Zhao R.-B.,Nanjing Normal University |
Zhao R.-B.,Anhui Center for Collaborative Innovation in Geographical Information Integration and Application |
Zhang Y.-L.,Chuzhou University |
Pang M.-Y.,Nanjing Normal University |
Zhao S.-H.,Chuzhou University
Journal of Applied Science and Engineering | Year: 2016
Cloud and fog always lead to unbalance brightness in digital images, which limit information recognition and extraction. Based on an assumption that a cloud-fog covered image is an overlaying result of a normal ground image and a cloud-fog maskimage, this paper proposes an improved method for balancing brightness of digital image by removing cloud-fog effect through the following four steps: generating cloud-fog mask image, subtracting cloud-fog maskimage, choosing reference image, and locally adaptive enhancing. Additionally, in order to avoid time-consuming for large images, a parallel solution is introduced for accelerating the method based on graphics processing unit (GPU) acceleration. Finally, the method was tested by using different cloud-fog covered images, and the experiments verify that the method is effective at balancing brightness and its efficiency can be significantly improved through central processing unit and graphics processing unit (CPU-GPU) cooperative computing.
Zhao S.,Chuzhou University |
Zhao S.,Anhui Center for Collaborative Innovation in Geographical Information Integration and Application |
Chen H.,Chuzhou University |
Chen H.,Anhui Center for Collaborative Innovation in Geographical Information Integration and Application |
And 6 more authors.
Journal of Applied Science and Engineering | Year: 2016
In order to guarantee the cloud service quality, the service should be able to dynamically predict the change of data processing request. Existing prediction methods in cloud are mostly focused on the amount of computing resource required by service. In fact, in cloud computing environment for big data processing, it is not enough to simply predict the computing resource, because when the created virtual machine is far from the data, it will need a certain time to transfer data to the virtual machine for processing. To solve this problem, in this paper, we propose a data-centered prediction method using Bayes classifier, which can make prediction for data type or location based on the data resources needed by the service request. We carry out experiments with Google cluster trace, and the experimental results show that our method performs better than the existing methods. For example, our method improves the load prediction accuracy by 45-60% compared to other state-of-the-art methods based on final state-based method, simple moving average method, linear weighted moving average method, exponential moving average method, and prior probability-based method.
Xu J.,Chuzhou University |
Xu J.,Nanjing University |
Xu J.,Anhui Center for Collaborative Innovation in Geographical Information Integration and Application |
Jiang H.,Nanjing University |
And 6 more authors.
Sustainability (Switzerland) | Year: 2016
The deteriorating air quality in the Yangtze delta region is attracting growing public concern. In this paper, seasonal estimation models of the surface particulate matter (PM) were established by using aerosol optical thickness (AOT) retrievals from the moderate resolution imaging spectro-radiometer (MODIS) on board NASA's Terra satellite. The change of the regional distribution of the atmospheric mixed layer, relative humidity and meteorological elements have been taken into account in these models. We also used PM mass concentrations of ground measurements to evaluate the estimation accuracy of those models. The results show that model estimation of PM2.5 and PM10 mass concentrations were in good agreement with the ground-based observation of PM mass concentrations (p < 0.01, the R2 value of the PM2.5 concentrations experimental model for four seasons are 0.48, 0.62, 0.61 and 0.52 respectively. The R2 value of PM10 concentrations experimental model for four seasons are 0.57, 0.56, 0.64 and 0.68 respectively). At the same time, spatial and temporal variations of PM2.5 and PM10 mass concentrations were analysed over the Yangtze delta region from 2000 to 2013. The results show that PM2.5 and PM10 show a trend of increase in the Yangtze delta region from 2000 to 2013 and change periodically. The maximum mass concentration of PM2.5 and PM10 was in January-February, and the minimum was in July-August. The highest values of PM2.5 and PM10 mass concentration are in the region of urban agglomeration which is grouped to a delta-shaped region by Shanghai, Hangzhou and Nanjing, while the low values are in the forest far away from the city. PM mass concentration over main cities and rural areas increased gradually year by year, and were increasing more quickly in urban areas than in rural areas. © 2016 by the authors.
Zhang Q.,Chuzhou University |
Chen G.,Chuzhou University |
Chen G.,Anhui Center for Collaborative Innovation in Geographical Information Integration and Application |
Zhao L.,Chuzhou University |
Chang C.-Y.,Tamkang University
Journal of Network and Computer Applications | Year: 2016
Bluetooth and IEEE 802.11 (Wi-Fi) are two of the most popular communication standards that define physical and MAC layers for wireless transmissions and operate on 2.4 GHz industrial scientific medical (ISM) band. To avoid the rich interference existed in ISM band, Bluetooth adopts a time-slotted frequency-hopping spread-spectrum scheme, preventing the Bluetooth device communication from being interfered for a long time on specific channel. However, the coexistence of Bluetooth and Wi-Fi in the neighborhood degrades the performance of both networks because the two wireless technologies cannot negotiate with each other. To improve the throughput of a given piconet, this paper presents two interference aware approaches. First, an interference aware piconet establishment mechanism, called IAPE, is proposed to consider the frequencies occupied by Wi-Fi and then minimize the interference from Wi-Fi transmissions, when Bluetooth and Wi-Fi coexist in the same space. To further improve the throughput of the constructed piconet, an interference aware piconet restructuring mechanism, called IAPR, is proposed. Performance study reveals that the proposed IAPE and IAPR approaches further reduce the interference between Bluetooth and Wi-Fi and thereby save the energy of Bluetooth device, improving the throughput of Bluetooth personal area networks (PANs). © 2016 Elsevier Ltd
Li W.,Beijing Forestry University |
Li W.,Chuzhou University |
Li W.,Anhui Center for Collaborative Innovation in Geographical Information Integration and Application |
Wu J.,Chuzhou University |
And 4 more authors.
Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering | Year: 2016
Dustfall is an important indicator to characterize the regional atmospheric environment quality. The dustfall status and regional environmental quality can be reflected directly by dust deposition content on plant leaves. The acquisition of hyperspectral data measured at ground surface is more and more convenient in recent years with the development of hyperspectral technology. Study on inversion model for foliar dust deposition content based on hyperspectral data will improve the efficiency of atmospheric dust monitoring and spatial sampling. And the model can not only be used as an effective complement to traditional atmospheric dust monitoring means, but also improve the time accuracy and spatial accuracy of dustfall monitoring. The aim of exploring the construction of hyperspectral estimation model of foliar dust deposition content is to promote the application of hyperspectral and remote sensing techniques on dustfall monitoring, and provide theoretical basis for the quantitative monitoring of regional dustfall based on the ground hyperspectral data. The adult Beijing poplar leaves were collected in Beijing urban area during the period from September 17 to September 18 in 2014.In order to collect the hyperspectral data and the data of per unit area dust deposition content on leaf samples, the work was carried out in the following sequence: spectral measurement, weighing, dust removal, weighing, spectral measurement, and measurement of leaf area. We finally got 59 valid sample data. We analyzed the influence of foliar dust deposition content on the spectral reflectance and trilateral parameters of poplar leaves. And the relationships between leaf spectral characteristics and foliar dust deposition content were studied. Then, the estimation model of foliar dust deposition content based on spectral parameters was established. The results showed that foliar dust deposition content enhanced the reflectivity of 400-700 nm band and inhibited the reflectivity of 710-1110 nm band. And foliar dust deposition content had no obvious effect on red edge position, yellow edge position and blue edge position. The linear relationship between spectral reflectance of the near infrared wavelengths (730-1000 nm) and foliar dust deposition content was obvious, and the coefficient of each band was higher than 0.7. The reflectance of green band was not sensitive to the influence of leaf dust deposition content. And the relationships between red edge amplitude, red edge area and leaf dust deposition content achieved significant relation. Three correlation coefficients' matrices were constructed by the indices calculated based on different spectra reflectance and foliar dust deposition content. The maximum value in each matrix was higher than the maximum value of correlation coefficient between single band and foliar dust deposition content. The highest value of correlation coefficients of the 3 matrices was 0.7615, which was in the matrix of correlation coefficient of normalized index and foliar dust deposition content. Models based on multivariate linear regression, principal component regression and partial least squares regression all had stronger ability to predict. The partial least squares regression model with the independent variables, which included spectral reflectance at the band of 749, 644 and 514 nm, red edge slope, red edge area, normalized difference index composed by the band of 924 and 1010 nm, difference index composed by the band of 713 and 725 nm, and normalized difference vegetation index composed by the band of 749 and 644 nm, had the highest estimate accuracy with the modeling decision coefficient of 0.734, the forecasting decision coefficient of 0.731, and the root mean square error of 0.311 for prediction. © 2016, Editorial Department of the Transactions of the Chinese Society of Agricultural Engineering. All right reserved.
Liu M.,Nanjing Normal University |
Liu M.,Key Laboratory of Virtual Geographic Environment of Ministry of Education |
Liu M.,Chuzhou University |
Liu M.,Anhui Center for Collaborative Innovation in Geographical Information Integration and Application |
And 4 more authors.
Cehui Xuebao/Acta Geodaetica et Cartographica Sinica | Year: 2016
In view of the fact that drainage line simplification using conversional methods is usually hard to keep the three-dimensional characteristics and topological relationships, this paper proposes a new method of three-dimensional drainage line simplification which maintains topological consistency. It firstly expends the conversional D-P algorithm to three-dimensional in order to keep three-dimensional characteristics during the simplification. Then it constructs tree structures for drainage lines to express their topological relations. Finally, it simplifies river lines and reconstructs topological relations of main streams and their branches according to the hierarchical order of water system tree. The experimental results show that this method has a higher accuracy in simplification and can maintain not only three-dimensional shape characteristics of water system but also the topological consistency at river confluences. © 2016, Surveying and Mapping Press. All right reserved.
Li W.-T.,Beijing Forestry University |
Li W.-T.,Chuzhou University |
Li W.-T.,Anhui Center for Collaborative Innovation in Geographical Information Integration and Application |
Peng D.-L.,Beijing Forestry University |
And 5 more authors.
Guang Pu Xue Yu Guang Pu Fen Xi/Spectroscopy and Spectral Analysis | Year: 2015
The physiological mechanism and ecological structure of forest trees can change with the changes of years. In a certain extent, the changes were expressed through the canopy spectral features. The mastery of changing rules about spectral characteristics of trees over the years is benefit to remote sensing interpretation and provide scientific basis for the classification of different trees. The study adopted high-resolution spectrometer to measure the canopy spectral characteristics for seven major deciduous trees and seven evergreen trees to gain the spectrum curve of four different ages and calculate the first derivative curve. The analysis of changing rules about spectral characteristics of different deciduous trees and evergreen trees and the comparison of changes about spectrum of various trees in the visible and infrared band could find the best year and best band for identification of trees. The results showed that the canopy spectral reflectance of deciduous and evergreen trees increases with the increase of age. And the spectral changes of two species were most obvious in the near infrared band. ©, 2015, Science Press. All right reserved.