Automatic Generation of Virtual Work Guide for Complex Procedures: A Case

Practical work guides for complex procedures are significant and highly affect the efficiency and accuracy of on-site users. This paper presents a technique to generate virtual work guides automatically for complex procedures. Firstly, the procedure information is extracted from the electronic manual in PDF format. And then, the extracted procedure steps are mapped to the virtual model parts in preparation for animation between adjacent steps. Next, smooth animations of the procedure are generated based on a 3D natural cubic spline curve to improve the spatial ability of the work guide. In addition, each step\u27s annotation is automatically adjusted to improve the visual effect of the work guide. A troubleshooting procedure example of the M16A4 Rifle shows that the generated work guide is well instructive, which provides the interactive simulation of the procedure and process-based display of technical annotation

Non-fragile Dynamic Output Feedback H∞ Control for a Class of Uncertain Switched Systems with Time-varying Delay

The problem of non-fragile dynamic output feedback H∞ control for a class of uncertain switched systems with time-varying delay is discussed. Firstly, the form of non-fragile dynamic output feedback H∞ controller is given. Under the condition that the upper bound of time delay and the upper bound of delay derivative are limited simultaneously, Lyapunov functional and its corresponding switching rules are constructed by using single Lyapunov function method and convex combination technique; Secondly, we use the inequality lemma to scale the derived Lyapunov functional in order to eliminate the time-varying delay term in the inequality, and then introduce the J-function to obtain a nonlinear matrix inequality that satisfies the H∞ performance index γ, we also employ Schur complement lemma to transform the nonlinear matrix inequality into set of linear matrix inequalities consisting of two linear matrix inequalities, a sufficient condition for the existence of a non-fragile dynamic output feedback H∞ controller and satisfying the H∞ performance index γ is concluded for a class of uncertain switching systems with variable time delay; Finally, a switched system composed of two subsystems is considered and the effectiveness and practicability of the theorem are illustrated by numerical simulation with LMI toolbox.

Real-Time External Labeling for Interactive Visualization in Virtual Environments

A real-time external labeling algorithm has been developed to explore the potential for applying annotation and visualization to virtual reality environments, which manages label placement in the projections of virtual 3D models on the view plane. The approach intends to place labels with visual constraints, such as no overlapping, intersections, and occlusions, close proximity to the model parts, by adjusting external annotations\u27 positions concerning available space in the view plane. This algorithm is based on the projected model\u27s contour and adapts to camera viewpoint changes within interactive frame rates. It solves the visibility problem of annotations and operates in real-time when the model is rotated. The results show that the proposed method can improve user understanding of complicated 3D models and can be applied to interactive virtual environments

Perceptual Decision Making of Humans and Deep Learning Machines: aBehavioral Study

Human visual perception system is a key issue of the cognitive researches. It is also an inspiring prototype of thecutting-edge artificial intelligence researches - deep learning. It is interesting to investigate the behaviors of humans and deeplearning machines on vision tasks. In this paper, we focus on the perceptual decision making and object recognition on distortedimages. We found that in a wide range of distortion levels, the recognition rates of human subjects are smoothly increased alongwith the decreases of distortions. Although the deep learning machines perform obviously worse than human subjects, theirrecognition rates vary with the similar trends. It indicates that the deep learning machines make a good simulation to the humanbeing on the perceptual decision making tasks

Uterine Contraction Modeling and Simulation

Building a training system for medical personnel to properly interpret fetal heart rate tracing requires developing accurate models that can relate various signal patterns to certain pathologies. In addition to modeling the fetal heart rate signal itself, the change of uterine pressure that bears strong relation to fetal heart rate and provides indications of maternal and fetal status should also be considered. In this work, we have developed a group of parametric models to simulate uterine contractions during labor and delivery. Through analysis of real patient records, we propose to model uterine contraction signals by three major components: regular contractions, impulsive noise caused by fetal movements, and low amplitude noise invoked by maternal breathing and measuring apparatus. The regular contractions are modeled by an asymmetric generalized Gaussian function and least squares estimation is used to compute the parameter values of the asymmetric generalized Gaussian function based on uterine contractions of real patients. Regular contractions are detected based on thresholding and derivative analysis of uterine contractions. Impulsive noise caused by fetal movements and low amplitude noise by maternal breathing and measuring apparatus are modeled by rational polynomial functions and Perlin noise, respectively. Experiment results show the synthesized uterine contractions can mimic the real uterine contractions realistically, demonstrating the effectiveness of the proposed algorithm