Data mining for lifetime prediction of metallic components

The ability to accurately predict the lifetime of building components is crucial to optimizing building design, material selection and scheduling of required maintenance. This paper discusses a number of possible data mining methods that can be applied to do the lifetime prediction of metallic components and how different sources of service life information could be integrated to form the basis of the lifetime prediction model

Mining in Northern British Columbia

The history of the settlement of the province is tied to patterns of exploration and min development. In Northern British Columbia the Cariboo goldfields provided the impetus for settlement of the region and the beginning for mining to extend into the watern and northern regions in a series of minor gold rushes. The northern half of the province has a geological diverse mineral base that supports a wide variety of mining, and a gradual improvement of exploration and mining methods due to scientific knowledge and technology provided opportunities for lode gold and base metal mines to be developed. The success of mining is based on world ore prices and competitive markets that impact the economic viability of developing a mine. Mining faces increasing pressures in the northern half of the province due to other resource values, such as tourism or protected areas, that claim and compete for a similar land base.

Increasing relevance and interest : teaching environmental and planning law to built environment students

A new approach was taken to delivering a challenging "stewarship of land" unit to over 350 predominantly first year built environment students stewardship. The new approach involved incorporating environmental and planning law into the syllabus, exposing students to a wide range of statutes, selecting legal cases according to a et of criteria and revisiting the material using different modes of delivery and teaching resources. To evaluate the effectiveness of the new approach, the students were surveyed to elicit their learning experience and preferences. The survey found that most students perceived learning about environmental and planning law, including legal cases, worthwhile.----- Areas identified by the surcey for improvement included the perception by some students that: environmenatl and planning law is irrelevant to their discipline and future caree; studying law is dull and sometimes daunting; and the prescribed reading could be omitted.----- To address student perceptions, it is proposed to reorder the topics commencing with local, charismatic topics, while explanding international content and cases, to enlarge and enhance the repertoire of video clips to include sites of legal cawses and development projects, and to reformat the online weekly quizzes to promote reading of primary material.----- Overall, the approach to teaching environmental and planning law to built environment students, including the criteria for selecting legal cases, described in this paper, was found to be effective.

Effective web service discovery using a combination of a semantic model and a data mining technique

With the advent of Service Oriented Architecture, Web Services have gained tremendous popularity. Due to the availability of a large number of Web services, finding an appropriate Web service according to the requirement of the user is a challenge. This warrants the need to establish an effective and reliable process of Web service discovery. A considerable body of research has emerged to develop methods to improve the accuracy of Web service discovery to match the best service. The process of Web service discovery results in suggesting many individual services that partially fulfil the user’s interest. By considering the semantic relationships of words used in describing the services as well as the use of input and output parameters can lead to accurate Web service discovery. Appropriate linking of individual matched services should fully satisfy the requirements which the user is looking for. This research proposes to integrate a semantic model and a data mining technique to enhance the accuracy of Web service discovery. A novel three-phase Web service discovery methodology has been proposed. The first phase performs match-making to find semantically similar Web services for a user query. In order to perform semantic analysis on the content present in the Web service description language document, the support-based latent semantic kernel is constructed using an innovative concept of binning and merging on the large quantity of text documents covering diverse areas of domain of knowledge. The use of a generic latent semantic kernel constructed with a large number of terms helps to find the hidden meaning of the query terms which otherwise could not be found. Sometimes a single Web service is unable to fully satisfy the requirement of the user. In such cases, a composition of multiple inter-related Web services is presented to the user. The task of checking the possibility of linking multiple Web services is done in the second phase. Once the feasibility of linking Web services is checked, the objective is to provide the user with the best composition of Web services. In the link analysis phase, the Web services are modelled as nodes of a graph and an allpair shortest-path algorithm is applied to find the optimum path at the minimum cost for traversal. The third phase which is the system integration, integrates the results from the preceding two phases by using an original fusion algorithm in the fusion engine. Finally, the recommendation engine which is an integral part of the system integration phase makes the final recommendations including individual and composite Web services to the user. In order to evaluate the performance of the proposed method, extensive experimentation has been performed. Results of the proposed support-based semantic kernel method of Web service discovery are compared with the results of the standard keyword-based information-retrieval method and a clustering-based machine-learning method of Web service discovery. The proposed method outperforms both information-retrieval and machine-learning based methods. Experimental results and statistical analysis also show that the best Web services compositions are obtained by considering 10 to 15 Web services that are found in phase-I for linking. Empirical results also ascertain that the fusion engine boosts the accuracy of Web service discovery by combining the inputs from both the semantic analysis (phase-I) and the link analysis (phase-II) in a systematic fashion. Overall, the accuracy of Web service discovery with the proposed method shows a significant improvement over traditional discovery methods.

Contemporary issues in Australian family law: Do we need a more unified and interventionist judicial model

Recent decisions of the Family Court of Australian reflect concerns over the adversarial nature of the legal process. The processes and procedures of the judicial system militate against a detailed examination of the issues and rights of the parties in dispute. The limitations of the family law framework are particularly demonstrated in disputes over the custody of children where the Court has tended to neglect the rights and interests of the primary carer. An alternative "unified family court" framework will be examined in which the Court pursues a more active and interventionist approach in the determination of family law disputes.

Retrospectivity and the rule of law

This book analyses and refines the arguments for and against retrospective rule making, concluding that there is one really strong argument against it: the expectation that, if an individual's actions are considered by a future court, the legal consequences of that action will be determined by the law that was discoverable at the time the action was performed. This argument, which goes to the heart of the rule of law, is generally determinative. However, in some cases the argument does not run and this book suggests that, in some areas of law, reliance should be actively discouraged by prospective warnings that the law is subject to change.

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.

Using Agents for Mining Maintenance Data while interacting in 3D Objectoriented Virtual Environments

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.

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