Curvilinear lattice in chiral carbon nanotubes

In this paper, the energy bands of chiral-type single-walled carbon nanotubes are studied employing a new curvilinear lattice theory and its reciprocal lattice aided by the spherical triangle theory. In this theory, the notion of a distance law is introduced as a constraint to determine the electronic characteristics of carbon nanotubes. The chiral tubes are proven to be semiconducting or metallic, depending on the diameters and helical angles of the tubes. The distance law also predicts an uncertainty for the electronic characteristics of chiral tubes due to the metallic states tightly surrounding the semiconducting states on the direct lattice, and vice versa. Results predicted by the distance law agree well with theoretical calculations of the electron density of states and published measurements.     

基于COM+组件技术的网上购物车的设计与实现

网上购物车是电子商务中一个重要的组成部分,该文采用最新的COM+组件技术有效地解决了使用一般ASP技术开发网上购物车的缺陷,并在所设计的网上购物车系统中实现了这些改进,增强了网上购物车系统的安全性和使用效率。     

面向大批量定制的产品族设计技术研究

介绍了产品族与产品平台的概念和特征,分析了典型产品族的设计开发过程,提出了一种适合于大批量定制生产模式的产品族设计框架。分析并指出了目前产品族优化设计研究中的不足,提出了基于主从关联结构的层次优化设计理念以及实现这一理念的方法和模型框架,阐述了模型的学形式——模糊层次优化。     

Semi-supervised transfer discriminant analysis based on cross-domain mean constraint

In this paper, a novel semi-supervised feature extraction algorithm, i.e., semi-supervised transfer discriminant analysis (STDA) with knowledge transfer capability is proposed, based on the traditional algorithm that cannot get adapted in the change of the learning environment. By using both the pseudo label information from target domain samples and the actual label information from source domain samples in the label iterative refinement process, not only the between-class scatter is maximized while that within-class scatter is minimized, but also the original space structure is maintained via Laplacian matrix, and the distribution difference is reduced by using maximum mean discrepancy as well. Moreover, semi-supervised transfer discriminant analysis based on cross-domain mean constraint (STDA-CMC) is proposed. In this algorithm, the cross-domain mean constraint term is incorporated into STDA, such that knowledge transfer between domains is facilitated by making source and target samples after being projected are located more closely in the low-dimensional feature subspace. The proposed algorithm is proved efficient and feasible from experiments on several datasets.     

基于GIS耦合HEC-RAS的城市洪水灾害风险评估——以重庆市主城区长江、嘉陵江段为例

本文通过GIS耦合HEC-RAS模拟洪水淹没情况,采用自然灾害风险评价的理论和方法 ,综合重庆主城区九个区的自然、社会经济、防灾减灾等数据,得出主城区洪水灾害风险指数,并基于GIS绘制出重庆主城区洪水灾害风险区划图,为后续制定应急预案和防洪规划提供依据。     

Highly efficient MOF-templated Ni catalyst towards CO selective methanation in hydrogen-rich reformate gases

Highly efficient and non-noble metal-based Ni/ZrO₂ catalyst templated with Ni/UiO-66 precursor was successfully prepared and applied to CO selective methanation in H₂-rich gases. This catalyst showed excellent activity and selectivity in an extremely wide temperature window of 215–350 °C, and it also had high stability with no deactivation during a long-term stability test (120 h). The increased specific surface area, smaller crystallite size (3.5 nm) and higher dispersion (15.3%) of Ni nanoparticles, and the enhanced chemisorption capability for CO might contribute to its excellent performance.     

SplitPass: A Mutually Distrusting Two-Party Password Manager

Using a password manager is known to be more convenient and secure than not using one, on the assumption that the password manager itself is safe. However recent studies show that most popular password managers have security vulnerabilities that may be fooled to leak passwords without users’ awareness. In this paper, we propose a new password manager, SplitPass, which vertically separates both the storage and access of passwords into two mutually distrusting parties. During login, all the parties will collaborate to send their password shares to the web server, but none of these parties will ever have the complete password, which significantly raises the bar of a successful attack to compromise all of the parties. To retain transparency to existing applications and web servers, SplitPass seamlessly splits the secure sockets layer (SSL) and transport layer security (TCP) sessions to process on all parties, and makes the joining of two password shares transparent to the web servers. We have implemented SplitPass using an Android phone and a cloud assistant and evaluated it using 100 apps from top free apps in the Android official market. The evaluation shows that SplitPass securely protects users’ passwords, while incurring little performance overhead and power consumption.     

Artistic preprocessing for painterly rendering and image stylization

A practical image enhancing technique is presented as a preprocessing step for painterly rendering and image stylization, which transforms the input image mimicking the vision of artists. The new method contains mainly two parts dealing with artistic enhancement and color adjustment, respectively. First, through feature extraction and simplification, an abstract shadow map is constructed for the input image, which is then taken as a guide for emphasizing the light–shadow contrast and the important shadow lines. Next, to simulate the intense color emotion often subjectively added by the artist, a color adjustment technique is proposed to generate lively colors with sharp contrast imitating the artistic vision. The preprocessing operation is compatible with existing stylization and stroke-based painterly rendering techniques, and it can also produce different types of stylization results independently.