花艺之旅：氤氲江南

“周庄”这个地名是在大学课堂上知道的，即将毕业的那个黄梅天，我们忽然决定去周庄。     

液力偶合器变速的渣浆泵系统能耗问题分析及节能降耗对策

以应用液力偶合器变速的渣浆泵系统的运行数据力基础．通过对这些数据的分析处理，得出了这种系统在实际运行时的能耗特点。并提出了应对这些问题的措施，在合理使用液力偶合器和节能降耗方面很有实际意义。     

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.     

A stochastic realization algorithm via block LQ decomposition in Hilbert space

A stochastic realization problem of a stationary stochastic process is re-visited, and a new stochastically balanced realization algorithm is derived in a Hilbert space generated by second-order stationary processes. The present algorithm computes a stochastically balanced realization by means of the singular value decomposition of a weighted block Hankel matrix derived by a “block LQ decomposition”. Extension to a stochastic subspace identification method explains how the proposed abstract algorithm is implemented in system identification.     

Driving Mechanisms of Delamination Related Reliability Problems in Exposed Pad Packages

Exposed pad packages were introduced in the late 1980s and early 1990s because of their excellent thermal and electrical performance. Despite these advantages, the exposed pad packages experience a lot of thermo-hygro-mechanical related reliability problems during qualification and testing. Examples are die lift, which occurs predominantly after moisture sensitivity level conditions, and die-attach to leadframe delamination leading to downbond stitch breaks during temperature cycling. In this chapter, nonlinear finite element (FE) models using fracture mechanics based J-integral calculations are used to assess the reliability problems of the exposed pad package family. Using the parametric FE models any geometrical and material effects can be explored to their impact on the occurrence diepad delamination, and dielift. For instance the impact of diepad size is found to be of much less importance as the impact of die thickness is. Using the fracture mechanics approach, the starting location for the delamination from thermo-hygro-mechanical point of view is deducted. The results indicate that when diepad delamination is present, cracks are likely to grow beneath the die and dielift will occur. The interaction between dielift and other failure modes, such as lifted ball bonds, are not found to be very significant. The FE models are combined with simulation-based optimization methods to deduct design guidelines for optimal reliability of the exposed pad family.     

Optimal transfer trees and distinguishing trees for testing observable nondeterministic finite-state machines

The fault-state detection approach for blackbox testing consists of two phases. The first is to bring the system under test (SUT) from its initial state to a targeted state t and the second is to check various specified properties of the SUT at t. This paper investigates the first phase for testing systems specified as observable nondeterministic finite-state machines with probabilistic and weighted transitions. This phase involves two steps. The first step transfers the SUT to some state t' and the second step identifies whether t' is indeed the targeted state t or not. State transfer is achieved by moving the SUT along one of the paths of a transfer tree (TT) and state identification is realized by using diagnosis trees (DT). A theoretical foundation for the existence and characterization of TT and DT with minimum weighted height or minimum average weight is presented. Algorithms for their computation are proposed.     

Fundamental properties of reset control systems

Reset controllers are linear controllers that reset some of their states to zero when their input is zero. We are interested in their feedback connection with linear plants, and in this paper we establish fundamental closed-loop properties including stability and asymptotic tracking. This paper considers more general reset structures than previously considered, allowing for higher-order controllers and partial-state resetting. It gives a testable necessary and sufficient condition for quadratic stability and links it to both uniform bounded-input bounded-state stability and steady-state performance. Unlike previous related research, which includes the study of impulsive differential equations, our stability results require no assumptions on the evolution of reset times.     

Pedestrian detection and tracking at crossroads

This paper presents a system that can perform pedestrian detection and tracking using vision-based techniques. A very important issue in the field of intelligent transportation system is to prevent pedestrians from being hit by vehicles. Recently, a great number of vision-based techniques have been proposed for this purpose. In this paper, we propose a vision-based method, which combines the use of a pedestrian model as well as the walking rhythm of pedestrians to detect and track walking pedestrians. Through integrating some spatial and temporal information grabbed by a vision system, we are able to develop a reliable system that can be used to prevent traffic accidents happened at crossroads. In addition, the proposed system can deal with the occlusion problem. Experimental results obtained by executing some real world cases have demonstrated that the proposed system is indeed superb.