CoPs-Centered Knowledge Management

Rajiv Khosla is an Associate Professor at School of Business, La Trobe University. He is the director of externally funded Business Intelligence Institute-Business Systems and Knowledge Modelling research laboratory. Rajiv has a multi-disciplinary background in management, engineering and computer science. He has published over 120 refereed journal and conference papers. He has also authored four books (research monographs) in the area of Emotional Intelligence, Human-Centred e-Business, Multimedia based Socio-technical Information systems, Intelligent Hybrid Multi-agent Systems. Rajiv is the Associate editor of the International Journal of Pattern Recognition, Regional editor of Journal of Intelligent Manufacturing (Springer-verlag), and Action Editor of Journal of Cognitive Systems Research. He has been a project leader of over a dozen industry projects and has commercialised four IT products in Australia. Associate Professor Rajiv Khosla Business Intelligence Institute and Business Systems Knowledge Modeling Laboratory (http://www.latrobe.edu.au/bskm) School of Business, La Trobe University, Melbourne, Victoria – 3086, Australia E-Mail: [email protected] of the primary reasons identified for the failure of existing knowledge management solutions has been that knowledge management tools and research have primarily been designed around technology push-models as against strategy pull-models. In an era where organizations are undergoing rapid and discontinuous change it is imperative that knowledge management systems and organizational entities like CoPs that facilitate knowledge management and organizational transformation are more closely aligned with business strategies and goals of an organization. This would enable organizations to respond more quickly to changing business environments and corresponding change in their knowledge management needs from time to time. This seminar presents a strategy-pull approach for Modeling and Design of CoPs-centered Knowledge Management Systems to facilitate organizational transformation. Among other aspects the seminar will focus on definition of dimensions and criteria for defining CoPs in an organization, application of fuzzy integral techniques to rank 16 criteria employed by CoPs to engage in knowledge management. From a knowledge management and organizational transformation perspective this approach will enable a more direct relationship between business strategy, CoPs and Knowledge Management solutions.published_or_final_versionCentre for Information Technology in Education, University of Hong Kon

Secure data sharing and processing in heterogeneous clouds

The extensive cloud adoption among the European Public Sector Players empowered them to own and operate a range of cloud infrastructures. These deployments vary both in the size and capabilities, as well as in the range of employed technologies and processes. The public sector, however, lacks the necessary technology to enable effective, interoperable and secure integration of a multitude of its computing clouds and services. In this work we focus on the federation of private clouds and the approaches that enable secure data sharing and processing among the collaborating infrastructures and services of public entities. We investigate the aspects of access control, data and security policy languages, as well as cryptographic approaches that enable fine-grained security and data processing in semi-trusted environments. We identify the main challenges and frame the future work that serve as an enabler of interoperability among heterogeneous infrastructures and services. Our goal is to enable both security and legal conformance as well as to facilitate transparency, privacy and effectivity of private cloud federations for the public sector needs. © 2015 The Authors

An intelligent framework and prototype for autonomous maintenance planning in the rail industry

This paper details the development of the AUTONOM project, a project that aims to provide an enterprise system tailored to the planning needs of the rail industry. AUTONOM extends research in novel sensing, scheduling, and decision-making strategies customised for the automated planning of maintenance activities within the rail industry. This paper sets out a framework and software prototype and details the current progress of the project. In the continuation of the AUTONOM project it is anticipated that the combination of techniques brought together in this work will be capable of addressing a wider range of problem types, offered by Network rail and organisations in different industries

Expert systems and finite element structural analysis - a review

Finite element analysis of many engineering systems is practised more as an art than as a science . It involves high level expertise (analytical as well as heuristic) regarding problem modelling (e .g. problem specification,13; choosing the appropriate type of elements etc .), optical mesh design for achieving the specified accuracy (e .g . initial mesh selection, adaptive mesh refinement), selection of the appropriate type of analysis and solution13; routines and, finally, diagnosis of the finite element solutions . Very often such expertise is highly dispersed and is not available at a single place with a single expert. The design of an expert system, such that the necessary expertise is available to a novice to perform the same job even in the absence of trained experts, becomes an attractive proposition. 13; In this paper, the areas of finite element structural analysis which require experience and decision-making capabilities are explored . A simple expert system, with a feasible knowledge base for problem modelling, optimal mesh design, type of analysis and solution routines, and diagnosis, is outlined. Several efforts in these directions, reported in the open literature, are also reviewed in this paper

Soft computing agents for e-health applied to the research and control of unknown diseases

This paper presents an Ontology-based Holonic Diagnostic System (OHDS) that combines the advantages of the holonic paradigm with multi-agent system technology and ontology design, for the organization of unstructured biomedical research into structured disease information. We use ontologies as 'brain' for the holonic diagnostic system to enhance its ability to structure information in a meaningful way and share information fast. To integrate dispersed heterogeneous knowledge available on the web we use a fuzzy mechanism ruled by intelligent agents, which automatically structures the information in the adequate ontology template. Our vision of how this system implementation should be backed by a solid security shield that ensures the privacy and safety of medical information concludes the paper

Semantic interoperability for an integrated product development process: a systematic literature review

International audienceGlobal competitiveness challenges manufacturing industry to rationalise different ways of bringing to the market new products in a short lead-time with competitive prices while ensuring higher quality levels and customisation. Industries need to effectively share heterogeneous information during Product Development Process (PDP) within and across their institutional boundaries to be competitive. However, problems with misinterpretation and mistakes have been identified during information exchange due to the semantic interoperability obstacles. Thus, this research proposes a systematic literature review to identify the main researches and the milestones reference works on semantic interoperability field. A rigorous methodology was conducted in different databases, covering the articles published in scientific journals from 2005 to 2015 as a preliminary study had indicated that the incidence of articles related to the subject was more frequent from the second half of the 2000s. The research structure consisted of four steps: Survey-searching, analysis and selection of recent researches; Categorization-categorization of the selected papers; References citation frequency analysis-the selected papers were analysed and the main researches and milestones references were identified; and Main researches critical analysis – the main researches were analysed for their contributions and limitations, their contributions and limitations, resulting in 14 selected scientific articles and 8 identified milestones references. It is evident that this field has interesting perspectives on future research opportunities on semantic interoperability of information issues across PDP, contributing to the new concepts of future factories

Towards the realisation of an integratated decision support environment for organisational decision making

Traditional decision support systems are based on the paradigm of a single decision maker working at a stand‐alone computer or terminal who has a specific decision to make with a specific goal in mind. Organizational decision support systems aim to support decision makers at all levels of an organization (from executive, middle management managers to operators), who have a variety of decisions to make, with different priorities, often in a distributed and dynamic environment. Such systems need to be designed and developed with extra functionality to meet the challenges such as collaborative working. This paper proposes an Integrated Decision Support Environment (IDSE) for organizational decision making. The IDSE distinguishes itself from traditional decision support systems in that it can flexibly configure and re‐configure its functions to support various decision applications. IDSE is an open software platform which allows its users to define their own decision processes and choose their own exiting decision tools to be integrated into the platform. The IDSE is designed and developed based on distributed client/server networking, with a multi‐tier integration framework for consistent information exchange and sharing, seamless process co‐ordination and synchronisation, and quick access to packaged and legacy systems. The prototype of the IDSE demonstrates good performance in agile response to fast changing decision situations

The design and implementation of fuzzy query processing on sensor networks

Sensor nodes and Wireless Sensor Networks (WSN) enable observation of the physical world in unprecedented levels of granularity. A growing number of environmental monitoring applications are being designed to leverage data collection features of WSN, increasing the need for efficient data management techniques and for comparative analysis of various data management techniques. My research leverages aspects of fuzzy database, specifically fuzzy data representation and fuzzy or flexible queries to improve upon the efficiency of existing data management techniques by exploiting the inherent uncertainty of the data collected by WSN. Herein I present my research contributions. I provide classification of WSN middleware to illustrate varying approaches to data management for WSN and identify a need to better handle the uncertainty inherent in data collected from physical environments and to take advantage of the imprecision of the data to increase the efficiency of WSN by requiring less information be transmitted to adequately answer queries posed by WSN monitoring applications. In this dissertation, I present a novel approach to querying WSN, in which semantic knowledge about sensor attributes is represented as fuzzy terms. I present an enhanced simulation environment that supports more flexible and realistic analysis by using cellular automata models to separately model the deployed WSN and the underlying physical environment. Simulation experiments are used to evaluate my fuzzy query approach for environmental monitoring applications. My analysis shows that using fuzzy queries improves upon other data management techniques by reducing the amount of data that needs to be collected to accurately satisfy application requests. This reduction in data transmission results in increased battery life within sensors, an important measure of cost and performance for WSN applications