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摘要： This study was designed to explore two possible causes of and solutions to poor dispersion prediction model performance in polytomous items. First, the impact of the correlation between the ‘level’ (e.g., the average score of the distribution) and the ‘strength’ (the dispersion among the data points in a distribution) on the dispersion effect was explored. Second, the extent to which non-linearity and heteroscedasticity influenced the dispersion effect was also explored. In order to explore these two factors, Monte Carlo studies were performed in which the dispersion index, the number of aggregated observations, the number of nested data points, the number of items from which the dispersion index was derived, the shape of the distribution, and the ‘level’ covariate in the multiple regression model were varied. The studies used a 5 point response polytomous item context. The evaluation criteria included power/Type I error rates, model R2, sr2 for the dispersion index, the VIF of the dispersion index, linearity of the dispersion index, and homoscedasticity of the errors in the dispersion prediction model. The results suggest that none of the dispersion indexes systematically violate the multiple regression assumptions of linearity or homoscedasticity. They also suggest that the choice of the dispersion index, the number of items used, and the central tendency covariate used in the dispersion prediction model are the prominent determinants of good performance in a 5 point response scale polytomous item context. The sample standard deviation (SD) and average deviation indexes (ADm and ADmd) performed equally well and substantially better than the MAD, CV, and awg in terms of the evaluation criteria across the conditions of the study. The performance of the SD, ADm, and ADmd improved substantially when computed from 5 different polytomous items as opposed to a single polytomous item. Finally, the results suggest that in skewed distributions the performance of the SD, ADm

摘要： The principal focus of this thesis lies on the investigation of new compu- tational approaches for the automated processing of medical images to identify normal and diseased structures. Medical images constitute a particularity for computer vision methods as they commonly result from highly complex acquisition techniques. Frequently, they visualize bio- logical objects that are hidden to the naked human eye. Two examples of medical images are investigated in this thesis: microscopic immunohisto- chemically stained cancer tissue images known from pathology and mac- roscopic abdominal magnetic resonance images known from radiology. In both cases, the medical task is to diagnose and if needed quantify ab- normal structures such as cancer or bowel diseases. We aim to solve this task in computer-aided or fully automated manner to be able to improve daily clinic diagnostics and scientific research on large patient cohorts. This thesis is structured in following parts: First, we introduce technical terms relevant for this thesis. Tissue microar- rays (TMA) are medical instruments for experimental cancer research in large patient cohorts. Magnetic resonance imaging (MRI) is a medical im- aging method used to visualize the gastrointestinal tract. Crohn's disease (CD) and CD severity are explained. The data basis of the computer-aided staining estimation pipeline is formed by eight TMA images of clear cell renal cell carcinoma patients and six TMA images of prostate cancer patients. Each image is fully la- beled by two medical doctors. Additionally, two labeled MRI datasets of 27 and 35 CD patients are introduced serving as development and vali- dation datasets of our automatic CD detection and severity estimation. For a medical understanding of a variety of cancers, the morphological evaluation of hundreds of histologic tissue images has emerged as fun- damental procedure in clinical cancer research. We define in this chapter a new computational pipeline for automated cell n

关键词： 高压开关柜   无线测温   zigbee   设计模式   数据结构   故障恢复   Modbus  

摘要： 高压开关柜是电力传输系统的枢纽,起着通断、控制或保护等作用。由于设备长期运行,高压开关柜的连接点因温度过高而酿成火灾的情况时有发生。这会造成极大的经济损失甚至人员伤亡,因此,对高压开关柜内的敏感设备进行温度检测变得尤为重要。本论设计了一套无线测温监控系统,主要从测点对象的结构模型、故障恢复算法、通讯协议等方面进行了优化,保证了系统的可靠性和稳定性。 论文主要做了以下几方面工作： (1)研究了温度测点的安装位置以及变电站的组织结构,提出了测点对象的树状抽象数据模型,在分析了树状模型及应用组合模式设计软件的优缺点之后提出了利用红黑树和哈希表进行改进的方案。 (2)提出了基于贪心算法的闲时故障恢复算法,以解决监控软件在不间断运行前提下自动对故障进行恢复的问题。 (3)提出了基于Modbus通讯协议的协议栈改进方案,以提高软件的通讯效率和执行效率。 (4)应用以上方案设计无线测温监控系统,并对系统进行测试和验证。 经测试和现场安装验证,本文提出的测点对象模型能够优化对树状结构模型内成员的访问和修改的效率；基于贪心算法的闲时故障恢复算法使软件故障恢复时间很好的逼近硬件故障实际恢复时间；改进的协议栈能有效的提高软件的执行效率,减少了软件在通讯上的时间,使软件能够更快地处理用户请求。本文所做工作在保证了系统稳定性和可靠性的前提下提高了系统的运行效率。

摘要： Many standard problems in computational geometry have been solved asymptotically optimally as far as comparison-based algorithms are concerned, but there has been little work focusing on improving the constant factors hidden in big-Oh bounds on the number of comparisons needed. In this thesis, we consider orthogonal-type problems and present a number of results that achieve optimality in the constant factors of the leading terms, including: An output-sensitive algorithm that computes the maxima for a set of n points in two dimensions using 1n log h + O(n log h) comparisons, where h is the size of the output. A randomized algorithm that computes the maxima in three dimensions that uses 1n log n + O(n log n) expected number of comparisons. A randomized output-sensitive algorithm that computes the maxima in three dimen- sions that uses 1n log h + O(n log 2 3 h) expected number of comparisons, where h is the size of the output. An output-sensitive algorithm that computes the convex hull for a set of n points in two dimensions using 1n log h + O(n log h) comparisons and O(n log h) sidedness tests, where h is the size of the output. A randomized algorithm for detecting whether of a set of n horizontal and vertical line segments in the plane intersect that uses 1n log n+O(n log n) expected number of comparisons. A data structure for point location among n axis-aligned disjoint boxes in three dimensions that answers queries using at most 3 2 log n + O(log log n) comparisons. The data structure can be extended to higher dimensions and uses at most d 2 log n + O(log log n) comparisons. A data structure for point location among n axis-aligned disjoint boxes that form a space-filling subdivision in three dimensions that answers queries using at most 4 3 log n + O( log n) comparisons. The data structure can be extended to higher dimensions and uses at most d+1 3 log n + O( log n) comparisons. Our algorithms and data structures use a variety of techniques, including Seidel and Ad

关键词： 高职   数据结构   信息化   教学设计  

摘要： 本文结合高职软件技术专业学生特点及实际教学情况,从课程基本信息、教学设计思路、教学活动过程、学习效果评价四方面分析《数据结构》——《二叉树与树、森林之间的转换》的信息化教学设计。

关键词： 计算机   数据   案例  

摘要： 数据结构是中高等职业院校计算机应用、计算机软件及信息管理专业的一门基础课程。由于该课程要求学生掌握较为扎实的计算机基础知识,同时还必须具有一定的逻辑思维能力,因此在教学过程中,教师要充分考虑职校生的认知现状,真正做到因材施教。

关键词： 教材   数据结构   C语言   高等学校   程序设计  

ISBN: (纸本)9787302362593

摘要： 本书内容主要包括三部分：1.预备知识。介绍项目中实验环境、程序组织方式和管理方法，讲解程序及算法的效率估算方法和分析技巧，描述一般测试技术和调试方法以及测试数据及测试用例的设计安排技巧；2.基础实验。首先安排重要的验证性实验，然后设计基于基本数据结构的简单应用实验；3.综合实验(或课程设计)。介绍在一个项目中选择和使用多种基本数据结构的依据和方法，讲解如何有效地将它们融合在一起解决实际的复杂应用问题。

关键词： 微课   数据结构   教学技巧   螺旋上升  

摘要： 数据结构是计算机大类专业的一门重要核心课程,在整个课程体系中起着承上启下的作用。文章分析了微课在数据结构课程中的应用,探讨了微课的特点、微课视频设置的内容以及微课的授课技巧。实践证明将微课作为辅助教学手段,对学生掌握课程内容、增强动手能力有着较大的帮助。

关键词： 数据结构   实验教学   两极分化  

摘要： 本文分析了数据结构课程实验教学的特点、教学现状,针对存在的"两极分化"问题,提出了改善该问题的分层次教学设计方案。该方案对于激发学生的学习兴趣,提高学生的学习积极性和培养学生学以致用的能力非常有益。

关键词： 数据结构   C语言   数据结构   C语言   程序设计  

ISBN: (纸本)9787560633183

摘要： 本书具体内容包括：线性表、栈和队列、串、数组与广义表、树与二叉树、图、查找、排序、数据结构实践应用等。