In the automatic assembly line of the disconnector, the upper cover and the base of the circuit breaker housing are separated by a separation station. If the upper cover and the base are placed too far apart or placed...
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In the automatic assembly line of the disconnector, the upper cover and the base of the circuit breaker housing are separated by a separation station. If the upper cover and the base are placed too far apart or placed in the opposite direction, the separation station cannot be separated normally, and it will affect the normal operation of subsequent processes. In this paper, a machine vision recognition and detection system for the circuit breaker shell is proposed. The image of the circuit breaker casing is captured by the CCD camera. The image processing technology is used to detect the edge of the original image of the circuit breaker shell and feature extraction. The algorithm of convexhull is used to calculate the rotation angle. Then the least square method is used to calculate the center position of the largest circle, and the upper cover and the base are identified according to the quadrant of the center of the circle.
With the advances of sensory, satellite and mobile communication technologies in recent decades, locational data become widely available. A lot of work has been developed to find useful information from these data, an...
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ISBN:
(纸本)9781450327459
With the advances of sensory, satellite and mobile communication technologies in recent decades, locational data become widely available. A lot of work has been developed to find useful information from these data, and various approaches have been proposed. In this work, we aim to use one specific type of locational data -- network connection logs of mobile devices, which is widely available and easily accessible to telecom companies, to identify and extract active areas of users. This is a challenging topic due to the existence of inaccurate location and fluctuating log time intervals of this kind of data. In order to observe user behavior from this kind of data set, we propose a new algorithm, namely Behavior Observation Tool (BOT), which uses convex hull algorithm with sliding time windows to model the user's movement, and thus knowledge about the user's lifestyle and habits can extracted from the mobile device network logs.
With the surging usage of e-scooters worldwide, there is a growing interest in understanding different aspects of e-scooters trips and their impact on urban mobility. Further, the emergence of this new mode of transpo...
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With the surging usage of e-scooters worldwide, there is a growing interest in understanding different aspects of e-scooters trips and their impact on urban mobility. Further, the emergence of this new mode of transportation has led to questions regarding the spatial accessibility of e-scooters and understanding how the built environment and urbanism characteristics affect riders' abilities to reach certain destinations. In this study, initially, a datadriven approach was proposed to construct the service areas for dockless e-scooter using origin-destination trip data. Service areas are defined as spatial areas that riders are regularly able to reach via an e-scooter. Escooter service areas were constructed for traffic analysis zones in Louisville, KY, using agglomerative hierarchical clustering and convex hull algorithms. Then, the relationship between various built environments and urbanism characteristics and the e-scooter service areas was examined using principal component analysis and random forest regression. The results showed that percent of residential properties, length of the block, Walk Score (R), Transit Score (R), and Dining and Drinking Score contributed most to the size of the e-scooter service area. The findings of this research offer a transferable method to estimate e-scooter service areas to quantify access to goods and services. Further, the study discusses how the built environment and urbanism characteristics might affect the size of the service areas.
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