5.1 Performance of individual sensor and video camera data For evaluat dịch - 5.1 Performance of individual sensor and video camera data For evaluat Việt làm thế nào để nói

5.1 Performance of individual senso

5.1 Performance of individual sensor and video camera data

For evaluating the performance of the sensors (i.e., CCC, URF), sensor data were analyzed to determine individual success rate of each type of sensor for detecting the damage on each building component. The only group of sensors that were not individually assessed was four CCC sensors that were attached to four corners of the suspended ceiling. The reason is that the blockage level that is caused by a suspended ceiling in a hallway can only be determined by considering the condition of each corner (e.g., if one connection is detached, the suspended ceiling does not cause blockage in the hallway). Therefore, the results from four CCC sensors were integrated to detect the final condition of the suspended ceiling. For example, if the results from four CCCs attached on a suspended celling are (1, 1, 0,1), this means that three
connections of the suspended ceiling are detached. On the other hand,video camera data was analyzed to determine the accuracy of video camera in estimating the blockage level at the nodes.
The results given in Table 6 show that the accuracies of the each CCC sensor in determining If a wall is damaged or not are 95.5% or 97.3%. Similarly, position of bookshelves (i.e, fell down or standing) could be determined by each CCC with 97.3% accuracy. Out of 168 tests in which suspended ceilings are damaged, combined results from four CCCs correctly detected the position of suspended ceilings in 146 tests (i.e., 86.9% success rate). In the case of suspended ceilings, the URF could detect whether there is a significant change in the initial position
of the element (e.g., distance in between the suspended ceiling and the hallway's ceiling) with a 93.5% accuracy. However, it should be noted that a URF cannot indicate how the suspended ceiling connections are detached, but only shows whether any of the connections are detached
or not with an accuracy of 51.7%. The reason is that the URF senses the condition at a single location on the suspended ceiling (i.e., in the center), However, to determine how the suspended ceiling got damaged, data from four corners of the ceiling need to be collected.
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5.1 Performance of individual sensor and video camera data

For evaluating the performance of the sensors (i.e., CCC, URF), sensor data were analyzed to determine individual success rate of each type of sensor for detecting the damage on each building component. The only group of sensors that were not individually assessed was four CCC sensors that were attached to four corners of the suspended ceiling. The reason is that the blockage level that is caused by a suspended ceiling in a hallway can only be determined by considering the condition of each corner (e.g., if one connection is detached, the suspended ceiling does not cause blockage in the hallway). Therefore, the results from four CCC sensors were integrated to detect the final condition of the suspended ceiling. For example, if the results from four CCCs attached on a suspended celling are (1, 1, 0,1), this means that three
connections of the suspended ceiling are detached. On the other hand,video camera data was analyzed to determine the accuracy of video camera in estimating the blockage level at the nodes.
The results given in Table 6 show that the accuracies of the each CCC sensor in determining If a wall is damaged or not are 95.5% or 97.3%. Similarly, position of bookshelves (i.e, fell down or standing) could be determined by each CCC with 97.3% accuracy. Out of 168 tests in which suspended ceilings are damaged, combined results from four CCCs correctly detected the position of suspended ceilings in 146 tests (i.e., 86.9% success rate). In the case of suspended ceilings, the URF could detect whether there is a significant change in the initial position
of the element (e.g., distance in between the suspended ceiling and the hallway's ceiling) with a 93.5% accuracy. However, it should be noted that a URF cannot indicate how the suspended ceiling connections are detached, but only shows whether any of the connections are detached
or not with an accuracy of 51.7%. The reason is that the URF senses the condition at a single location on the suspended ceiling (i.e., in the center), However, to determine how the suspended ceiling got damaged, data from four corners of the ceiling need to be collected.
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Kết quả (Việt) 2:[Sao chép]
Sao chép!
5.1 Performance of individual sensor and video camera data

For evaluating the performance of the sensors (i.e., CCC, URF), sensor data were analyzed to determine individual success rate of each type of sensor for detecting the damage on each building component. The only group of sensors that were not individually assessed was four CCC sensors that were attached to four corners of the suspended ceiling. The reason is that the blockage level that is caused by a suspended ceiling in a hallway can only be determined by considering the condition of each corner (e.g., if one connection is detached, the suspended ceiling does not cause blockage in the hallway). Therefore, the results from four CCC sensors were integrated to detect the final condition of the suspended ceiling. For example, if the results from four CCCs attached on a suspended celling are (1, 1, 0,1), this means that three
connections of the suspended ceiling are detached. On the other hand,video camera data was analyzed to determine the accuracy of video camera in estimating the blockage level at the nodes.
The results given in Table 6 show that the accuracies of the each CCC sensor in determining If a wall is damaged or not are 95.5% or 97.3%. Similarly, position of bookshelves (i.e, fell down or standing) could be determined by each CCC with 97.3% accuracy. Out of 168 tests in which suspended ceilings are damaged, combined results from four CCCs correctly detected the position of suspended ceilings in 146 tests (i.e., 86.9% success rate). In the case of suspended ceilings, the URF could detect whether there is a significant change in the initial position
of the element (e.g., distance in between the suspended ceiling and the hallway's ceiling) with a 93.5% accuracy. However, it should be noted that a URF cannot indicate how the suspended ceiling connections are detached, but only shows whether any of the connections are detached
or not with an accuracy of 51.7%. The reason is that the URF senses the condition at a single location on the suspended ceiling (i.e., in the center), However, to determine how the suspended ceiling got damaged, data from four corners of the ceiling need to be collected.
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