Combined frequency-prediction error identification approach for Wiener systems with backlash and backlash-inverse operators

Wiener systems identification is studied in the presence of possibly infinite-order linear dynamics and memory nonlinear operators of backlash and backlash-inverse types. The latter is laterally bordered with polynomial lines of arbitrary-shape. It turns out that the borders are allowed to be noninvertible and crossing making possible to account, within a unified theoretical framework, for memory and memoryless nonlinearities. Moreover, the prior knowledge of the nonlinearity type, being backlash or backlash-inverse or memoryless, is not required. Using sine excitations, and getting benefit from model plurality, the initial complex identification problem is made equivalent to two tractable (though still nonlinear) prediction-error problems. These are coped with using linear and nonlinear least squares estimators which all are shown to be consistent.     

An object-oriented approach to teaching mathematics for engineering and science students

It is suggested to teach mathematics for engineering and science students as exploration of mathematics-related classes. Similarity with classes and objects of object-oriented programming is demonstrated. In the framework of the suggested approach, each relatively self-contained unit of mathematics curriculum is assigned a data type and is considered a class. In such setting, a theorem proof may be viewed as an assignment of values to object properties. The approach augments the role of recognition of mathematical objects, their properties and methods （operations） and diminishes the value of comprehensive study of rigorous proofs. The approach emphasizes the importance of development of mathematical intuition and combines conceptual and operational approaches to teaching and learning mathematics. Prospective implementation assumes using of computer-based systems of formal proof.     

An object-oriented blackboard based approach for automated finite element modeling and analysis of multichip modules

This paper addresses the application of the blackboard system architecture and object-oriented data abstraction techniques to the domain of finite element modeling and analysis. Specifically, a hierarchical object-oriented database was used to represent the physical system at different levels of abstraction including the user-defined physical system level, a computer-generated, simplified physical model level, and the finite element model level. Object link relationships within a given abstraction level and across different abstraction levels resulted in seamless bidirectional information exchange. The blackboard system architecture employed provided a framework for distributed cooperative problem solving, for the application of simplifying domain-specific modeling assumptions, and for integrating the various software modules that are involved in the entire finite element modeling and analysis process. These methodologies were implemented in a prototype computational tool calledIMCMA theIntelligentMultichipModuleAnalyzer. An example illustrates howIMCMA automates finite element thermal analysis of small integrated circuit features in multichip modules through a two-step finite element submodeling process.     

An approach for the identification of diffusion coefficients in the quasi-steady state of a post-discharge nitriding process

This work presents a model for the nitrogen concentration in iron nitride layers at the quasi-steady state and a method for computing the diffusion coefficients for post-discharge nitriding. The method is based upon an inverse problem of coefficient identification. The related moving boundary diffusion problem is modeled assuming constant diffusion coefficients and taking into account the observed qualitative behavior of the post-discharge nitriding process. To develop an algorithm for the identification of the diffusion coefficients the solution of the least square problem is transformed, with some algebraic manipulations, into a simple geometrical rule.     

A counterexample to the uniqueness of the asymptotic estimate in ARMAX model identification via the correlation approach

This paper deals with the identifiability of an ARMAX system when the correlation approach is adopted. In general, identifiability depends on both the parametrization of the model class and on the informativeness of the data. Here, we focus on the latter aspect and, therefore, a full-order model class is considered. The main goal is to provide a counterexample to the uniqueness of the asymptotic estimate when a persistently exciting input is adopted. This shows the somehow counterintuitive fact that the identifiability of ARMAX systems within the correlation approach is related to the “color” of the input.     

A behavioral analysis and verification approach to pattern-based design composition

Integrating software components to produce large-scale software systems is an effective way to reuse experience and reduce cost. However, unexpected interactions among components when integrated into software systems are often the cause of failures. Discovering these composition errors early in the development process could lower the cost and effort in fixing them. This paper introduces a rigorous analysis approach to software design composition based on automated verification techniques. We show how to represent, instantiate and integrate design components, and how to find design composition errors using model checking techniques. We illustrate our approach with a Web-based hypermedia case study.     

A variational integrators approach to second order modeling and identification of linear mechanical systems

The theory of variational integration provides a systematic procedure to discretize the equations of motion of a mechanical system, preserving key properties of the continuous time flow. The discrete-time model obtained by variational integration theory inherits structural conditions which in general are not guaranteed under general discretization procedures. We discuss a simple class of variational integrators for linear second order mechanical systems and propose a constrained identification technique which employs simple linear transformation formulas to recover the continuous time parameters of the system from the discrete-time identified model. We test this approach on a simulated eight degrees of freedom system and show that the new procedure leads to an accurate identification of the continuous-time parameters of second-order mechanical systems starting from discrete measured data.