983 resultados para Territory management


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The purpose of this study is to demonstrate the appropriateness of “Japanese Manufacturing Management” (JMM) strategies in the Asian, ASEAN and Australasian automotive sectors. Secondly, the study assessed JMM as a prompt, effective and efficient global manufacturing management practice for automotive manufacturing companies to learn; benchmark for best practice; acquire product and process innovation, and enhance their capabilities and capacities. In this study, the philosophies, systems and tools that have been adopted in various automotive manufacturing assembly plants and their tier 1 suppliers in the three Regions were examined. A number of top to middle managers in these companies were located in Thailand, Indonesia, Malaysia, Singapore, Philippines, Viet Nam, and Australia and were interviewed by using a qualitative methodology. The results confirmed that the six pillars of JMM (culture change, quality at shop floor, consensus, incremental continual improvement, benchmarking, and backward-forward integration) are key enablers to success in adopting JMM in both automotive and other manufacturing sectors in the three Regions. The analysis and on-site interviews identified a number of recommendations that were validated by the automotive manufacturing company’s managers as the most functional JMM strategies.

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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.

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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.

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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.

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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.

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Business Service Management describes the emerging discipline dedicated to the IT-enabled management of services as corporate assets. Business Service Management deals with the service orientation of the organisation and the provisioning and use of business services. The term business service describes an autonomous transformational capability that is offered to and consumed by external or internal customers for their benefit. The prefix ‘business’ stresses that such a service has a market value, requires the ability to be managed internally as a corporate asset and that its implementation is technology-agnostic. While business services (or so called capabilities) have attracted the attention of many vendors and organisations, a lack of understanding of the activities required for the successful management of such business services remains a critical issue. In order to fill this gap, a framework consisting of Service Lifecycle Management, Service Value Management, Service Relationship Management and Service Enablement is proposed. This Framework has the potential to provide organisations with the much needed guidance in their attempts to convert current IT-driven service initiatives into successful service-centric business models.

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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.

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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.

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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.

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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

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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.

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Since the 1980s, in Australia and other developed nations, public sector management philosophies and how the public sector is organized have changed dramatically. At the same time, there have been many demands, and several attempts, to preserve and promote ethical behaviour within the public sector - though few go much beyond the publication of a code. Both developments require an understanding of how public organizations operate in this new environment. Organizational and management theory are seen as providing important potential insights into the opportunities and pitfalls for building ethics into the practices, culture and norms of public organizations. This book brings together the experience and research of a range of "reflective practitioners" and "engaged academics" in public sector management, organizational theory, management theory, public sector ethics and law. It addresses what management and organization theory might suggest about the nature of public organizations and the institutionalization of ethics.

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Australia’s civil infrastructure assets of roads, bridges, railways, buildings and other structures are worth billions of dollars. Road assets alone are valued at around A$ 140 billion. As the condition of assets deteriorate over time, close to A$10 billion is spent annually in asset maintenance on Australia's roads, or the equivalent of A$27 million per day. To effectively manage road infrastructures, firstly, road agencies need to optimise the expenditure for asset data collection, but at the same time, not jeopardise the reliability in using the optimised data to predict maintenance and rehabilitation costs. Secondly, road agencies need to accurately predict the deterioration rates of infrastructures to reflect local conditions so that the budget estimates could be accurately estimated. And finally, the prediction of budgets for maintenance and rehabilitation must provide a certain degree of reliability. A procedure for assessing investment decision for road asset management has been developed. The procedure includes: • A methodology for optimising asset data collection; • A methodology for calibrating deterioration prediction models; • A methodology for assessing risk-adjusted estimates for life-cycle cost estimates. • A decision framework in the form of risk map

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This document provides a review of international and national practices in investment decision support tools in road asset management. Efforts were concentrated on identifying analytic frameworks, evaluation methodologies and criteria adopted by current tools. Emphasis was also given to how current approaches support Triple Bottom Line decision-making. Benefit Cost Analysis and Multiple Criteria Analysis are principle methodologies in supporting decision-making in Road Asset Management. The complexity of the applications shows significant differences in international practices. There is continuing discussion amongst practitioners and researchers regarding to which one is more appropriate in supporting decision-making. It is suggested that the two approaches should be regarded as complementary instead of competitive means. Multiple Criteria Analysis may be particularly helpful in early stages of project development, say strategic planning. Benefit Cost Analysis is used most widely for project prioritisation and selecting the final project from amongst a set of alternatives. Benefit Cost Analysis approach is useful tool for investment decision-making from an economic perspective. An extension of the approach, which includes social and environmental externalities, is currently used in supporting Triple Bottom Line decision-making in the road sector. However, efforts should be given to several issues in the applications. First of all, there is a need to reach a degree of commonality on considering social and environmental externalities, which may be achieved by aggregating the best practices. At different decision-making level, the detail of consideration of the externalities should be different. It is intended to develop a generic framework to coordinate the range of existing practices. The standard framework will also be helpful in reducing double counting, which appears in some current practices. Cautions should also be given to the methods of determining the value of social and environmental externalities. A number of methods, such as market price, resource costs and Willingness to Pay, are found in the review. The use of unreasonable monetisation methods in some cases has discredited Benefit Cost Analysis in the eyes of decision makers and the public. Some social externalities, such as employment and regional economic impacts, are generally omitted in current practices. This is due to the lack of information and credible models. It may be appropriate to consider these externalities in qualitative forms in a Multiple Criteria Analysis. Consensus has been reached in considering noise and air pollution in international practices. However, Australia practices generally omitted these externalities. Equity is an important consideration in Road Asset Management. The considerations are either between regions, or social groups, such as income, age, gender, disable, etc. In current practice, there is not a well developed quantitative measure for equity issues. More research is needed to target this issue. Although Multiple Criteria Analysis has been used for decades, there is not a generally accepted framework in the choice of modelling methods and various externalities. The result is that different analysts are unlikely to reach consistent conclusions about a policy measure. In current practices, some favour using methods which are able to prioritise alternatives, such as Goal Programming, Goal Achievement Matrix, Analytic Hierarchy Process. The others just present various impacts to decision-makers to characterise the projects. Weighting and scoring system are critical in most Multiple Criteria Analysis. However, the processes of assessing weights and scores were criticised as highly arbitrary and subjective. It is essential that the process should be as transparent as possible. Obtaining weights and scores by consulting local communities is a common practice, but is likely to result in bias towards local interests. Interactive approach has the advantage in helping decision-makers elaborating their preferences. However, computation burden may result in lose of interests of decision-makers during the solution process of a large-scale problem, say a large state road network. Current practices tend to use cardinal or ordinal scales in measure in non-monetised externalities. Distorted valuations can occur where variables measured in physical units, are converted to scales. For example, decibels of noise converts to a scale of -4 to +4 with a linear transformation, the difference between 3 and 4 represents a far greater increase in discomfort to people than the increase from 0 to 1. It is suggested to assign different weights to individual score. Due to overlapped goals, the problem of double counting also appears in some of Multiple Criteria Analysis. The situation can be improved by carefully selecting and defining investment goals and criteria. Other issues, such as the treatment of time effect, incorporating risk and uncertainty, have been given scant attention in current practices. This report suggested establishing a common analytic framework to deal with these issues.