Implementation and experimental study on fast object modeling based on multiple structured stripes

In this paper, a practical structured light-based system for fast object modeling and reconstruction is reported. The system consists of an off-the-shelf digital projector, a video camera and a turntable. The system calibration is implemented accurately and automatically by taking a single image of an illuminated calibration template. The multiple color light stripes emitted by the projector adopt only three colors and the color can be modified easily according to the surface texture of the object. This makes the system widely applicable in many situations, and the assumption about color neutrality, which is a limitation to other similar systems, can be largely relaxed. The registration and merging algorithm is greatly simplified by employing a turntable. The validity and high accuracy of the method are demonstrated by extensive real experiments.     

近红外传感器在汽车改造技术中的应用研究

利用反射式近红外传感器及语音录放组件,研究了汽车倒车防撞语音提示器。当汽车倒车时,只要距车身后尾一定的距离内有人或物体存在,就会有一部分红外光信号经人或物体反射回来,被与发射管同排安装的光敏接收管收到并转换成同频率的电信号后,由模块内部电路进行放大、解调、整形、比较处理后,在输出端输出控制信号,控制语音录放组件工作,告诉司机车后有人、车后有物体。由于近红外线传感器、语音录放组件均为一体化结构,成本低、接线简单、抗震能力强、测量准确、工作稳定可靠,适合在汽车上安装使用。     

排序问题中优化准则关于基本参数的正则性及其应用

本文提出了优化准则关于加工时间、准备时间、应交工时间的正则性，利用这种正则性对寻找参数可控排序问题中的有效值、有效解给出了一直观算法，并指出对一些具体的参数可控排序问题，其有效值、有效解的寻找可通过对这一直观算法加以具体化而得．文中还对平均流程问题给出了这样一个具体化算法．     

共焦扫描显微成象系统的点扩散函数再商讨

针对共焦扫描显微成象中物体相对于被扫描点的位置矢量是反向移动的特性,探讨了物体移动后的物函数在此基础上,根据成象的理论进行了计算,得到新的系统点扩散函数表达式,最后根据计算结果分析成象的性质,得出了系统成象的相干性.     

结合区域提取和改进卷积神经网络的水下小目标检测

针对水下小目标信息量有限而难以提取有效特征导致的检测性能不佳问题,提出了一种结合区域提取和融合Hu矩特征的改进卷积神经网络水下小目标检测方法。该方法包含区域提取和分类两个步骤。首先以马尔可夫随机场分割算法为基础进行区域提取,对潜在目标定位的同时降低伪目标对后续分类的干扰;然后提取潜在目标区域的Hu矩特征并融入卷积神经网络,形成一种形状特征表征能力更强的改进卷积神经网络用于分类。声呐实测数据处理结果表明,该方法可以有效提升对水下小目标的发现概率和正确报警率,与其他目标检测方法相比,该方法具有更好的检测性能和泛化性。     

INFORMA基于TMN 的OXC''''s 信息建模(英文)

本文介绍了对多波长光传送网实施基于ＴＭＮ 管理中涉及的信息建模的方法问题，在建议了一组用于描述光传送网通用功能的基本传送对象类的基础上，讨论了几种典型ＯＸＣ′ｓ 信息建模的方法，包括可能用到的对象类，这些方法和对象类为建立实际的、完整的ＯＸＣ′ｓ 信息模型提供了的基础－     

基于形式概念的对象粒的属性逻辑公式描述

基于形式概念在属性集上建立逻辑语言系统,证明基于形式概念的基本对象粒描述定理,讨论合取原子属性逻辑公式所描述对象粒的性质,提出一个求解描述对象粒的属性逻辑公式的算法。     

Sub-sample swapping for sequential Monte Carlo approximation of high-dimensional densities in the context of complex object tracking

In this paper, we address the problem of complex object tracking using the particle filter framework, which essentially amounts to estimate high-dimensional distributions by a sequential Monte Carlo algorithm. For this purpose, we first exploit Dynamic Bayesian Networks to determine conditionally independent subspaces of the object’s state space, which allows us to independently perform the particle filter’s propagations and corrections over small spaces. Second, we propose a swapping process to transform the weighted particle set provided by the update step of the particle filter into a “new particle set” better focusing on high peaks of the posterior distribution. This new methodology, called Swapping-Based Partitioned Sampling, is proved to be mathematically sound and is successfully tested and validated on synthetic video sequences for single or multiple articulated object tracking.     

An exploration of students’ errors in derivatives in a university of technology

This paper reports on an exploration of errors that were displayed by students who studied mathematics in chemical engineering in derivatives of various functions such as algebraic, exponential, logarithmic and trigonometric functions. The participants of this study were a group of twenty students who were at risk in an extended curriculum programme in a university of technology in Western Cape, South Africa. The researcher used a qualitative case study approach and collected data from students’ written work. This research uses action, process, object, and schema (APOS) theory to classify errors into categories and to analyse and interpret the data collected. The students displayed five different kinds of errors, namely, conceptual, interpretation, linear extrapolation, procedural and arbitrary. The use of APOS theory as a framework revealed that several students’ errors might be caused by over-generalisation of mathematical rules and properties such as the power rule of differentiation and distributive property in manipulation of algebraic expressions. This study suggests that teaching of the standard rules of differentiation should put emphasis on its restrictions to eliminate common errors that normally crop up due to over-generalisation of certain differentiation rules.     

基于ICA的X射线医学图像目标提取

X射线医学成像能观察到患者体内病变组织,对医学诊断有重要参考价值。针对传统医学X射线图像噪声强、层次感差和器官组织重叠的问题,提出利用多能谱X射线成像结合独立成分分析(independent component analysis, ICA)进行图像去噪和目标提取。首先ICA结合稀疏编码收缩法对图像降噪预处理以保证目标提取精度;然后根据图像中各目标组成特性,分离图像中每个像素对应的目标厚度矩阵;最后ICA以盲分离理论获得收敛矩阵重建出目标对象。在ICA算法中,借助于主观评价标准,发现当收敛次数大于40时目标分离成功;当幅值尺度在[25, 45]区间内,目标图像对比度高且失真较小。同时,通过观测实验得到的三维峰值信噪比图表明：ICA算法中收敛次数和幅值对图像质量有较大影响,当重建图像的对比度和边缘信息均达到较好效果时,收敛次数与幅值为85和35。