Perceived stress management skill mediates the relationship between optimism and positive mood following radical prostatectomy.

This study evaluated relations among optimism, perceived stress management skills (PSMS), and positive mood in 46 men who had surgical treatment for localized prostate cancer. The authors found that optimism, PSMS, and positive mood scores were positively correlated. Positive mood was unrelated to demographic and disease-related control variables. In a hierarchical regression model controlling for PSMS, the relationship between optimism and positive mood became nonsignificant, whereas PSMS remained a correlate of positive mood. Results suggest that the relationship between optimism and positive mood may be mediated by belief in being able to use stress management techniques effectively. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

校园文化与大学发展

校园文化看不见、摸不着，却支撑着大学的脊梁，它潜移默化影响和造就一所大学的文化品格。它不仅对大学发展起着重要作用，也是大学发展的重要内容，是大学建设的题中应有之义。为此，需要建设民主和谐，具有学术自由、人文精神和创新精神的校园文化，并将它提高到学校战略发展的高度来看，以校园文化整合学校发展战略。     

Control of discrete time nonlinear systems with a time-varying structure

In this paper, we present a control methodology for a class of discrete time nonlinear systems that depend on a possibly exogenous scheduling variable. This class of systems consists of an interpolation of nonlinear dynamic equations in strict feedback form, and it may represent systems with a time-varying nonlinear structure. Moreover, this class of systems is able to represent some cases of gain scheduling control, Takagi-Sugeno fuzzy systems, as well as input-output realizations of nonlinear systems which are approximated via localized linearizations. We present two control theorems, one using what we call a “global” approach (akin to traditional backstepping), and a “local” approach, our main result, where backstepping is again used but the control law is an interpolation of local control terms. An aircraft wing rock regulation problem with varying angle of attack is used to illustrate and compare the two approaches.     

Stability robustness of networked control systems with respect to packet loss

This paper is concerned with stability analysis of discrete-time networked control systems over a communication channel subject to packet loss whose behavior is modeled by an i.i.d Bernoulli process with a packet dropping probability bounded by a constant. A necessary and sufficient condition for stability is obtained. A packet dropping margin is introduced as a measure of stability robustness of a system against packet dropping, and a formula for it is derived. A design method is proposed for achieving a large margin subject to a constraint that the system has a set of prescribed nominal closed-loop poles.     

An investigation into physicochemical characteristics of ash produced from combustion of oil palm biomass wastein a boiler

Ash derived from combustion of Malaysian oil palm biomass (empty fruit bunches consisting of fibers) was physically and chemically characterized in order to provide a comprehensive understanding of its specific properties in terms of toxicity, compositions and reusability. Principal analyses conducted include particle size distribution, scanning electron microscopy, elemental dispersive X-ray, elemental analysis, toxicity characteristic leaching procedure (TCLP) as well as thermogravimetric, X-ray diffractometry and Fourier-transform infrared analyses. TCLP result indicated that the oil palm ash (OPA) should not be classified as toxic wastes in terms of heavy metal leachability since leachable copper, cadmium, lead and nickel concentrations were detected below the stipulated leachability limits. It was determined that the OPA contained high amount of potassium as well as presence of silica which implied its suitability to be reused as crude fertilizer or cement replacement material.     

Decentralized adaptive coordinated control of multiple robot arms without using a force sensor

This paper presents a distributed adaptive coordinated control method for multiple robot arms grasping a common object. The cases of rigid contact and rolling contact are analyzed. In the proposed controller, the dynamic parameters of both object and robot arms are estimated adaptively. The desired motions of the robot arms are generated by an estimated object reference model. The control method requires only the measurements of the positions and velocities of the object and robot arms, but not the measurements of forces and moments at contact points. The asymptotic convergence of trajectory is proven by the Lyapunov-like Lemma. Experiments involving two robot arms handling a common object are shown.     

Conceptual damage-sensitive features for structural health monitoring: Laboratory and field demonstrations

The use of damage-sensitive features to evaluate structural condition or health is a very critical aspect of structural health monitoring. The purpose of this paper is to investigate the potential of two different damage-sensitive features for detecting damage. Different damage scenarios are simulated on a large-scale laboratory structure and a three-span highway bridge for demonstration. The features presented in this paper are the modal flexibility-based deflection and curvature both of which are obtained directly from dynamic properties. In the literature, flexibility associated with mode shapes and mode shapes curvatures have been mostly explored. In this study, multi-input–multi-output dynamic data are used to obtain modal flexibility, which is a close approximation to the actual flexibility. A main novelty is that the curvature is calculated from the deflected shapes using the modal flexibility as opposed to using modal vectors. In this paper, the theory of the methodology is explained and then experimental studies and results are presented. For the experimental studies, the laboratory specimen and the three-span bridge were gradually damaged. It is shown that both deflection and curvature are conceptual and physically meaningful features for damage detection and localization. The issues and the requirements for these features to perform successfully are also presented.     

Controlled linear system with delayed relay output under impulse random disturbances

The paper is devoted to the first order delayed linear system with relay output controlled by the proportional-integral (PI) regulator. The deterministic system exhibits stable oscillations, and, since the system itself is stable, it can be suitable to switch off the controller if there are no disturbances during a long time interval. In the present work, the random disturbances are modelled by a Poisson stream of impulses, and the goal is to determine the instants of switching on (off) of the PI controller. After several assumptions and quantization of the time axis, we construct the new optimal control problem which is successfully solved with the help of the dynamic programming approach.     

基于FPGA乘法器架构的RNS与有符号二进制量转换

RNS(余数数制系统)是一种整数运算系统,在粒度精确性,能源损耗和响应速度上有很大的优势.从RNS到二进制数的输入输出转换是基于余数算法的专用架构实现的关键.本文提出了一个基于N类模的RNS与有符号二进制量的通用转换算法在FPGAs的乘法器上的实现过程.该算法能更有效地进行有符号数与RNS的转换.基于该算法类型乘法器在同类型乘法器中显示出了速度优势.文章中该架构被映射到Altera的10K系列的FPGA上.     

Solving the small sample size problem in face recognition using generalized discriminant analysis

The goal of face recognition is to distinguish persons via their facial images. Each person's images form a cluster, and a new image is recognized by assigning it to the correct cluster. Since the images are very high-dimensional, it is necessary to reduce their dimension. Linear discriminant analysis (LDA) has been shown to be effective at dimension reduction while preserving the cluster structure of the data. It is classically defined as an optimization problem involving covariance matrices that represent the scatter within and between clusters. The requirement that one of these matrices be nonsingular restricts its application to datasets in which the dimension of the data does not exceed the sample size. For face recognition, however, the dimension typically exceeds the number of images in the database, resulting in what is referred to as the small sample size problem. Recently, the applicability of LDA has been extended by using the generalized singular value decomposition (GSVD) to circumvent the nonsingularity requirement, thus making LDA directly applicable to face recognition data. Our experiments confirm that LDA/GSVD solves the small sample size problem very effectively as compared with other current methods.