419 resultados para Minichromosome maintenance complex


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Two distinct maintenance-data-models are studied: a government Enterprise Resource Planning (ERP) maintenance-data-model, and the Software Engineering Industries (SEI) maintenance-data-model. The objective is to: (i) determine whether the SEI maintenance-data-model is sufficient in the context of ERP (by comparing with an ERP case), (ii) identify whether the ERP maintenance-data-model in this study has adequately captured the essential and common maintenance attributes (by comparing with the SEI), and (iii) proposed a new ERP maintenance-data-model as necessary. Our findings suggest that: (i) there are variations to the SEI model in an ERP-context, and (ii) there are rooms for improvements in our ERP case’s maintenance-data-model. Thus, a new ERP maintenance-data-model capturing the fundamental ERP maintenance attributes is proposed. This model is imperative for: (i) enhancing the reporting and visibility of maintenance activities, (ii) monitoring of the maintenance problems, resolutions and performance, and (iii) helping maintenance manager to better manage maintenance activities and make well-informed maintenance decisions.

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The concept of a substantive integrator is introduced as a method for integrated resource and environmental management as a means to assimilate different resource values at the operational or field level. A substantive integrator is a strategic management tool for integrating multiple uses into coprorate management regimes that traditionally manage for single values. Wildlife habitat management is presented as a substantive integrator for managing vegetation on electric utility power line corridors. A case study from northern British Columbia provides an example of wildlife habitat management as a means to integrate other resource values such as aesthetics, access and subsistence along British Columbia Hydro and Power Authority's transmission rights-of-way.

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Most departmental computing infrastructure reflects the state of networking technology and available funds at the time of construction, which converge in a preconceived notion of homogeneity of network architecture and usage patterns. The DMAN (Digital Media Access Network) project, a large-scale server and network foundation for the Hong Kong Polytechnic University's School of Design was created as a platform that would support a highly complex academic environment while giving maximum freedom to students, faculty and researchers through simplicity and ease of use. As a centralized multi-user computation backbone, DMAN faces an extremely hetrogeneous user and application profile, exceeding implementation and maintenance challenges of typical enterprise, and even most academic server set-ups. This paper sumarizes the specification, implementation and application of the system while describing its significance for design education in a computational context.

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The firm is faced with a decision concerning the nature of intra-organizational exchange relationships with internal human resources and the nature or inter-organizational exchange relationships with market firms. In both situations, the firm can develop an exchange that ranges from a discrete exchange to a relational exchange. Transaction Cost Economics (TCE) and the Resource Dependency View (RDV) represent alternative efficiency-based explanations fo the nature of the exchange relationship. The aim of the paper is to test these two theories in respect of air conditioning maintenance in retail centres. Multiple sources of information are genereated from case studies of Australian retail centres to test these theories in respoect of internalized operations management (concerning strategic aspects of air conditioning maintenance) and externalized planned routine air conditioning maintenance. The analysis of the data centres on pattern matching. It is concluded that the data supports TCE - on the basis of a development in TCE's contractual schema. Further research is suggested towards taking a pluralistic stance and developing a combined efficiency and power hypothesis - upon which Williamson has speculated. For practice, the conclusions also offer a timely cautionary note concerning the adoption of one approach in all exchange relationships.

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It is questionable whether activities like construction, including maintenance and repair, can be considered a single entity or industry - on the basis that different sectors of construction/maintenance use fundamentally distinct resource and skill bases. This creates a number of issues including the development of competition and reform policy. de Valance deployed the Structure-Conduct-Performance model (SCP) to delineate sectors of new/installation construction activity and, in doing so, proposes that there exists multiple market structures in a given project. The purpose of this paper is to apply the SCP model to a different sector of construction activity, that is air conditioning maintenance and test de Valance's proposition concerning the existence of multiple market structures in a supply chain but this time to a built facility. The research method combines secondary data concerning the "Structure" component of the SCP model and primary data with regard to the "Conduct" and "Performance" parts of the SCP model. The results provide further support (beyond de Valance's analysis of new/installation activity) that a sector system approach using the SCP model is a more effective way to analyse market structures in construction activity. This paper also supports de Valance's proposition concerning the existence of multiple market structures in a supply chain to a project/facility.

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The research presented in this thesis addresses inherent problems in signaturebased intrusion detection systems (IDSs) operating in heterogeneous environments. The research proposes a solution to address the difficulties associated with multistep attack scenario specification and detection for such environments. The research has focused on two distinct problems: the representation of events derived from heterogeneous sources and multi-step attack specification and detection. The first part of the research investigates the application of an event abstraction model to event logs collected from a heterogeneous environment. The event abstraction model comprises a hierarchy of events derived from different log sources such as system audit data, application logs, captured network traffic, and intrusion detection system alerts. Unlike existing event abstraction models where low-level information may be discarded during the abstraction process, the event abstraction model presented in this work preserves all low-level information as well as providing high-level information in the form of abstract events. The event abstraction model presented in this work was designed independently of any particular IDS and thus may be used by any IDS, intrusion forensic tools, or monitoring tools. The second part of the research investigates the use of unification for multi-step attack scenario specification and detection. Multi-step attack scenarios are hard to specify and detect as they often involve the correlation of events from multiple sources which may be affected by time uncertainty. The unification algorithm provides a simple and straightforward scenario matching mechanism by using variable instantiation where variables represent events as defined in the event abstraction model. The third part of the research looks into the solution to address time uncertainty. Clock synchronisation is crucial for detecting multi-step attack scenarios which involve logs from multiple hosts. Issues involving time uncertainty have been largely neglected by intrusion detection research. The system presented in this research introduces two techniques for addressing time uncertainty issues: clock skew compensation and clock drift modelling using linear regression. An off-line IDS prototype for detecting multi-step attacks has been implemented. The prototype comprises two modules: implementation of the abstract event system architecture (AESA) and of the scenario detection module. The scenario detection module implements our signature language developed based on the Python programming language syntax and the unification-based scenario detection engine. The prototype has been evaluated using a publicly available dataset of real attack traffic and event logs and a synthetic dataset. The distinct features of the public dataset are the fact that it contains multi-step attacks which involve multiple hosts with clock skew and clock drift. These features allow us to demonstrate the application and the advantages of the contributions of this research. All instances of multi-step attacks in the dataset have been correctly identified even though there exists a significant clock skew and drift in the dataset. Future work identified by this research would be to develop a refined unification algorithm suitable for processing streams of events to enable an on-line detection. In terms of time uncertainty, identified future work would be to develop mechanisms which allows automatic clock skew and clock drift identification and correction. The immediate application of the research presented in this thesis is the framework of an off-line IDS which processes events from heterogeneous sources using abstraction and which can detect multi-step attack scenarios which may involve time uncertainty.

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This report demonstrates the development of: (a) object-oriented representation to provide 3D interactive environment using data provided by Woods Bagot; (b) establishing basis of agent technology for mining building maintenance data, and (C) 3D interaction in virtual environments using object-oriented representation. Applying data mining over industry maintenance database has been demonstrated in the previous report.

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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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The building life cycle process is complex and prone to fragmentation as it moves through its various stages. The number of participants, and the diversity, specialisation and isolation both in space and time of their activities, have dramatically increased over time. The data generated within the construction industry has become increasingly overwhelming. Most currently available computer tools for the building industry have offered productivity improvement in the transmission of graphical drawings and textual specifications, without addressing more fundamental changes in building life cycle management. Facility managers and building owners are primarily concerned with highlighting areas of existing or potential maintenance problems in order to be able to improve the building performance, satisfying occupants and minimising turnover especially the operational cost of maintenance. In doing so, they collect large amounts of data that is stored in the building’s maintenance database. The work described in this paper is targeted at adding value to the design and maintenance of buildings by turning maintenance data into information and knowledge. Data mining technology presents an opportunity to increase significantly the rate at which the volumes of data generated through the maintenance process can be turned into useful information. This can be done using classification algorithms to discover patterns and correlations within a large volume of data. This paper presents how and what data mining techniques can be applied on maintenance data of buildings to identify the impediments to better performance of building assets. It demonstrates what sorts of knowledge can be found in maintenance records. The benefits to the construction industry lie in turning passive data in databases into knowledge that can improve the efficiency of the maintenance process and of future designs that incorporate that maintenance knowledge.

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The objective of the project “Value Alignment Process for Project Delivery” is to provide a catalyst and tools for reform in the building and construction industry to transform business-as-usual performance into exceptional performance. The outcomes of this project will be beneficial to not only the construction industry, but to the community as a whole because a more sophisticated industry can deliver more effective use of assets, financing, operating and maintenance of facilities to suit the community’s needs. The research project consists of a study into best practice project delivery and the development of a suite of products, resources and services to guide project teams towards the best approach for a specific project. These resources will be focused on promoting the principles that underlie best practice project delivery, rather than on identifying a particular delivery system. The need for such tools and resources becomes more and more acute as the environment within which the construction industry operates becomes more and more complex, and as business and political imperatives shift to encompass or represent diverse stakeholder interests. To this end, this literature review looks at why it is essential to achieve transformation in the Australian construction industry in the context of its importance to the Australian economy. It seeks to investigate the concepts of ‘alignment’ and value’ as they pertain to construction industry processes and relationships. It comprehensively reviews drivers of project excellence and best practice project delivery principles and looks at how clients approach selection of project delivery systems. It critiques existing project delivery strategies and gives an overview of recent best practice initiatives. The literature review represents a milestone against the Project Agreement and forms a foundation document for this research project