Selection of Plus Tree Based on Growth Performance and Fiber Morphology Characteristics as Improved Sources for Propagation of <i>Eucalyptus camaldulensis</i>

One of the most successful techniques in planting trees is tree improvement in which trees with high qualities are selected for mass plantation. This study seeks to identify good properties of Eucalyptus camaldulensis through selective phases. Sixty Eucalyptus camaldulensis trees (30 ten-year-old and 30 five-year-old) were randomly selected through stratified sampling from two plantation sites in Kurdistan region, North of Iraq. The trees were examined for fiber morphology and quality parameters such as height, number of branches, diameter and straightness. In the first phase of property selection, sixteen trees with high rank in growth properties and fiber morphology were selected. In the final phase of selection, the selected trees were re-examined according to the number of properties and fiber morphology features and seven trees with the highest number of good parameters were chosen. The 7 selected trees had higher qualities in growth characteristics and fiber morphology compared with the other trees in the sample. This article reports on a selection method for E. camaldulensis trees through tree improvement techniques. The results of the study indicates that high genotype qualities were identified among both 5- and 10-year-old E. camaldulensis trees as the final selection consisted of three 5-year-old trees and four 10-year-old trees.

Improved Pattern Tree for Incremental Frequent-Pattern Mining

By analyzing the existing prefix-tree data structure, an improved pattern tree was introduced for processing new transactions. It firstly stored transactions in a lexicographic order tree and then restructured the tree by sorting each path in a frequency-descending order. While updating the improved pattern tree, there was no need to rescan the entire new database or reconstruct a new tree for incremental updating. A test was performed on synthetic dataset T1014D100K with 100 000 transactions and 870 items. Experimental results show that the smaller the minimum sup- port threshold, the faster the improved pattern tree achieves over CanTree for all datasets. As the minimum support threshold increased from 2% to 3.5%, the runtime decreased from 452.71 s to 186.26 s. Meanwhile, the runtime re- quired by CanTree decreased from 1 367.03 s to 432.19 s. When the database was updated, the execution time of im- proved pattern tree consisted of construction of original improved pattern trees and reconstruction of initial tree. The experiment results showed that the runtime was saved by about 15% compared with that of CanTree. As the number of transactions increased, the runtime of improved pattern tree was about 25% shorter than that of FP-tree. The improved pattern tree also required less memory than CanTree.

An Improved Indexing and Matching Method for Mathematical Expressions Based on Inter-Relevant Successive Tree

In recent years, a growing number of math contents are available on the Web. When conventional search engines deal with mathematical expressions, the two-dimen- sion-al structure of mathematical expressions is lost, which results in a low performance of math retrieval. While the retrieval technology specifically designed for mathematical expressions is not mature currently. Aiming at these problems, an improved mathematical expression indexing and matching method was proposed through employing full text index method to deal with the two-dimensional structure of mathematical expressions. Firstly, through the fully consideration of LaTeX formulae’ characteristics, a feature representation method of mathematical expressions and a clustering method of feature keywords were put forward. Then, an improved inter-relevant successive trees index model was applied to the construction of the mathematical expression index, in which the cluster algorithm of mathematical expression features was employed to solve the problem of the quantity growth of the trees in processing large amount of formulae. Finally, the matching algorithms of mathematical expressions were given which provide four query modes called exact matching, compatible matching, sub-expression matching and fuzzy matching. In browser/server mode, 110027 formulae were used as experimental samples. The index file size was 29.02 Mb. The average time of retrieval was 1.092 seconds. The experimental result shows the effectiveness of the method.

A retinal blood vessel extraction algorithm based on CART decision tree and improved AdaBoost

This paper presents a supervised learning algorithm for retinal vascular segmentation based on classification and regression tree (CART) algorithm and improved adptive bosting (AdaBoost). Local binary patterns (LBP) texture features and local features are extracted by extracting,reversing,dilating and enhancing the green components of retinal images to construct a 17-dimensional feature vector. A dataset is constructed by using the feature vector and the data manually marked by the experts. The feature is used to generate CART binary tree for nodes,where CART binary tree is as the AdaBoost weak classifier,and AdaBoost is improved by adding some re-judgment functions to form a strong classifier. The proposed algorithm is simulated on the digital retinal images for vessel extraction (DRIVE). The experimental results show that the proposed algorithm has higher segmentation accuracy for blood vessels,and the result basically contains complete blood vessel details. Moreover,the segmented blood vessel tree has good connectivity,which basically reflects the distribution trend of blood vessels. Compared with the traditional AdaBoost classification algorithm and the support vector machine (SVM) based classification algorithm,the proposed algorithm has higher average accuracy and reliability index,which is similar to the segmentation results of the state-of-the-art segmentation algorithm.

2-median location improvement problems under weighted l_1 norm and l_∞ norm on trees

This paper focuses on the 2-median location improvement problem on tree networks and the problem is to modify the weights of edges at the minimum cost such that the overall sum of the weighted distance of the vertices to the respective closest one of two prescribed vertices in the modified network is upper bounded by a given value.l1 norm and l∞norm are used to measure the total modification cost. These two problems have a strong practical application background and important theoretical research value. It is shown that such problems can be transformed into a series of sum-type and bottleneck-type continuous knapsack problems respectively.Based on the property of the optimal solution two O n2 algorithms for solving the two problems are proposed where n is the number of vertices on the tree.

Morphological parameters and genetic diversity of progenies from seed production areas and unimproved stands of teak(Tectona grandis L.f.)in India

We compared morphological and genetic attributes of prog- eny obtained from three seed production areas （SPAs） and three corre- sponding unimproved stands （UIS） of teak （Tectona grandis L.f） at three broad teak growing regions in the state of Karnataka, India. In general, seed morphological parameters such as seed weight, seed size and seed emptiness were significantly superior in SPAs compared to UISs. Seed germination percentage was also higher in seeds from SPAs. Seedling performance measured at two monthly intervals for six months was ob- served to be superior in SPAs at two of the three regions compared. Although the genetic diversity of progeny of SPAs was lower than UIS at all regions, the values were moderately high. Germination percent was positively correlated with fruit weight and kernel weight per seed, while diversity indices were negatively correlated with fruit weight, fruit di- ameter and kernel weight per seed. SPAs proved important as a source of moderately improved planting material with no severe threat to the ge- netic diversity of future plantations.

基于Dual-Tree CWT和自适应双边滤波器的图像去噪算法

针对目前图像去噪方法主要局限于单一噪声,无法有效解决多种混合噪声的不足,提出了一种基于DualTree CWT和自适应双边滤波器的图像去噪算法。该算法使用双树复小波变换对含噪图像进行多尺度和多方向的分解,由改进阈值对各个方向子带的高频系数进行阈值量化,同时由自适应双边滤波对每尺度下低频子带系数进行滤波,并将重构得到的图像进一步去除噪声。实验仿真结果表明,该方法对混合噪声的滤除效果明显优于现有算法,且能较好地保护图像的边缘细节信息,通过客观评价指标峰值信噪比(PSNR)和均方根误差(RMSE)定量比较,PSNR提升了5.333 2~6.527 8 d B,RMSE可降低29.41%~46.03%,运行时间仅为1.492 0 s,整体降噪性能更优。

日志模板提取的FT-Tree改进算法研究

计算机日志能够真实、全面记录事件信息,已经作为一种电子证据在侦查办案中得到普遍应用.要实现对海量日志信息的快速自动分析,需要有高效可靠的日志模板提取方法.鉴于目前日志模板提取方法存在的不足,本文以网络服务器日志作为模板提取的研究对象,基于FT-Tree算法,提出了利用Apriori算法计算剪枝阈值,再利用该值控制剪枝的FT-Tree改进算法,并以某高校网络服务器真实日志进行了模板提取实验.结果表明,改进算法较之FT-Tree算法显著提高了日志模板提取的准确度,能更好地满足实际应用需要.

Indigenous Fruit Trees of Tropical Africa: Status, Opportunity for Development and Biodiversity Management

Tropical fruit trees constitute important biological resources in the global agrobiodiversity context. Unlike the tropical fruit trees of American and Asian origin, indigenous fruit trees (IFT) of tropical Africa have scarcely achieved the status of international recognition in commodity markets and research arena outside Africa. This paper presented a critical review of the status of IFT in the Tropical African sub-regions (of West Africa, Central Africa, East Africa, Southern Africa and the Indian Ocean Islands) in relation to the introduced naturalised fruit trees from tropical America and Asia, threats to the diversity and sustainable use of IFT, analysis of the opportunities and challenges of developing IFT, as well as targets for crop improvement of the rich IFT of Tropical Africa. Domestication programme via relevant vegetative propagation techniques for priority IFT of the sub-regions was examined and advocated, in addition to the adoption of complementary conservation strategies, including Field GeneBanks in the management of the continent’s IFT diversity.

腐殖酸钾对杨梅土壤改良和生长结实的影响

针对杨梅种植区土壤环境恶化导致杨梅树体衰弱、果实品质下降的问题,开展腐殖酸钾调理杨梅根系土壤的研究,施用不同剂量的腐殖酸钾,测定土壤理化性质,微生物生物量碳、氮,土壤酶活性,以及杨梅茎、叶的营养元素含量,果实品质与产量的变化。结果表明,施用腐殖酸钾可显著(P<0.05)提高土壤pH值、阳离子交换量、电导率和最大持水量,显著增加土壤速效氮、速效钾含量和土壤交换性钙含量,显著提高土壤脲酶、蔗糖酶、过氧化氢酶活性,显著增加杨梅茎、叶的钾、钙含量,显著提高杨梅果实的总糖和可溶性糖含量,显著促进花色素苷的积累,显著提升杨梅的商品果率和优质果率。综上,腐殖酸钾可作为适宜的土壤调理剂,改善杨梅根系的土壤健康状况,提高杨梅果实品质。

改进灰狼算法优化GBDT在PM_(2.5)预测中的应用

针对灰狼算法易陷入局部最优解和全局搜索能力不足的问题,通过霍尔顿序列(Halton Sequence)搜索算法初始化狼群位置,避免灰狼算法陷入局部最优解和重复运算;引入莱维飞行和随机游动策略对灰狼算法的寻优过程进行优化,以增加算法的全局搜索能力;利用粒子群算法模拟灰狼种群得出的最佳适应度以用于惩罚项改进灰狼算法中的头狼更新策略。使用改进算法优化的梯度提升树(Gradient Boosting Decision Trees,GBDT)模型对北京市大气污染物监测数据中PM_(2.5)质量浓度进行预测,采用3种评估函数对各模型以及混合模型预测效果得分进行评估。结果显示,本文改进的灰狼算法对梯度提升树的优化效果优于其他算法,均方根误差E RMS为6.65μg/m^(3),平均绝对值误差E MA为3.20μg/m^(3),拟合优度(R^(2))为99%,比传统灰狼算法优化结果的均方根误差减少了19.19μg/m^(3),平均绝对值误差降低了10.03μg/m^(3),拟合优度增加了9百分点;与霍尔顿序列和莱维飞行改进的(Levy Flight-Halton Sequence,LHGWO)相比,改进的灰狼算法预测得分的均方根误差降低了10.39μg/m^(3),平均绝对值误差减小了6.71μg/m^(3),拟合优度提高了5百分点。研究表明了预测模型优化的有效性,为未来城市改善空气质量提供了科学依据和技术支持。

基于复杂特征提取和Sinkhorn距离的风光荷多阶段场景树生成方法

新能源发电出力和负荷长期增长的不确定性增加了电网规划复杂性,开展新能源出力和负荷长时间尺度上的不确定性分析,对电网的规划与建设具有重要意义。提出了一种基于复杂特征提取和Sinkhorn距离的风光荷多阶段场景树生成方法。首先,为提高风光荷场景的聚类效率,提出基于堆叠稀疏自编码器的风光荷场景特征提取方法,并采用基于密度峰值改进的近邻传播算法对风光荷场景特征集合进行聚类,获得风光荷典型曲线,作为场景树的根节点;然后,考虑负荷不同增长率,逐年生成风光荷场景树,并提出基于Sinkhorn距离的场景树削减方法以降低场景树的规模;最后,算例仿真结果表明,所提方法计算效率高,生成的风光荷多阶段场景树可反映风光出力和负荷增长的不确定性。

改进人工势场引导的双向扩展随机树路径规划算法

针对地面移动机器人在复杂环境之下要求规划路径实时性强、路线平滑度高、避障精确完备等需求,在快速扩展随机树算法(RRT)的基础之上,提出一种由改进人工势场法(APF)引导的双向扩展随机树算法(APF-Bi-RRT^(*))。首先,在每次迭代的过程之中两棵随机树同时分别从起始点和目标点进行扩展,以加快算法收敛速度;其次,在算法随机树生长方向上,引入目标偏置策略来优化随机子节点的选取,并在随机树和障碍物中加入人工势场分量,限制路径方向选择的随机性,改进算法克服引力和斥力过大导致陷入局部最优值或目标不可达的问题;最后,在形成锯齿型规划路径之上应用一种采样优化和关键节点平滑策略,进一步缩短和平滑原路径的总距离。对比实验结果证明,该算法既克服了传统随机树算法的节点盲目扩展的问题,又兼顾了生成路径的效率和平滑性,与目标偏置RRT算法相比,在规划路径长度上减少了9.7%左右,在运行时间上缩短了65.3%左右,在算法迭代次数上减少了78.2%左右。

亚热带生态系统5种修复树种的光合特征

分析不同树种生长状况以及光合特征和不同树种光合能力的差异,为提高低效公益林质量提供依据。以苦槠(Castanopsis sclerophylla)、木荷(Schima superba)、浙江楠(Phoebe chekiangensis)、刨花楠(Machilus pauhoi)和红楠(Machilus thunbergii)等5种亚热带地区生态修复树种幼苗为试验对象,测定其生长指标、叶绿素质量分数、光合指标和叶绿素荧光指标,采用直角双曲线修正模型进行光响应曲线拟合以及估算光响应特征参数,并对各项指标进行单因素方差分析和相关性分析。结果表明:不同树种的生长指标和叶绿素质量分数之间存在显著差异(P<0.05);不同树种的光响应曲线均呈现出随光合有效辐射增加先直线上升后缓慢增高再有所下降的变化趋势,且光合特征参数存在显著差异(P<0.05);5种树种的净光合速率(Pn)、气孔导度(Gs)、胞间CO_(2)摩尔分数(Ci)之间存在显著性差异(P<0.05);光系统(PS)Ⅱ潜在荧光活性(Fv/Fo)和光系统(PS)Ⅱ最大光化学效率(Fv/Fm)表现为苦槠显著高于木荷、浙江楠和刨花楠;生长特征参数、光响应曲线特征参数和叶绿素荧光参数之间存在较强的相关性。因此,不同树种光环境适应情况差异较大,苦槠阳性特征显著,可选择低效公益林改造的林窗中心位置进行栽植;木荷对光环境适应范围广,可以作为林窗近中心位置的补植树种;浙江楠、刨花楠和红楠均属于耐阴性较强的树种,可选择林窗边缘位置或者阴坡、半阴坡林窗进行补植。

机器人锅炉冷态空气动力场测量系统开发

针对锅炉冷态空气动力场试验自动化程度低、操作危险性大的问题,开发了机器人锅炉冷态空气动力场试验测量系统。系统下位机采用STM32芯片作为主控芯片,控制爬壁机器人的运动以及与上位机的信息交换,同时引入混沌线性惯性权重对粒子群优化模糊PID算法进行优化,并将改进后的算法作为机器人运动路径的控制策略,对于机械臂的控制引入D-H法。上位机为LabVIEW搭建的操作平台,通过嵌入双树复小波变换去噪算法,对采集到的风速信号进行降噪处理。结果表明:所提出的系统各个模块均可正常且稳定运行,与人工测试的误差保持在±10%,能够满足锅炉冷态试验的要求。

知识-数据融合的直流送端系统暂态过电压幅值预测

对于含大规模风电的高压直流外送系统,换相失败、直流闭锁等故障可能导致送端交流母线出现暂态过电压,进而引发新能源连锁脱网,严重威胁电网的安全稳定运行。为刻画直流故障对系统安全稳定运行能力的影响,提出一种知识-数据融合的直流送端系统暂态过电压幅值预测方法。首先,通过修正决策树分裂过程中的分支质量衡量指标提出改进决策树算法,挖掘暂态过电压与关键电气量的映射关系,提升过电压幅值预测模型的评估性能。其次,基于系统机理模型分析送端系统功率交换情况与交流母线电压的关联关系,推导模型驱动的换流站母线暂态过电压幅值解析表达式。最后,结合理论分析方法,建立知识-数据融合模型以快速修正过电压幅值理论计算结果,提升融合模型在训练样本不足或输入特征选择不当情况下的鲁棒性。面向存在暂态过电压问题的直流送端系统,仿真结果验证了所提暂态过电压幅值预测方法的有效性。

基于改进模糊聚类算法的大数据随机挖掘仿真

大数据挖掘是从大量有噪声的、随机模糊的大数据中提取有价值信息的过程,由于海量大数据具有多维性、稀疏性以及动态性等特点,准确获取其分布特征的难度较大,随机挖掘难以直接实现。为此提出基于改进模糊聚类算法的大数据随机挖掘方法。利用建立的语义概念树模型获取大数据的特征分布关系,并根据模糊语义分析法得出大数据的语义相似性、关联性条件,提取大数据特征。优先确定最佳聚类数,采用改进模糊聚类算法对其聚类,实现基于改进模糊算法的大数据随机挖掘。实验结果表明,上述方法的大数据模糊聚类效果较好,随机挖掘准确率可达到95%以上,实验所得结果验证了上述方法较强的应用有效性。

基于故障树分析法的某控制系统故障与可靠性研究

针对复杂卫星载荷控制系统高可靠性提升问题,聚焦系统故障潜在原因,提出一种基于量化底事件与顶事件重要度解析的故障树分析方法。以卫星载荷控制系统设计原理及功能为基础,利用故障树分析法定义故障树顶事件,查找故障原因,确定与底事件之间的逻辑关系,构建故障树;利用布尔代数方法确定故障树最小割集,对故障树底事件进行定性分析;通过最小割集失效率对顶事件进行定性分析,调整单一底事件的质量参数,对底事件与顶事件重要度依赖关系进行量化。研究结果表明,故障树能直观显示系统存在的故障原因,主控芯片故障、时钟信号异常、上位机复位通道故障等为影响系统可靠性的主要故障因素,可根据量化底事件对顶事件故障的影响程度,实现对产品设计、生产、调试、运行过程中潜在故障的预先排查。

‘乌壳雷竹’良种及其栽培技术

‘乌壳雷竹’(Phyllostachys violascens‘Wuqiaoleizhu’)属于竹亚科(Bambusoideae)刚竹属(Phyllostachys)雷竹的变异种,2006年3月发现于湖南省芷江县从浙江引种的雷竹群体中,经多年繁育观测,其性状表现一致、稳定。与雷竹的箨鞘红褐色、具稀疏褐色斑点明显不同,‘乌壳雷竹’箨鞘整体为青褐色或乌褐色,具不均匀、大小不一的黑褐色斑块。‘乌壳雷竹’具有出笋早、笋期长、产量高、笋质优等特点,2021年3月通过湖南省林木良种审定(湘S-SV-PV-001-2021)。文章介绍了‘乌壳雷竹’特性及其栽培技术,以期为其扩大栽培提供参考。