The cognitive mechanism of haptic recognition of two-dimension images

触觉二维图像可以辅助视觉受损人群,将视觉信息转化为触觉信息,从而感知外部世界。触觉二维图像的识别可能是通过触觉信息在大脑中进行"视觉转化"的方式而完成,并且会受到图形的几何特征、视角与透视、视觉经验、视觉表象能力、触觉探索过程、训练以及年龄的影响。探索触觉二维图像识别的认知神经机制,对于触觉二维图像设计的改进和可用性的提高,具有重要意义

基于CA模型的城市边缘区土地利用演变模拟——以广州市花都区为例

研究目的:探索土地利用的多地类CA模拟方法,并掌握城市边缘区土地利用变化规律。研究方法:选取典型城市边缘区——广州市花都区为研究区域,利用C#语言结合ArcEngine GIS平台编程进行花都区土地利用演变CA模拟研究。以不同时间研究区土地利用图为基础数据,比较研究期内各地类的变化数量与方向以确定地类转换之间的优先级,并确定各地类的转换概率阈值。然后利用蒙特卡罗方法结合控制因素进行判断,最终确定元胞的转化状态。研究结果:模拟结果表明,2000—2005年间,新增建设用地分布在除北部山区以外的所有区域,但主要集中在城市中心区域,农用地主要分布在西南部和东北部,而且破碎化程度越来越高。在流向上,仍然有不少数量的农用地(主要为耕地和林地)转向建设用地。与实际情况相比,模拟的数量精度为84.8%,位置精度为71.3%。研究结论:研究结果表明此方法便于理解与操作,同时模拟精度较高

Multi-factor Analysis Assisting T-Image Design for Tactile Cognition

为了使更多盲人能受益于盲文书籍所伴随的插图,区别于传统的V图像(视觉图像),对设计适合触觉认知的T图像(触觉图像)提出新的设计原则.首先将242张常见物品的V图像制作为线条凸起的可触摸图片;然后邀请10位盲人被试和10位蒙眼明眼人被试通过触摸来尽量准确地命名这些线条图,并要求被试在触摸的过程中进行"出声思维";再根据被试对线条图的描述,提取22个可能影响二维线条图触觉识别的特征;最后以识别正确率作为图片识别难易程度的指标,使用随机森林算法进行了特征建模,并对所有特征进行单因素和多因素的回归分析.实验结果表明,通过随机森林算法建立的模型,可以基于图片中这些特征预测图片触觉识别的难易程度;通过多因素回归分析,提取出对触觉识别有显著影响力的几个重要特征,并用于指导T图像的设计

适应月面环境的机器人化全景相机转台

本实用新型涉及一种转台，特别涉及一种适应月面环境的机器人化全景相机转台。包括俯仰关节、方位关节、基连杆、火工锁紧单元及相机安装板，其中方位关节的一端与基连杆连接，另一端与俯仰关节的一端连接，俯仰关节的另一端与相机安装板连接，火工锁紧单元与方位关节和相机安装板连接。本实用新型的全景相机转台应用于月面及深空探测，和高、低温、真空、月尘、辐射等恶劣工况环境，为相机等功能载荷提供二维协同自由转动功能

JUNO Sensitivity on Proton Decay p→νˉK+p\to \bar\nu K^+ Searches

The Jiangmen Underground Neutrino Observatory (JUNO) is a large liquid scintillator detector designed to explore many topics in fundamental physics. In this paper, the potential on searching for proton decay in $p\to \bar\nu K^+$ mode with JUNO is investigated.The kaon and its decay particles feature a clear three-fold coincidence signature that results in a high efficiency for identification. Moreover, the excellent energy resolution of JUNO permits to suppress the sizable background caused by other delayed signals. Based on these advantages, the detection efficiency for the proton decay via $p\to \bar\nu K^+$ is 36.9% with a background level of 0.2 events after 10 years of data taking. The estimated sensitivity based on 200 kton-years exposure is $9.6 \times 10^{33}$ years, competitive with the current best limits on the proton lifetime in this channel

JUNO sensitivity on proton decay p → ν K + searches*

The Jiangmen Underground Neutrino Observatory (JUNO) is a large liquid scintillator detector designed to explore many topics in fundamental physics. In this study, the potential of searching for proton decay in the $p\to \bar{\nu} K^+$ mode with JUNO is investigated. The kaon and its decay particles feature a clear three-fold coincidence signature that results in a high efficiency for identification. Moreover, the excellent energy resolution of JUNO permits suppression of the sizable background caused by other delayed signals. Based on these advantages, the detection efficiency for the proton decay via $p\to \bar{\nu} K^+$ is 36.9% ± 4.9% with a background level of $0.2\pm 0.05({\rm syst})\pm$$0.2({\rm stat})$ events after 10 years of data collection. The estimated sensitivity based on 200 kton-years of exposure is $9.6 \times 10^{33}$ years, which is competitive with the current best limits on the proton lifetime in this channel and complements the use of different detection technologies