样本

The traditional mean shift algorithm requires a symmetric kernel, such as a circle or a rectangle, and assumes that the target's scale is symmetric during the course of tracking.

与采用对称核函数的均值迁移目标跟踪算法相比，采用目标边缘点作为核函数中的样本点，参与计算的样本点为核窗口中样本的5%～10%，使图像处理速度达到了50 帧/s 以上，满足了实时跟踪的要求。

In this framework, image frame, audio and text are represented, which are the three modalities in video shots as data points by the 3rd-order tensor. Then a subspace embedding and dimension reduction method is proposed, which explicitly considers the manifold structure of the tensor space from temporal-sequenced associated co-occurring multimodal media data in video. It is called TensorShot approach. Transductive learning uses a large amount of unlabeled data together with the labeled data to build better classifiers. A transductive support tensor machines algorithm is proposed to train effective classifier. This algorithm preserves the intrinsic structure of the submanifold where tensorshots are sampled, and is also able to map out-of-sample data points directly. Moreover, the utilization of unlabeled data improves classification ability.

在此框架中，视频镜头首先被表示成由视频中所包含的文本、视觉和听觉等多模态数据构成的三阶张量；其次，基于此三阶张量表达及视频的时序关联共生特性设计了一种子空间嵌入降维方法，称为张量镜头；由于直推式学习从已知样本出发能对特定的未知样本进行学习和识别，最后在这个框架中提出了一种基于张量镜头的直推式支持张量机算法，它不仅保持了张量镜头所在的流形空间的本征结构，而且能够将训练集合外数据直接映射到流形子空间，同时充分利用未标记样本改善分类器的学习性能。

The long term trend of silicon content series was removed by performing multi-resolution analysis and the multi-fractal characteristics of the remaining part was analyzed.

以包钢6号高炉、邯钢7号高炉和莱钢1号高炉在线采集的铁水含硅量的时间序列为样本，利用多分辨分析剔除样本的长期趋势，对样本保留的波动趋势进行多重分形特征辨识。

Unlike unbiasedness―which is a feature of an estimator for a given sample size―consistency involves the behavior of the sampling distribution of the estimator as the sample size n gets large.

无偏性是，给定样本容量n下，估计量的性质；一致性则是，当样本容量n变大时，估计量的样本分布的变化特征。

Stressing on "fine reputation","quality","service","credit","practice", not only the grandeur.④Encouraging the innovation, not the unearthliness, playing down the effect of entertainment stars or idols, decreasing the fashion index.⑤"personality" is not the "self central". Social sense of responsibility and interpersonal "feeling of affinity" are both intensified.3.1.2 Factor analysis, revealing 19 value element vectors, which include "comfort","personality","simple","fine reputation","responsibility","service","price","wisdom","distinction","enthusiasm","stimulation","taste","sex difference","quality","vigor","idol","fashion","affinity","aesthetic" and so on. Four orientation diagrams coordinated with the average factors and the standard deviations of these 19 value elements, described the multi directional value orientation structure for China college students' sportswear consumption.3.1.3 Clustering analysis are applied to classify the former 19 value elements, which discovered that three inferior group are classified from the college students' consumption group based on the whole specimen data. It could be the reference of enterprise brand building for the orientation of consumption values.3.2 General personal values, self conception and demographic are lead into as three major variables for the interrelationship analysis of sportswear consumption value system.3.2.1 Firstly, the college students having their general values and existing the inferior group feature regarding to the consumption values.

三、研究的主要成果及其意义对中国大学生休闲服消费价值体系进行探索性分析1、首先对中国大学生休闲服消费价值观量化问卷所调查的样本数据进行频数统计趋向性分析，发现呈现的主要特点有：(1)"个性化"和"简约"已成为潮流，而寻"刺激"、找"激情"总体收敛；(2)追求"美感"，更不放弃"舒适"，两者兼得才是完美；(3)重"美誉"、讲"质量"，重"服务"、讲"信用"，求实际、不求高贵，"明智"有素；(4)求新不求怪异，明星、偶像效应淡化、时尚指数不高；(5)"个性化"不是"唯我化"，社会责任感和人际"亲和力"在强化。2、其次对样本数据进行因子分析，揭示出以"舒适"、"个性"、"简约"、"美誉"、"责任"、"服务"、"价格"、"明智"、"独特"、"激情"、"刺激"、"品位"、"性差"、"质量"、"活力"、"偶像"、"时尚"、"亲和"和"美感"等十九个价值元素为矢量的休闲服消费价值体系，并以因子均值和标准差为参数勾画出19个价值元素坐标四方位图，从总体上描述了中国大学生休闲服消费多维的价值取向结构。3、再者进行聚类分析，对上述十九个休闲服消费价值元素作不同量值的分类，发现在样本总量中可以细分为有较大区分度的三个类别，呈现出大学生消费群体中存在休闲服消费价值体系不同的亚群体，可为以消费价值观为取向的企业品牌价值定位提供参考基谱。

In this paper, a progressive transductive support vector machine is devised and the experimental results show that the algorithm is very promising on a mixed training set of a small number of unlabeled examples and a large number of labeled examples.

提出了一种基于支持向量机的渐进直推式分类学习算法，在少量有标签样本和大量无标签样本所构成的混合样本训练集上取得了良好的学习效果。

The population statistics and life style of this questionnaire are obvious different in 10 of the MP3 players. The statistics investigates 7 of user emotions with the shape of products all fall in the same line, which are desire、pleasant surprise、inspiration、amusement、admiration、satisfaction and fascination. The phenomenon explains user' impression with the shape of product are partial to equal pleasure or unpleasure.

在人口统计问项与生活型态族群对十组MP3随身听样本的情感，会有显著的差异性，研究统计中，发现个人对产品外观愉悦的七个情感，几乎落在同一直线上，其对所观看的样本之七个情感（鼓舞、惊喜、赞赏、乐趣、渴望、满意、迷恋）是偏向相同愉悦或相同不愉悦的，也就是观看此样本的愉悦性是一致的。

Based on the analysis on the physical property of complex HRRP samples, we point out that the frame template, classification algorithm and feature extraction method for complex HRRP samples should be unvaried with the initial phases.

在分析复数HRRP样本特性的基础上，指出由于初相敏感性问题，原先适用于实数HRRP样本的方位模板、识别方法和特征提取方法一般都不能直接用于基于复数HRRP的RATR，我们必须重新寻找既与复数HRRP样本的初相无关又能利用其剩余相位信息的方法。

The samples of 600℃ group didn't crystallize, but the color became darker and yellower as the peolongation of the heating time; the samples of 650℃ and 700℃ groups crystallized in different degrees, the translucency and Chroma decreased as the prolongation of the heating time, but the Value increased.

600℃组各样本均未晶化，随着保温时间的延长，其颜色逐渐加深，偏黄，650℃及700℃组各样本均发生不同程度的晶化，随晶化温度的升高及保温时间的延长，样本的透明度逐渐降低，亮度逐渐升高，色调变浅且饱和度逐渐降低

Blood lead concentrations were analyzed by seven participating laboratories, each used flameless atomic absorption spectrophotometry and followed the same protocols for BLL measurements.

每个受到实验室参考标准的样本处理分析程序，以石墨炉原子吸收光谱仪来测试血液样本中的铅含量，并需於收到测试样本两个星期内完成测试工作。

The concept of equivalent rotationally rigidity is offered and the formula of rotationally rigidity is obtained.

主要做了如下几个方面的工作：对伸臂位于顶部的单层框架—筒体模型进行分析，提出了等效转动约束的概念和转动约束刚度的表达式。

Male cats normally do not need aftercare with the exception of the night after the anesthetic.

男猫通常不需要善后除了晚上的麻醉。