Edith Cowan University

About: Edith Cowan University is a education organization based out in Perth, Western Australia, Australia. It is known for research contribution in the topics: Population & Context (language use). The organization has 4040 authors who have published 13529 publications receiving 339582 citations. The organization is also known as: Edith Cowan & ECU.

A robust MIMO terminal sliding mode control scheme for rigid robotic manipulators

Abstract: In this paper, a robust multi-input/multi-output (MIMO) terminal sliding mode control technique is developed for n-link rigid robotic manipulators. It is shown that an MIMO terminal switching plane variable vector is first defined, and the relationship between the terminal switching plane variable vector and system error dynamics is established. By using the MIMO terminal sliding mode technique and a few structural properties of rigid robotic manipulators, a robust controller can then be designed so that the output tracking error can converge to zero in a finite time, and strong robustness with respect to large uncertain dynamics can be guaranteed. It is also shown that the high gain of the terminal sliding mode controllers can be significantly reduced with respect to the one of the linear sliding mode controller where the sampling interval is nonzero. >

Skin segmentation using color pixel classification: analysis and comparison

Abstract: This work presents a study of three important issues of the color pixel classification approach to skin segmentation: color representation, color quantization, and classification algorithm. Our analysis of several representative color spaces using the Bayesian classifier with the histogram technique shows that skin segmentation based on color pixel classification is largely unaffected by the choice of the color space. However, segmentation performance degrades when only chrominance channels are used in classification. Furthermore, we find that color quantization can be as low as 64 bins per channel, although higher histogram sizes give better segmentation performance. The Bayesian classifier with the histogram technique and the multilayer perceptron classifier are found to perform better compared to other tested classifiers, including three piecewise linear classifiers, three unimodal Gaussian classifiers, and a Gaussian mixture classifier.

Rate of force development: physiological and methodological considerations

Abstract: The evaluation of rate of force development during rapid contractions has recently become quite popular for characterising explosive strength of athletes, elderly individuals and patients. The main aims of this narrative review are to describe the neuromuscular determinants of rate of force development and to discuss various methodological considerations inherent to its evaluation for research and clinical purposes. Rate of force development (1) seems to be mainly determined by the capacity to produce maximal voluntary activation in the early phase of an explosive contraction (first 50–75 ms), particularly as a result of increased motor unit discharge rate; (2) can be improved by both explosive-type and heavy-resistance strength training in different subject populations, mainly through an improvement in rapid muscle activation; (3) is quite difficult to evaluate in a valid and reliable way. Therefore, we provide evidence-based practical recommendations for rational quantification of rate of force development in both laboratory and clinical settings.

The Dual Imperatives of Action Research

Abstract: Action research (AR) is not without its critics, and those who reject some of the paradigmatic assumptions embodied in AR maintain that AR is little more than consultancy, that it is impossible to establish causal relationships, that it is difficult to generalize from AR studies, that there is a risk of researcher bias, and that generally speaking, it lacks some of the key qualities that are normally associated with rigorous research. The authors are sensitive to such criticisms, for although they are committed action researchers, they have elsewhere voiced their concerns about the quality of AR practice in the field of information systems. The authors argue that part of the issue concerns the way in which we currently conceptualize AR. In this article, the argument for a deeper and more reflective analysis of the meaning and full implications of AR is developed, culminating in a model of AR being developed that explicitly includes both a problem solving interest cycle and a research interest cycle. Important implications of this new model are articulated, with examples to illustrate these points being drawn from a real‐life AR study.