The article investigates some properties of square root of T3 tree’s nodes. It first proves several inequalities that are helpful to estimate the square root of a node, and then proves several theorems to describe th...The article investigates some properties of square root of T3 tree’s nodes. It first proves several inequalities that are helpful to estimate the square root of a node, and then proves several theorems to describe the distribution of the square root of the nodes on T3 tree.展开更多
为了提高呼吸信号判别驾驶疲劳的准确率,通过模拟驾驶试验探究呼吸信号与驾驶员疲劳状态的关系,提出呼吸疲劳节点的概念,并基于呼吸疲劳节点判别驾驶员的疲劳状态。首先,通过模拟驾驶试验采集驾驶员的呼吸信号,采用Karolinska嗜睡量表(K...为了提高呼吸信号判别驾驶疲劳的准确率,通过模拟驾驶试验探究呼吸信号与驾驶员疲劳状态的关系,提出呼吸疲劳节点的概念,并基于呼吸疲劳节点判别驾驶员的疲劳状态。首先,通过模拟驾驶试验采集驾驶员的呼吸信号,采用Karolinska嗜睡量表(Karolinska sleepiness scale, KSS)对疲劳程度进行主观自评量化。其次,把单位时间内眼睛闭合百分比(percentage of eyelid closure over the pupil over time, PERCLOS)作为参考,与主观自评反馈结合,对驾驶员呼吸疲劳节点进行标定。最后,基于呼吸疲劳节点利用随机树算法(random tree, RT)获得轻/重度呼吸疲劳变化节点的判别模型。结果表明:该模型能更加及时、准确地判别出驾驶员的疲劳状态;基于随机树算法获得的筛选条件对轻度呼吸疲劳变化节点识别的准确性要高于重度呼吸疲劳变化节点;轻/重度呼吸疲劳变化节点的平均识别误差分别为3.50 min和3.66 min,预测准确率分别为92.09%和92.03%。展开更多
This paper studies and analyses the character of the tree structure,and then presents an algorithm which is concise and convinent for the construction of tree structure.It is especially fit for the application system ...This paper studies and analyses the character of the tree structure,and then presents an algorithm which is concise and convinent for the construction of tree structure.It is especially fit for the application system using database.The special storege organization needn’t to be established in the database using this algorithm.By SQL statement,the data dispersed in different storeage organization can be dynamically combined into the data set including two fields:father node field and child node field.Then the algorithm can process those data and display the tree structure rapidly. At last,we design a control called TFDTreeView which inherits from TTreeView control using this algorithm. TFDTreeView control provide a interface function,through which we can construct the tree structure convinently. On some occasions,this method will be good for the application system.And ,by building the control ,we can reuse it in many system development.展开更多
文摘The article investigates some properties of square root of T3 tree’s nodes. It first proves several inequalities that are helpful to estimate the square root of a node, and then proves several theorems to describe the distribution of the square root of the nodes on T3 tree.
文摘为了提高呼吸信号判别驾驶疲劳的准确率,通过模拟驾驶试验探究呼吸信号与驾驶员疲劳状态的关系,提出呼吸疲劳节点的概念,并基于呼吸疲劳节点判别驾驶员的疲劳状态。首先,通过模拟驾驶试验采集驾驶员的呼吸信号,采用Karolinska嗜睡量表(Karolinska sleepiness scale, KSS)对疲劳程度进行主观自评量化。其次,把单位时间内眼睛闭合百分比(percentage of eyelid closure over the pupil over time, PERCLOS)作为参考,与主观自评反馈结合,对驾驶员呼吸疲劳节点进行标定。最后,基于呼吸疲劳节点利用随机树算法(random tree, RT)获得轻/重度呼吸疲劳变化节点的判别模型。结果表明:该模型能更加及时、准确地判别出驾驶员的疲劳状态;基于随机树算法获得的筛选条件对轻度呼吸疲劳变化节点识别的准确性要高于重度呼吸疲劳变化节点;轻/重度呼吸疲劳变化节点的平均识别误差分别为3.50 min和3.66 min,预测准确率分别为92.09%和92.03%。
文摘This paper studies and analyses the character of the tree structure,and then presents an algorithm which is concise and convinent for the construction of tree structure.It is especially fit for the application system using database.The special storege organization needn’t to be established in the database using this algorithm.By SQL statement,the data dispersed in different storeage organization can be dynamically combined into the data set including two fields:father node field and child node field.Then the algorithm can process those data and display the tree structure rapidly. At last,we design a control called TFDTreeView which inherits from TTreeView control using this algorithm. TFDTreeView control provide a interface function,through which we can construct the tree structure convinently. On some occasions,this method will be good for the application system.And ,by building the control ,we can reuse it in many system development.
