Abstract Human, machine, environment, management are the most important fur factors in the Accident-causing mechanism, and this idea has been accepted by all of us. But the relationship of the four factors, that is how the four factors mutual influence and lead to accidents, is not very clear. This will lead to difficulty in generating calculation model. This study considers these four factors in... Human, machine, environment, management are the most important fur factors in the Accident-causing mechanism, and this idea has been accepted by all of us. But the relationship of the four factors, that is how the four factors mutual influence and lead to accidents, is not very clear. This will lead to difficulty in generating calculation model. This study considers these four factors in the accident formation process are not in a hierarchy. Human, machine and environment are accident triggered and in the basic layer, management belongs to the second level. Based on this idea, this paper establishes a logic calculation model for the accident-causing mechanism, and the status simulation method is used to calculate the model. The simulation results show that, the model for mechanism is explained more clearly on the accident. According to the model and simulation results, some measures controlling accidents are put forward at last. Read More Read Less

Abstract Aiming at long registration time and mismatch problems resulted by images that exist local region similar or generated SIFT vector similar in the traditional SIFT registration method, a fine registration method based on geometric constraints of block and parallel architecture is put forward. This method using SIFT algorithm parallelly extract feature points to calculate initial transform matrix, in order to provide geometric constraints... Aiming at long registration time and mismatch problems resulted by images that exist local region similar or generated SIFT vector similar in the traditional SIFT registration method, a fine registration method based on geometric constraints of block and parallel architecture is put forward. This method using SIFT algorithm parallelly extract feature points to calculate initial transform matrix, in order to provide geometric constraints for block and fine registration, after segment the overlapping region into several blocks, we do blockwise SIFT matching using parallel architecture to achieve fine registration. During the fine registration, we use affine invariance of Mahalanobis distance to screen feature points and eliminate duplicate matches and mismatches. The experimental results show that this method eliminates the mismatch generated by same local features, registration accuracy and speed has improved, the proposed approach has practical value. Read More Read Less

Abstract In this paper a three-dimensional visualized integrated framework of landslide monitoring data is presented. The proposed framework presents a strategy for the integration of the data in landslide monitoring based on a thematic point-source landslide monitoring database and three-dimensional geological model of landslide. The framework is applied to the HuangTuPo landslide monitoring project in Three Gorges Reservoir of China. Comparison of the result... In this paper a three-dimensional visualized integrated framework of landslide monitoring data is presented. The proposed framework presents a strategy for the integration of the data in landslide monitoring based on a thematic point-source landslide monitoring database and three-dimensional geological model of landslide. The framework is applied to the HuangTuPo landslide monitoring project in Three Gorges Reservoir of China. Comparison of the result with the common method shows a more efficient fusion of landslide monitoring data with the feature of multi-source, multi-class, large quantity and multi-themes. Read More Read Less