一种有效的历史移动对象轨迹的k最近邻居查询算法

近10多年来,研究者们已经在k最近邻居(kNN)查询方面做了很多工作,但是对于移动对象轨迹的kNN查询处理却研究得很少.鉴于此,研究了在存储有历史移动对象轨迹信息的TB树结构上的kNN查询问题,并且提出了一种有效的基于最佳优先搜索范例的kNN(k≥1)查询算法,称为BFPkNN.BFPkNN是一种I/O最佳的算法,即它仅仅访问有可能包含最终结果的结点.同时,为了减少存储空间和CPU代价,又提出了若干有效的剪枝策略.大量的实验证明BFPkNN在效率和可扩展性上均大大胜过其他同类算法.     

Virtual grasps recognition using fusion of Leap Motion and force myography

Hand gesture recognition is important for interactions under VR environment. Traditional vision-based approaches encounter occlusion problems, and thus, wearable devices could be an effective supplement. This study presents a hand grasps recognition method in virtual reality settings, by fusing signals acquired using force myography (FMG), a muscular activity-based hand gesture recognition method, and Leap Motion. We conducted an experiment where participants performed grasping of virtual objects with VR goggles on their head, an FMG band on their wrist, and a Leap Motion positioned either on the desk or on the goggles (two experimental settings). The FMG, Leap Motion, and fusion of both signals were used for training and testing a simple, but effective linear discriminant analysis classifier, as well as three other mainstream classification algorithms. The results showed that the fusion of both signals achieved a significant improvement in classification accuracy, compared to using Leap Motion alone in both experimental settings.     

利用语料库技术的中文自动文摘系统

本文着重介绍利用“后邻字符树”的方法在领域语料库中生成字符树库,用于自动文摘候选句子选取时提高精度,介绍了后邻字符树的构造、后邻字符树库的生成及优化和句子权值计算方法。     

公文流转中复杂工作流程的通用设计

该文针对传统办公自动化系统中公文流转的固定流程和流转复杂性的矛盾,提出了以动态流程为基础的复杂工作流程的通用设计方法.同时结合开发实例加以剖析,并展望了今后的发展前景.     

Uncertainty Visualization for Mobile and Wearable Devices Based Activity Recognition Systems

Mobile and wearable devices based activity recognition systems utilize built-in sensors to identify the activities performed by users pervasively. However, most of these systems do not explicitly present the sensing process to users and are prone to uncertainty. The presence of uncertainty makes users feel confused about the behaviors of activity recognition systems, which may affect the confidence of users. Uncertainty visualization has become an interesting research topic purporting to help users better understand systems. In this paper, we present an uncertainty visualization to reveal the process of mobile and wearable devices based activity recognition systems. We conducted an experiment to evaluate the uncertainty visualization by using a particular simulated mobile and wearable devices based activity recognition application. The results showed that the uncertainty visualization was effective in helping users understand and trust the judgments and inferences of the activity recognition application. Based on the advice of participants, we concluded a few directions to improve the uncertainty visualization.     

Tactile object recognition in early phases of grasping using underactuated robotic hands

Intelligent Service Robotics - Identifying objects during the early phases of robotic grasping in unstructured environments is a crucial step toward successful dexterous robotic manipulation....