Depth from Refraction Using a Transparent Medium with Unknown Pose and Refractive Index

In this paper, we introduce a novel method for depth acquisition based on refraction of light. A scene is captured directly by a camera and by placing a transparent medium between the scene and the camera. A depth map of the scene is then recovered from the displacements of scene points in the images. Unlike other existing depth from refraction methods, our method does not require prior knowledge of the pose and refractive index of the transparent medium, but instead can recover them directly from the input images. By analyzing the displacements of corresponding scene points in the images, we derive closed form solutions for recovering the pose of the transparent medium and develop an iterative method for estimating the refractive index of the medium. Experimental results on both synthetic and real-world data are presented, which demonstrate the effectiveness of the proposed method.     

A new moving target interception algorithm for mobile robots based on sub-goal forecasting and an improved scout ant algorithm

It is difficult to make a robot intercept a moving target, whose trajectory and speed are unknown and dynamically changing, in a comparatively short distance when the environment contains complex objects. This paper presents a new moving target interception algorithm in which the robot can intercept such a target by following many short straight line trajectories. In the algorithm, an intercept point is first forecasted assuming that the robot and the target both move along straight line trajectories. The robot rapidly plans a navigation path to this projected intercept point by using the new ant algorithm. The robot walks along the planned path while continuously monitoring the target. When the robot detects that the target has moved to a new grid it will re-forecast the intercept point and re-plan the navigation path. This process will be repeated until the robot has intercepted the moving target. The simulation results have shown that the algorithm is very effective and can successfully intercept a moving target while moving along a relatively short path no matter whether the environment has complex obstacles or not and the actual trajectory of the moving target is a straight line or a complex curve.     

Feature engineering for semantic place prediction

We present in this paper our winning solution to Dedicated Task 1 in Nokia Mobile Data Challenge (MDC). MDC Task 1 is to infer the semantic category of a place based on the smartphone sensing data obtained at that place. We approach this task in a standard supervised learning setting: we extract discriminative features from the sensor data and use state-of-the-art classifiers (SVM, Logistic Regression and Decision Tree Family) to build classification models. We have found that feature engineering, or in other words, constructing features using human heuristics, is very effective for this task. In particular, we have proposed a novel feature engineering technique, Conditional Feature (CF), a general framework for domain-specific feature construction. In total, we have generated 2,796,200 features and in our final five submissions we use feature selection to select 100 to 2000 features. One of our key findings is that features conditioned on fine-granularity time intervals, e.g. every 30 min, are most effective. Our best 10-fold CV accuracy on training set is 75.1% by Gradient Boosted Trees, and the second best accuracy is 74.6% by L1-regularized Logistic Regression. Besides the good performance, we also report briefly our experience of using F# language for large-scale (～70 GB raw text data) conditional feature construction.     

An integrated e-service model for electronic medical records

In this paper, we discuss the critical issues with the implementation of electronic medical records and argue that the emerging e-services will not fully resolve the issues if they do not work together. To meet the challenge, we propose an integrated e-service model consisting of both process- and data-oriented grids that glue together distributed electronic medical services, records, and application services. We also provide an implementation architecture and prototype that validates the model.     

欧美小型电动机能效法规最新动态研究

欧盟和美国先后对小型电动机的能效要求出台强制性法规,分别于2009年、2010年正式实施。从主要内容和技术指标解读两项法规,重点研究欧美对于2.2kW以下的小型电动机的最低能效要求及我国相关国家标准要求的差异。在此基础上,提出应对两项法规的思路和建议。     

密炼机动态消谐无功补偿设备

对某公司橡胶密炼机设备负荷进行实测分析,提出采用动态消谐无功补偿设备的解决方案,并介绍了该设备的特点、技术指标、校验以及补偿效果。     

基于流固耦合方法的运载火箭安全阀颤振问题研究

安全阀是运载火箭增压输送系统所属重要单机,用于保护推进剂贮箱免受过压,在地面测试中曾出现安全阀在启闭过程中主阀颤振现象,导致零件受损并影响产品性能.基于动网格下的N-S流动方程和非线性接触下的刚体运动控制方程的流固耦合方法,采用Realizable k-ε湍流模型和显式动力学算法分析了阀门的气动载荷,进而分析出阀门颤振产生的机理为流场压力脉动与结构频率耦合和活塞在冲击响应作用下与阀杆都产生了塑性变形,据此提出增大运动部件尺寸来改善结构频率的措施,并对改善后的产品开展抽样试验验证,测试结果表明采取的改善措施有效地解决了阀门颤振问题,具有实际的工程价值.     

一体式活塞内模结构设计及应用

采用一体式内模代替原来的两体式内模铸造模具,简化了模具制造工艺、节约了制造成本、美化了活塞内腔。利用Magma软件模拟浇注,发现一体式内模容易出现的缺陷以及缺陷存在的位置,并提出有效的解决方法。通过在小缸径活塞上的实际应用,取得了良好的效果。