Theoretical research progress in new-generation Internet architecture

Internet has become the most important information infrastructure supporting modern socio-economic development, social progress and technological Innovation. Invented 30 years ago, today Internet is facing increasingly severe technical challenges. This paper introduces the progress of the major international newgeneration Internet research plans; analyzes its basic characteristics and the principal contradictions during the development; detsiledly introduces the research carried out by 973 Project ＂Research of Future Internet Architecture＂ on the key scientific issues of new-generation Internet architecture and its latest research results; and looks to the future of the research-focus faced with the new situations of the basic research of new-generation Internet architecture as well as the new demands of innovative applications on Internet architecture.     

An encoding-based dual distance tree high-dimensional index

The paper proposes a novel symmetrical encoding-based index structure, which is called EDD-tree （for encoding-based dual distance tree）, to support fast k-nearest neighbor （k-NN） search in high-dimensional spaces. In the EDD-tree, all data points are first grouped into clusters by a k-means clustering algorithm. Then the uniform ID number of each data point is obtained by a dual-distance-driven encoding scheme, in which each cluster sphere is partitioned twice according to the dual distances of start- and centroid-distance. Finally, the uniform ID number and the centroid-distance of each data point are combined to get a uniform index key, the latter is then indexed through a partition-based B^＋-tree. Thus, given a query point, its k-NN search in high-dimensional spaces can be transformed into search in a single dimensional space with the aid of the EDD-tree index. Extensive performance studies are conducted to evaluate the effectiveness and efficiency of our proposed scheme, and the results demonstrate that this method outperforms the state-of-the-art high-dimensional search techniques such as the X-tree, VA-file, iDistance and NB-tree, especially when the query radius is not very large.     

基于SOPC的USB密码模块硬件与固件设计

SOPC是一种灵活、高效的软硬件解决方案。本文在研究SOPC密码模块设计技术的基础上,提出了基于SOPC的USB密码模块“双核＋双总线”硬件架构;针对此架构,设计实现了MCU、双核协调控制、内部总线桥,完成了其固件功能的编程,并通过实验验证了该密码模块的正确性。     

SPI总线的UART扩展方法

借助于微处理器的SPI总线接口,利用NXP公司的一款芯片SC16IS752,提出一种基于SPI转UART的软硬件设计方案;着重介绍SPI-UART转换原理,并结合实际的应用系统,讨论了整个设计的可行性和实用性.实际应用表明,该方案经济、实用.     

Operational Regimes and Physics Present in Optoelectronic Tweezers

Optoelectronic tweezers (OET) are a powerful light-based technique for the manipulation of micro- and nanoscopic particles. In addition to an optically patterned dielectrophoresis (DEP) force, other light-induced electrokinetic and thermal effects occur in the OET device. In this paper, we present a comprehensive theoretical and experimental investigation of various fluidic, optical, and electrical effects present during OET operation. These effects include DEP, light-induced ac electroosmosis, electrothermal flow, and buoyancy-driven flow. We present finite-element modeling of these effects to establish the dominant mode for a given set of device parameters and bias conditions. These results are confirmed experimentally and present a comprehensive outline of the operational regimes of the OET device.     

Robust H∞ control of uncertain linear impulsive stochastic systems

This paper develops robust stability theorems and robust H_∞ control theory for uncertain impulsive stochastic systems. The parametric uncertainties are assumed to be time varying and norm bounded. Impulsive stochastic systems can be divided into three cases, namely, the systems with stable/stabilizable continuous‐time stochastic dynamics and unstable/unstabilizable discrete‐time dynamics, the systems with unstable/unstabilizable continuous dynamics and stable/stabilizable discrete‐time dynamics, and the systems in which both the continuous‐time stochastic dynamics and the discrete‐time dynamics are stable/stabilizable. Sufficient conditions for robust exponential stability and robust stabilization for uncertain impulsive stochastic systems are derived in terms of an average dwell‐time condition. Then, a linear matrix inequality‐based approach to the design of a robust H_∞ controller for each system is presented. Finally, the numerical examples are provided to demonstrate the effectiveness of the proposed approach. Copyright © 2007 John Wiley & Sons, Ltd.     

Characteristics of an electron source of a surface‐conduction electron‐emitter display

Abstract— The electron source is an essential part of a surface‐conduction electron‐emitter display (SED). An electron source for an SED was obtained after certain procedures were performed. By introducing a carbon atmosphere, the electron‐emission characteristics of a SED were studied experimentally. The electron‐emission characteristic curves were drawn after comparing the experimental data of the electron source obtained in a vacuum environment with the data obtained in a carbon atmosphere, from which it had proved that a carbon atmosphere could significantly improve the electron‐emission characteristics of a SED. As a result, both the device current and the emission current had become stronger and the efficiency of surface‐conduction electron emission had been improved significantly. The possible reasons were analyzed: more carbon, which could possibly form the electron‐emission region of a SED, was produced from the carbon atmosphere during the electrical activation process.     

Alpha-cut implemented fuzzy clustering algorithms and switching regressions.

In the fuzzy c-means (FCM) clustering algorithm, almost none of the data points have a membership value of 1. Moreover, noise and outliers may cause difficulties in obtaining appropriate clustering results from the FCM algorithm. The embedding of FCM into switching regressions, called the fuzzy c-regressions (FCRs), still has the same drawbacks as FCM. In this paper, we propose the alpha-cut implemented fuzzy clustering algorithms, referred to as FCMalpha, which allow the data points being able to completely belong to one cluster. The proposed FCMalpha algorithms can form a cluster core for each cluster, where data points inside a cluster core will have a membership value of 1 so that it can resolve the drawbacks of FCM. On the other hand, the fuzziness index m plays different roles for FCM and FCMalpha. We find that the clustering results obtained by FCMalpha are more robust to noise and outliers than FCM when a larger m is used. Moreover, the cluster cores generated by FCMalpha are workable for various data shape clusters, so that FCMalpha is very suitable for embedding into switching regressions. The embedding of FCMalpha into switching regressions is called FCRalpha. The proposed FCRalpha provides better results than FCR for environments with noise or outliers. Numerical examples show the robustness and the superiority of our proposed methods.     

Correlating burst events on streaming stock market data

We address the problem of monitoring and identification of correlated burst patterns in multi-stream time series databases. We follow a two-step methodology: first we identify the burst sections in our data and subsequently we store them for easy retrieval in an efficient in-memory index. The burst detection scheme imposes a variable threshold on the examined data and takes advantage of the skewed distribution that is typically encountered in many applications. The detected bursts are compacted into burst intervals and stored in an interval index. The index facilitates the identification of correlated bursts by performing very efficient overlap operations on the stored burst regions. We present the merits of the proposed indexing scheme through a thorough analysis of its complexity. We also manifest the real-time response of our burst indexing technique, and demonstrate the usefulness of the approach for correlating surprising volume trading events using historical stock data of the NY stock exchange. While the focus of this work is on financial data, the proposed methods and data-structures can find applications for anomaly or novelty detection in telecommunication, network traffic and medical data.