noise ratio(SNR)with the LSR,the input SNR,the integration time and the filtering bandwidth of different algorithms bring the selection principle of the critical LSR.As the basis,the detection gain of wideband energy integration and the narrowband line spectrum algorithm are theoretically analyzed.The simulation detection gain demonstrates a good match with the theoretical model.The application conditions of all methods are verified by the receiver operating characteristic(ROC)curve and experimental data from Qiandao Lake.In fact,combining the two methods for target detection reduces the missed detection rate.The proposed post-processing method in2-dimension with the Kalman filter in the time dimension and the background equalization algorithm in the azimuth dimension makes use of the strong correlation between adjacent frames,could further remove background fluctuation and improve the display effect.展开更多
The travel time data collection method is used to assist the congestion management. The use of traditional sensors (e.g. inductive loops, AVI sensors) or more recent Bluetooth sensors installed on major roads for coll...The travel time data collection method is used to assist the congestion management. The use of traditional sensors (e.g. inductive loops, AVI sensors) or more recent Bluetooth sensors installed on major roads for collecting data is not sufficient because of their limited coverage and expensive costs for installation and maintenance. Application of the Global Positioning Systems (GPS) in travel time and delay data collections is proven to be efficient in terms of accuracy, level of details for the data and required data collection of man-power. While data collection automation is improved by the GPS technique, human errors can easily find their way through the post-processing phase, and therefore data post-processing remains a challenge especially in case of big projects with high amount of data. This paper introduces a stand-alone post-processing tool called GPS Calculator, which provides an easy-to-use environment to carry out data post-processing. This is a Visual Basic application that processes the data files obtained in the field and integrates them into Geographic Information Systems (GIS) for analysis and representation. The results show that this tool obtains similar results to the currently used data post-processing method, reduces the post-processing effort, and also eliminates the need for the second person during the data collection.展开更多
When castings become complicated and the demands for precision of numerical simulation become higher,the numerical data of casting numerical simulation become more massive.On a general personal computer,these massive ...When castings become complicated and the demands for precision of numerical simulation become higher,the numerical data of casting numerical simulation become more massive.On a general personal computer,these massive numerical data may probably exceed the capacity of available memory,resulting in failure of rendering.Based on the out-of-core technique,this paper proposes a method to effectively utilize external storage and reduce memory usage dramatically,so as to solve the problem of insufficient memory for massive data rendering on general personal computers.Based on this method,a new postprocessor is developed.It is capable to illustrate filling and solidification processes of casting,as well as thermal stess.The new post-processor also provides fast interaction to simulation results.Theoretical analysis as well as several practical examples prove that the memory usage and loading time of the post-processor are independent of the size of the relevant files,but the proportion of the number of cells on surface.Meanwhile,the speed of rendering and fetching of value from the mouse is appreciable,and the demands of real-time and interaction are satisfied.展开更多
In order to carry out numerical simulation using geologic structural data obtained from Landmark(seismic interpretation system), underground geological structures are abstracted into mechanical models which can reflec...In order to carry out numerical simulation using geologic structural data obtained from Landmark(seismic interpretation system), underground geological structures are abstracted into mechanical models which can reflect actual situations and facilitate their computation and analyses.Given the importance of model building, further processing methods about traditional seismic interpretation results from Landmark should be studied and the processed result can then be directly used in numerical simulation computations.Through this data conversion procedure, Landmark and FLAC(the international general stress software) are seamlessly connected.Thus, the format conversion between the two systems and the pre-and post-processing in simulation computation is realized.A practical application indicates that this method has many advantages such as simple operation, high accuracy of the element subdivision and high speed, which may definitely satisfy the actual needs of floor grid cutting.展开更多
Low contrast of Magnetic Resonance(MR)images limits the visibility of subtle structures and adversely affects the outcome of both subjective and automated diagnosis.State-of-the-art contrast boosting techniques intole...Low contrast of Magnetic Resonance(MR)images limits the visibility of subtle structures and adversely affects the outcome of both subjective and automated diagnosis.State-of-the-art contrast boosting techniques intolerably alter inherent features of MR images.Drastic changes in brightness features,induced by post-processing are not appreciated in medical imaging as the grey level values have certain diagnostic meanings.To overcome these issues this paper proposes an algorithm that enhance the contrast of MR images while preserving the underlying features as well.This method termed as Power-law and Logarithmic Modification-based Histogram Equalization(PLMHE)partitions the histogram of the image into two sub histograms after a power-law transformation and a log compression.After a modification intended for improving the dispersion of the sub-histograms and subsequent normalization,cumulative histograms are computed.Enhanced grey level values are computed from the resultant cumulative histograms.The performance of the PLMHE algorithm is comparedwith traditional histogram equalization based algorithms and it has been observed from the results that PLMHE can boost the image contrast without causing dynamic range compression,a significant change in mean brightness,and contrast-overshoot.展开更多
This paper proposed improvements to the low bit rate parametric audio coder with sinusoid model as its kernel. Firstly, we propose a new method to effectively order and select the perceptually most important sinusoids...This paper proposed improvements to the low bit rate parametric audio coder with sinusoid model as its kernel. Firstly, we propose a new method to effectively order and select the perceptually most important sinusoids. The sinusoid which contributes most to the reduction of overall NMR is chosen. Combined with our improved parametric psychoacoustic model and advanced peak riddling techniques, the number of sinusoids required can be greatly reduced and the coding efficiency can be greatly enhanced. A lightweight version is also given to reduce the amount of computation with only little sacrifice of performance. Secondly, we propose two enhancement techniques for sinusoid synthesis: bandwidth enhancement and line enhancement. With little overhead, the effective bandwidth can be extended one more octave; the timbre tends to sound much brighter, thicker and more beautiful.展开更多
In the analysis of high-rise building, traditional displacement-based plane elements are often used to get the in-plane internal forces of the shear walls by stress integration. Limited by the singular problem produce...In the analysis of high-rise building, traditional displacement-based plane elements are often used to get the in-plane internal forces of the shear walls by stress integration. Limited by the singular problem produced by wall holes and the loss of precision induced by using differential method to derive strains, the displacement-based elements cannot always present accuracy enough for design. In this paper, the hybrid post-processing procedure based on the Hellinger-Reissner variational principle is used for improving the stress precision of two quadrilateral plane elements. In order to find the best stress field, three different forms are assumed for the displacement-based plane elements and with drilling DOF. Numerical results show that by using the proposed method, the accuracy of stress solutions of these two displacement-based plane elements can be improved.展开更多
Laser additive manufacturing(LAM)of titanium(Ti)alloys has emerged as a transformative technology with vast potential across multiple industries.To recap the state of the art,Ti alloys processed by two essential LAM t...Laser additive manufacturing(LAM)of titanium(Ti)alloys has emerged as a transformative technology with vast potential across multiple industries.To recap the state of the art,Ti alloys processed by two essential LAM techniques(i.e.,laser powder bed fusion and laser-directed energy deposition)will be reviewed,covering the aspects of processes,materials and post-processing.The impacts of process parameters and strategies for optimizing parameters will be elucidated.Various types of Ti alloys processed by LAM,includingα-Ti,(α+β)-Ti,andβ-Ti alloys,will be overviewed in terms of micro structures and benchmarking properties.Furthermore,the post-processing methods for improving the performance of L AM-processed Ti alloys,including conventional and novel heat treatment,hot isostatic pressing,and surface processing(e.g.,ultrasonic and laser shot peening),will be systematically reviewed and discussed.The review summarizes the process windows,properties,and performance envelopes and benchmarks the research achievements in LAM of Ti alloys.The outlooks of further trends in LAM of Ti alloys are also highlighted at the end of the review.This comprehensive review could serve as a valuable resource for researchers and practitioners,promoting further advancements in LAM-built Ti alloys and their applications.展开更多
Developing reliable weather prediction systems is still a challenging task due to the complexity of the Earth System and the chaotic behavior of its compo-nents.Small errors introduced by observations,their assimilati...Developing reliable weather prediction systems is still a challenging task due to the complexity of the Earth System and the chaotic behavior of its compo-nents.Small errors introduced by observations,their assimilation and the forecast model configuration escalate chaotically,leading to a significant loss in forecast skill with time.Traditionally,rainfall forecasts have been generated at grid-based spatial resolutions,providing valuable information on regional precipitation patterns.However,Weather varies markedly within a grid box and forecasts for specific sites have occasionally failed inevitably.The grid-based forecasts may not always meet the needs of decision-makers at specific points of interest.The major challenge is dealing with variations in sub-grid variability,that is to say,the variation seen amongst rainfall point values within a given model grid box,more especially in convective situations.While ensemble forecasts have shown promise in capturing the uncertainty inherent in average rainfall predictions of much larger grid boxes,their utility at point locations has not been extensively explored.Most evaluation studies focus on grid-based verification metrics,which may not accurately reflect forecast per-formance at individual points of interest.EcPoint,a post-processing approach developed at the European Centre for Medium Range Forecasts(ECMWF),is tailored to forecast rainfall at point locations.In this study,we evaluate the performance of the EcPoint post-processing method over the south China re-gion.The analysis focuses on the reliability,accuracy and discrimination skill of this post-processing method over the three provinces in south China(An-hui,Zhejiang and Jiangsu).We examine performance versus lead time,sea-sons,and altitude.Through verifications,the study highlighted the added value of the post-processing method over Raw ensemble forecasts.One year of verification demonstrates that,between the Raw ensemble and post-pro-cessed EcPoint forecasts,EcPoint is the more reliable and skillful system,add-ing significant value to most rainfall events occurring during the day and the seasonal associated events,as well as the topography-associated rainfall events.To complement the one-year verification analysis,a case study was conducted on an extremely heavy rainfall event observed on June 2,2022 at 12 UTC.The analysis demonstrated EcPoint’s ability to provide more localized and refined forecasts whereas Raw didn’t provide any possibility of rainfall,particularly at short lead times.At longer lead times,EcPoint ensembles maintained rela-tively low probabilities,but offered improved performance in capturing rain-fall variability,while Raw ensemble exhibited broader but less precise rainfall predictions with a tendency of over warning of some areas.Future work can extend the evaluation to more diverse climatic and topographic regions of China to enhance the general applicability of the method.Although based solely on the global ECMWF-IFS model,EcPoint performs well over the small domain of south China(three provinces).Besides verifying EcPoint,the study confirms that the post-processing method can significantly improve the fore-cast performance.展开更多
Metal halide perovskites have become one of the most competitive new-generation optoelectronic materials due to their excellent optoelectronic properties. Vacuum evaporation can produce high-purity and large-area film...Metal halide perovskites have become one of the most competitive new-generation optoelectronic materials due to their excellent optoelectronic properties. Vacuum evaporation can produce high-purity and large-area films, leading to the wide application of this method in the semiconductor industry and optoelectronics field. However, the electroluminescent performance of vacuum-evaporated perovskite light-emitting diodes(PeLEDs) still lags behind those counterparts fabricated by solution methods. Herein, based on vacuum evaporation, 3D perovskite films are obtained by three-source co-evaporation.Considering the unique quantum well structure of quasi-2D perovskite can significantly enhance the exciton binding energy and improve the radiative recombination rate, leading to a high photoluminescence quantum yield(PLQY). Subsequently,the highly stable and low-defect-density quasi-2D perovskite is introduced into 3D perovskite films through post-treatment with phenethylammonium chloride(PEACl). To minimize the degradation of film quality caused by PEACl treatment, a layer of guanidinium bromide(GABr) is vacuum evaporated on top of PEACl treatment to further improve the quality of emitting layer. Finally, under the synergistic post-processing modification of PEACl and GABr, blue PeLEDs with a maximum external quantum efficiency(EQE) of 6.09% and a maximum brightness of 1325 cd/m^(2) are successfully obtained. This work deepens the understanding of 2D/3D heterojunctions and provides a new approach to construct PeLEDs with high performance.展开更多
The laser shock processing implemented by a laser-induced high-pressure plasma which propagates into the sample as a shockwave is innovatively applied as a post-processing technique on HfO_(2)/SiO_(2) multilayer coati...The laser shock processing implemented by a laser-induced high-pressure plasma which propagates into the sample as a shockwave is innovatively applied as a post-processing technique on HfO_(2)/SiO_(2) multilayer coatings for the first time.The pure mechanical post-processing has provided evidence of a considerable promotion effect of the laser-induced damage threshold,which increased by a factor of about 4.6 with appropriate processing parameters.The promotion mechanism is confirmed to be the comprehensive modification of the intrinsic defects and the mechanical properties,which made the applicability of this novel post-processing technique on various types of coatings possible.Based on experiments,an interaction equation for the plasma pressure is established,which clarifies the existence of the critical pressure and provides a theoretical basis for selecting optimal processing parameters.In addition to the further clarification of the underlying damage mechanism,the laser shock post-processing provides a promising technique to realize the comprehensive and effective improvement of the laser-induced damage resistance of coatings.展开更多
A number of processes for post-production treatment of“raw”biochars,including leaching,aeration,grinding or sieving to reduce particle size,and chemical or steam activation,have been suggested as means to enhance bi...A number of processes for post-production treatment of“raw”biochars,including leaching,aeration,grinding or sieving to reduce particle size,and chemical or steam activation,have been suggested as means to enhance biochar effectiveness in agriculture,forestry,and environmental restoration.Here,I review studies on post-production processing methods and their effects on biochar physio-chemical properties and present a meta-analysis of plant growth and yield responses to post-processed vs.“raw”biochars.Data from 23 studies provide a total of 112 comparisons of responses to processed vs.unprocessed biochars,and 103 comparisons allowing assessment of effects relative to biochar particle size;additional 8 published studies involving 32 comparisons provide data on effects of biochar leachates.Overall,post-processed biochars resulted in significantly increased average plant growth responses 14%above those observed with unprocessed biochar.This overall effect was driven by plant growth responses to reduced biochar particle size,and heating/aeration treatments.The assessment of biochar effects by particle size indicates a peak at a particle size of 0.5-1.0 mm.Biochar leachate treatments showed very high heterogeneity among studies and no average growth benefit.I conclude that physiochemical post-processing of biochar offers substantial additional agronomic benefits compared to the use of unprocessed biochar.Further research on post-production treatments effects will be important for biochar utilization to maximize benefits to carbon sequestration and system productivity in agriculture,forestry,and environmental restoration.展开更多
In this paper, we propose a deep spatio-temporal forecasting model (DeepSTF) for multi-site weather prediction post-processing by using both temporal andspatial information. In our proposed framework, the spatio-tempo...In this paper, we propose a deep spatio-temporal forecasting model (DeepSTF) for multi-site weather prediction post-processing by using both temporal andspatial information. In our proposed framework, the spatio-temporal information ismodeled by a CNN (convolutional neural network) module and an encoder-decoderstructure with the attention mechanism. The novelty of our work lies in that our modeltakes full account of temporal and spatial characteristics and obtain forecasts of multiple meteorological stations simultaneously by using the same framework. We applythe DeepSTF model to short-term weather prediction at 226 meteorological stations inBeijing. It significantly improves the short-term forecasts compared to other widelyused benchmark models including the Model Output Statistics method. In order toevaluate the uncertainty of the model parameters, we estimate the confidence intervals by bootstrapping. The results show that the prediction accuracy of the DeepSTFmodel has strong stability. Finally, we evaluate the impact of seasonal changes and topographical differences on the accuracy of the model predictions. The results indicatethat our proposed model has high prediction accuracy.展开更多
True random number generators(TRNG)are important counterparts to pseudorandom number generators(PRNG).especially for high security applications such as cryptography.They produce unpredictable,non-repeatablerandom sequ...True random number generators(TRNG)are important counterparts to pseudorandom number generators(PRNG).especially for high security applications such as cryptography.They produce unpredictable,non-repeatablerandom sequences.However,most TRNGs require specialized hardware to extract entropy from physical phenomena and tend to be slower than PRNGs.These generators usually require post-processing algorithms to eliminate biases but in tun.reduces performance.In this paper.a newpost-processing method based on hyperchaos is proposed forsoftware-based TRNGs which not only eliminates statisticalbiases but also provides amplification in order to improve the performance of TRNGs.The proposed method utilizes the inherent characteristics of chaos such as hypersensitivity to input shanugeri,diffusisn,and csnfusion sapabilities to ushievethese goals.Quantized bits of a physical entropy source areused to perturb the parameters of a hyperchaotic map,which is then iterated to produce a set of random output bits.To de-pict the feasibility of the proposed post-processing algorithm.it is applied in designing TRNGs based on digital audio.Thegenerators are analyzed to identify statistical defects in addition to forward and backward security.Results indicate that the proposed generators are able to produce secure true random sequences at a high throughput,which in turn reflects on the effectiveness of the proposed post-processing method.展开更多
基金the Young Investigator Group“Artificial Intelligence for Probabilistic Weather Forecasting”funded by the Vector Stiftungfunding from the Federal Ministry of Education and Research(BMBF)and the Baden-Württemberg Ministry of Science as part of the Excellence Strategy of the German Federal and State Governments。
文摘Weather forecasts from numerical weather prediction models play a central role in solar energy forecasting,where a cascade of physics-based models is used in a model chain approach to convert forecasts of solar irradiance to solar power production.Ensemble simulations from such weather models aim to quantify uncertainty in the future development of the weather,and can be used to propagate this uncertainty through the model chain to generate probabilistic solar energy predictions.However,ensemble prediction systems are known to exhibit systematic errors,and thus require post-processing to obtain accurate and reliable probabilistic forecasts.The overarching aim of our study is to systematically evaluate different strategies to apply post-processing in model chain approaches with a specific focus on solar energy:not applying any post-processing at all;post-processing only the irradiance predictions before the conversion;post-processing only the solar power predictions obtained from the model chain;or applying post-processing in both steps.In a case study based on a benchmark dataset for the Jacumba solar plant in the U.S.,we develop statistical and machine learning methods for postprocessing ensemble predictions of global horizontal irradiance(GHI)and solar power generation.Further,we propose a neural-network-based model for direct solar power forecasting that bypasses the model chain.Our results indicate that postprocessing substantially improves the solar power generation forecasts,in particular when post-processing is applied to the power predictions.The machine learning methods for post-processing slightly outperform the statistical methods,and the direct forecasting approach performs comparably to the post-processing strategies.
文摘In the present computational fluid dynamics （CFD） community, post-processing is regarded as a procedure to view parameter distribution, detect characteristic structure and reveal physical mechanism of fluid flow based on computational or experimental results. Field plots by contours, iso-surfaces, streamlines, vectors and others are traditional post-processing techniques. While the shock wave, as one important and critical flow structure in many aerodynamic problems, can hardly be detected or distinguished in a direct way using these traditional methods, due to possible confusions with other similar discontinuous flow structures like slip line, contact discontinuity, etc. Therefore, method for automatic detection of shock wave in post-processing is of great importance for both academic research and engineering applications. In this paper, the current status of methodologies developed for shock wave detection and implementations in post-processing platform are reviewed, as well as discussions on advantages and limitations of the existing methods and proposals for further studies of shock wave detection method. We also develop an advanced post-processing software, with improved shock detection.
基金Supported by the Chinese Academy of Sciences Center for Excellence and Synergetic Innovation Center in Quantum Information and Quantum Physics,Shanghai Branch,University of Science and Technology of Chinathe National Natural Science Foundation of China under Grant No 11405172
文摘Quantum random number generators adopting single negligible dead time of avalanche photodiodes （APDs） photon detection have been restricted due to the non- We propose a new approach based on an APD array to improve the generation rate of random numbers significantly. This method compares the detectors＇ responses to consecutive optical pulses and generates the random sequence. We implement a demonstration experiment to show its simplicity, compactness and scalability. The generated numbers are proved to be unbiased, post-processing free, ready to use, and their randomness is verified by using the national institute of standard technology statistical test suite. The random bit generation efficiency is as high as 32.8% and the potential generation rate adopting the 32× 32 APD array is up to tens of Gbits/s.
基金supported by the National Natural Science Foundation of China(51875535)the Natural Science Foundation for Young Scientists of Shanxi Province(201701D221017,201901D211242)。
文摘To improve the ability of detecting underwater targets under strong wideband interference environment,an efficient method of line spectrum extraction is proposed,which fully utilizes the feature of the target spectrum that the high intense and stable line spectrum is superimposed on the wide continuous spectrum.This method modifies the traditional beam forming algorithm by calculating and fusing the beam forming results at multi-frequency band and multi-azimuth interval,showing an excellent way to extract the line spectrum when the interference and the target are not in the same azimuth interval simultaneously.Statistical efficiency of the estimated azimuth variance and corresponding power of the line spectrum band depends on the line spectra ratio(LSR)of the line spectrum.The change laws of the output signal to noise ratio(SNR)with the LSR,the input SNR,the integration time and the filtering bandwidth of different algorithms bring the selection principle of the critical LSR.As the basis,the detection gain of wideband energy integration and the narrowband line spectrum algorithm are theoretically analyzed.The simulation detection gain demonstrates a good match with the theoretical model.The application conditions of all methods are verified by the receiver operating characteristic(ROC)curve and experimental data from Qiandao Lake.In fact,combining the two methods for target detection reduces the missed detection rate.The proposed post-processing method in2-dimension with the Kalman filter in the time dimension and the background equalization algorithm in the azimuth dimension makes use of the strong correlation between adjacent frames,could further remove background fluctuation and improve the display effect.
文摘The travel time data collection method is used to assist the congestion management. The use of traditional sensors (e.g. inductive loops, AVI sensors) or more recent Bluetooth sensors installed on major roads for collecting data is not sufficient because of their limited coverage and expensive costs for installation and maintenance. Application of the Global Positioning Systems (GPS) in travel time and delay data collections is proven to be efficient in terms of accuracy, level of details for the data and required data collection of man-power. While data collection automation is improved by the GPS technique, human errors can easily find their way through the post-processing phase, and therefore data post-processing remains a challenge especially in case of big projects with high amount of data. This paper introduces a stand-alone post-processing tool called GPS Calculator, which provides an easy-to-use environment to carry out data post-processing. This is a Visual Basic application that processes the data files obtained in the field and integrates them into Geographic Information Systems (GIS) for analysis and representation. The results show that this tool obtains similar results to the currently used data post-processing method, reduces the post-processing effort, and also eliminates the need for the second person during the data collection.
基金supported by the New Century Excellent Talents in University(NCET-09-0396)the National Science&Technology Key Projects of Numerical Control(2012ZX04014-031)+1 种基金the Natural Science Foundation of Hubei Province(2011CDB279)the Foundation for Innovative Research Groups of the Natural Science Foundation of Hubei Province,China(2010CDA067)
文摘When castings become complicated and the demands for precision of numerical simulation become higher,the numerical data of casting numerical simulation become more massive.On a general personal computer,these massive numerical data may probably exceed the capacity of available memory,resulting in failure of rendering.Based on the out-of-core technique,this paper proposes a method to effectively utilize external storage and reduce memory usage dramatically,so as to solve the problem of insufficient memory for massive data rendering on general personal computers.Based on this method,a new postprocessor is developed.It is capable to illustrate filling and solidification processes of casting,as well as thermal stess.The new post-processor also provides fast interaction to simulation results.Theoretical analysis as well as several practical examples prove that the memory usage and loading time of the post-processor are independent of the size of the relevant files,but the proportion of the number of cells on surface.Meanwhile,the speed of rendering and fetching of value from the mouse is appreciable,and the demands of real-time and interaction are satisfied.
基金Projects 50221402, 50490271 and 50025413 supported by the National Natural Science Foundation of Chinathe National Basic Research Program of China (2009CB219603, 2009 CB724601, 2006CB202209 and 2005CB221500)+1 种基金the Key Project of the Ministry of Education (306002)the Program for Changjiang Scholars and Innovative Research Teams in Universities of MOE (IRT0408)
文摘In order to carry out numerical simulation using geologic structural data obtained from Landmark(seismic interpretation system), underground geological structures are abstracted into mechanical models which can reflect actual situations and facilitate their computation and analyses.Given the importance of model building, further processing methods about traditional seismic interpretation results from Landmark should be studied and the processed result can then be directly used in numerical simulation computations.Through this data conversion procedure, Landmark and FLAC(the international general stress software) are seamlessly connected.Thus, the format conversion between the two systems and the pre-and post-processing in simulation computation is realized.A practical application indicates that this method has many advantages such as simple operation, high accuracy of the element subdivision and high speed, which may definitely satisfy the actual needs of floor grid cutting.
基金This work was supported by Taif university Researchers Supporting Project Number(TURSP-2020/114),Taif University,Taif,Saudi Arabia.
文摘Low contrast of Magnetic Resonance(MR)images limits the visibility of subtle structures and adversely affects the outcome of both subjective and automated diagnosis.State-of-the-art contrast boosting techniques intolerably alter inherent features of MR images.Drastic changes in brightness features,induced by post-processing are not appreciated in medical imaging as the grey level values have certain diagnostic meanings.To overcome these issues this paper proposes an algorithm that enhance the contrast of MR images while preserving the underlying features as well.This method termed as Power-law and Logarithmic Modification-based Histogram Equalization(PLMHE)partitions the histogram of the image into two sub histograms after a power-law transformation and a log compression.After a modification intended for improving the dispersion of the sub-histograms and subsequent normalization,cumulative histograms are computed.Enhanced grey level values are computed from the resultant cumulative histograms.The performance of the PLMHE algorithm is comparedwith traditional histogram equalization based algorithms and it has been observed from the results that PLMHE can boost the image contrast without causing dynamic range compression,a significant change in mean brightness,and contrast-overshoot.
文摘This paper proposed improvements to the low bit rate parametric audio coder with sinusoid model as its kernel. Firstly, we propose a new method to effectively order and select the perceptually most important sinusoids. The sinusoid which contributes most to the reduction of overall NMR is chosen. Combined with our improved parametric psychoacoustic model and advanced peak riddling techniques, the number of sinusoids required can be greatly reduced and the coding efficiency can be greatly enhanced. A lightweight version is also given to reduce the amount of computation with only little sacrifice of performance. Secondly, we propose two enhancement techniques for sinusoid synthesis: bandwidth enhancement and line enhancement. With little overhead, the effective bandwidth can be extended one more octave; the timbre tends to sound much brighter, thicker and more beautiful.
文摘In the analysis of high-rise building, traditional displacement-based plane elements are often used to get the in-plane internal forces of the shear walls by stress integration. Limited by the singular problem produced by wall holes and the loss of precision induced by using differential method to derive strains, the displacement-based elements cannot always present accuracy enough for design. In this paper, the hybrid post-processing procedure based on the Hellinger-Reissner variational principle is used for improving the stress precision of two quadrilateral plane elements. In order to find the best stress field, three different forms are assumed for the displacement-based plane elements and with drilling DOF. Numerical results show that by using the proposed method, the accuracy of stress solutions of these two displacement-based plane elements can be improved.
基金financially supported by the 2022 MTC Young Individual Research Grants under Singapore Research,Innovation and Enterprise(RIE)2025 Plan(No.M22K3c0097)the Natural Science Foundation of US(No.DMR-2104933)the sponsorship of the China Scholarship Council(No.202106130051)。
文摘Laser additive manufacturing(LAM)of titanium(Ti)alloys has emerged as a transformative technology with vast potential across multiple industries.To recap the state of the art,Ti alloys processed by two essential LAM techniques(i.e.,laser powder bed fusion and laser-directed energy deposition)will be reviewed,covering the aspects of processes,materials and post-processing.The impacts of process parameters and strategies for optimizing parameters will be elucidated.Various types of Ti alloys processed by LAM,includingα-Ti,(α+β)-Ti,andβ-Ti alloys,will be overviewed in terms of micro structures and benchmarking properties.Furthermore,the post-processing methods for improving the performance of L AM-processed Ti alloys,including conventional and novel heat treatment,hot isostatic pressing,and surface processing(e.g.,ultrasonic and laser shot peening),will be systematically reviewed and discussed.The review summarizes the process windows,properties,and performance envelopes and benchmarks the research achievements in LAM of Ti alloys.The outlooks of further trends in LAM of Ti alloys are also highlighted at the end of the review.This comprehensive review could serve as a valuable resource for researchers and practitioners,promoting further advancements in LAM-built Ti alloys and their applications.
文摘Developing reliable weather prediction systems is still a challenging task due to the complexity of the Earth System and the chaotic behavior of its compo-nents.Small errors introduced by observations,their assimilation and the forecast model configuration escalate chaotically,leading to a significant loss in forecast skill with time.Traditionally,rainfall forecasts have been generated at grid-based spatial resolutions,providing valuable information on regional precipitation patterns.However,Weather varies markedly within a grid box and forecasts for specific sites have occasionally failed inevitably.The grid-based forecasts may not always meet the needs of decision-makers at specific points of interest.The major challenge is dealing with variations in sub-grid variability,that is to say,the variation seen amongst rainfall point values within a given model grid box,more especially in convective situations.While ensemble forecasts have shown promise in capturing the uncertainty inherent in average rainfall predictions of much larger grid boxes,their utility at point locations has not been extensively explored.Most evaluation studies focus on grid-based verification metrics,which may not accurately reflect forecast per-formance at individual points of interest.EcPoint,a post-processing approach developed at the European Centre for Medium Range Forecasts(ECMWF),is tailored to forecast rainfall at point locations.In this study,we evaluate the performance of the EcPoint post-processing method over the south China re-gion.The analysis focuses on the reliability,accuracy and discrimination skill of this post-processing method over the three provinces in south China(An-hui,Zhejiang and Jiangsu).We examine performance versus lead time,sea-sons,and altitude.Through verifications,the study highlighted the added value of the post-processing method over Raw ensemble forecasts.One year of verification demonstrates that,between the Raw ensemble and post-pro-cessed EcPoint forecasts,EcPoint is the more reliable and skillful system,add-ing significant value to most rainfall events occurring during the day and the seasonal associated events,as well as the topography-associated rainfall events.To complement the one-year verification analysis,a case study was conducted on an extremely heavy rainfall event observed on June 2,2022 at 12 UTC.The analysis demonstrated EcPoint’s ability to provide more localized and refined forecasts whereas Raw didn’t provide any possibility of rainfall,particularly at short lead times.At longer lead times,EcPoint ensembles maintained rela-tively low probabilities,but offered improved performance in capturing rain-fall variability,while Raw ensemble exhibited broader but less precise rainfall predictions with a tendency of over warning of some areas.Future work can extend the evaluation to more diverse climatic and topographic regions of China to enhance the general applicability of the method.Although based solely on the global ECMWF-IFS model,EcPoint performs well over the small domain of south China(three provinces).Besides verifying EcPoint,the study confirms that the post-processing method can significantly improve the fore-cast performance.
基金supported by the National Key Research and Development Program of China(No.2022YFA1204800)the National Natural Science Foundation of China(Grant No.U2001219)+1 种基金Hubei Provincial Natural Science Foundation of China(No.2023AFA034)the Key R&D program of Hubei Province(No.2023BAB102).
文摘Metal halide perovskites have become one of the most competitive new-generation optoelectronic materials due to their excellent optoelectronic properties. Vacuum evaporation can produce high-purity and large-area films, leading to the wide application of this method in the semiconductor industry and optoelectronics field. However, the electroluminescent performance of vacuum-evaporated perovskite light-emitting diodes(PeLEDs) still lags behind those counterparts fabricated by solution methods. Herein, based on vacuum evaporation, 3D perovskite films are obtained by three-source co-evaporation.Considering the unique quantum well structure of quasi-2D perovskite can significantly enhance the exciton binding energy and improve the radiative recombination rate, leading to a high photoluminescence quantum yield(PLQY). Subsequently,the highly stable and low-defect-density quasi-2D perovskite is introduced into 3D perovskite films through post-treatment with phenethylammonium chloride(PEACl). To minimize the degradation of film quality caused by PEACl treatment, a layer of guanidinium bromide(GABr) is vacuum evaporated on top of PEACl treatment to further improve the quality of emitting layer. Finally, under the synergistic post-processing modification of PEACl and GABr, blue PeLEDs with a maximum external quantum efficiency(EQE) of 6.09% and a maximum brightness of 1325 cd/m^(2) are successfully obtained. This work deepens the understanding of 2D/3D heterojunctions and provides a new approach to construct PeLEDs with high performance.
基金the National Natural Science Foundation of China(NSFC)(No.11704285)the Natural Science Foundation of Zhejiang Province(No.LY20E050027)the Wenzhou Science and Technology Plan Projects(No.G20170012).
文摘The laser shock processing implemented by a laser-induced high-pressure plasma which propagates into the sample as a shockwave is innovatively applied as a post-processing technique on HfO_(2)/SiO_(2) multilayer coatings for the first time.The pure mechanical post-processing has provided evidence of a considerable promotion effect of the laser-induced damage threshold,which increased by a factor of about 4.6 with appropriate processing parameters.The promotion mechanism is confirmed to be the comprehensive modification of the intrinsic defects and the mechanical properties,which made the applicability of this novel post-processing technique on various types of coatings possible.Based on experiments,an interaction equation for the plasma pressure is established,which clarifies the existence of the critical pressure and provides a theoretical basis for selecting optimal processing parameters.In addition to the further clarification of the underlying damage mechanism,the laser shock post-processing provides a promising technique to realize the comprehensive and effective improvement of the laser-induced damage resistance of coatings.
基金This work was funded by grants from Natural Science and Engineering Research Council of Canada,with additional support from Haliburton Forest and Wild Life Reserve and the Ontario Mining Association.
文摘A number of processes for post-production treatment of“raw”biochars,including leaching,aeration,grinding or sieving to reduce particle size,and chemical or steam activation,have been suggested as means to enhance biochar effectiveness in agriculture,forestry,and environmental restoration.Here,I review studies on post-production processing methods and their effects on biochar physio-chemical properties and present a meta-analysis of plant growth and yield responses to post-processed vs.“raw”biochars.Data from 23 studies provide a total of 112 comparisons of responses to processed vs.unprocessed biochars,and 103 comparisons allowing assessment of effects relative to biochar particle size;additional 8 published studies involving 32 comparisons provide data on effects of biochar leachates.Overall,post-processed biochars resulted in significantly increased average plant growth responses 14%above those observed with unprocessed biochar.This overall effect was driven by plant growth responses to reduced biochar particle size,and heating/aeration treatments.The assessment of biochar effects by particle size indicates a peak at a particle size of 0.5-1.0 mm.Biochar leachate treatments showed very high heterogeneity among studies and no average growth benefit.I conclude that physiochemical post-processing of biochar offers substantial additional agronomic benefits compared to the use of unprocessed biochar.Further research on post-production treatments effects will be important for biochar utilization to maximize benefits to carbon sequestration and system productivity in agriculture,forestry,and environmental restoration.
基金This work is supported by the National Key Research and Development Program of China(Grant Nos.2017YFC0209804 and 2018YFF0300104)Beijing Academy of Artificial Intelligence(BAAI)+1 种基金the National Natural Science Foundation of China(Grant No.11421101)the Open Research Fund of Shenzhen Research Institute of Big Data(Grant No.2019ORF01001).
文摘In this paper, we propose a deep spatio-temporal forecasting model (DeepSTF) for multi-site weather prediction post-processing by using both temporal andspatial information. In our proposed framework, the spatio-temporal information ismodeled by a CNN (convolutional neural network) module and an encoder-decoderstructure with the attention mechanism. The novelty of our work lies in that our modeltakes full account of temporal and spatial characteristics and obtain forecasts of multiple meteorological stations simultaneously by using the same framework. We applythe DeepSTF model to short-term weather prediction at 226 meteorological stations inBeijing. It significantly improves the short-term forecasts compared to other widelyused benchmark models including the Model Output Statistics method. In order toevaluate the uncertainty of the model parameters, we estimate the confidence intervals by bootstrapping. The results show that the prediction accuracy of the DeepSTFmodel has strong stability. Finally, we evaluate the impact of seasonal changes and topographical differences on the accuracy of the model predictions. The results indicatethat our proposed model has high prediction accuracy.
基金supported in part by the Min-istry of Education Malaysia under the Fundamental Research Grant Scheme(FRGS/1/2019/I1CT05/USM/02/1)Universiti Sains Malaysia(304/PKOMP/6315190)the National Natural Science Foundation of China(Grant No.61702212).
文摘True random number generators(TRNG)are important counterparts to pseudorandom number generators(PRNG).especially for high security applications such as cryptography.They produce unpredictable,non-repeatablerandom sequences.However,most TRNGs require specialized hardware to extract entropy from physical phenomena and tend to be slower than PRNGs.These generators usually require post-processing algorithms to eliminate biases but in tun.reduces performance.In this paper.a newpost-processing method based on hyperchaos is proposed forsoftware-based TRNGs which not only eliminates statisticalbiases but also provides amplification in order to improve the performance of TRNGs.The proposed method utilizes the inherent characteristics of chaos such as hypersensitivity to input shanugeri,diffusisn,and csnfusion sapabilities to ushievethese goals.Quantized bits of a physical entropy source areused to perturb the parameters of a hyperchaotic map,which is then iterated to produce a set of random output bits.To de-pict the feasibility of the proposed post-processing algorithm.it is applied in designing TRNGs based on digital audio.Thegenerators are analyzed to identify statistical defects in addition to forward and backward security.Results indicate that the proposed generators are able to produce secure true random sequences at a high throughput,which in turn reflects on the effectiveness of the proposed post-processing method.
