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.     

Comparison of two scaling approaches for the development of biomechanical multi-body human models

Dimensional scaling approaches are widely used to develop multi-body human models in injury biomechanics research. Given the limited experimental data for any particular anthropometry, a validated model can be scaled to different sizes to reflect the biological variance of population and used to characterize the human response. This paper compares two scaling approaches at the whole-body level: one is the conventional mass-based scaling approach which assumes geometric similarity; the other is the structure-based approach which assumes additional structural similarity by using idealized mechanical models to account for the specific anatomy and expected loading conditions. Given the use of exterior body dimensions and a uniform Young’s modulus, the two approaches showed close values of the scaling factors for most body regions, with 1.5 % difference on force scaling factors and 13.5 % difference on moment scaling factors, on average. One exception was on the thoracic modeling, with 19.3 % difference on the scaling factor of the deflection. Two 6-year-old child models were generated from a baseline adult model as application example and were evaluated using recent biomechanical data from cadaveric pediatric experiments. The scaled models predicted similar impact responses of the thorax and lower extremity, which were within the experimental corridors; and suggested further consideration of age-specific structural change of the pelvis. Towards improved scaling methods to develop biofidelic human models, this comparative analysis suggests further investigation on interior anatomical geometry and detailed biological material properties associated with the demographic range of the population.     

Feature aggregating hashing for image copy detection

Currently, research on content based image copy detection mainly focuses on robust feature extraction. However, due to the exponential growth of online images, it is necessary to consider searching among large scale images, which is very time-consuming and unscalable. Hence, we need to pay much attention to the efficiency of image detection. In this paper, we propose a fast feature aggregating method for image copy detection which uses machine learning based hashing to achieve fast feature aggregation. Since the machine learning based hashing effectively preserves neighborhood structure of data, it yields visual words with strong discriminability. Furthermore, the generated binary codes leads image representation building to be of low-complexity, making it efficient and scalable to large scale databases. Experimental results show good performance of our approach.     

Similarity of binary relations based on <Emphasis Type="Italic">L</Emphasis>-fuzzy topologies

Binary relations play an important role in rough set theory. This paper investigates the similarity of binary relations based on L-fuzzy topologies, where L is a boolean algebra. First, rough approximations based on a boolean algebra are proposed through successor neighborhoods on binary relations. Next, L-fuzzy topologies induced by binary relations are investigated. Finally, similarity of binary relations is introduced by using the L-fuzzy topologies and the fact that every binary relation is solely similar to some preorder relation is proved. It is worth mentioning that similarity of binary relations are both originated in the L-fuzzy topology and independent of the L-fuzzy topology.     

Hierarchical classification in text mining for sentiment analysis of online news

Sentiment analysis in text mining is a challenging task. Sentiment is subtly reflected by the tone and affective content of a writer’s words. Conventional text mining techniques, which are based on keyword frequencies, usually run short of accurately detecting such subjective information implied in the text. In this paper, we evaluate several popular classification algorithms, along with three filtering schemes. The filtering schemes progressively shrink the original dataset with respect to the contextual polarity and frequent terms of a document. We call this approach “hierarchical classification”. The effects of the approach in different combination of classification algorithms and filtering schemes are discussed over three sets of controversial online news articles where binary and multi-class classifications are applied. Meanwhile we use two methods to test this hierarchical classification model, and also have a comparison of the two methods.     

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.     

Quantum state transfer between an optomechanical cavity and a diamond nuclear spin ensemble

We explore an efficient scheme for transferring quantum state between an optomechanical cavity and nuclear spins of nitrogen-vacancy centers in diamond, where quantum information can be efficiently stored (retrieved) into (from) the nuclear spin ensemble assisted by a mechanical resonator in a dispersive regime. Our scheme works for a broad range of cavity frequencies and might have potential applications in employing the nuclear spin ensemble as a memory in quantum information processing. The feasibility of our protocol is analyzed using currently available parameters.     

Practical chosen-ciphertext secure Hierarchical Identity-Based Broadcast Encryption

We focus on practical Hierarchical Identity-Based Broadcast Encryption (HIBBE) with semantic security against adaptively chosen-ciphertext attacks (CCA2) in the standard model. We achieve this goal in two steps. First, we propose a new HIBBE scheme that is secure against chosen-plaintext attacks (CPA). Compared with the existing HIBBE scheme that is built from composite-order bilinear groups, our construction is based on prime-order bilinear groups. The much better efficiency of group operations in prime-order bilinear groups makes our proposed HIBBE scheme more practical. Then, we convert it into a CCA2-secure scheme at the cost of a one-time signature. Instead of extending one user hierarchy in the Canetti–Halevi–Katz approach from CPA-secure (\(l+1\))-Hierarchical Identity-Based Encryption [(\(l+1\))-HIBE] to CCA2-secure \(l\)-HIBE, our construction merely adds one on-the-fly dummy user in the basic scheme. We formally prove the security of these two schemes in the standard model. Comprehensive theoretical analyses and experimental results demonstrate that the proposed HIBBE schemes achieve desirable performance.     

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.     

基于Web的网上作业系统设计与实现

按照网上作业平台系统实现目标,完成了系统功能性需求分析。对文件的数据库方式存储和文件系统方式的存储进行了比较,并分析、设计了本系统的存储结构。完成了数据库概念模型设计和数据表物理模型设计,详细给出了数据库关系图。设计并实现了基于Internet的课程网上作业子系统、个人网络硬盘子系统、课程资源库共享等子系统。该系统已经应用到日常的教学管理中,并取得了不错的效果。