一类多输入多输出系统的冗余设计

分析了多输入多输出多变量系统在某环节失效时系统的整体性,给出了针对开环传递函数矩阵以及解耦后新对象均为本质稳定对象时系统的冗余设计方法.该方法有效解决了某环节失效后对系统稳定性的影响,实现了复杂系统的容错控制.仿真结果表明,该冗余设计方法可行,能够实现系统的容错控制.     

Determination of lysozyme at the nanogram level in chicken egg white using Resonance Rayleigh-scattering method with Cd-doped ZnSe quantum dots as probe

A new method for the determination of lysozyme with high sensitivity based on Resonance Rayleigh scattering (RRS) by using Cd doped ZnSe quantum dots (QDs) as a probe was proposed in this experiment. Cd doped ZnSe QDs capped with glutathione were prepared in the water phase. Further, the RRS spectrum, transmission electron microscope, and absorption spectrum of the QDs-lysozyme system have been characterized. In addition, the effects of several factors on scattering intensities were investigated, including pH value of solution, amount of QDs, mixing sequence of each reagent and the coexisting substances. Moreover, the possible mechanism for the RRS enhancement of Cd doped ZnSe QDs-lysozyme system was preliminary discussed. The RRS method for the determination of lysozyme has good sensitivity with the detection limits 6.5 × 10⁻¹⁰ g mL⁻¹. The contents of lysozyme were determined with recoveries of 97.1-101.6% and relativity standard deviation of 2.5-3.1%, respectively. It proved that the method established in our study is very sensitive, rapid, convenient and tolerant for the determination of lysozyme in synthetically and chicken egg white.     

Reliability analysis and optimal version-updating for open source software

Context

Although reliability is a major concern of most open source projects, research on this problem has attracted attention only recently. In addition, the optimal version-dating for open source software considering its special properties is not yet discussed.

Objective

In this paper, the reliability analysis and optimal version-updating for open source software are studied.

Method

A modified non-homogeneous Poisson process model is developed for open source software reliability modeling and analysis. Based on this model, optimal version-updating for open source software is investigated as well. In the decision process, the rapid release strategy and the level of reliability are the two most important factors. However, they are essentially contradicting with each other. In order to consider these two conflicting factors simultaneously, a new decision model based on multi-attribute utility theory is proposed.

Results

Our models are tested on the real world data sets from two famous open source projects: Apache and GNOME. It is found that traditional software reliability models provide overestimations of the reliability of open source software. In addition, the proposed decision model can help management to make a rational decision on the optimal version-updating for open source software.

Conclusion

Empirical results reveal that the proposed model for open source software reliability can describe the failure process more accurately. Furthermore, it can be seen that the proposed decision model can assist management to appropriately determine the optimal version-update time for open source software.     

Construction of 1-Resilient Boolean Functions with Optimal Algebraic Immunity and Good Nonlinearity

This paper presents a construction for a class of 1-resilient functions with optimal algebraic immunity on an even number of variables. The construction is based on the concatenation of two balanced functions in associative classes. For some n, a part of 1-resilient functions with maximum algebraic immunity constructed in the paper can achieve almost optimal nonlinearity. Apart from their high nonlinearity, the functions reach Siegenthaler's upper bound of algebraic degree. Also a class of 1-resilient functions on any number n > 2 of variables with at least sub-optimal algebraic immunity is provided.     

嵌入式平台下的RFID数据处理终端

介绍一种以AT91SAM9260处理器和Linux嵌入式操作系统为平台的RFID信息采集与处理系统。该系统充分利用AT91SAM9260芯片丰富的标准接口资源,集门禁、考勤、监控为一体,以Linux操作系统为软件平台,完成了RFID数据信息和USB摄像头照片数据的采集、保存与TCP/IP远程数据传输等。介绍了系统的硬件组成原理、软件设计方案和实现方法,为射频识别技术在智能一卡通系统中的应用提供了一种先进的解决方案。     

New global optimization algorithms for model-based clustering

The Expectation-Maximization (EM) algorithm is a very popular optimization tool for mixture problems and in particular for model-based clustering problems. However, while the algorithm is convenient to implement and numerically very stable, it only produces local solutions. Thus, it may not achieve the globally optimal solution in problems that have a large number of local optima. This paper introduces several new algorithms designed to produce global solutions in model-based clustering. The building blocks for these algorithms are methods from the operations research literature, namely the Cross-Entropy (CE) method and Model Reference Adaptive Search (MRAS). One problem with applying these methods directly is the efficient simulation of positive definite covariance matrices. We propose several new solutions to this problem. One solution is to apply the principles of Expectation-Maximization updating, which leads to two new algorithms, CE-EM and MRAS-EM. We also propose two additional algorithms, CE-CD and MRAS-CD, which rely on the Cholesky decomposition. We conduct numerical experiments of varying complexity to evaluate the effectiveness of the proposed algorithms in comparison to classical EM. We find that although a single run of the new algorithms is slower than a single run of EM, all have the potential for producing significantly better solutions. We also find that although repeat application of EM may achieve similar results, our algorithms provide automated, data-driven decision rules which may significantly reduce the burden of searching for the global optimum.     

Analysis of the nonlinear dynamic stability for an electrically actuated viscoelastic microbeam

In this article, based on the standard linear solid model, the Euler-Bernoulli hypothesis and the Galerkin method, an analysis of the nonlinear dynamic stability for a clamped-guided viscoelastic microbeam under both a periodic axial force and a symmetric electrostatic load is presented. By using the incremental harmonic balanced method, the boundary of the principal region of instability is got. In the numerical calculation, the effect of the environmental and inner damping, geometric nonlinear, creep quantity and the symmetric electrostatic load on the principal region of instability is discussed.     

Visualizing Waypoints‐Constrained Origin‐Destination Patterns for Massive Transportation Data

Origin‐destination (OD) pattern is a highly useful means for transportation research since it summarizes urban dynamics and human mobility. However, existing visual analytics are insufficient for certain OD analytical tasks needed in transport research. For example, transport researchers are interested in path‐related movements across congested roads, besides global patterns over the entire domain. Driven by this need, we propose waypoints‐constrained OD visual analytics, a new approach for exploring path‐related OD patterns in an urban transportation network. First, we use hashing‐based query to support interactive filtering of trajectories through user‐specified waypoints. Second, we elaborate a set of design principles and rules, and derive a novel unified visual representation called the waypoints‐constrained OD view by carefully considering the OD flow presentation, the temporal variation, spatial layout and user interaction. Finally, we demonstrate the effectiveness of our interface with two case studies and expert interviews with five transportation experts.     

Structure‐adaptive Shape Editing for Man‐made Objects

One of the challenging problems for shape editing is to adapt shapes with diversified structures for various editing needs. In this paper we introduce a shape editing approach that automatically adapts the structure of a shape being edited with respect to user inputs. Given a category of shapes, our approach first classifies them into groups based on the constituent parts. The group‐sensitive priors, including both inter‐group and intra‐group priors, are then learned through statistical structure analysis and multivariate regression. By using these priors, the inherent characteristics and typical variations of shape structures can be well captured. Based on such group‐sensitive priors, we propose a framework for real‐time shape editing, which adapts the structure of shape to continuous user editing operations. Experimental results show that the proposed approach is capable of both structure‐preserving and structure‐varying shape editing.