Toward Better Understanding of Task Difficulty during Physicians’ Interaction with Electronic Health Record System (EHRs)

ABSTRACT

The goal of this study was to assess the relationship of task difficulty and mental effort with performance during physicians’ interaction with electronic health records (EHRs). A total of 38 physicians were asked to identify abnormal results and take follow-up action to “close the loop” on care delivery. Task difficulty was quantified via task-flow strategies and computer mouse-click patterns. Mental effort was quantified using eye movements based on changes in pupillary dilations (task evoked pupillary response or TEPR) and blink rate. Performance was quantified based on commission errors (error vs. no-error). Results indicated that physicians had different task-flow strategies; however, with improved awareness of the patient status, they exhibited an optimal task-flow strategy. Overall, performance was related to task-flow strategies, computer mouse-click patterns, and blink rate, indicating that physicians had lower task-difficulty and experienced lower mental effort with improved awareness of patient follow-up status. This is an important finding demonstrating that task-flows are a dominant predictor of physician performance when comparing between EHR designs. On the contrary, mouse-click patterns and blink rate are both useful predictors of physician performance when assessment was done within an EHR.     

Speech authentication by semi-fragile speech watermarking utilizing analysis by synthesis and spectral distortion optimization

This paper proposes an improved semi-fragile speech watermarking scheme by quantization of linear prediction (LP) parameters, i.e., the inverse sine (IS) parameters. The spectral distortion due to watermark embedding is controlled to meet the ‘transparency’ criterion in speech coding. A modified bit allocation algorithm combined with watermarking is developed to determine the quantization step so that the ‘transparency’ requirement is satisfied. Due to the statistical nature, the LP coefficients estimated from the watermarked speech signal are different from the watermarked LP coefficients even in the absence of attacks. This effect is the cause of increase in decoding error and minimum authentication length. To tackle this problem, an Analysis by Synthesis (AbS) scheme is developed to reduce the difference between the estimated LP coefficients and the watermarked ones. The watermark detection threshold and minimum authentication length are then derived according to the probability of error and the signal to noise ratio (SNR) requirements. Experimental results show that the proposed AbS based method can effectively reduce the difference between the watermarked IS parameter and the extracted IS parameter when there is no attacks. In addition, the modified bit allocation algorithm can automatically find the appropriate quantization step used in the odd-even modulation so that the transparency requirement is satisfied.     

On Controllability of Switched Linear Systems

This paper investigates the number of switchings and design of switching sequences for controllability of switched linear systems. Two related results are established. One is a new constructive approach to designing switching sequences. The controllable state set of each switching sequence designed via the approach coincides with the controllable subspace of switched linear systems. The other is a well-estimated value for the minimum number of switchings required for controllability. Each state in the controllable subspace can be steered to origin within this value of switching times.     

New insights on survivability in multi-domain optical networks

With the development of intelligent optical networks and the general multi-protocol label switching (GMPLS) technique, the seamless convergence between IP network and optical network is no longer be a dream but a practical reality. Similar to the Internet, current optical networks have been divided into multiple domains each of which has its own network provider and management policy. Therefore, the development of multi-domain optical networks will be the trend of new-generation intelligent optical networks, and GMPLS-based survivability for multi-domain optical networks will become a hot topic of research in the future. This paper provides a comprehensive review of the existing survivable schemes in multi-domain optical networks and analyzes the shortcomings of current research. Based on previous studies, we present possible challenges and propose new ideas to design efficient survivable schemes to guide the future work of researchers in multi-domain optical networks.     

基于运动估算的多分辨率地形分块调度方法

针对常用的基于视点位置进行地形分块调度方法存在可视窗口固定、调度范围和时机不能根据视点运动特点进行调整而导致内存利用率低的问题,提出一种基于运动估算的地形分块调度方法.以数据密度为标准进行多分辨率地形划分,结合四叉树和二维矩阵对地形分块建立空间索引,重点研究以视点位置、视线方向、视点运动向量和地形分块数据量为参数的调度方法;通过计算预加载区域和卸载区域的地形分块,实时更新其调度范围和调度时机.实验结果表明,与基于视点位置的方法相比,该方法平均能提高3～4倍左右的内存有效数据比例和绘制帧速.     

液剂视频序列中运动异物的模糊自适应分割

运动异物的正确分割是实现液剂自动检测的关键.提出一种基于帧差图空间方差和方差梯度的液剂异物模糊自适应阈值分割算法.首先将4帧序列图像差分得到的2幅帧差图分为5×5的图像块,计算2幅帧差图对应图像块间的方差和方差梯度,并以两者的乘积构成新特征图;然后使用自适应阈值对新特征图进行运动异物分割和提取.为使阈值能够跟随图像块灰度变化,阈值的调整采用模糊推理依据方差和方差梯度变化自适应实现.实验及实际测试结果表明,该算法能够满足低对比度和局部光照变化的液剂异物实时检测要求,是一种实用有效的图像分割算法.     

面向业务问题求解的知识供应过程模型

为了满足企业在业务问题求解方面的实际需求,提出了一个面向业务问题求解的知识供应过程模型。该模型提出了知识供应过程中的问题空间、知识空间和流程空间的概念及其关联关系,并进一步给出了包含知识的获取、评价、存储和重用的知识供应过程的有关算法。该模型与算法将业务问题求解过程与知识供应过程进行了融合,通过关联关系实现了知识的主动供应,在优化了业务问题求解过程的同时,提高了知识积累的质量和知识重用的效率。基于该模型建立了知识管理问题求解的原型系统KMPSS,并得到了初步应用验证。     

基于LabVIEW 8.0测定纯液体蒸发焓的虚拟仪器

将常规的数字温度仪与压力计通过串行口和计算机连接,构建基于LabVIEW 8.0测定纯液体蒸发焓的虚拟仪器,实现实验数据的动态采集、实时显示、自动绘制p～T曲线并显示曲线方程、自动数据处理和写成结果报告等。应用结果表明:基于LabVIEW构建的测定纯液体蒸发焓的虚拟仪器,免除人工操作的繁琐和人为误差,测定乙醇和苯蒸发焓的相对误差分别为0.86%、-2.97%,提高了测量结果的准确度,且具有界面友好,操作简便和功能易扩展等诸多优点。     

基于3D可视化GIS的前视参考图生成方法

基于匹配识别的导航系统不能缺少匹配参考图的支持,制备前视匹配参考图更是前视目标匹配识别的一个关键环节。为了利用航空航天图象信息制备出有效的前视匹配识别所需的参考图,提出了基于3D可视化GIS的前视参考图生成方法,介绍了该方法总体思路,分析了其中的三维数据制备、目标区三维场景生成和前视匹配序列参考图生成等关键环节,给出了部分制备的参考图与实时图的匹配实验结果。实验结果表明,利用这种方法制备的前视参考图可以满足前视匹配识别的需求。     

A hybrid clustering and graph based algorithm for tagSNP selection

TagSNP selection, which aims to select a small subset of informative single nucleotide polymorphisms (SNPs) to represent the whole large SNP set, has played an important role in current genomic research. Not only can this cut down the cost of genotyping by filtering a large number of redundant SNPs, but also it can accelerate the study of genome-wide disease association. In this paper, we propose a new hybrid method called CMDStagger that combines the ideas of the clustering and the graph algorithm, to find the minimum set of tagSNPs. The proposed algorithm uses the information of the linkage disequilibrium association and the haplotype diversity to reduce the information loss in tagSNP selection, and has no limit of block partition. The approach is tested on eight benchmark datasets from Hapmap and chromosome 5q31. Experimental results show that the algorithm in this paper can reduce the selection time and obtain less tagSNPs with high prediction accuracy. It indicates that this method has better performance than previous ones.