Two methods for separating the magnetospheric solar wind charge exchange soft X-ray emission from the diffuse X-ray background

Solar wind charge exchange(SWCX)is the process of solar wind high-valence ions exchanging charges with neutral components and generating soft X-rays.Recently,detecting the SWCX emission from the magnetosphere is proposed as a new technique to study the magnetosphere using panoramic soft X-ray imaging.To better prepare for the data analysis of upcoming magnetospheric soft X-ray imaging missions,this paper compares the magnetospheric SWCX emission obtained by two methods in an XMM-Newton observation,during which the solar wind changed dramatically.The two methods differ in the data used to fit the diffuse X-ray background(DXB)parameters in spectral analysis.The method adding data from the ROSAT All-Sky Survey(RASS)is called the RASS method.The method using the quiet observation data is called the Quiet method,where quiet observations usually refer to observations made by the same satellite with the same target but under weaker solar wind conditions.Results show that the spectral compositions of magnetospheric SWCX emission obtained by the two methods are very similar,and the changes in intensity over time are highly consistent,although the intensity obtained by the RASS method is about 2.68±0.56 keV cm^(-2)s^(-1)sr^(-1)higher than that obtained by the Quiet method.Since the DXB intensity obtained by the RASS method is about 2.84±0.74 keV cm^(-2)s^(-1)sr^(-1)lower than that obtained by the Quiet method,and the linear correlation coefficient between the difference of SWCX and DXB obtained by the two methods in diffe rent energy band is close to-1,the diffe rences in magnetospheric SWCX can be fully attributed to the diffe rences in the fitted DXB.The difference between the two methods is most significant when the energy is less than 0.7 keV,which is also the main energy band of SWCX emission.In addition,the difference between the two methods is not related to the SWCX intensity and,to some extent,to solar wind conditions,because SWCX intensity typically va ries with the solar wind.In summary,both methods are robust and reliable,and should be considered based on the best available options.

Simulation of the SMILE Soft X-ray Imager response to a southward interplanetary magnetic field turning

The Solar wind Magnetosphere Ionosphere Link Explorer(SMILE)Soft X-ray Imager(SXI)will shine a spotlight on magnetopause dynamics during magnetic reconnection.We simulate an event with a southward interplanetary magnetic field turning and produce SXI count maps with a 5-minute integration time.By making assumptions about the magnetopause shape,we find the magnetopause standoff distance from the count maps and compare it with the one obtained directly from the magnetohydrodynamic(MHD)simulation.The root mean square deviations between the reconstructed and MHD standoff distances do not exceed 0.2 RE(Earth radius)and the maximal difference equals 0.24 RE during the 25-minute interval around the southward turning.

A Corpus-Based Analysis of the Animal Images in The Wind Among the Reeds

The Wind Among the Reeds, written from 1889 to 1939, is regarded as one of the most remarkable poetry collections of William Butler Yeats. It altogether includes 80 poems touching upon several themes such as love, religion, dignity, and life. Yeats is one of the most distinguished Irish poets throughout the world, whose works perfectly embody the incorporation of romanticism, modernism, and occultism. It is noteworthy that in some of his poems, animals are portrayed frequently or even taken as the title of a poem, such as bird, fish, swan and so on. Therefore, this essay attempts to study the meaning of animal images of this poetry anthology in terms of different writing phases of Yeats. Firstly, the author builds the corpus of The Wind Among the Reeds and employs corpus search software Ant Cone to check the number and distribution of the animal image. Next, the author focuses on certain prominent images and investigates them further by analyzing the concordance lines of them. Thirdly, according to the result of distribution information, the author also attaches importance to the phenomenon of image combination in the poetry and then explores its function and effect. To conclude, by exploring the animal image in The WindAmong the Reeds, a deeper understanding of the poetry and the writing style of the poet will be gained on another level. What is more, a more direct and objective data is provided through the method of corpus and its relevant software, thereupon a new research approach is introduced.

Discussion Measurement Models and Algorithms of the Wind Vector Field Based on Satellite Images

This article aims to discuss the strike two-dimensional wind vector on geostationary satellite imageries. The magnitude and direction of the wind vector are decided by the moving speed of the clouds. First, based on the features of the cloud map, we extract the characteristics of clouds and establish matching model for the clouds image. Maximum correlation coefficient between the target modules and tracking module is obtained by using infrared brightness temperature cross-correlation coefficient method. Then, the beginning and end of the wind vector can be ascertained. Using the spherical triangles of the law of cosines, we determine the magnitude and direction of the wind vector.

Using restored two-dimensional X-ray images to reconstruct the three-dimensional magnetopause

Astronomical imaging technologies are basic tools for the exploration of the universe,providing basic data for the research of astronomy and space physics.The Soft X-ray Imager(SXI)carried by the Solar wind Magnetosphere Ionosphere Link Explorer(SMILE)aims to capture two-dimensional(2-D)images of the Earth’s magnetosheath by using soft X-ray imaging.However,the observed 2-D images are affected by many noise factors,destroying the contained information,which is not conducive to the subsequent reconstruction of the three-dimensional(3-D)structure of the magnetopause.The analysis of SXI-simulated observation images shows that such damage cannot be evaluated with traditional restoration models.This makes it difficult to establish the mapping relationship between SXIsimulated observation images and target images by using mathematical models.We propose an image restoration algorithm for SXIsimulated observation images that can recover large-scale structure information on the magnetosphere.The idea is to train a patch estimator by selecting noise–clean patch pairs with the same distribution through the Classification–Expectation Maximization algorithm to achieve the restoration estimation of the SXI-simulated observation image,whose mapping relationship with the target image is established by the patch estimator.The Classification–Expectation Maximization algorithm is used to select multiple patch clusters with the same distribution and then train different patch estimators so as to improve the accuracy of the estimator.Experimental results showed that our image restoration algorithm is superior to other classical image restoration algorithms in the SXI-simulated observation image restoration task,according to the peak signal-to-noise ratio and structural similarity.The restoration results of SXI-simulated observation images are used in the tangent fitting approach and the computed tomography approach toward magnetospheric reconstruction techniques,significantly improving the reconstruction results.Hence,the proposed technology may be feasible for processing SXI-simulated observation images.

Theoretical derivation of risk-ratios for assessing wind damage in a coastal forest

Based on the discussion of relationships between thinning and wind damage, and published information, a method for estimating risk ratios of wind damage was developed. Estimations of risk-ratio for Pinus thunbergii trees and stands were de-duced from stem bending theory and coefficients characterizing wind profile, distribution of branches and optical stratification po-rosity. The results showed that if the value of constant b in the branch distribution-model equals the attenuation coefficient s in the wind profile model for a single tree crown, then the parameter H/D1.33 (height over stem diameter cubed) can be used to compare and evaluate the risk-ratio of wind damage for individual trees. The same method can be applied to stands using the coefficient of wind profile in a stand, i.e. attenuation coefficient , the coefficient from distributions of optical stratification porosity, i.e. extinction coefficient , and the parameter D1.33. The application of parameter H/D1.33 and the process of determining risk ra-tios of wind damage for stands were also given in the paper.

Particle image velocimetry (PIV) measurements of tip vortex wake structure of wind turbine

Large-view flow field measurements using the particle image velocimetry （PIV） technique with high resolution CCD cameras on a rotating 1/8 scale blade model of the NREL UAE phase VI wind turbine are conducted in the engineering-oriented q53.2 m wind tunnel. The motivation is to establish the database of the initiation and development of the tip vortex to study the flow structure and mechanism of the wind turbine. The results show that the tip vortex first moves inward for a very short period and then moves outward with the wake expansion, while its vorticity decreases with time after being trailed from the trailing edge of the blade tip, and then increases continuously with the rapid rolling-up to form a strong tip vortex. The measurements also indicate that the downstream movement of the tip vortex is nearly linear in the very near wake under the test condition.

The influence of runoff and wind on the dispersion patterns of suspended sediment in the Zhujiang(Pearl) River Estuary based on MODIS data

Cloud-free moderate-resolution imaging spectroradiometer(MODIS) images of the Zhujiang(Pearl) River Estuary(ZRE) taken between 2002 and 2012 are retrieved and used to study the spatial and temporal patterns of suspended sediment concentrations(SSCs) across the estuary under runoff, wind, and tropical storm conditions.Five typical dispersal patterns of suspended sediments in the estuary are defined: Case I shows generally low SSCs under low dynamics; Case Ⅱ shows a river-dominant dispersal pattern of suspended sediments from the outlets,particularly from Modaomen, Jiaomen, Hengmen, and others; Case Ⅲ shows wind-dominant dispersal of high SSCs derived from the west shoal and southwesterly transport under a strong NE wind; Case IV is the combination of relatively large runoff and wind; and Case V is caused by a strong tropical storm with high river discharge and wind, which is characterized by the high SSCs across the entire estuary that are transported eastward by winddriven and buoyancy currents outside the estuary. Runoff is a dominant factor that controls seasonal and annual SSC variations in the ZRE, with the area of high SSCs being largest in the summer and smallest in the spring. The correlation coefficients between the monthly averaged river-suspended sediment discharge and the area of the high SSCs are approximately 0.6. The wind power over the west shoal increases with a wind speed, which induces more sediment resuspension and shows a close relationship between the wind speed and high SSC area.

Research on Surface Defect Detection Technology of Wind Turbine Blade Based on UAV Image

In the background of“double carbon,”vigorously developing new energy is particularly important.Wind power is an important clean energy source.In the field of new energy,wind power scale is also expanding.With the wind turbine,the probability of large-scale blade damage is also increasing.Because the large wind turbine blade crack detection cost is high and because of the poor working environment,this paper proposes a wind turbine blade surface defect detection method based on UAV acquisition images and digital image pro-cessing.The application of weighted averages to achieve grayscale processing,followed by median filtering to achieve image noise reduction,and an improved histogram equalization algorithm is proposed and used for the characteristics of the UAV acquisition images,which enhances the image by limiting the contrast adaptive his-togram equalization algorithm to make the details at the target area and defects more clear and complete,and improves the detection efficiency.The detection of the blade surface is achieved by separating and extracting the feature information from the defects through image foreground segmentation,threshold processing,and framing by the connected domain.The validity and accuracy of the proposed method in leaf detection were verified by experiments.

Recent Developments of Image Based Measurement Methods for Application to Transonic Flows in Industrial Wind Tunnels

The experimental investigation of unsteady complex flow fields in wind tunnels requires advanced measurement techniques. The most important of such image based measurement techniques are those for the measurement of planar flow velocity fields, planar pressure distribution, model location and deformation, model temperature and quantitative high speed flow visualization. The applications as carried out by DLR range from low speed flows to transonic flows, from high lift configurations to propellers and rotors, from wake vortex investigations in catapult facilities and water towing tanks to investigations of vortex break down phenomena on delta wings. The capability to use image based measurement techniques in transonic flows requires dedicated technical developments and experienced scientists due to the special environment of a transonic wind tunnel. In this paper an overview of the state-of-the art of the application of image based measurement techniques in transonic flows as performed by DLR＇s Institute of Aerodynamics and Flow Technology will be given.

Exact calculation of the minimal thickness of the large optical path difference wind imaging interferometer

This paper gives the relation between spatial ray and its projection on paper plane based on the vector form of reflective law. Using the method of prism expansion, it obtains the exact expression of the exit height. The exit height can ensure that the incident rays, at arbitrary direction and arbitrary angle, after several transmission and reflection in the two right-angle reflectors, finally pass through the exit surface. Furthermore, it analyses the effects of different parameters on the exit height through computer simulation, and some important conclusions are obtained. The physical meaning of the sign of exit height is described, and the exact expression of the minimal thickness of the large optical path difference wind imaging interferometer is gained. This work is of great scientific significance to the static, real- time simultaneous detection of atmospheric wind field, and it will provide a theoretical and practical guidance for the miniaturization design and engineering realization of wind imaging interferometer.

Evolution of crescent-shaped sand dune under the influence of injected sand flux:scaling law and wind tunnel experiment

This paper studies the evolution of crescent-shaped dune under the influence of injected flux. A scaling law and a wind tunnel experiment are carried out for comparison. The experiment incorporates a novel image processing algorithm to recover the evolutionary process. The theoretical and experimental results agree well in the middle stage of dune evolution, but deviate from each other in the initial and final stages, suggesting that the crescent-shaped dune evolution is intrinsically scale-variant and that the crescent shape breaks down under unsaturated condition.

Wind speed inversion and in-orbit assessment of the imaging altimeter on Tiangong-2 space station

Imaging altimeter(IALT)is a new type of radar altimeter system.In contrast to the conventional nadir-looking altimeters,such as HY-2 A altimeter,Jason-1/2,and TOPEX/Poseidon,IALT observes the earth surface at low incident angles(2.5°–8°),so its swath is much wider and its spatial resolution is much higher than the previous altimeters.This paper presents a wind speed inversion method for the recently launched IALT onboard Tiangong-2 space station.Since the current calibration results of IALT do not agree well with the well-known wind geophysical model function at low incidence angles,a neural network is used to retrieve the ocean surface wind speed in this study.The wind speed inversion accuracy is evaluated by comparing with the ECMWF reanalysis wind speed,buoy wind speed,and in-situ ship measurements.The results show that the retrieved wind speed bias is about–0.21 m/s,and the root-mean-square(RMS)error is about 1.85 m/s.The wind speed accuracy of IALT meets the performance requirement.

A method of convolutional neural network based on frequency segmentation for monitoring the state of wind turbine blades

Wind turbine blades are prone to failure due to high tip speed,rain,dust and so on.A surface condition detecting approach based on wind turbine blade aerodynamic noise is proposed.On the experimental measurement data,variational mode decomposition filtering and Mel spectrogram drawing are conducted first.The Mel spectrogram is divided into two halves based on frequency characteristics and then sent into the convolutional neural network.Gaussian white noise is superimposed on the original signal and the output results are assessed based on score coefficients,considering the complexity of the real environment.The surfaces of Wind turbine blades are classified into four types:standard,attachments,polishing,and serrated trailing edge.The proposed method is evaluated and the detection accuracy in complicated background conditions is found to be 99.59%.In addition to support the differentiation of trained models,utilizing proper score coefficients also permit the screening of unknown types.

Early detection of pine wilt disease in Pinus tabuliformis in North China using a field portable spectrometer and UAV-based hyperspectral imagery

Background:Pine wilt disease(PWD)is a major ecological concern in China that has caused severe damage to millions of Chinese pines(Pinus tabulaeformis).To control the spread of PWD,it is necessary to develop an effective approach to detect its presence in the early stage of infection.One potential solution is the use of Unmanned Airborne Vehicle(UAV)based hyperspectral images(HIs).UAV-based HIs have high spatial and spectral resolution and can gather data rapidly,potentially enabling the effective monitoring of large forests.Despite this,few studies examine the feasibility of HI data use in assessing the stage and severity of PWD infection in Chinese pine.Method:To fill this gap,we used a Random Forest(RF)algorithm to estimate the stage of PWD infection of trees sampled using UAV-based HI data and ground-based data(data directly collected from trees in the field).We compared relative accuracy of each of these data collection methods.We built our RF model using vegetation indices(VIs),red edge parameters(REPs),moisture indices(MIs),and their combination.Results:We report several key results.For ground data,the model that combined all parameters(OA:80.17%,Kappa:0.73)performed better than VIs(OA:75.21%,Kappa:0.66),REPs(OA:79.34%,Kappa:0.67),and MIs(OA:74.38%,Kappa:0.65)in predicting the PWD stage of individual pine tree infection.REPs had the highest accuracy(OA:80.33%,Kappa:0.58)in distinguishing trees at the early stage of PWD from healthy trees.UAV-based HI data yielded similar results:the model combined VIs,REPs and MIs(OA:74.38%,Kappa:0.66)exhibited the highest accuracy in estimating the PWD stage of sampled trees,and REPs performed best in distinguishing healthy trees from trees at early stage of PWD(OA:71.67%,Kappa:0.40).Conclusion:Overall,our results confirm the validity of using HI data to identify pine trees infected with PWD in its early stage,although its accuracy must be improved before widespread use is practical.We also show UAV-based data PWD classifications are less accurate but comparable to those of ground-based data.We believe that these results can be used to improve preventative measures in the control of PWD.

Effects of Inflow Conditions on Wind Turbine Performance and near Wake Structure

Knowledge about the structure and development of wakes behind wind turbines is important for power optimization of wind power farms. The high turbulence levels in the wakes give rise to undesired unsteady loadings on the downstream turbines, which in the long run might cause fatigue damages. In the present study, the near wake behind a small-scale model wind turbine was investigated experimentally in a wind tunnel. The study consists of measurements with particle image velocimetry using two different inlet conditions: a freely developing boundary layer, causing an almost uniform inflow across the rotor disc, and an inflow with strong shear across the rotor disc, in order to model the atmospheric boundary layer. The results show a faster recovery of the wake in the case with shear inflow, caused by the higher turbulence levels and enhanced mixing of momentum. The increased inlet turbulence levels in this case also resulted in a faster breakdown of the tip vortices as well as different distributions of the streamwise and vertical components of the turbulence intensity in the wake. An analysis comparing vortex statistics for the two cases also showed the presence of strong tip vortices in the case with lower inlet turbulence, while the case with higher inlet turbulence developed a different distribution of vortices in the wake.

Commentary of Wind and Window Flower by Robert Frost

Wind and Window Flower is a special metaphorical love poem by Robert Frost. This tale of love actually presents a love journey of temptation, excitement, and disappointment. This paper tries to analysis the poem from the perspective of the sound of the poetry, the metro and rhyme, the conceptual and rhetorical.

基于NASA World Wind的GeoTIFF影像显示方案研究

鉴于遥感影像GeoTIFF研究过程中对地理信息的需求,提出了基于World Wind的GeoTIFF显示方案。在对World Wind分层显示进行深入研究的基础上,采用添加GeoTIFF图层的方式显示影像数据和设置影像alpha值的方式透视影像覆盖区域的地表特征。实验证明该方案能够快速地显示GeoTIFF影像,能方便地查看GeoTIFF覆盖区域的地表特征。

Surveillance of pine wilt disease by high resolution satellite

Pine wilt disease caused by the pinewood nematode Bursaphelenchus xylophilus has led to the death of a large number of pine trees in China.This destructive disease has the characteristics of bring wide-spread,fast onset,and long incubation time.Most importantly,in China,the fatality rate in pines is as high as 100%.The key to reducing this mortality is how to quickly find the infected trees.We proposed a method of automatically identifying infected trees by a convolution neural network and bounding box tool.This method rapidly locates the infected area by classifying and recognizing remote sensing images obtained by high resolution earth observation Satellite.The recognition accuracy of the test data set was 99.4%,and the remote sensing image combined with convolution neural network algorithm can identify and determine the distribution of the infected trees.It can provide strong technical support for the prevention and control of pine wilt disease.

Pine wilt disease detection in high-resolution UAV images using object-oriented classification

Pine wilt disease(PWD)is currently one of the main causes of large-scale forest destruction.To control the spread of PWD,it is essential to detect affected pine trees quickly.This study investigated the feasibility of using the object-oriented multi-scale segmentation algorithm to identify trees discolored by PWD.We used an unmanned aerial vehicle(UAV)platform equipped with an RGB digital camera to obtain high spatial resolution images,and multiscale segmentation was applied to delineate the tree crown,coupling the use of object-oriented classification to classify trees discolored by PWD.Then,the optimal segmentation scale was implemented using the estimation of scale parameter(ESP2)plug-in.The feature space of the segmentation results was optimized,and appropriate features were selected for classification.The results showed that the optimal scale,shape,and compactness values of the tree crown segmentation algorithm were 56,0.5,and 0.8,respectively.The producer’s accuracy(PA),user’s accuracy(UA),and F1 score were 0.722,0.605,and 0.658,respectively.There were no significant classification errors in the final classification results,and the low accuracy was attributed to the low number of objects count caused by incorrect segmentation.The multi-scale segmentation and object-oriented classification method could accurately identify trees discolored by PWD with a straightforward and rapid processing.This study provides a technical method for monitoring the occurrence of PWD and identifying the discolored trees of disease using UAV-based high-resolution images.