Hue-Saturation-Intensity （HSI） color model, a psychologically appealing color model, was employed to visualize uncertainty represented by relative prediction error based on the case of spatial prediction of pH of to...Hue-Saturation-Intensity （HSI） color model, a psychologically appealing color model, was employed to visualize uncertainty represented by relative prediction error based on the case of spatial prediction of pH of topsoil in the peri-urban Beijing. A two-dimensional legend was designed to accompany the visualization-vertical axis （hues） for visualizing the predicted values and horizontal axis （whiteness） for visualizing the prediction error. Moreover, different ways of visualizing uncertainty were briefly reviewed in this paper. This case study indicated that visualization of both predictions and prediction uncertainty offered a possibility to enhance visual exploration of the data uncertainty and to compare different prediction methods or predictions of totally different variables. The whitish region of the visualization map can be simply interpreted as unsatisfactory prediction results, where may need additional samples or more suitable prediction models for a better prediction results.展开更多
The study developed a triple-exposure color particle image velocimetry(TE-CPIV) technique associated with pressure reconstruction, and validated its feasibility. A light source with the three primary colors of red, gr...The study developed a triple-exposure color particle image velocimetry(TE-CPIV) technique associated with pressure reconstruction, and validated its feasibility. A light source with the three primary colors of red, green, and blue(R, G, and B) is produced in a time sequence by a liquid crystal display(LCD) projector. Particle images at three different instants under the color illuminations are captured in one snapshot using a color digital single-lens reflex(SLR) camera with a complementary metal-oxide semiconductor(CMOS) sensor. A contamination correction algorithm based on a specific calibration is performed on the different color layers(R layer, G layer, and B layer) of the raw color image to reduce the contaminated intensity of each color illumination on the other two color layers. The corrected intensity generates three new color layers, from which a standard cross-correlation process in the classical PIV method is used to obtain two velocity fields. Eventually, an instantaneous pressure field is reconstructed from the two velocity fields. The feasibility of TE-CPIV was tested by two experiments with a solid body rotation flow and a cylinder wake flow. The results show acceptable accuracy and robustness of the new technique. The idea of the TE-CPIV is believed to provide a simple and effective way of estimating a pressure field with low cost and high convenience.展开更多
基金Under the auspices of Knowledge Innovation Frontier Project of Institute of Soil Science,Chinese Academy of Sciences(No.ISSASIP0716 )the National Nature Science Foundation of China ( No.40701070,40571065)
文摘Hue-Saturation-Intensity （HSI） color model, a psychologically appealing color model, was employed to visualize uncertainty represented by relative prediction error based on the case of spatial prediction of pH of topsoil in the peri-urban Beijing. A two-dimensional legend was designed to accompany the visualization-vertical axis （hues） for visualizing the predicted values and horizontal axis （whiteness） for visualizing the prediction error. Moreover, different ways of visualizing uncertainty were briefly reviewed in this paper. This case study indicated that visualization of both predictions and prediction uncertainty offered a possibility to enhance visual exploration of the data uncertainty and to compare different prediction methods or predictions of totally different variables. The whitish region of the visualization map can be simply interpreted as unsatisfactory prediction results, where may need additional samples or more suitable prediction models for a better prediction results.
基金supported by the National Natural Science Foundation of China(Grant Nos.11472030,11327202&11490552)the Fundamental Research Funds for the Central Universities(Grant No.YWF-16-JCTD-A-05)
文摘The study developed a triple-exposure color particle image velocimetry(TE-CPIV) technique associated with pressure reconstruction, and validated its feasibility. A light source with the three primary colors of red, green, and blue(R, G, and B) is produced in a time sequence by a liquid crystal display(LCD) projector. Particle images at three different instants under the color illuminations are captured in one snapshot using a color digital single-lens reflex(SLR) camera with a complementary metal-oxide semiconductor(CMOS) sensor. A contamination correction algorithm based on a specific calibration is performed on the different color layers(R layer, G layer, and B layer) of the raw color image to reduce the contaminated intensity of each color illumination on the other two color layers. The corrected intensity generates three new color layers, from which a standard cross-correlation process in the classical PIV method is used to obtain two velocity fields. Eventually, an instantaneous pressure field is reconstructed from the two velocity fields. The feasibility of TE-CPIV was tested by two experiments with a solid body rotation flow and a cylinder wake flow. The results show acceptable accuracy and robustness of the new technique. The idea of the TE-CPIV is believed to provide a simple and effective way of estimating a pressure field with low cost and high convenience.
