A direct observation instrument for assessment of nurses' patient transfer technique (DINO)

The aim of this project was to develop a direct observation instrument to assess the work technique of nursing personnel during patient transfers and to test the validity and reliability of the instrument. An expert group developed this instrument, called DINO (DIrect Nurse Observation instrument for assessment of work technique during patient transfers), which contains 16 items divided into three phases of a transfer: the preparation, performance and result phases. To quantify the assessments a scoring system was constructed, giving an overall score for each transfer, depending on the level of musculoskeletal health and safety. Four observers assessed 45 patient transfers at hospital wards and showed in an evaluation that the inter-observer reliability and criterion-related validity of DINO was satisfactory. The assessments with the DINO instrument are done directly when the transfer occurs, without costly equipment. Therefore, it has a wide range of applications. For example, when evaluating training in work technique or when identifying an unsafe work technique as a risk factor for musculoskeletal problems in epidemiological studies.     

非线性参数估计中的观测集预处理技术

非线性参数估计模型中,若系统的可观测度较弱,被估计参数相互耦合,那么参数的估计精度不仅与随机观测噪声有关,与系统的可观测度也有着密切的关系。该文提出一种观测集预处理方法,依据可观测度指标对观测数据进行筛选,然后利用筛选集对参数进行估计。以雷达的系统误差估计为例,使用筛选集估计雷达的系统误差,比直接使用原观测集估计所得结果更为精确。     

矿用运输车的全自动检测系统

介绍了矿用运输车的全自动检测系统,此系统采用智能采集板通过多路传感器对运输车辆的轴重、速度、侧滑和制动等项目的信号采集,借助于计算机实现对运输车辆的全自动检测。     

北洺河铁矿地表及岩层移动观测系统研究

地表塌陷严重威胁着矿山安全生产,破坏地表生念环境。为了全面系统地研究地表塌陷和岩层移动问题,获得准确可靠的监测资料,不但要在地表布设测点,还要住岩层内部布设测点,从地表和岩层内部2个方面着手建迂岩移观测系统,为后期研究地表及岩层的移动和变形规律做好准备工作。     

Do facial reactions add new dimensions to measuring sensory responses to basic tastes?

Basic taste solutions induce sensory perceptions via taste receptors and give rise to specific facial reactions. Many of these have been shown to be innate. The aim of this study was to explore relationships between the sensory perception of basic taste solutions at different concentrations and facial reactions.Basic taste solutions each at three levels plus water were served to a panel. The assessors individually identified quality, intensity and pleasantness. They were recorded during tasting and their facial reactions (based on FACS) were coded and analysed.Facial reactions indicated both quality and concentration of the stimuli. The intensity of most facial reactions increased with increasing stimulus concentration, most pronounced for sourness (lips) and bitterness (eyes and forehead). Pleasantness ratings decreased with increasing concentrations of all basic tastes. Water and the lowest sucrose concentration were perceived as the most pleasant samples and gave rise to the lowest intensity of facial reactions. The study showed that a combination of sensory analyses and facial expressions was successful in adding further insight to the knowledge of perception of basic tastes.     

Iterative Learning Control for discrete nonlinear systems with randomly iteration varying lengths

This note proposes ILC for discrete-time affine nonlinear systems with randomly iteration varying lengths. No prior information on the probability distribution of random iteration length is required prior for controller design. The conventional P-type update law is used with a modified tracking error because of randomly iteration varying lengths. A novel technical lemma is proposed for the strict convergence analysis in pointwise sense. An illustrative example verifies the theoretical results.     

观察运动与想象运动范式的脑电活动相关性研究

当进行想象左右手运动和观察左右手运动时，会以几乎同样的方式改变大脑主要感觉区域的神经活动，引起脑电相关频率成分的特征变化。但是还没有有效的理论来解释两种范式之间是否存在较强的相关性。本文为了研究两种范式之间是否存在着相关性，从对比实验的方法出发，设计了观察运动和运动想象的实验范式，并邀请八名受试者进行了两种范式的对比实验。分类结果显示，相同受试在参与两种范式实验的结果上，没有呈现出明显的相关性，表现虽然两种实验范式可以激发相似的脑电活动现象，但是他们产生的基理还是有差异，本文工作为下一步的研究提供了方向和思路。     

Neighbor embedding XOM for dimension reduction and visualization

We present an extension of the Exploratory Observation Machine (XOM) for structure-preserving dimensionality reduction. Based on minimizing the Kullback-Leibler divergence of neighborhood functions in data and image spaces, this Neighbor Embedding XOM (NE-XOM) creates a link between fast sequential online learning known from topology-preserving mappings and principled direct divergence optimization approaches. We quantitatively evaluate our method on real-world data using multiple embedding quality measures. In this comparison, NE-XOM performs as a competitive trade-off between high embedding quality and low computational expense, which motivates its further use in real-world settings throughout science and engineering.