The Experts below are selected from a list of 501 Experts worldwide ranked by ideXlab platform

Changxi Ma - One of the best experts on this subject based on the ideXlab platform.

  • The analysis of urban taxi carpooling impact from taxi GPS data
    Archives of Transport, 2018
    Co-Authors: Qiang Xiao, Ruichun He, Changxi Ma
    Abstract:

    Taxi is an important part of urban passenger transportation system. The research and analysis of taxi trip behavior is the key to meet the demand of urban passenger transport and solve the traffic congestion problem. Based on the GPS data of taxis in Nanjing, the statistical method is used to analyze the taxi characteristics of the average number of passengers, the average passenger time, the no-load distance and the passenger distance. By using the Double Logarithmic Coordinate, the trip distance and trip time of taxi passengers are analyzed, it is found that the average trip distance of taxi passengers is mainly concentrated in 3-20km, and the average trip time of taxi passengers is mainly concentrated in 10-30 minutes. Using the information entropy theory to construct the equilibrium model of taxi passenger-carrying point, and analyze the spatial distribution of taxi, it is found that the distribution of urban taxi is unbalanced. The peak clustering algorithm is used to determine the location of passenger gathering points, and the hot spot of taxi trip is analyzed, it is found that the hot spots of taxi trip are mainly concentrated in the central city of Nanjing. Combined with the results of urban taxi trip analysis, from the perspective of taxi and passenger, we found that the number of urban taxis, the passenger carrying rate of taxis, the duration period of passenger trip, the duration and distance of passenger trip and the location of passenger trip points will have an impact on the urban taxi carpooling in Nanjing. By using the probability model of urban taxi carpooling, this paper discusses and analyzes the influence of these factors on urban taxi carpooling. The research in this paper can provide a reference for the effective implementation of urban taxi carpooling policy.

Walter E L Spiess - One of the best experts on this subject based on the ideXlab platform.

  • rheological properties of raisins part i compression test
    Journal of Food Engineering, 1995
    Co-Authors: Piotr P Lewicki, Walter E L Spiess
    Abstract:

    Abstract Thompson seedless raisins were subjected to compressive unidirectional force and deformation at constant crosshead speed was measured. Relaxation behaviour of the berry was also studied. The force-apparent strain relationship is described by a straight line on a semi-Logarithmic Coordinate system. The correlation coefficient is high, although the spread of points is large and reflects the geometrical, rheological and chemical heterogeneity of raisins. The stress-true strain curves are composed of both a concave upward and a convex upward part. Curves plotted on a Double-Logarithmic Coordinate system yield straight lines with high correlation coefficients. Analysis shows a tendency for the stiffness of a raisin to increase with increasing load. Calculated work of deformation has shown that the probability of breaking of the raisin is related to the unit work applied to compress the sample. At unit work less than 20 mJ/g the probability of breakage is zero. Relaxation curves normalized according to Peleg and Pollak give straight lines with a very high correlation coefficient. Data collected in this work suggest that the compression of a raisin is a process of relocation of concentrated cell sap enclosed in a berry with a stretching wrinkled skin. During relaxation there is little possibility for the viscous concentrated liquid to move. It exerts pressure on the skin and a high unrelaxed stress remains in a raisin. From a rheological point of view a raisin is a viscoelastic body.

Qiang Xiao - One of the best experts on this subject based on the ideXlab platform.

  • The analysis of urban taxi carpooling impact from taxi GPS data
    Archives of Transport, 2018
    Co-Authors: Qiang Xiao, Ruichun He, Changxi Ma
    Abstract:

    Taxi is an important part of urban passenger transportation system. The research and analysis of taxi trip behavior is the key to meet the demand of urban passenger transport and solve the traffic congestion problem. Based on the GPS data of taxis in Nanjing, the statistical method is used to analyze the taxi characteristics of the average number of passengers, the average passenger time, the no-load distance and the passenger distance. By using the Double Logarithmic Coordinate, the trip distance and trip time of taxi passengers are analyzed, it is found that the average trip distance of taxi passengers is mainly concentrated in 3-20km, and the average trip time of taxi passengers is mainly concentrated in 10-30 minutes. Using the information entropy theory to construct the equilibrium model of taxi passenger-carrying point, and analyze the spatial distribution of taxi, it is found that the distribution of urban taxi is unbalanced. The peak clustering algorithm is used to determine the location of passenger gathering points, and the hot spot of taxi trip is analyzed, it is found that the hot spots of taxi trip are mainly concentrated in the central city of Nanjing. Combined with the results of urban taxi trip analysis, from the perspective of taxi and passenger, we found that the number of urban taxis, the passenger carrying rate of taxis, the duration period of passenger trip, the duration and distance of passenger trip and the location of passenger trip points will have an impact on the urban taxi carpooling in Nanjing. By using the probability model of urban taxi carpooling, this paper discusses and analyzes the influence of these factors on urban taxi carpooling. The research in this paper can provide a reference for the effective implementation of urban taxi carpooling policy.

Yue-jun Sun - One of the best experts on this subject based on the ideXlab platform.

  • Spatial Up-Scaling Correction for Leaf Area Index Based on the Fractal Theory
    Remote Sensing, 2016
    Co-Authors: Qiming Qin, Xiang-nan Liu, Huazhong Ren, Jianhua Wang, Xiao Po Zheng, Yue-jun Sun
    Abstract:

    The scaling effect correction of retrieved parameters is an essential and difficult issue in analysis and application of remote sensing information. Based on fractal theory, this paper developed a scaling transfer model to correct the scaling effect of the leaf area index (LAI) estimated from coarse spatial resolution image. As the key parameter of the proposed model, the information fractal dimension (D) of the up-scaling pixel was calculated by establishing the Double Logarithmic linear relationship between D-2 and the normalized difference vegetation index (NDVI) standard deviation (σNDVI) of the up-scaling pixel. Based on the calculated D and the fractal relationship between the exact LAI and the approximated LAI estimated from the coarse resolution pixel, a LAI scaling transfer model was established. Finally, the model accuracy in correcting the scaling effect was discussed. Results indicated that the D increases with increasing σNDVI, and the D-2 was highly linearly correlated with σNDVI on the Double Logarithmic Coordinate axis. The scaling transfer model corrected the scaling effect of LAI with a maximum value of root-mean-square error (RMSE) of 0.011. The maximum absolute correction error (ACE) and relative correction error (RCE) were only 0.108% and 8.56%, respectively. The spatial heterogeneity was the primary cause resulting in the scaling effect and the key influencing factor of correction effect. The results indicated that the developed method based on fractal theory could effectively correct the scaling effect of LAI estimated from the heterogeneous pixels.

Sun Yuejun - One of the best experts on this subject based on the ideXlab platform.

  • Spatial Up-Scaling Correction for Leaf Area Index Based on the Fractal Theory
    REMOTE SENSING, 2016
    Co-Authors: Wu Ling, Qin Qiming, Liu Xiangnan, Ren Huazhong, Wang Jianhua, Zheng Xiaopo, Ye Xin, Sun Yuejun
    Abstract:

    The scaling effect correction of retrieved parameters is an essential and difficult issue in analysis and application of remote sensing information. Based on fractal theory, this paper developed a scaling transfer model to correct the scaling effect of the leaf area index (LAI) estimated from coarse spatial resolution image. As the key parameter of the proposed model, the information fractal dimension (D) of the up-scaling pixel was calculated by establishing the Double Logarithmic linear relationship between D-2 and the normalized difference vegetation index (NDVI) standard deviation (sigma(NDVI)) of the up-scaling pixel. Based on the calculated D and the fractal relationship between the exact LAI and the approximated LAI estimated from the coarse resolution pixel, a LAI scaling transfer model was established. Finally, the model accuracy in correcting the scaling effect was discussed. Results indicated that the D increases with increasing sigma(NDVI), and the D-2 was highly linearly correlated with sigma(NDVI) on the Double Logarithmic Coordinate axis. The scaling transfer model corrected the scaling effect of LAI with a maximum value of root-mean-square error (RMSE) of 0.011. The maximum absolute correction error (ACE) and relative correction error (RCE) were only 0.108% and 8.56%, respectively. The spatial heterogeneity was the primary cause resulting in the scaling effect and the key influencing factor of correction effect. The results indicated that the developed method based on fractal theory could effectively correct the scaling effect of LAI estimated from the heterogeneous pixels.National Natural Science Foundation of China [41230747, 41401375]; China Post-doctoral Science Foundation Special Program [2015T80012]SCI(E)EIARTICLEwl_19830807@163.com; qmqin@pku.edu.cn; liuxncugb@163.com; renhuazhong@pku.edu.cn; wjhdg@163.com; xiaopo@pku.edu.cn; lanlang524@126.com; syj_1113@163.com3