基于大数据的成绩可视化分析与研究

从海量的大数据中挖掘出潜在的有价值的信息并进行可视化分析已成为研究的热点.文章根据成绩大数据,从班级、课程等多维度进行成绩可视化分析,为教学管理者提供学生学习情况分析服务.经研究发现,成绩的可视化分析不仅能为管理者提供精准的教学支持,还能使学生及时发现学业问题.     

Haptic teleoperation of a multirotor aerial robot using path planning with human intention estimation

Classical haptic teleoperation systems heavily rely on operators’ intelligence and efforts in aerial robot navigation tasks, thereby posing significantly users’ workloads. In this paper, a novel shared control scheme is presented facilitating a multirotor aerial robot haptic teleoperation system that exhibits autonomous navigation capability. A hidden Markov model filter is proposed to identify the intention state of operator based on human inputs from haptic master device, which is subsequently adopted to derive goal position for a heuristic sampling based local path planner. The human inputs are considered as commanded velocity for a trajectory servo controller to drive the robot along the planned path. In addition, vehicle velocity is perceived by the user via haptic feedback on master device to enhance situation awareness and navigation safety of the user. An experimental study was conducted in a simulated and a physical environment, and the results verify the effectiveness of the novel scheme in safe navigation of aerial robots. A user study was carried out between a classical haptic teleoperation system and the proposed approach in the identical simulated complex environment. The flight data and task load index (TLX) are acquired and analyzed. Compared with the conventional haptic teleoperation scheme, the proposed scheme exhibits superior performance in safe and fast navigation of the multirotor vehicle, and is also of low task and cognitive loads.

     

云存储中加密数据的自适应重复删除方法

为了保护个人隐私,用户倾向于在数据上传至云服务器之前将其加密. 相同的明文数据被加密成不同密文数据,使云服务器无法识别出重复的加密数据. 现存的解决方案多数倚赖可信第三方,且没有划分数据流行度,导致安全性与执行效率较低. 提出一种无需可信第三方的自适应重复删除方法.利用完美散列函数检查数据的流行度,使用口令认证密钥交换协议与同态加密安全传递数据的加密密钥,在保证用户数据隐私的前提下进行安全的重复数据删除. 与现有其它方案相比,安全性与实用性更强. 实验和仿真证明了方案的高效性.     

Electrochemical investigation of La0.4Sr0.6TiO3 synthesized in air for SOFC application

Journal of Applied Electrochemistry - La-doped titanate materials have been widely investigated as alternative Ni-free anodes for solid oxide fuel cells (SOFCs). In this study, La0.4Sr0.6TiO3 (LST)...     

基于分块分形的工业CT图像缺陷自动定位算法

针对传统的缺陷定位必须经过图像分割和缺陷提取等步骤,识别过程比较麻烦而且费时,提出了一种基于分块分形的工业CT图像缺陷自动定位算法.该方法首先对图像进行分块处理,对每个分块区域进行分形维数计算.通过分形维数频域分布直方图进行阈值处理,标记边缘块,最后通过连通区域处理标记块,进而对缺陷进行标记定位.通过对含有不同缺陷数目的固体火箭发动机模型工业CT图像处理,均可以准确地定位缺陷.实验结果表明,该方法能有效、准确地自动定位工业CT图像缺陷,且具有较强的鲁棒性.     

Incorporating Intra‐Query Term Dependencies in an Aspect Query Language Model

Query language modeling based on relevance feedback has been widely applied to improve the effectiveness of information retrieval. However, intra‐query term dependencies (i.e., the dependencies between different query terms and term combinations) have not yet been sufficiently addressed in the existing approaches. This article aims to investigate this issue within a comprehensive framework, namely the Aspect Query Language Model (AM). We propose to extend the AM with a hidden Markov model (HMM) structure to incorporate the intra‐query term dependencies and learn the structure of a novel aspect HMM (AHMM) for query language modeling. In the proposed AHMM, the combinations of query terms are viewed as latent variables representing query aspects. They further form an ergodic HMM, where the dependencies between latent variables (nodes) are modeled as the transitional probabilities. The segmented chunks from the feedback documents are considered as observables of the HMM. Then the AHMM structure is optimized by the HMM, which can estimate the prior of the latent variables and the probability distribution of the observed chunks. Our extensive experiments on three large‐scale text retrieval conference (TREC) collections have shown that our method not only significantly outperforms a number of strong baselines in terms of both effectiveness and robustness but also achieves better results than the AM and another state‐of‐the‐art approach, namely the latent concept expansion model. © 2014 Wiley Periodicals, Inc.     

基于曲线拟合和SVM的眼动信号分类算法研究

为提高基于EOG的眼动信号分类算法精度,改进基于EOG的人—机交互系统性能,提出了一种基于曲线拟合(curve fitting)与支持向量机(SVM)的眼动信号分类算法(CF-SVM),并设计了新的实验范式,增加了“扫视保持”环节.该算法采用曲线拟合方法进行特征提取,在此基础上,使用SVM分类器对眼动信号进行分类.实验室环境下,对9名眼部活动正常的受试者进行了眼动数据采集与识别,CF-SVM算法的平均分类准确率达到98.3％,与其他几种眼动识别方法相比较,其平均正确率分别提升了9.4％、5.9％、1.0％.实验结果表明,CF-SVM算法在眼动信号识别中表现了良好的性能,具有高的分类精度和鲁棒性.     

A setup for panoramic stereo imaging

In this paper, based on the proposed basic implementation of circular projection, a multi-camera setup which can be used for panoramic stereo imaging is presented. Firstly, we get multiple stereo pairs instantly by fixing multiple cameras on the proposed setup, which is an approximate implementation of circular projection. We then prove that the influence on the resultant stereo pairs generated by this approximate setup is slight based on similar triangles and structural similarity (SSIM). With these stereo pairs, the automatic panoramic image stitching algorithm is applied to generate panoramas for both eyes. In addition, with reasonable distance between cameras and the scene, physical dimensions of this setup are given. Finally, experimental results demonstrate that our scheme can be used to generate cylindrical stereo panoramic image with proper scene depth, which can provide viewers with distinguishing stereoscopic experience. The device can be installed on the mobile equipment and captures panoramic stereo image in a moment without stopping. In the future, the proposed setup can be used in the field of network navigation, video monitor and virtual reality.     

Nonlinear entanglement witnesses based on continuous-variable local orthogonal observables for bipartite systems

In this paper, a nonlinear entanglement witness criterion based on continuous-variable local orthogonal observables for bipartite states is established, which is strictly stronger than the the linear entanglement witnesses criterion introduced by Zhang et al. (Phys. Rev. Lett. 111:190501, 2013). This criterion is particularly applied to two-mode Gaussian states yielding a criterion in terms of the covariance matrix. Comparison with CCNR criterion is discussed.     

Viscosity-difference-induced asymmetric selective focusing for large stroke particle separation

We developed a new approach for particle separation by introducing viscosity difference of the sheath flows to form an asymmetric focusing of sample particle flow. This approach relies on the high-velocity gradient in the asymmetric focusing of the particle flow to generate a lift force, which plays a dominated role in the particle separation. The larger particles migrate away from the original streamline to the side of the higher relative velocity, while the smaller particles remain close to the streamline. Under high-viscosity (glycerol–water solution) and low-viscosity (PBS) sheath flows, a significant large stroke separation between the smaller (1.0 μm) and larger (9.9 μm) particles was achieved in a sample microfluidic device. We demonstrate that the flow rate and the viscosity difference of the sheath flows have an impact on the interval distance of the particle separation that affects the collected purity and on the focusing distribution of the smaller particles that affects the collected concentration. The interval distance of 293 μm (relative to the channel width: 0.281) and the focusing distribution of 112 μm (relative to the channel width: 0.107) were obtained in the 1042-μm-width separation area of the device. This separation method proposed in our work can potentially be applied to biological and medical applications due to the wide interval distance and the narrow focusing distribution of the particle separation, by easy manufacturing in a simple device.