Cover ratio of cloud is a very important factor which affects the quality of a satellite image, therefore cloud detection from satellite images is a necessary step in assessing the image quality. The study on cloud de...Cover ratio of cloud is a very important factor which affects the quality of a satellite image, therefore cloud detection from satellite images is a necessary step in assessing the image quality. The study on cloud detection from the visual band of a satellite image is developed. Firstly, we consider the differences between the cloud and ground including high grey level, good continuity of grey level, area of cloud region, and the variance of local fractal dimension (VLFD) of the cloud region. A single cloud region detection method is proposed. Secondly, by introducing a reference satellite image and by comparing the variance in the dimensions corresponding to the reference and the tested images, a method that detects multiple cloud regions and determines whether or not the cloud exists in an image is described. By using several Ikonos images, the performance of the proposed method is demonstrated.展开更多
Digital mine is the inevitable outcome of the information processing, and is also a complicated system engineering. Firstly, for the 3D visualization application of the digital mine, the ground and underground integra...Digital mine is the inevitable outcome of the information processing, and is also a complicated system engineering. Firstly, for the 3D visualization application of the digital mine, the ground and underground integrative visualization framework model was proposed based on the mine entity database. So, the visualization problem was availably resolved, as well as the professional analytical ability was improved. Secondly, aiming at the irregularities, non-uniformity, dynamics of mine entities, mix modeling method based on the entity character was put forward, in which 3D expression of mine entities was realized. Lastly, the 3D visualization project for a copper mine was experimentally studied. Satisfactory results were acquired, and the rationality of visualization model and feasibility of 3D modeling were validated.展开更多
Inclusions with sizes less than 1 μm in molten steel are difficult to float up to the molten steel and slag interface owing to their slow terminal velocity. Thus, increasing the size of inclusion is essential for acc...Inclusions with sizes less than 1 μm in molten steel are difficult to float up to the molten steel and slag interface owing to their slow terminal velocity. Thus, increasing the size of inclusion is essential for accelerating the removal of inclusions. Polystyrene particles simulating inclusions in molten steel were quantified by direct observation of the particle collision behavior in a turbulent flow in a water model. The box-counting fractal dimension of particles was calculated by processing the binary images of aggregated particles. The fractal dimension of the outer contours of the single plastic particles was smaller than that of the aggregated particles. The fractal dimension was varied from 1.14 to 1.35. When two or more monomer particles collide, the aggregates are separated more easily, as the temperature increases from 40 to 80 ℃. The aggregated particles were loose and easy to separate in the high-temperature aqueous solution. The effect of temperature on the surface tension of liquid and the interracial tension of solid and liquid is obvious. The particles are wetting in the water solution at a temperature more than 60 ℃. The relationship between the velocity of the particles and the fractal dimension of the solid particles with the equivalent diameter was discussed.展开更多
Single-cell RNA sequencing(scRNA-seq) is a powerful technique to analyze the transcriptomic heterogeneities at the single cell level. It is an important step for studying cell subpopulations and lineages, with an effe...Single-cell RNA sequencing(scRNA-seq) is a powerful technique to analyze the transcriptomic heterogeneities at the single cell level. It is an important step for studying cell subpopulations and lineages, with an effective low-dimensional representation and visualization of the original scRNA-Seq data. At the single cell level, the transcriptional fluctuations are much larger than the average of a cell population, and the low amount of RNA transcripts will increase the rate of technical dropout events. Therefore, scRNA-seq data are much noisier than traditional bulk RNA-seq data. In this study, we proposed the deep variational autoencoder for scRNA-seq data(VASC), a deep multi-layer generative model, for the unsupervised dimension reduction and visualization of scRNA-seq data. VASC can explicitly model the dropout events and find the nonlinear hierarchical feature representations of the original data. Tested on over 20 datasets, VASC shows superior performances in most cases and exhibits broader dataset compatibility compared to four state-of-the-art dimension reduction and visualization methods. In addition, VASC provides better representations for very rare cell populations in the 2D visualization. As a case study, VASC successfully re-establishes the cell dynamics in pre-implantation embryos and identifies several candidate marker genes associated with early embryo development. Moreover, VASC also performs well on a 10× Genomics dataset with more cells and higher dropout rate.展开更多
基金supported by the National Natural Science Foundation of China(61702385)the Key Projects of National Social Science Foundation of China(11&ZD189)
文摘Cover ratio of cloud is a very important factor which affects the quality of a satellite image, therefore cloud detection from satellite images is a necessary step in assessing the image quality. The study on cloud detection from the visual band of a satellite image is developed. Firstly, we consider the differences between the cloud and ground including high grey level, good continuity of grey level, area of cloud region, and the variance of local fractal dimension (VLFD) of the cloud region. A single cloud region detection method is proposed. Secondly, by introducing a reference satellite image and by comparing the variance in the dimensions corresponding to the reference and the tested images, a method that detects multiple cloud regions and determines whether or not the cloud exists in an image is described. By using several Ikonos images, the performance of the proposed method is demonstrated.
基金Project(41061043)supported by the National Natural Science Foundation of China
文摘Digital mine is the inevitable outcome of the information processing, and is also a complicated system engineering. Firstly, for the 3D visualization application of the digital mine, the ground and underground integrative visualization framework model was proposed based on the mine entity database. So, the visualization problem was availably resolved, as well as the professional analytical ability was improved. Secondly, aiming at the irregularities, non-uniformity, dynamics of mine entities, mix modeling method based on the entity character was put forward, in which 3D expression of mine entities was realized. Lastly, the 3D visualization project for a copper mine was experimentally studied. Satisfactory results were acquired, and the rationality of visualization model and feasibility of 3D modeling were validated.
文摘Inclusions with sizes less than 1 μm in molten steel are difficult to float up to the molten steel and slag interface owing to their slow terminal velocity. Thus, increasing the size of inclusion is essential for accelerating the removal of inclusions. Polystyrene particles simulating inclusions in molten steel were quantified by direct observation of the particle collision behavior in a turbulent flow in a water model. The box-counting fractal dimension of particles was calculated by processing the binary images of aggregated particles. The fractal dimension of the outer contours of the single plastic particles was smaller than that of the aggregated particles. The fractal dimension was varied from 1.14 to 1.35. When two or more monomer particles collide, the aggregates are separated more easily, as the temperature increases from 40 to 80 ℃. The aggregated particles were loose and easy to separate in the high-temperature aqueous solution. The effect of temperature on the surface tension of liquid and the interracial tension of solid and liquid is obvious. The particles are wetting in the water solution at a temperature more than 60 ℃. The relationship between the velocity of the particles and the fractal dimension of the solid particles with the equivalent diameter was discussed.
基金supported by the National Natural Science Foundation of China (Grant Nos.61370035 and 31361163004)Tsinghua University Initiative Scientific Research Program
文摘Single-cell RNA sequencing(scRNA-seq) is a powerful technique to analyze the transcriptomic heterogeneities at the single cell level. It is an important step for studying cell subpopulations and lineages, with an effective low-dimensional representation and visualization of the original scRNA-Seq data. At the single cell level, the transcriptional fluctuations are much larger than the average of a cell population, and the low amount of RNA transcripts will increase the rate of technical dropout events. Therefore, scRNA-seq data are much noisier than traditional bulk RNA-seq data. In this study, we proposed the deep variational autoencoder for scRNA-seq data(VASC), a deep multi-layer generative model, for the unsupervised dimension reduction and visualization of scRNA-seq data. VASC can explicitly model the dropout events and find the nonlinear hierarchical feature representations of the original data. Tested on over 20 datasets, VASC shows superior performances in most cases and exhibits broader dataset compatibility compared to four state-of-the-art dimension reduction and visualization methods. In addition, VASC provides better representations for very rare cell populations in the 2D visualization. As a case study, VASC successfully re-establishes the cell dynamics in pre-implantation embryos and identifies several candidate marker genes associated with early embryo development. Moreover, VASC also performs well on a 10× Genomics dataset with more cells and higher dropout rate.
