Knowledge-based strategic planning: harnessing (in)tangible assets of city-regions

Purpose – The aim of this paper is to investigate the ways of best managing city-regions’ valuable tangible and intangible assets while pursuing a knowledge-based urban development that is sustainable and competitive. Design/methodology/approach – The paper provides a theoretical framework to conceptualise a new strategic planning mechanism, knowledge-based strategic planning, which has been emerged as a planning mechanism for the knowledge-based urban development of post-industrial city-regions. Originality/value – The paper develops a planning framework entitled 6K1C for knowledge-based strategic planning to be used in the analysis of city-regions’ tangible and intangible assets. Practical implications – The paper discusses the importance of asset mapping of cityregions, and explores the ways of successfully managing city-regions’ tangible/intangible assets to achieve an urban development that is sustainable and knowledge-based. Keywords – Knowledge-based urban development, Knowledge-based strategic planning, Tangible assets, Intangible assets, City-regions. Paper type – Academic Research Paper

Ubiquitous infrastructure : urban infrastructure planning and management experience of Korea

Urban infrastructure development in Korea has recently shifted from an old paradigm of conventional infrastructure planning to a new paradigm of intelligent infrastructure provision. This new paradigm, so called ubiquitous infrastructure, is based on a combination of urban infrastructure, information and communication technologies and digital networks. Ubiquitous infrastructure basically refers to an urban infrastructure where any citizen could access any infrastructure and services via any electronic device regardless of time and location. This paper introduces this new paradigm of intellectual infrastructure planning and its design schemes. The paper also examines the ubiquitous infrastructure development in Korea and discusses the positive effects of ubiquitous infrastructure on sustainable urban development.

Urban management revolution : intelligent management systems for ubiquitous cities

A successful urban management support system requires an integrated approach. This integration includes bringing together economic, socio-cultural and urban development with a well orchestrated transparent and open decision making mechanism. The paper emphasises the importance of integrated urban management to better tackle the climate change, and to achieve sustainable urban development and sound urban growth management. This paper introduces recent approaches on urban management systems, such as intelligent urban management systems, that are suitable for ubiquitous cities. The paper discusses the essential role of online collaborative decision making in urban and infrastructure planning, development and management, and advocates transparent, fully democratic and participatory mechanisms for an effective urban management system that is particularly suitable for ubiquitous cities. This paper also sheds light on some of the unclear processes of urban management of ubiquitous cities and online collaborative decision making, and reveals the key benefits of integrated and participatory mechanisms in successfully constructing sustainable ubiquitous cities.

A framework for analyzing system intelligence of the building control system : a study of the integrated building management system

The lack of satisfactory consensus for characterizing the system intelligence and structured analytical decision models has inhibited the developers and practitioners to understand and configure optimum intelligent building systems in a fully informed manner. So far, little research has been conducted in this aspect. This research is designed to identify the key intelligent indicators, and develop analytical models for computing the system intelligence score of smart building system in the intelligent building. The integrated building management system (IBMS) was used as an illustrative example to present a framework. The models presented in this study applied the system intelligence theory, and the conceptual analytical framework. A total of 16 key intelligent indicators were first identified from a general survey. Then, two multi-criteria decision making (MCDM) approaches, the analytic hierarchy process (AHP) and analytic network process (ANP), were employed to develop the system intelligence analytical models. Top intelligence indicators of IBMS include: self-diagnostic of operation deviations; adaptive limiting control algorithm; and, year-round time schedule performance. The developed conceptual framework was then transformed to the practical model. The effectiveness of the practical model was evaluated by means of expert validation. The main contribution of this research is to promote understanding of the intelligent indicators, and to set the foundation for a systemic framework that provide developers and building stakeholders a consolidated inclusive tool for the system intelligence evaluation of the proposed components design configurations.

SELinux policy management framework for HIS

Health Information Systems (HIS) make extensive use of Information and Communication Technologies (ICT). The use of ICT aids in improving the quality and efficiency of healthcare services by making healthcare information available at the point of care (Goldstein, Groen, Ponkshe, and Wine, 2007). The increasing availability of healthcare data presents security and privacy issues which have not yet been fully addressed (Liu, Caelli, May, and Croll, 2008a). Healthcare organisations have to comply with the security and privacy requirements stated in laws, regulations and ethical standards, while managing healthcare information. Protecting the security and privacy of healthcare information is a very complex task (Liu, May, Caelli and Croll, 2008b). In order to simplify the complexity of providing security and privacy in HIS, appropriate information security services and mechanisms have to be implemented. Solutions at the application layer have already been implemented in HIS such as those existing in healthcare web services (Weaver et al., 2003). In addition, Discretionary Access Control (DAC) is the most commonly implemented access control model to restrict access to resources at the OS layer (Liu, Caelli, May, Croll and Henricksen, 2007a). Nevertheless, the combination of application security mechanisms and DAC at the OS layer has been stated to be insufficient in satisfying security requirements in computer systems (Loscocco et al., 1998). This thesis investigates the feasibility of implementing Security Enhanced Linux (SELinux) to enforce a Role-Based Access Control (RBAC) policy to help protect resources at the Operating System (OS) layer. SELinux provides Mandatory Access Control (MAC) mechanisms at the OS layer. These mechanisms can contain the damage from compromised applications and restrict access to resources according to the security policy implemented. The main contribution of this research is to provide a modern framework to implement and manage SELinux in HIS. The proposed framework introduces SELinux Profiles to restrict access permissions over the system resources to authorised users. The feasibility of using SELinux profiles in HIS was demonstrated through the creation of a prototype, which was submitted to various attack scenarios. The prototype was also subjected to testing during emergency scenarios, where changes to the security policies had to be made on the spot. Attack scenarios were based on vulnerabilities common at the application layer. SELinux demonstrated that it could effectively contain attacks at the application layer and provide adequate flexibility during emergency situations. However, even with the use of current tools, the development of SELinux policies can be very complex. Further research has to be made in order to simplify the management of SELinux policies and access permissions. In addition, SELinux related technologies, such as the Policy Management Server by Tresys Technologies, need to be researched in order to provide solutions at different layers of protection.

Full-time is a given here : part-time versus full-time job quality

This study explores full-time workers' understanding of and assumptions about part-time work against six job quality components identified in recent literature. Forty interviews were conducted with employees in a public sector agency in Australia, a study context where part-time work is ostensibly 'good quality' and is typically long term, voluntary, involving secure contracts (i.e. permanent rather than casual) and having predictable hours distributed evenly over the week and year. Despite strong collective bargaining arrangements as well as substantial legal and industrial obligations, the findings revealed some serious concerns for part-time job quality. These concerns included reduced responsibilities and lesser access to high status roles and projects, a lack of access to promotion opportunities, increased work intensity and poor workplace support. The highly gendered, part-time labour market also means that it is women who disproportionately experience this disadvantage. To foster equity, greater attention needs to focus on monitoring and enhancing job quality, regardless of hours worked.

Life cycle modelling and design knowledge development in 3D virtual environments : final report

Experience plays an important role in building management. “How often will this asset need repair?” or “How much time is this repair going to take?” are types of questions that project and facility managers face daily in planning activities. Failure or success in developing good schedules, budgets and other project management tasks depend on the project manager's ability to obtain reliable information to be able to answer these types of questions. Young practitioners tend to rely on information that is based on regional averages and provided by publishing companies. This is in contrast to experienced project managers who tend to rely heavily on personal experience. Another aspect of building management is that many practitioners are seeking to improve available scheduling algorithms, estimating spreadsheets and other project management tools. Such “micro-scale” levels of research are important in providing the required tools for the project manager's tasks. However, even with such tools, low quality input information will produce inaccurate schedules and budgets as output. Thus, it is also important to have a broad approach to research at a more “macro-scale.” Recent trends show that the Architectural, Engineering, Construction (AEC) industry is experiencing explosive growth in its capabilities to generate and collect data. There is a great deal of valuable knowledge that can be obtained from the appropriate use of this data and therefore the need has arisen to analyse this increasing amount of available data. Data Mining can be applied as a powerful tool to extract relevant and useful information from this sea of data. Knowledge Discovery in Databases (KDD) and Data Mining (DM) are tools that allow identification of valid, useful, and previously unknown patterns so large amounts of project data may be analysed. These technologies combine techniques from machine learning, artificial intelligence, pattern recognition, statistics, databases, and visualization to automatically extract concepts, interrelationships, and patterns of interest from large databases. The project involves the development of a prototype tool to support facility managers, building owners and designers. This final report presents the AIMMTM prototype system and documents how and what data mining techniques can be applied, the results of their application and the benefits gained from the system. The AIMMTM system is capable of searching for useful patterns of knowledge and correlations within the existing building maintenance data to support decision making about future maintenance operations. The application of the AIMMTM prototype system on building models and their maintenance data (supplied by industry partners) utilises various data mining algorithms and the maintenance data is analysed using interactive visual tools. The application of the AIMMTM prototype system to help in improving maintenance management and building life cycle includes: (i) data preparation and cleaning, (ii) integrating meaningful domain attributes, (iii) performing extensive data mining experiments in which visual analysis (using stacked histograms), classification and clustering techniques, associative rule mining algorithm such as “Apriori” and (iv) filtering and refining data mining results, including the potential implications of these results for improving maintenance management. Maintenance data of a variety of asset types were selected for demonstration with the aim of discovering meaningful patterns to assist facility managers in strategic planning and provide a knowledge base to help shape future requirements and design briefing. Utilising the prototype system developed here, positive and interesting results regarding patterns and structures of data have been obtained.

Controlled flexibility and lifecycle management of business processes through extensibility

Vendors provide reference process models as consolidated, off-the-shelf solutions to capture best practices in a given industry domain. Customers can then adapt these models to suit their specific requirements. Traditional process flexibility approaches facilitate this operation, but do not fully address it as they do not sufficiently take controlled change guided by vendors' reference models into account. This tension between the customer's freedom of adapting reference models, and the ability to incorporate with relatively low effort vendor-initiated reference model changes, thus needs to be carefully balanced. This paper introduces process extensibility as a new paradigm for customizing reference processes and managing their evolution over time. Process extensibility mandates a clear recognition of the different responsibilities and interests of reference model vendors and consumers, and is concerned with keeping the effort of customer-side reference model adaptations low while allowing sufficient room for model change.

A-REIT seasoned equity offerings : determinants and market reaction

The paper examines the decision by Australian Real Estate Trusts (A-REITs) to issue seasoned equity offerings from 2000 - 2008 and stock market reaction to the offerings using panel data and event study methodologies, respectively. The global financial crisis has resulted in freezing of the Australian bond markets, with several A-REITs left with seasoned equity issuance and asset sales as the only viable modes of raising additional capital. The findings review that leverage and operating risk are negative significant determinants of seasoned equity offerings; profitability and growth opportunities are positive significant determinants. Of the structure and type of properties held by the A-REIT, only stapled management structure and international operations are significant determinants. Type of properties held by A-REITs show inconsistent results. Similar to previous studies of seasoned equity offerings, we find a significant negative abnormal return associated with their announcement and no evidence of excessive leakage of information. Cross-sectional regressions show that the issued amount raised and leverage are significant factors affecting abnormal returns.

Improving the management of building life cycle : a data mining approach

The construction industry has adapted information technology in its processes in terms of computer aided design and drafting, construction documentation and maintenance. The data generated within the construction industry has become increasingly overwhelming. Data mining is a sophisticated data search capability that uses classification algorithms to discover patterns and correlations within a large volume of data. This paper presents the selection and application of data mining techniques on maintenance data of buildings. The results of applying such techniques and potential benefits of utilising their results to identify useful patterns of knowledge and correlations to support decision making of improving the management of building life cycle are presented and discussed.

Business and software service lifecycle management

Although the service-oriented paradigm has been well established in the technical domain for quite some time now, service governance is still considered a research gap. To ensure adequate governance, there is a necessity to manage services as first-class assets throughout the lifecycle. Now that the concept of ser-vice-orientation is also increasingly applied on the business level to structure an organisation’s capabili-ties, the problem has become an even bigger chal-lenge. This paper presents a generic business and software service lifecycle and aligns it with the com-mon management layers in organisations. Using ser-vice analysis as an example, it moreover illustrates how activities in the service lifecycle may vary on lower levels of granularity depending on the focus on business or software services.

Developing Software Agents for Data Mining : [AIMM] Agents for Improving Maintenance Management

This report demonstrates the development of: • Development of software agents for data mining • Link data mining to building model in virtual environments • Link knowledge development with building model in virtual environments • Demonstration of software agents for data mining • Populate with maintenance data

Demonstration of Software Agents Prototype System : [AIMM] Agents for Improving Maintenance Management

This report presents the demonstration of software agents prototype system for improving maintenance management [AIMM] including: • Developing and implementing a user focused approach for mining the maintenance data of buildings. This report presents the demonstration of software agents prototype system for improving maintenance management [AIMM] including: • Developing and implementing a user focused approach for mining the maintenance data of buildings. • Refining the development of a multi agent system for data mining in virtual environments (Active Worlds) by developing and implementing a filtering agent on the results obtained from applying data mining techniques on the maintenance data. • Integrating the filtering agent within the multi agents system in an interactive networked multi-user 3D virtual environment. • Populating maintenance data and discovering new rules of knowledge.