Knowledge management: a review of the field and of OR's contribution

This paper examines the field of knowledge management (KM) and identifies the role of operational research (OR) in key milestones and in KM's future. With the presence of the OR Society journal Knowledge Management Research and Practice and with the INFORMS journal Organization Science, OR may be assumed to have an explicit and a leading role in KM. Unfortunately, the origins and the evidence of recent research efforts do not fully support this assumption. We argue that while OR has been inside many of the milestones there is no explicit recognition of its role and while OR research on KM has considerably increased in the last 5 years, it still forms a rather modest explicit contribution to KM research. Nevertheless, the depth of OR's experience in decision-making models and decision support systems, soft systems with hard systems and in risk management suggests that OR is uniquely placed to lead future KM developments. We suggest that a limiting aspect of whether OR will be seen to have a significant profile will be the extent to which developments are recognized as being informed by OR

Proposing a systems vision of knowledge management in emergency care

This paper makes a case for taking a systems view of knowledge management within health-care provision, concentrating on the emergency care process in the UK National Health Service. It draws upon research in two casestudy organizations (a hospital and an ambulance service). The case-study organizations appear to be approaching knowledge (and information) management in a somewhat fragmented way. They are trying to think more holistically, but (perhaps) because of the ways their organizations and their work are structured, they cannot ‘see’ the whole of the care process. The paper explores the complexity of knowledge management in emergency health care and draws the distinction for knowledge management between managing local and operational knowledge, and global and clinical knowledge

Managing software engineers and their knowledge

This chapter begins by reviewing the history of software engineering as a profession, especially the so-called software crisis and responses to it, to help focus on what it is that software engineers do. This leads into a discussion of the areas in software engineering that are problematic as a basis for considering knowledge management issues. Some of the previous work on knowledge management in software engineering is then examined, much of it not actually going under a knowledge management title, but rather “learning” or “expertise”. The chapter goes on to consider the potential for knowledge management in software engineering and the different types of knowledge management solutions and strategies that might be adopted, and it touches on the crucial importance of cultural issues. It concludes with a list of challenges that knowledge management in software engineering needs to address

Comparison of Different Neuro-Fuzzy Classification Systems for the Detection of Prostate Cancer in Ultrasonic Images

We selected five trainable Neuro-Fuzzy classification algorithms in order to investigate their ability to differentiate areas of malign tissue in ultrasonic prostate images. The algorithms were compared with results from two commonly used classifiers, the K-nearest neighbor (KNN) classifier and the Bayes classifier. The best Neuro-Fuzzy classification system, which is based on a mountain clustering algorithm published by Yager et al and refined by Chiu reached recognition rates above 86 % in comparison to the Bayes classifier (79 %) and the KNN classifier (78 %). Our results suggest that Neuro-Fuzzy classification algorithms have the potential to significantly improve common classification methods for the use in ultrasonic tissue characterization. INTRODUCTION The aim of our work was to investigate the performance of different Neuro-Fuzzy classification methods for the distinction of benign and malign tissue in ultrasound prostate diagnosis. The motivation to use Neuro-Fuzzy systems ..