Validation of a videogrammetry technique for analysing American football helmet kinematics

ABSTRACT

Professional American football games are recorded in digital video with multiple cameras, often at high resolution and high frame rates. The purpose of this study was to evaluate the accuracy of a videogrammetry technique to calculate translational and rotational helmet velocity before, during and after a helmet impact. In total, 10 football impacts were staged in a National Football League (NFL) stadium by propelling helmeted 50th percentile male crash test dummies into each other or the ground at speeds and orientations representative of concussive impacts for NFL players. The tests were recorded by experienced sports film crews to obtain video coverage and quality typically available for NFL games. A videogrammetry procedure was used to track the position and rotation of the helmet throughout the relevant time interval of the head impact. Compared with rigidly mounted retroreflective marker three dimensional (3-D) motion tracking that was concurrently collected in the experiments, videogrammetry accurately calculated changes in translational and rotational velocity of the helmet using high frame rate (two cameras at 240 Hz) video (7% and 15% error, respectively). Low frame rate (2 cameras at 60 Hz) video was adequate for calculating pre-impact translational velocity but not for calculating the translational or rotational velocity change of the helmet during impact.     

Is academic tracking related to gains in learning competence? Using propensity score matching and differential item change functioning analysis for better understanding of tracking implications

This study analyzes gains in cognitive components of learning competence with respect to cohorts based on ability tracking in a Czech longitudinal study. Propensity score matching is used to form parallelized samples of academic and non-academic track students and to eliminate the effect of selective school intake. We applied regression models on the total scores to test for the overall track effect. Furthermore, we analyze scores and gains on the subscores and check for differential item functioning in Grade 6 and in change to Grade 9. While after 3 years, no significant difference between the two tracks was apparent in the total learning competence score, we did, however, find significant differences in some subscores and in the functioning of some items. We argue that item-level analysis is important for deeper understanding of the tracking implications and may provide the basis for more precise evidence-based decisions regarding the tracking policy.     

A compressed self-index using a Ziv–Lempel dictionary

A compressed full-text self-index for a text T, of size u, is a data structure used to search for patterns P, of size m, in T, that requires reduced space, i.e. space that depends on the empirical entropy (H _k or H ₀) of T, and is, furthermore, able to reproduce any substring of T. In this paper we present a new compressed self-index able to locate the occurrences of P in O((m + occ)log u) time, where occ is the number of occurrences. The fundamental improvement over previous LZ78 based indexes is the reduction of the search time dependency on m from O(m ²) to O(m). To achieve this result we point out the main obstacle to linear time algorithms based on LZ78 data compression and expose and explore the nature of a recurrent structure in LZ-indexes, the suffix tree. We show that our method is very competitive in practice by comparing it against other state of the art compressed indexes.

加权的布尔型文本匹配算法研究

本文分析了传统的布尔型文本匹配算法的弊端和缺陷,结合图书文本信息的快速、高效的检索匹配要求,提出了加权的布尔型文本匹配算法。该算法对传统的文本匹配算法中漏检、误检和模糊查询等方面的问题进行了加权处理和结果校正,既保证查询算法的高效与全面性,同时又有效地控制了匹配的准确度,为图书信息查询系统的建立提供一种更好的解决方法。     

基于Fourier-Mellin变换的全景图像拼接与曲线匹配

基于Fourier—Mellin变换的图像配准方法,本文对于图像拼接与曲线匹配进行新探讨。该方法在不需要准确控制相机运动,不需要知道相机的焦距等内部参数及检测图像特征,在配准精度要求不是很高的情况下,直接生成的全景图像可以满足很多实际需求;先将图像曲线转化为二值图像,然后应用Fourier—Mellin变换对这些二值图像进行配准,从而达到两条曲线的匹配。     

自适应回声消除器的设计与实现

介绍了回声消除器的基本结构、回声路径的脉冲响应以及语音信号的特点,分析输入信号为白噪声、有色噪声和语音的情况下自适应算法的性能,在此基础上应用一种参数筛选更新归一化最小均方差(NLMS)算法以及基于互相关的双边对话侦测算法,并提供详细仿真结果。     

基于教师评定的留守儿童学校适应特点

采用学生学校适应教师评定量表对650名留守儿童和698名非留守儿童进行研究,发现：留守儿童学校适应的总体水平极其显著低于非留守儿童,在适应良好的学生中,留守儿童显著少于非留守儿童;留守儿童积极完成学校任务、人际自表与交往信心显著低于非留守儿童,而学习中的消极行为、学校问题行。为以及不良社交问题显著多于非留守儿童;不同性别、学段、学习成绩留守儿童学校适应差异性显著,监护的不同对学校适应影响不明显;留守儿童中,男生、初中生、学业成绩不良学生应得到更多的关注和引导。     

Environment map building and localization for robot navigation based on image sequences

SLAM is one of the most important components in robot navigation. A SLAM algorithm based on image sequences captured by a single digital camera is proposed in this paper. By this algorithm, SIFT feature points are selected and matched between image pairs sequentially. After three images have been captured, the environment＇s 3D map and the camera＇s positions are initialized based on matched feature points and intrinsic parameters of the camera. A robust method is applied to estimate the position and orientation of the camera in the forthcoming images. Finally, a robust adaptive bundle adjustment algorithm is adopted to optimize the environment＇s 3D map and the camera＇s positions simultaneously. Results of quantitative and qualitative experiments show that our algorithm can reconstruct the environment and localize the camera accurately and efficiently.     

Constructing normalcy: a qualitative study of parenting children with Asperger's Disorder

Children with Asperger's Disorder present unique challenges due to their impairments in social functioning. In order to better understand the experiences of parents of children with Asperger's Disorder, interviews were conducted with 20 parents. The interviews were taped, transcribed, and coded using the systematic methods of Grounded Theory. The central phenomenon of “constructing normalcy” emerged from the data as a salient construct for participants. Parents interviewed described a process of meaning‐making with respect to standards of “normalcy” and an effort to create adaptive environments for their children.     

一种基于模糊模型相似测量的字符无监督分类法

提出了一种能有效完成对无监督字符分类的模糊逻辑方法 ,以提高字符识别系统的速度 ,正确性和鲁棒性 .字符首先被分为 8种印刷结构类 ,然后采用模式匹配方法将各类字符分别转换成基于一非线性加权相似函数的模糊样板集合 .模糊无监督字符的分类是字符匹配的一种自然范例并发展了加权模糊相似测量的研究 .本文讨论了该模糊模型的特性并用以加快字符分类处理 ,经过字符分类 ,在字符识别时由于只需针对较小的模糊样板集合而变得容易和快速