Object data MODEL = object-oriented + semantic models

The term ‘object-oriented database’ has been used to refer to different characteristics and mechanisms supported by semantic databases and (behaviorally) object-oriented ones. While this indicates the current confusion due to the lack of a common model, it also suggests the potential desirability of combining these two kinds of modeling facilities into the same nutshell. This paper summarizes from these two paradigms the features common to both, the features influenced/adopted by each other, and the features which are presented in one paradigm but missing from the other. After a brief analysis and discussion of these features, we conclude this paper by proposing our major theme: a complete object data model should take the union of the facilities offered by these two kinds of models.     

Issues in nonlinear stochastic grey box identification

Grey box identification refers to the practice of identifying dynamical systems in model structures exploiting partial prior information. This contribution reviews a method for stochastic grey box identification and surveys experiences and lessons of applying it to a number of industrial processes. Issues to be addressed include advantages and costs of introducing stochastics into the model, the question of what contribution must be expected from the model designer as opposed to what can be formalized in computer algorithms, and an outlook on future plans to resolve present shortcomings.     

Sensorless control of synchronous reluctance motors using on‐line parameter identification method not affected by position estimation accuracy

This paper presents a novel on‐line parameter identification method for sensorless control of Synchronous Reluctance Motors (SynRMs). Although conventional sensorless control methods based on mathematical models usually need some complex measurements of motor parameters in advance, the proposed identification method does not require them and can be realized on‐line. The proposed method identifies motor parameters under sensorless control, so rotor position and velocity cannot be used to identify these parameters. However, the proposed method does not need rotor position and velocity, and identified parameters are not affected by these estimation errors. The sensorless control using identified motor parameters is realized, and the effectiveness of the proposed method is verified by experimental results. © 2006 Wiley Periodicals, Inc. Electr Eng Jpn, 155(3): 62–69, 2006; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/eej.20258     

Important features of Iris OSQL

OSQL is the object-oriented database language developed for the Iris object-oriented database management system at Hewlett-Packard Laboratories. Its three fundamental constructs are objects, types, and functions. This paper provides an overview of the underlying concepts and some important features of OSQL.     

Performance analysis of the forgetting factor RLS algorithm

An analysis is given of the performance of the standard forgetting factor recursive least squares (RLS) algorithm when used for tracking time-varying linear regression models. Three basic results are obtained: (1) the ‘P-matrix’ in the algorithm remains bounded if and only if the (time-varying) covariance matrix of the regressors is uniformly non-singular; (2) if so, the parameter tracking error covariance matrix is of the order O(μ + γ²/μ), where μ = 1 - λ, λ is the forgetting factor and γ is a quantity reflecting the speed of the parameter variations; (3) this covariance matrix can be arbitrarily well approximated (for small enough μ) by an expression that is easy to compute.     

基于模块化模型的自适应预失真技术

系统地比较和分析了OFDM传输系统里高功率放大器（HPA）预失真方法的优缺点,提出一种基于模块化模型的有记忆高功率放大器自适应数字预失真方法,该方法分别基于Wiener、Hammerstein和Wiener-Hammerstein模型各自构成一个有记忆HPA的自适应预失真器。从而避免了因分别估计Wiener-Hammerstein模型各个环节特性参数所带来的复杂性。使得有记忆高功率放大器的预失真设计变得简单了。     

论我国没收程序的没收对象问题

我国违法所得没收的特别程序规定的没收对象是违法所得及其他涉案财产,我国程序法规定的没收对象与实体法规定的没收对象有所不同,也与国际公约所规定的犯罪所得不一致.在分析违法所得与犯罪所得区别的基础上,认为我国刑事诉讼法新增违法所得没收程序的没收对象应该进一步明确和完善.     

Tackling the Password Problem: Image- and Gesture-Based Alternatives to Alphanumeric Passwords

Abstract

Alphanumeric passwords remain a ubiquitous means of user authentication, yet they are plagued by a fundamental problem: Secure passwords are difficult to create and remember. This paper suggests that image- or gesture-based passwords might strike a better balance between security and usability. It examines two such systems that are currently in widespread commercial use and examines alternative approaches that may offer insights for future improvements. Finally, it considers the possibility that touch-screen gesture passwords may become a viable biometric measure, which may allow them to provide multi-factor gesture-based authentication.     

Precise identification of moving vehicular parameters based on improved glowworm swarm optimization algorithm

This paper proposes an indirect method for the identification of moving vehicular parameters using the dynamic responses of the vehicle. The moving vehicle is modelled as 2-DOF system with 5 parameters and 4-DOF system with 12 parameters, respectively. Finite element method is used to establish the equation of the coupled bridge–vehicle system. The dynamic responses of the system are calculated by Newmark direct integration method. The parameter identification problem is transformed into an optimization problem by minimizing errors between the calculated dynamic responses of the moving vehicle and those of the simulated measured responses. Glowworm swarm optimization algorithm (GSO) is used to solve the objective function of the optimization problem. A local search method is introduced into the movement phase of GSO to enhance the accuracy and convergence rate of the algorithm. Several test cases are carried out to verify the efficiency of the proposed method and the results show that the vehicular parameters can be identified precisely with the present method and it is not sensitive to artificial measurement noise.     

Numerical identification of a nonlinear diffusion coefficient by discrete mollification

The discrete mollification method is a convolution-based filtering procedure suitable for the regularization of ill-posed problems. Combined with explicit space-marching finite difference schemes, it provides stability and convergence for a variety of coefficient identification problems in linear parabolic equations. In this paper, we extend such a technique to identify some nonlinear diffusion coefficients depending on an unknown space dependent function in one dimensional parabolic models. For the coefficient recovery process, we present detailed error estimates and to illustrate the performance of the algorithms, several numerical examples are included.