A reinforcement discrete neuro-adaptive control for unknown piezoelectric actuator systems with dominant hysteresis

The theoretical and experimental studies of a reinforcement discrete neuro-adaptive control for unknown piezoelectric actuator systems with dominant hysteresis are presented. Two separate nonlinear gains, together with an unknown linear dynamical system, construct the nonlinear model (NM) of the piezoelectric actuator systems. A nonlinear inverse control (NIC) according to the learned NM is then designed to compensate the hysteretic phenomenon and to track the reference input without the risk of discontinuous response. Because the uncertainties are dynamic, a recurrent neural network (RNN) with residue compensation is employed to model them in a compact subset. Then, a discrete neuro-adaptive sliding-mode control (DNASMC) is designed to enhance the system performance. The stability of the overall system is verified by Lyapunov stability theory. Comparative experiments for various control schemes are also given to confirm the validity of the proposed control.     

Key principles for user-centred systems design

The concept of user-centred systems design (UCSD) has no agreed upon definition. Consequently, there is a great variety in the ways it is applied, which may lead to poor quality and poor usability in the resulting systems, as well as misconceptions about the effectiveness of UCSD. The purpose of this paper is to propose a definition of UCSD. We have identified 12 key principles for the adoption of a user-centred development process, principles that are based on existing theory, as well as research in and experiences from a large number of software development projects. The initial set of principles were applied and evaluated in a case study and modified accordingly. These principles can be used to communicate the nature of UCSD, evaluate a development process or develop systems development processes that support a user-centred approach. We also suggest activity lists and some tools for applying UCSD.     

Experience with a Hybrid Processor: K-Means Clustering

We discuss hardware/software co-processing on a hybrid processor for a compute- and data-intensive multispectral imaging algorithm, k-means clustering. The experiments are performed on two models of the Altera Excalibur board, the first using the soft IP core 32-bit NIOS 1.1 RISC processor, and the second with the hard IP core ARM processor. In our experiments, we compare performance of the sequential k-means algorithm with three different accelerated versions. We consider granularity and synchronization issues when mapping an algorithm to a hybrid processor. Our results show that speedup of 11.8X is achieved by migrating computation to the Excalibur ARM hardware/software as compared to software only on a Gigahertz Pentium III. Speedup on the Excalibur NIOS is limited by the communication cost of transferring data from external memory through the processor to the customized circuits. This limitation is overcome on the Excalibur ARM, in which dual-port memories, accessible to both the processor and configurable logic, have the biggest performance impact of all the techniques studied.     

High Order Finite Difference Approximations of Electromagnetic Wave Propagation Close to Material Discontinuities

Electromagnetic wave propagation close to a material discontinuity is simulated by using summation by part operators of second, fourth and sixth order accuracy. The interface conditions at the discontinuity are imposed by the simultaneous approximation term procedure. Stability is shown and the order of accuracy is verified numerically.     

The ARCHIMEDES Network System: a system for searching and accessing information in multiple multimedia sources

The amount of information available to information workers recently has becomeoverwhelming. This confronts information workers with two majorproblems: finding the information needed, and accessing it; they arecalled the search problem and the access problem, respectively. Asthe main result of our research an architecture is specified of anautomated tool that provides integrated support for searching andaccessing multimedia documents that may be located at arbitraryplaces. The architecture contains a database with information aboutthe documents and with thesaurus-like information. The architecturealso contains a browse mechanism and a query mechanism for inspectingthe database. In the design process of the architecture, severalfundamental questions arose, like “What is a document?”and “ What is a medium kind?”. The developed answers tosome of these questions are considered to have a general characterand thus to be useful also outside the scope of the research at hand.The paper concludes with an overview of the current status of theproject and a discussion of future work.     

Nonmonotonic reasoning with multiple belief sets

In complex reasoning tasks it is often the case that there is no single, correct set of conclusions given some initial information. Instead, there may be several such conclusion sets, which we will call belief sets. In the present paper we introduce nonmonotonic belief set operators and selection operators to formalize and to analyze structural aspects of reasoning with multiple belief sets. We define and investigate formal properties of belief set operators as absorption, congruence, supradeductivity and weak belief monotony. Furthermore, it is shown that for each belief set operator satisfying strong belief cumulativity there exists a largest monotonic logic underlying it, thus generalizing a result for nonmonotonic inference operations. Finally, we study abstract properties of selection operators connected to belief set operators, which are used to choose some of the possible belief sets. This revised version was published online in June 2006 with corrections to the Cover Date.     

Preserving Topology by a Digitization Process

The main task of digital image processing is to recognize properties of real objects based on their digital images. These images are obtained by some sampling device, like a CCD camera, and represented as finite sets of points that are assigned some value in a gray-level or color scale. Based on technical properties of sampling devices, these points are usually assumed to form a square grid and are modeled as finite subsets of Z². Therefore, a fundamental question in digital image processing is which features in the digital image correspond, under certain conditions, to properties of the underlying objects. In practical applications this question is mostly answered by visually judging the obtained digital images. In this paper we present a comprehensive answer to this question with respect to topological properties. In particular, we derive conditions relating properties of real objects to the grid size of the sampling device which guarantee that a real object and its digital image are topologically equivalent. These conditions also imply that two digital images of a given object are topologically equivalent. This means, for example, that shifting or rotating an object or the camera cannot lead to topologically different images, i.e., topological properties of obtained digital images are invariant under shifting and rotation.     

Short cycle time systems development

Abstract. An analysis of two studies in the US and Denmark reveals that short cycle time systems development is a new form that can be clearly distinguished among other forms. The distinction consists of a package of five systems development practices. These practices include a focus on completion speed, release‐oriented parallel prototyping, adherence to a fixed architecture, negotiable quality, and an ideal workforce. The package is consistent with amethodical development concepts. Systems are not built in a single project that completes with a delivery, but rather are continually ‘growing’ to adapt to an organizational emergence.     

Benchmarking Least Squares Support Vector Machine Classifiers

In Support Vector Machines (SVMs), the solution of the classification problem is characterized by a (convex) quadratic programming (QP) problem. In a modified version of SVMs, called Least Squares SVM classifiers (LS-SVMs), a least squares cost function is proposed so as to obtain a linear set of equations in the dual space. While the SVM classifier has a large margin interpretation, the LS-SVM formulation is related in this paper to a ridge regression approach for classification with binary targets and to Fisher's linear discriminant analysis in the feature space. Multiclass categorization problems are represented by a set of binary classifiers using different output coding schemes. While regularization is used to control the effective number of parameters of the LS-SVM classifier, the sparseness property of SVMs is lost due to the choice of the 2-norm. Sparseness can be imposed in a second stage by gradually pruning the support value spectrum and optimizing the hyperparameters during the sparse approximation procedure. In this paper, twenty public domain benchmark datasets are used to evaluate the test set performance of LS-SVM classifiers with linear, polynomial and radial basis function (RBF) kernels. Both the SVM and LS-SVM classifier with RBF kernel in combination with standard cross-validation procedures for hyperparameter selection achieve comparable test set performances. These SVM and LS-SVM performances are consistently very good when compared to a variety of methods described in the literature including decision tree based algorithms, statistical algorithms and instance based learning methods. We show on ten UCI datasets that the LS-SVM sparse approximation procedure can be successfully applied.     

The Relationship Between Inhibition of Return and Saccade Trajectory Deviations.

After presentation of a peripheral cue, a subsequent saccade to the cued location is delayed (inhibition of return: IOR). Furthermore, saccades typically deviate away from the cued location. The present study examined the relationship between these inhibitory effects. IOR and saccade trajectory deviations were found after central (endogenous) and peripheral (exogenous) cuing of attention, and both effects were larger with an onset cue than with a color singleton cue. However, a dissociation in time course was found between IOR and saccade trajectory deviations. Saccade trajectory deviations occurred at short delays between the cue and the saccade, but IOR was found at longer delays. A model is proposed in which IOR is caused by inhibition applied to a preoculomotor attentional map, whereas saccade trajectory deviations are caused by inhibition applied to the saccade map, in which the final stage of oculomotor programming takes place. (PsycINFO Database Record (c) 2010 APA, all rights reserved)