Quantitative analysis of digital images requires detection and segmentation of the borders of the object of interest. Accurate segmentation is required for volume determination, 3D rendering, radiation therapy, and su...Quantitative analysis of digital images requires detection and segmentation of the borders of the object of interest. Accurate segmentation is required for volume determination, 3D rendering, radiation therapy, and surgery planning. In medical images, segmentation has traditionally been done by human experts. Substantial computational and storage requirements become especially acute when object orientation and scale have to be considered. Therefore, automated or semi-automated segmentation techniques are essential if these software applications are ever to gain widespread clinical use. Many methods have been proposed to detect and segment 2D shapes, most of which involve template matching. Advanced segmentation techniques called Snakes or active contours have been used, considering deformable models or templates. The main purpose of this work is to apply segmentation techniques for the definition of 3D organs (anatomical structures) when big data information has been stored and must be organized by the doctors for medical diagnosis. The processes would be implemented in the CT images from patients with COVID-19.展开更多
As COVID-19 poses a major threat to people’s health and economy,there is an urgent need for forecasting methodologies that can anticipate its trajectory efficiently.In non-stationary time series forecasting jobs,ther...As COVID-19 poses a major threat to people’s health and economy,there is an urgent need for forecasting methodologies that can anticipate its trajectory efficiently.In non-stationary time series forecasting jobs,there is frequently a hysteresis in the anticipated values relative to the real values.The multilayer deep-time convolutional network and a feature fusion network are combined in this paper’s proposal of an enhanced Multilayer Deep Time Convolutional Neural Network(MDTCNet)for COVID-19 prediction to address this problem.In particular,it is possible to record the deep features and temporal dependencies in uncertain time series,and the features may then be combined using a feature fusion network and a multilayer perceptron.Last but not least,the experimental verification is conducted on the prediction task of COVID-19 real daily confirmed cases in the world and the United States with uncertainty,realizing the short-term and long-term prediction of COVID-19 daily confirmed cases,and verifying the effectiveness and accuracy of the suggested prediction method,as well as reducing the hysteresis of the prediction results.展开更多
Due to the low spatial resolution of images taken from the Chang＇e-1 （CE-I） orbiter, the details of the lunar surface are blurred and lost. Considering the limited spatial resolution of image data obtained by a CCD...Due to the low spatial resolution of images taken from the Chang＇e-1 （CE-I） orbiter, the details of the lunar surface are blurred and lost. Considering the limited spatial resolution of image data obtained by a CCD camera on CE-1, an example-based super-resolution （SR） algorithm is employed to obtain high- resolution （HR） images. SR reconstruction is important for the application of image data to increase the resolution of images. In this article, a novel example-based algorithm is proposed to implement SR reconstruction by single-image analysis, and the computational cost is reduced compared to other example-based SR methods. The results show that this method can enhance the resolution of images using SR and recover detailed information about the lunar surface. Thus it can be used for surveying HR terrain and geological features. Moreover, the algorithm is significant for the HR processing of remotely sensed images obtained by other imaging systems.展开更多
Attitude is one of the crucial parameters for space objects and plays a vital role in collision prediction and debris removal.Analyzing light curves to determine attitude is the most commonly used method.In photometri...Attitude is one of the crucial parameters for space objects and plays a vital role in collision prediction and debris removal.Analyzing light curves to determine attitude is the most commonly used method.In photometric observations,outliers may exist in the obtained light curves due to various reasons.Therefore,preprocessing is required to remove these outliers to obtain high quality light curves.Through statistical analysis,the reasons leading to outliers can be categorized into two main types:first,the brightness of the object significantly increases due to the passage of a star nearby,referred to as“stellar contamination,”and second,the brightness markedly decreases due to cloudy cover,referred to as“cloudy contamination.”The traditional approach of manually inspecting images for contamination is time-consuming and labor-intensive.However,we propose the utilization of machine learning methods as a substitute.Convolutional Neural Networks and SVMs are employed to identify cases of stellar contamination and cloudy contamination,achieving F1 scores of 1.00 and 0.98 on a test set,respectively.We also explore other machine learning methods such as ResNet-18 and Light Gradient Boosting Machine,then conduct comparative analyses of the results.展开更多
Chang＇e-3 （CE-3） landed on the Mare Imbrium basin in the east part of Sinus Iridum （19.51°W, 44.12°N）, which was China＇s first soft landing on the Moon and it started collecting data on the lunar surfa...Chang＇e-3 （CE-3） landed on the Mare Imbrium basin in the east part of Sinus Iridum （19.51°W, 44.12°N）, which was China＇s first soft landing on the Moon and it started collecting data on the lunar surface environment. To better understand the environment of this region, this paper utilizes the available high-resolution topography data, image data and geological data to carry out a detailed analysis and research on the area surrounding the landing site （Sinus Iridum and 45 km×70 km of the landing area） as well as on the topography, landform, geology and lunar dust of the area surrounding the landing site. A general topographic analysis of the surrounding area is based on a digital elevation model and digital elevation model data acquired by Chang＇e-2 that have high resolution; the geology analysis is based on lunar geological data published by USGS; the study on topographic factors and distribution of craters and rocks in the surrounding area covering 4km^4km or even smaller is based on images from the CE-3 landing camera and images from the topographic camera; an analysis is done of the effect of the CE-3 engine plume on the lunar surface by comparing images before and after the landing using data from the landing camera. A comprehensive analysis of the results shows that the landing site and its surrounding area are identified as typical lunar mare with flat topography. They are suitable for maneuvers by the rover, and are rich in geological phenomena and scientific targets, making it an ideal site for exploration.展开更多
The Kehdolan area is located at 20 kilometers to the?south-east of Dozdozan Town (Eastern Azarbaijan Province). According to structural geology, volconic rocks are situated in Alborz-Azarbyjan zone, and faults?are?obs...The Kehdolan area is located at 20 kilometers to the?south-east of Dozdozan Town (Eastern Azarbaijan Province). According to structural geology, volconic rocks are situated in Alborz-Azarbyjan zone, and faults?are?observed?in?the?same direction to this system with SE-NW trend. The results show that kaolinite alteration trend with Argilic and propylitic veins?is the?same direction with SW-NE faults in this area. Therefore, these faults with these trends can be considered as the mineralization control for determination of the alterations. Different image processing techniques,?such as false color composite?(FCC), band ratios, color ratio composite?(CRC), principal component?analysis?(PCA), Crosta technique, supervised spectral angle mapping?(SAM), are used for?identification of the alteration zones associated with copper mineralization. In this project ASTER?data are process and spectral analysis to fit for recognizing intensity and kind of argillic, propylitic,?philic, and ETM+ data?which?are process and to fit for iron oxide and relation to metal mineralization of the area. For recognizing different alterations of the study area, some chemical and mineralogical analysis data from the samples showed that ASTER data and ETM+ data were?capable of hydrothermal alteration mapping with copper mineralization.?Copper mineralization in the region is in agreement with argillic alteration. SW-NE trending faults controlled the mineralization process.展开更多
In this editorial,we comment on the recent article by Fei et al exploring the field of near-infrared spectroscopy(NIRS)research in schizophrenia from a bibliometrics perspective.In recent years,NIRS has shown unique a...In this editorial,we comment on the recent article by Fei et al exploring the field of near-infrared spectroscopy(NIRS)research in schizophrenia from a bibliometrics perspective.In recent years,NIRS has shown unique advantages in the auxiliary diagnosis of schizophrenia,and the introduction of bibliometrics has provided a macro perspective for research in this field.Despite the opportunities brought about by these technological developments,remaining challenges require multidi-sciplinary approach to devise a reliable and accurate diagnosis system for schizo-phrenia.Nonetheless,NIRS-assisted technology is expected to contribute to the division of methods for early intervention and treatment of schizophrenia.展开更多
An astronomical observatory is the core component of any astronomical research facility that connects astronomers with their lab: the Cosmos. The research quality of an astronomical facility is rooted in the precision...An astronomical observatory is the core component of any astronomical research facility that connects astronomers with their lab: the Cosmos. The research quality of an astronomical facility is rooted in the precision of data, collected by its observatory. For optimal performance, an observatory is sited while considering certain astronomical, environmental, geological and social parameters. This study aims to identify the potential sites in Pakistan for locating an optical-astronomical observatory using the Multicriteria Decision Analysis(MCDA) technique. The study uses the Analytic Hierarchy Process(AHP) for deriving the influence weights of nine evaluation criteria: Photometric Night Fraction;Night-time Sky Brightness;Sky Transparency;Aerosol Concentration;Altitude;Terrain Slope;Accessibility;Seismic Vulnerability;and Landuse/Land Cover. On the basis of experts’ opinions and previous studies, the evaluation criteria have been ordered in two possible preference sequences for identifying their influence weights with respect to each other for taking part in MCDA. Consequently, the process of MCDA identified certain areas with respect to each preference sequence, whereas some areas were found to be suitable according to both preference sequences. The study synchronizes the required eclectic data into an evaluation matrix that augments the process of astronomical site selection. In the future, this study will be useful for astronomical societies and for furthering astronomical research in the country.展开更多
Sunspots are the most striking and easily observed magnetic structures of the Sun,and statistical analysis of solar historical data could reveal a wealth of information on the long-term variation of solar activity cyc...Sunspots are the most striking and easily observed magnetic structures of the Sun,and statistical analysis of solar historical data could reveal a wealth of information on the long-term variation of solar activity cycle.The hand-drawn sunspot records of Yunnan Observatories,Chinese Academy of Sciences have been accumulating for more than 60 years,and nearly 16000 images have been preserved.In the future,the observation mode of recording sunspots by hand-drawing will be replaced inevitably by digital images observed either at ground or in space.To connect the hand-drawn sunspot data and the purely digital sunspot data in future,it is necessary to analyze the systematic errors of the data which are observed by the two observation modes in the period of transition.In this paper,we choose 268 round sunspots(Htype in modified Zurich sunspot classification)from the drawing of Yunnan Observatories to compare their positions and areas with the CCD observations made by Helioseismic and Magnetic Imager(HMI)on board Solar Dynamic Observatory(SDO)and Global Oscillation Network Group(GONG).We find that the latitude and longitude accuracy of hand-drawn sunspot are within-0.127 and 2.29 degree respectively,and the area accuracy is about 16.36 sunspot unit(μHem).Systematic errors apparently decrease with large sunspot.展开更多
Classification of edge-on galaxies is important to astronomical studies due to our Milky Way galaxy being an edge-on galaxy.Edge-on galaxies pose a problem to classification due to their less overall brightness levels...Classification of edge-on galaxies is important to astronomical studies due to our Milky Way galaxy being an edge-on galaxy.Edge-on galaxies pose a problem to classification due to their less overall brightness levels and smaller numbers of pixels.In the current work,a novel technique for the classification of edge-on galaxies has been developed.This technique is based on the mathematical treatment of galaxy brightness data from their images.A special treatment for galaxies’brightness data is developed to enhance faint galaxies and eliminate adverse effects of high brightness backgrounds as well as adverse effects of background bright stars.A novel slimness weighting factor is developed to classify edge-on galaxies based on their slimness.The technique has the capacity to be optimized for different catalogs with different brightness levels.In the current work,the developed technique is optimized for the EFIGI catalog and is trained using a set of 1800 galaxies from this catalog.Upon classification of the full set of 4458 galaxies from the EFIGI catalog,an accuracy of 97.5% has been achieved,with an average processing time of about 0.26 seconds per galaxy on an average laptop.展开更多
In this study the medium-term response of beach profiles was investigated at two sites： a gently sloping sandy beach and a steeper mixed sand and gravel beach. The former is the Duck site in North Carolina, on the ea...In this study the medium-term response of beach profiles was investigated at two sites： a gently sloping sandy beach and a steeper mixed sand and gravel beach. The former is the Duck site in North Carolina, on the east coast of the USA, which is exposed to Atlantic Ocean swells and storm waves, and the latter is the Milford-on-Sea site at Christchurch Bay, on the south coast of England, which is partially sheltered from Atlantic swells but has a directionally bimodal wave exposure. The data sets comprise detailed bathymetric surveys of beach profiles covering a period of more than 25 years for the Duck site and over 18 years for the Milford-on-Sea site. The structure of the data sets and the data-driven methods are described. Canonical correlation analysis （CCA） was used to find linkages between the wave characteristics and beach profiles. The sensitivity of the linkages was investigated by deploying a wave height threshold to filter out the smaller waves incrementally. The results of the analysis indicate that, for the gently sloping sandy beach, waves of all heights are important to the morphological response. For the mixed sand and gravel beach, filtering the smaller waves improves the statistical fit and it suggests that low-height waves do not play a primary role in the medium-term morohological resoonse, which is primarily driven by the intermittent larger storm waves.展开更多
The extraction of high-temperature regions in active regions(ARs)is an important means to help understand the mechanism of coronal heating.The important observational means of high-temperature radiation in ARs is the ...The extraction of high-temperature regions in active regions(ARs)is an important means to help understand the mechanism of coronal heating.The important observational means of high-temperature radiation in ARs is the main emission line of Fe XVⅢin the 94?of the Atmospheric Imaging Assembly.However,the diagnostic algorithms for Fe XVⅢ,including the differential emission measure(DEM)and linear diagnostics proposed by Del based on the DEM,have been greatly limited for a long time,and the results obtained are different from the predictions.In this paper,we use the outlier detection method to establish the nonlinear correlation between 94?and 171,193,211?based on the former researches by others.A neural network based on 171,193,211?is constructed to replace the low-temperature emission lines in the ARs of 94?.The predicted results are regarded as the low-temperature components of 94?,and then the predicted results are subtracted from 94?to obtain the outlier component of 94?,or Fe XVⅢ.Then,the outlier components obtained by neural network are compared with the Fe XVⅢobtained by DEM and Del's method,and a high similarity is found,which proves the reliability of neural network to obtain the high-temperature components of ARs,but there are still many differences.In order to analyze the differences between the Fe XVⅢobtained by the three methods,we subtract the Fe XVⅢobtained by the DEM and Del's method from the Fe XVⅢobtained by the neural network to obtain the residual value,and compare it with the results of Fe XIV in the temperature range of 6.1-6.45 MK.It is found that there is a great similarity,which also shows that the Fe XVⅢobtained by DEM and Del's method still has a large low-temperature component dominated by Fe XIV,and the Fe XVⅢobtained by neural network is relatively pure.展开更多
In order to search for intensity fluctuations on the HCN（1-0） and HCO＋（1-0） line pro- files, which could arise due to possible small-scale inhomogeneous structure, long-term observations of high-mass star-forming...In order to search for intensity fluctuations on the HCN（1-0） and HCO＋（1-0） line pro- files, which could arise due to possible small-scale inhomogeneous structure, long-term observations of high-mass star-forming cores S140 and S199 were carried out. The data were processed by the Fourier filtering method. Line temperature fluctuations that exceed the noise level were detected. Assuming the cores consist of a large number of randomly moving small thermal fragments, the total number of frag- ments is - 4 × 106 for the region with linear size - 0.1 pc in S140 and - 106 for the region with linear size - 0.3 pc in S 199. Physical parameters of fragments in S 140 were obtained from detailed modeling of the HCN emission in the framework of the clumpy cloud model.展开更多
Olivine and pyroxene are important mineral end-members for studying the surface material compositions of mafic bodies.The profiles of visible and near-infrared spectra of olivine-orthopyroxene mixtures systematically ...Olivine and pyroxene are important mineral end-members for studying the surface material compositions of mafic bodies.The profiles of visible and near-infrared spectra of olivine-orthopyroxene mixtures systematically vary with their composition ratios.In our experiments,we combine the RELAB spectral database with new spectral data obtained from some assembled olivine-orthopyroxene mixtures.We found that the commonly-used band area ratio(BAR,Cloutis et al.)does not work well on our newly obtained spectral data.To investigate this issue,an empirical procedure based on fitted results by a modified Gaussian model is proposed to analyze the spectral curves.Following the new empirical procedure,the endmember abundances can be estimated with a 15%accuracy with some prior mineral absorption features.In addition,the mixture samples configured in our experiments are also irradiated by pulsed lasers to simulate and investigate the space weathering effects.Spectral deconvolution results confirm that low-content olivine on celestial bodies is difficult to measure and estimate.Therefore,the olivine abundance of space weathered materials may be underestimated from remote sensing data.This study may be utilized to quantify the spectral relationship of olivine-orthopyroxene mixtures and further reveal their correlation between the spectra of ordinary chondrites and silicate asteroids.展开更多
We performed detailed time-resolved spectroscopy of bright tong gamma- ray bursts （GRBs） which show significant GeV emissions （GRB 080916C, GRB 090902B and GRB 090926A）. In addition to the standard Band model, we ...We performed detailed time-resolved spectroscopy of bright tong gamma- ray bursts （GRBs） which show significant GeV emissions （GRB 080916C, GRB 090902B and GRB 090926A）. In addition to the standard Band model, we also use a model consisting of a black body and a power law to fit the spectra. We find that for the latter model there are indications of an additional soft component in the spectra. While previous studies have shown that such models are required for GRB 090902B, here we find that a composite spectral model consisting of two blackbodies and a power law adequately fits the data of all the three bright GRBs. We investigate the evolution of the spectral parameters and find several interesting features that appear in all three GRBs, like （a） temperatures of the blackbodies are strongly correlated with each other, （b） fluxes in the black body components are strongly correlated with each other, （c） the temperatures of the black body trace the profile of the individual pulses of the GRBs, and （d） the characteristics of power law components like the spectral index and the delayed onset bear a close similarity to the emission characteristics in the GeV regions. We discuss the implications of these results and the possibility of identifying the radiation mechanisms during the prompt emission of GRBs.展开更多
The cross-efficiency evaluation method is reviewed which is developed as a data envelopment analysis （DEA） extensive tool. The cross-efficiency evaluation method is utilized to identify the decision making unit （DM...The cross-efficiency evaluation method is reviewed which is developed as a data envelopment analysis （DEA） extensive tool. The cross-efficiency evaluation method is utilized to identify the decision making unit （DMU） with the best practice and to rank the DMUs by their respective cross-efficiency scores. The main drawbacks of the cross-efficiency evaluation method when the ultimate average cross-efficiency scores are used to evalu- ate and rank the DMUs are also pointed out. With the research gap, an improved technique for order preference by similarity to ideal solution （TOPSIS） is introduced to rank the crossfficiency by eliminating the average assumption. Finally, an empirical example is illustrated to examine the validity of the proposed method.展开更多
A ground data analysis center is very important to the success of a mission.We introduce the Science Operations and Data Center(SODC)for the ASO-S mission,which consists of a scientific operation subcenter,a data mana...A ground data analysis center is very important to the success of a mission.We introduce the Science Operations and Data Center(SODC)for the ASO-S mission,which consists of a scientific operation subcenter,a data management subcenter,a data analysis subcenter and a user service subcenter.The mission planning process,instrument observation modes and the data volume are presented.We describe the data flow and processing procedures from spacecraft telemetry to high-level science data,and the long-term archival as well.The data policy and distributions are also briefly introduced.展开更多
Traditional hourly rain gauges and automatic weather stations rarely measure solid precipitation, except for those stations with weighing-type precipitation sensors. Microwave remote sensing has only a low ability to ...Traditional hourly rain gauges and automatic weather stations rarely measure solid precipitation, except for those stations with weighing-type precipitation sensors. Microwave remote sensing has only a low ability to retrieve solid precipitation. In addition, there are no long-term, high-quality precipitation data in China that can be used to drive land surface models. To address these issues, in the China Meteorological Administration(CMA) Land Data Assimilation System(CLDAS), we blended the Climate Prediction Center(CPC) morphing technique(CMORPH) and Modern-Era Retrospective analysis for Research and Applications version 2(MERRA2) precipitation datasets with observed temperature and precipitation data on various temporal scales using multigrid variational analysis and temporal downscaling to produce a multi-source precipitation fusion dataset for China(CLDAS-Prcp). This dataset covers all of China at a resolution of 6.25 km at hourly intervals from 1998 to 2018. We performed dependent and independent evaluations of the CLDAS-Prcp dataset from the perspectives of seasonal total precipitation and land surface model simulation. Our results show that the CLDAS-Prcp dataset represents reasonably the spatial distribution of precipitation in China. The dependent evaluation indicates that the CLDAS-Prcp performs better than the MERRA2 precipitation, CMORPH precipitation, Global Land Data Assimilation System version 2(GLDAS-V2.1) precipitation,and CLDAS-V2.0 winter precipitation, as compared to the meteorological observational precipitation. The independent evaluation indicates that the CLDAS-Prcp dataset performs better than the Global Precipitation Measurement(GPM) precipitation dataset and is similar to the CLDAS-V2.0 summer precipitation dataset based on the hydrological observational precipitation. The simulated soil moisture content driven by CLDAS-Prcp is slightly better than that driven by the CLDAS-V2.0 precipitation, whereas the snow depth simulation driven by CLDAS-Prcp is much better than that driven by the CLDAS-V2.0 precipitation. This is because the CLDAS-Prcp data have included solid precipitation. Overall, the CLDAS-Prcp dataset can meet the needs of land surface and hydrological modeling studies.展开更多
The application of data mining in astronomical surveys,such as the Large Sky Area MultiObject Fiber Spectroscopic Telescope(LAMOST)survey,provides an effective approach to automatically analyze a large amount of compl...The application of data mining in astronomical surveys,such as the Large Sky Area MultiObject Fiber Spectroscopic Telescope(LAMOST)survey,provides an effective approach to automatically analyze a large amount of complex survey data.Unsupervised clustering could help astronomers find the associations and outliers in a big data set.In this paper,we employ the k-means method to perform clustering for the line index of LAMOST spectra with the powerful software Astro Stat.Implementing the line index approach for analyzing astronomical spectra is an effective way to extract spectral features for low resolution spectra,which can represent the main spectral characteristics of stars.A total of 144 340 line indices for A type stars is analyzed through calculating their intra and inter distances between pairs of stars.For intra distance,we use the definition of Mahalanobis distance to explore the degree of clustering for each class,while for outlier detection,we define a local outlier factor for each spectrum.Astro Stat furnishes a set of visualization tools for illustrating the analysis results.Checking the spectra detected as outliers,we find that most of them are problematic data and only a few correspond to rare astronomical objects.We show two examples of these outliers,a spectrum with abnormal continuum and a spectrum with emission lines.Our work demonstrates that line index clustering is a good method for examining data quality and identifying rare objects.展开更多
We investigate the wavelet transform of yearly mean relative sunspot number series from 1700 to 2002. The curve of the global wavelet power spectrum peaks at 11-yr, 53-yr and 101-yr periods. The evolution of the ampli...We investigate the wavelet transform of yearly mean relative sunspot number series from 1700 to 2002. The curve of the global wavelet power spectrum peaks at 11-yr, 53-yr and 101-yr periods. The evolution of the amplitudes of the three periods is studied. The results show that around 1750 and 1800, the amplitude of the 53-yr period was much higher than that of the the 11-yr period, that the ca. 53-yr period was apparent only for the interval from 1725 to 1850, and was very low after 1850, that around 1750, 1800 and 1900, the amplitude of the 101-yr period was higher than that of the 11-yr period and that, from 1940 to 2000, the 11-yr period greatly dominates over the other two periods.展开更多
文摘Quantitative analysis of digital images requires detection and segmentation of the borders of the object of interest. Accurate segmentation is required for volume determination, 3D rendering, radiation therapy, and surgery planning. In medical images, segmentation has traditionally been done by human experts. Substantial computational and storage requirements become especially acute when object orientation and scale have to be considered. Therefore, automated or semi-automated segmentation techniques are essential if these software applications are ever to gain widespread clinical use. Many methods have been proposed to detect and segment 2D shapes, most of which involve template matching. Advanced segmentation techniques called Snakes or active contours have been used, considering deformable models or templates. The main purpose of this work is to apply segmentation techniques for the definition of 3D organs (anatomical structures) when big data information has been stored and must be organized by the doctors for medical diagnosis. The processes would be implemented in the CT images from patients with COVID-19.
基金supported by the major scientific and technological research project of Chongqing Education Commission(KJZD-M202000802)The first batch of Industrial and Informatization Key Special Fund Support Projects in Chongqing in 2022(2022000537).
文摘As COVID-19 poses a major threat to people’s health and economy,there is an urgent need for forecasting methodologies that can anticipate its trajectory efficiently.In non-stationary time series forecasting jobs,there is frequently a hysteresis in the anticipated values relative to the real values.The multilayer deep-time convolutional network and a feature fusion network are combined in this paper’s proposal of an enhanced Multilayer Deep Time Convolutional Neural Network(MDTCNet)for COVID-19 prediction to address this problem.In particular,it is possible to record the deep features and temporal dependencies in uncertain time series,and the features may then be combined using a feature fusion network and a multilayer perceptron.Last but not least,the experimental verification is conducted on the prediction task of COVID-19 real daily confirmed cases in the world and the United States with uncertainty,realizing the short-term and long-term prediction of COVID-19 daily confirmed cases,and verifying the effectiveness and accuracy of the suggested prediction method,as well as reducing the hysteresis of the prediction results.
基金funded by the National Natural Science Foundation of China (Grant No. 51575388)
文摘Due to the low spatial resolution of images taken from the Chang＇e-1 （CE-I） orbiter, the details of the lunar surface are blurred and lost. Considering the limited spatial resolution of image data obtained by a CCD camera on CE-1, an example-based super-resolution （SR） algorithm is employed to obtain high- resolution （HR） images. SR reconstruction is important for the application of image data to increase the resolution of images. In this article, a novel example-based algorithm is proposed to implement SR reconstruction by single-image analysis, and the computational cost is reduced compared to other example-based SR methods. The results show that this method can enhance the resolution of images using SR and recover detailed information about the lunar surface. Thus it can be used for surveying HR terrain and geological features. Moreover, the algorithm is significant for the HR processing of remotely sensed images obtained by other imaging systems.
基金funded by the National Natural Science Foundation of China(NSFC,Nos.12373086 and 12303082)CAS“Light of West China”Program+2 种基金Yunnan Revitalization Talent Support Program in Yunnan ProvinceNational Key R&D Program of ChinaGravitational Wave Detection Project No.2022YFC2203800。
文摘Attitude is one of the crucial parameters for space objects and plays a vital role in collision prediction and debris removal.Analyzing light curves to determine attitude is the most commonly used method.In photometric observations,outliers may exist in the obtained light curves due to various reasons.Therefore,preprocessing is required to remove these outliers to obtain high quality light curves.Through statistical analysis,the reasons leading to outliers can be categorized into two main types:first,the brightness of the object significantly increases due to the passage of a star nearby,referred to as“stellar contamination,”and second,the brightness markedly decreases due to cloudy cover,referred to as“cloudy contamination.”The traditional approach of manually inspecting images for contamination is time-consuming and labor-intensive.However,we propose the utilization of machine learning methods as a substitute.Convolutional Neural Networks and SVMs are employed to identify cases of stellar contamination and cloudy contamination,achieving F1 scores of 1.00 and 0.98 on a test set,respectively.We also explore other machine learning methods such as ResNet-18 and Light Gradient Boosting Machine,then conduct comparative analyses of the results.
基金Supported by the National Natural Science Foundation of China
文摘Chang＇e-3 （CE-3） landed on the Mare Imbrium basin in the east part of Sinus Iridum （19.51°W, 44.12°N）, which was China＇s first soft landing on the Moon and it started collecting data on the lunar surface environment. To better understand the environment of this region, this paper utilizes the available high-resolution topography data, image data and geological data to carry out a detailed analysis and research on the area surrounding the landing site （Sinus Iridum and 45 km×70 km of the landing area） as well as on the topography, landform, geology and lunar dust of the area surrounding the landing site. A general topographic analysis of the surrounding area is based on a digital elevation model and digital elevation model data acquired by Chang＇e-2 that have high resolution; the geology analysis is based on lunar geological data published by USGS; the study on topographic factors and distribution of craters and rocks in the surrounding area covering 4km^4km or even smaller is based on images from the CE-3 landing camera and images from the topographic camera; an analysis is done of the effect of the CE-3 engine plume on the lunar surface by comparing images before and after the landing using data from the landing camera. A comprehensive analysis of the results shows that the landing site and its surrounding area are identified as typical lunar mare with flat topography. They are suitable for maneuvers by the rover, and are rich in geological phenomena and scientific targets, making it an ideal site for exploration.
文摘The Kehdolan area is located at 20 kilometers to the?south-east of Dozdozan Town (Eastern Azarbaijan Province). According to structural geology, volconic rocks are situated in Alborz-Azarbyjan zone, and faults?are?observed?in?the?same direction to this system with SE-NW trend. The results show that kaolinite alteration trend with Argilic and propylitic veins?is the?same direction with SW-NE faults in this area. Therefore, these faults with these trends can be considered as the mineralization control for determination of the alterations. Different image processing techniques,?such as false color composite?(FCC), band ratios, color ratio composite?(CRC), principal component?analysis?(PCA), Crosta technique, supervised spectral angle mapping?(SAM), are used for?identification of the alteration zones associated with copper mineralization. In this project ASTER?data are process and spectral analysis to fit for recognizing intensity and kind of argillic, propylitic,?philic, and ETM+ data?which?are process and to fit for iron oxide and relation to metal mineralization of the area. For recognizing different alterations of the study area, some chemical and mineralogical analysis data from the samples showed that ASTER data and ETM+ data were?capable of hydrothermal alteration mapping with copper mineralization.?Copper mineralization in the region is in agreement with argillic alteration. SW-NE trending faults controlled the mineralization process.
文摘In this editorial,we comment on the recent article by Fei et al exploring the field of near-infrared spectroscopy(NIRS)research in schizophrenia from a bibliometrics perspective.In recent years,NIRS has shown unique advantages in the auxiliary diagnosis of schizophrenia,and the introduction of bibliometrics has provided a macro perspective for research in this field.Despite the opportunities brought about by these technological developments,remaining challenges require multidi-sciplinary approach to devise a reliable and accurate diagnosis system for schizo-phrenia.Nonetheless,NIRS-assisted technology is expected to contribute to the division of methods for early intervention and treatment of schizophrenia.
文摘An astronomical observatory is the core component of any astronomical research facility that connects astronomers with their lab: the Cosmos. The research quality of an astronomical facility is rooted in the precision of data, collected by its observatory. For optimal performance, an observatory is sited while considering certain astronomical, environmental, geological and social parameters. This study aims to identify the potential sites in Pakistan for locating an optical-astronomical observatory using the Multicriteria Decision Analysis(MCDA) technique. The study uses the Analytic Hierarchy Process(AHP) for deriving the influence weights of nine evaluation criteria: Photometric Night Fraction;Night-time Sky Brightness;Sky Transparency;Aerosol Concentration;Altitude;Terrain Slope;Accessibility;Seismic Vulnerability;and Landuse/Land Cover. On the basis of experts’ opinions and previous studies, the evaluation criteria have been ordered in two possible preference sequences for identifying their influence weights with respect to each other for taking part in MCDA. Consequently, the process of MCDA identified certain areas with respect to each preference sequence, whereas some areas were found to be suitable according to both preference sequences. The study synchronizes the required eclectic data into an evaluation matrix that augments the process of astronomical site selection. In the future, this study will be useful for astronomical societies and for furthering astronomical research in the country.
基金supported by the National Natural Science Foundation of China(Grant Nos.U1731124,U1531247,11427901 and 11873089)the special foundation work of the Ministry of Science and Technology of China(Grant No.2014FY120300)+1 种基金the 13th Five-year Informatization Plan of Chinese Academy of Sciences(Grant No.XXH13505–04)the Youth Innovation Promotion Association CAS.The hand-drawing historic。
文摘Sunspots are the most striking and easily observed magnetic structures of the Sun,and statistical analysis of solar historical data could reveal a wealth of information on the long-term variation of solar activity cycle.The hand-drawn sunspot records of Yunnan Observatories,Chinese Academy of Sciences have been accumulating for more than 60 years,and nearly 16000 images have been preserved.In the future,the observation mode of recording sunspots by hand-drawing will be replaced inevitably by digital images observed either at ground or in space.To connect the hand-drawn sunspot data and the purely digital sunspot data in future,it is necessary to analyze the systematic errors of the data which are observed by the two observation modes in the period of transition.In this paper,we choose 268 round sunspots(Htype in modified Zurich sunspot classification)from the drawing of Yunnan Observatories to compare their positions and areas with the CCD observations made by Helioseismic and Magnetic Imager(HMI)on board Solar Dynamic Observatory(SDO)and Global Oscillation Network Group(GONG).We find that the latitude and longitude accuracy of hand-drawn sunspot are within-0.127 and 2.29 degree respectively,and the area accuracy is about 16.36 sunspot unit(μHem).Systematic errors apparently decrease with large sunspot.
文摘Classification of edge-on galaxies is important to astronomical studies due to our Milky Way galaxy being an edge-on galaxy.Edge-on galaxies pose a problem to classification due to their less overall brightness levels and smaller numbers of pixels.In the current work,a novel technique for the classification of edge-on galaxies has been developed.This technique is based on the mathematical treatment of galaxy brightness data from their images.A special treatment for galaxies’brightness data is developed to enhance faint galaxies and eliminate adverse effects of high brightness backgrounds as well as adverse effects of background bright stars.A novel slimness weighting factor is developed to classify edge-on galaxies based on their slimness.The technique has the capacity to be optimized for different catalogs with different brightness levels.In the current work,the developed technique is optimized for the EFIGI catalog and is trained using a set of 1800 galaxies from this catalog.Upon classification of the full set of 4458 galaxies from the EFIGI catalog,an accuracy of 97.5% has been achieved,with an average processing time of about 0.26 seconds per galaxy on an average laptop.
基金supported by the UK Natural Environment Research Council(Grant No.NE/J005606/1)the UK Engineering and Physical Sciences Research Council(Grant No.EP/C005392/1)the Ensemble Estimation of Flood Risk in a Changing Climate(EFRa CC)project funded by the British Council under its Global Innovation Initiative
文摘In this study the medium-term response of beach profiles was investigated at two sites： a gently sloping sandy beach and a steeper mixed sand and gravel beach. The former is the Duck site in North Carolina, on the east coast of the USA, which is exposed to Atlantic Ocean swells and storm waves, and the latter is the Milford-on-Sea site at Christchurch Bay, on the south coast of England, which is partially sheltered from Atlantic swells but has a directionally bimodal wave exposure. The data sets comprise detailed bathymetric surveys of beach profiles covering a period of more than 25 years for the Duck site and over 18 years for the Milford-on-Sea site. The structure of the data sets and the data-driven methods are described. Canonical correlation analysis （CCA） was used to find linkages between the wave characteristics and beach profiles. The sensitivity of the linkages was investigated by deploying a wave height threshold to filter out the smaller waves incrementally. The results of the analysis indicate that, for the gently sloping sandy beach, waves of all heights are important to the morphological response. For the mixed sand and gravel beach, filtering the smaller waves improves the statistical fit and it suggests that low-height waves do not play a primary role in the medium-term morohological resoonse, which is primarily driven by the intermittent larger storm waves.
基金supported by the National Natural Science Foundation of China under Grant Nos.U2031140,11873027,and 12073077。
文摘The extraction of high-temperature regions in active regions(ARs)is an important means to help understand the mechanism of coronal heating.The important observational means of high-temperature radiation in ARs is the main emission line of Fe XVⅢin the 94?of the Atmospheric Imaging Assembly.However,the diagnostic algorithms for Fe XVⅢ,including the differential emission measure(DEM)and linear diagnostics proposed by Del based on the DEM,have been greatly limited for a long time,and the results obtained are different from the predictions.In this paper,we use the outlier detection method to establish the nonlinear correlation between 94?and 171,193,211?based on the former researches by others.A neural network based on 171,193,211?is constructed to replace the low-temperature emission lines in the ARs of 94?.The predicted results are regarded as the low-temperature components of 94?,and then the predicted results are subtracted from 94?to obtain the outlier component of 94?,or Fe XVⅢ.Then,the outlier components obtained by neural network are compared with the Fe XVⅢobtained by DEM and Del's method,and a high similarity is found,which proves the reliability of neural network to obtain the high-temperature components of ARs,but there are still many differences.In order to analyze the differences between the Fe XVⅢobtained by the three methods,we subtract the Fe XVⅢobtained by the DEM and Del's method from the Fe XVⅢobtained by the neural network to obtain the residual value,and compare it with the results of Fe XIV in the temperature range of 6.1-6.45 MK.It is found that there is a great similarity,which also shows that the Fe XVⅢobtained by DEM and Del's method still has a large low-temperature component dominated by Fe XIV,and the Fe XVⅢobtained by neural network is relatively pure.
基金support of the RFBR grants(projects 15–02–06098,16–02–00761 and18–02–00660)support of the Russian Science Foundation grant(project 17–12–01256)
文摘In order to search for intensity fluctuations on the HCN（1-0） and HCO＋（1-0） line pro- files, which could arise due to possible small-scale inhomogeneous structure, long-term observations of high-mass star-forming cores S140 and S199 were carried out. The data were processed by the Fourier filtering method. Line temperature fluctuations that exceed the noise level were detected. Assuming the cores consist of a large number of randomly moving small thermal fragments, the total number of frag- ments is - 4 × 106 for the region with linear size - 0.1 pc in S140 and - 106 for the region with linear size - 0.3 pc in S 199. Physical parameters of fragments in S 140 were obtained from detailed modeling of the HCN emission in the framework of the clumpy cloud model.
基金supported by the Foundation of the State Key Laboratory of Lunar and Planetary Sciences, Macao University of Science and Technology, Macao, Chinafunded by The Science and Technology Development Fund, Macao SAR (No. 0073/2019/A2)+2 种基金the support from The Science and Technology Development Fund, Macao SAR (No. 0007/2019/A)supported by Beijing Municipal Science and Technology Commission (No. Z181100002918003)supported by the National Natural Science Foundation of China (NSFC, Nos. 11773023, 11941001, 12073024 and U1631124)
文摘Olivine and pyroxene are important mineral end-members for studying the surface material compositions of mafic bodies.The profiles of visible and near-infrared spectra of olivine-orthopyroxene mixtures systematically vary with their composition ratios.In our experiments,we combine the RELAB spectral database with new spectral data obtained from some assembled olivine-orthopyroxene mixtures.We found that the commonly-used band area ratio(BAR,Cloutis et al.)does not work well on our newly obtained spectral data.To investigate this issue,an empirical procedure based on fitted results by a modified Gaussian model is proposed to analyze the spectral curves.Following the new empirical procedure,the endmember abundances can be estimated with a 15%accuracy with some prior mineral absorption features.In addition,the mixture samples configured in our experiments are also irradiated by pulsed lasers to simulate and investigate the space weathering effects.Spectral deconvolution results confirm that low-content olivine on celestial bodies is difficult to measure and estimate.Therefore,the olivine abundance of space weathered materials may be underestimated from remote sensing data.This study may be utilized to quantify the spectral relationship of olivine-orthopyroxene mixtures and further reveal their correlation between the spectra of ordinary chondrites and silicate asteroids.
文摘We performed detailed time-resolved spectroscopy of bright tong gamma- ray bursts （GRBs） which show significant GeV emissions （GRB 080916C, GRB 090902B and GRB 090926A）. In addition to the standard Band model, we also use a model consisting of a black body and a power law to fit the spectra. We find that for the latter model there are indications of an additional soft component in the spectra. While previous studies have shown that such models are required for GRB 090902B, here we find that a composite spectral model consisting of two blackbodies and a power law adequately fits the data of all the three bright GRBs. We investigate the evolution of the spectral parameters and find several interesting features that appear in all three GRBs, like （a） temperatures of the blackbodies are strongly correlated with each other, （b） fluxes in the black body components are strongly correlated with each other, （c） the temperatures of the black body trace the profile of the individual pulses of the GRBs, and （d） the characteristics of power law components like the spectral index and the delayed onset bear a close similarity to the emission characteristics in the GeV regions. We discuss the implications of these results and the possibility of identifying the radiation mechanisms during the prompt emission of GRBs.
基金supported by the National Natural Science Foundation of China for Innovative Research Groups(70821001),the National Natural Science Foundation of China(70901069)the Special Fund for the Gainers of Excellent Ph.D.'s Dissertations and Dean's Scholarships of Chinese Academy of Sciences,the Research Fund for the Doctoral Program of Higher Education of China for New Teachers(20093402120013)+1 种基金the Research Fund for the Excellent Youth Scholars of Higher School of Anhui Province of China(2010SQRW001ZD)the Social Science Research Fund for Higher School of Anhui Province of China
文摘The cross-efficiency evaluation method is reviewed which is developed as a data envelopment analysis （DEA） extensive tool. The cross-efficiency evaluation method is utilized to identify the decision making unit （DMU） with the best practice and to rank the DMUs by their respective cross-efficiency scores. The main drawbacks of the cross-efficiency evaluation method when the ultimate average cross-efficiency scores are used to evalu- ate and rank the DMUs are also pointed out. With the research gap, an improved technique for order preference by similarity to ideal solution （TOPSIS） is introduced to rank the crossfficiency by eliminating the average assumption. Finally, an empirical example is illustrated to examine the validity of the proposed method.
基金supported by the National Natural Science Foundation of China (Grant Nos. 11203083, 11427803 and U1731241)supported by the Strategic Pioneer Program on Space Science, Chinese Academy of Sciences (Grant Nos. XDA15052200 and XDA15320300)
文摘A ground data analysis center is very important to the success of a mission.We introduce the Science Operations and Data Center(SODC)for the ASO-S mission,which consists of a scientific operation subcenter,a data management subcenter,a data analysis subcenter and a user service subcenter.The mission planning process,instrument observation modes and the data volume are presented.We describe the data flow and processing procedures from spacecraft telemetry to high-level science data,and the long-term archival as well.The data policy and distributions are also briefly introduced.
基金Supported by the National Key Research and Development Program of China(2018YFC1506601)National Natural Science Foundation of China(91437220)+1 种基金China Meteorological Administration Special Public Welfare Research Fund(GYHY201506002 and GYHY201206008)China Meteorological Administration“Meteorological Data Quality Control and Multi-source Data Fusion and Reanalysis”project。
文摘Traditional hourly rain gauges and automatic weather stations rarely measure solid precipitation, except for those stations with weighing-type precipitation sensors. Microwave remote sensing has only a low ability to retrieve solid precipitation. In addition, there are no long-term, high-quality precipitation data in China that can be used to drive land surface models. To address these issues, in the China Meteorological Administration(CMA) Land Data Assimilation System(CLDAS), we blended the Climate Prediction Center(CPC) morphing technique(CMORPH) and Modern-Era Retrospective analysis for Research and Applications version 2(MERRA2) precipitation datasets with observed temperature and precipitation data on various temporal scales using multigrid variational analysis and temporal downscaling to produce a multi-source precipitation fusion dataset for China(CLDAS-Prcp). This dataset covers all of China at a resolution of 6.25 km at hourly intervals from 1998 to 2018. We performed dependent and independent evaluations of the CLDAS-Prcp dataset from the perspectives of seasonal total precipitation and land surface model simulation. Our results show that the CLDAS-Prcp dataset represents reasonably the spatial distribution of precipitation in China. The dependent evaluation indicates that the CLDAS-Prcp performs better than the MERRA2 precipitation, CMORPH precipitation, Global Land Data Assimilation System version 2(GLDAS-V2.1) precipitation,and CLDAS-V2.0 winter precipitation, as compared to the meteorological observational precipitation. The independent evaluation indicates that the CLDAS-Prcp dataset performs better than the Global Precipitation Measurement(GPM) precipitation dataset and is similar to the CLDAS-V2.0 summer precipitation dataset based on the hydrological observational precipitation. The simulated soil moisture content driven by CLDAS-Prcp is slightly better than that driven by the CLDAS-V2.0 precipitation, whereas the snow depth simulation driven by CLDAS-Prcp is much better than that driven by the CLDAS-V2.0 precipitation. This is because the CLDAS-Prcp data have included solid precipitation. Overall, the CLDAS-Prcp dataset can meet the needs of land surface and hydrological modeling studies.
基金supported by the Joint Research Fund in Astronomy (U1631239) under cooperative agreement between the National Natural Science Foundation of China (NSFC) and Chinese Academy of Sciences (CAS)supported by the International Science and Technology Cooperation Program of China (2014DFE10030)the Basic Science and Engineering Special Project of Heilongjiang Province Education Department (135109219)
文摘The application of data mining in astronomical surveys,such as the Large Sky Area MultiObject Fiber Spectroscopic Telescope(LAMOST)survey,provides an effective approach to automatically analyze a large amount of complex survey data.Unsupervised clustering could help astronomers find the associations and outliers in a big data set.In this paper,we employ the k-means method to perform clustering for the line index of LAMOST spectra with the powerful software Astro Stat.Implementing the line index approach for analyzing astronomical spectra is an effective way to extract spectral features for low resolution spectra,which can represent the main spectral characteristics of stars.A total of 144 340 line indices for A type stars is analyzed through calculating their intra and inter distances between pairs of stars.For intra distance,we use the definition of Mahalanobis distance to explore the degree of clustering for each class,while for outlier detection,we define a local outlier factor for each spectrum.Astro Stat furnishes a set of visualization tools for illustrating the analysis results.Checking the spectra detected as outliers,we find that most of them are problematic data and only a few correspond to rare astronomical objects.We show two examples of these outliers,a spectrum with abnormal continuum and a spectrum with emission lines.Our work demonstrates that line index clustering is a good method for examining data quality and identifying rare objects.
基金Supported by the National Natural Science Foundation of China
文摘We investigate the wavelet transform of yearly mean relative sunspot number series from 1700 to 2002. The curve of the global wavelet power spectrum peaks at 11-yr, 53-yr and 101-yr periods. The evolution of the amplitudes of the three periods is studied. The results show that around 1750 and 1800, the amplitude of the 53-yr period was much higher than that of the the 11-yr period, that the ca. 53-yr period was apparent only for the interval from 1725 to 1850, and was very low after 1850, that around 1750, 1800 and 1900, the amplitude of the 101-yr period was higher than that of the 11-yr period and that, from 1940 to 2000, the 11-yr period greatly dominates over the other two periods.
