Recursive partition and amalgamation with the exponential family: Theory and applications

The theory of tree-growing (RECPAM approach) is developed for outcome variables which are distributed as the canonical exponential family. The general RECPAM approach (consisting of three steps: recursive partition, pruning and amalgamation), is reviewed. This is seen as constructing a partition with maximal information content about a parameter to be predicted, followed by simplification by the elimination of ‘negligible’ information. The measure of information is defined for an exponential family outcome as a deviance difference, and appropriate modifications of pruning and amalgamation rules are discussed. It is further shown how the proposed approach makes it possible to develop tree-growing for situations usually treated by generalized linear models (GLIM). In particular, Poisson and logistic regression can be tree-structured. Moreover, censored survival data can be treated, as in GLIM, by observing a formal equivalence of the likelihood under random censoring and an appropriate Poisson model. Three examples are given of application to Poisson, binary and censored survival data.     

树映射的分布混沌

设T是个有限树,f是T上的连续映射．证明了f是分布混沌的当且仅当它的拓扑熵是正数．一些已知结论得到了改进．     

Correlation of mercury concentrations in tree core and lichen samples in southeastern Louisiana

To determine if a correlation exists between mercury concentrations in lichens and wood from tree cores, tree core and lichen samples were taken from sites under mercury advisories and analyzed for mercury using a Bacharach 50B Mercury Analyzer System employing the Manual Cold Vapor Atomic Absorption EPA method 7471A. Wood from tree cores was dated using tree ring data. Wood samples from the cores were analyzed for various depths in the tree core (periods of time) to determine if variations occur throughout the cores. Preliminary data indicate that a strong correlation exists between mercury concentrations in tree core and lichen samples. Samples were analyzed for the 6-month period of summer 2003–winter 2004. A correlation coefficient of 0.882 was found between the tree core and lichen data sets. The derived correlations were used to estimate concentrations of mercury in tree rings for sites in lichen samples which were previously analyzed. These predicted values compared favorably to recently determined concentrations of Hg in tree cores. The strong correlation between lichen and tree core Hg concentrations suggests similar uptake mechanism for the two types of biota.     

植物化控在果树生产中的主要应用

本文综述了植物化控对果树的生长发育、开花结实、果实品质、休眠等方面的影响及应用现状,并简要介绍了植物生长调节剂在果树栽培中的残毒问题。     

关于图的路色数

本文证明了P_∞-K-临界图的一些简单性质,并给出了某些图类的路色数。主要证明了:(1)若x(G,P_∞)=K,则G包含一个P_∞-l-临界子图,这里对所有的l≤K;(2)设G是P_∞-K-临界图,H是G的子图,且H∈P_∞。,则x(G—H,P_∞)=K-1;(3)设T为m阶树,C_n为偶圈,则x(T×C_n,P_∞)=2;(4)若C_n为奇圈,则对任意树T,有x(T×C_n,P_∞)≤3;(5)若m≠n,则x(K_m×K_n,P_∞)=max{[(m 1)/2],[(n 1)/2]}。     

求最小部分树的新方法

本文给出了求最小部分树的一种新方法，同时给出最短路权的矩阵求法。     

在HBV和(或)AFB1诱发树鼩肝癌过程中肝组织ras癌基因的表达

为了解在人乙型肝炎病毒（ＨＢＶ）和／或黄曲霉毒素（ＡＦＢ１）诱发树Ｑｕ肝癌过程中Ｐ＾２１在肝组织的表达情况,用免疫组化方法观察人ＨＢＶ＋ＡＦＢ１双因素组（Ａ组）、单因素ＨＢＶ组（Ｂ组）、单因素ＡＦＢ１组（Ｃ组）、及对照组（Ｄ组）实验第４４周、１０５周、１１９周动物肝活检组织Ｐ＾２１蛋白的表达情况。结果,至１１９周,累计肝组织Ｐ＾２１阳性动物百分率分别为３５．３、５．３、１３．３、０。表明人ＨＢＶ与     

一种无线传感器网络的传输路径规划算法

针对层次不多的树型拓扑结构无线传感器网络,介绍了一种根据ID格式选择传输路径的路径规划算法,该算法可使无线传感器网络中各节点到达sink节点的路径最优。经在温度传感器中应用,证明该算法切实可行。     

基于一种改进RRT算法的足球机器人路径规划

针对足球机器人运用传统快速扩展随机树(RRT)算法进行路径规划时随机性大的问题,提出了一种目标引力式的RRT路径规划算法。该算法在RRT算法的基础上引入了一个目标引力函数,避免了扩展随机树向目标点以外的方向生长,改进了快速扩展随机树缺乏确定性的问题,提高了足球机器人在路径规划方面的效率。仿真实验结果表明,该算法能够得到最佳路径,同时可以有效提高路径的规划速度。     

一种深度学习网络的树木点云骨架重建方法

基于激光雷达(light detection and ranging, LiDAR)数据重建树体三维模型并精准获取林木空间枝干结构参数是精准林业发展的必然趋势。本文研究面向激光点云提出了一种融合基于晶格投影的深度学习网络,以及面向提取的枝干点云的树木模型骨架重建的方法。该深度学习网络包括旋转不变性模块、晶格投影与重心插值模块,多尺度变换与卷积操作层,通过将旋转变换后的点云晶格投影到三个坐标平面上再分别重心插值获得变换系数,解决了三维点云因排列无序而造成空间卷积困难的问题。以海南多类树木为研究对象,首先,把带枝叶标签的林木点云基团带入构造的深度学习网络中训练网络参数,实现测试样本中的林木数据的枝叶分离。其次,对分类后的树木枝干点云垂直分层并空间聚类,获取每层的聚类中心点并按相邻层中心点距离最小原则实现骨架链表构造,同时采用自适应随机抽样一致(random sample consensus, RANSAC)方法来计算的圆柱体拟合半径,以重建树木的各级枝干。最后,根据中心点连通的链表结构以及角度变化最小准则自动识别树木中的主枝干和各个一级分枝。通过与实测数据比对验证表明,深度学习枝叶分类准确...