892 resultados para Collective memory construction


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Many accidents occur world-wide in the use of construction plant and equipment, and safety training is considered by many to be one of the best approaches to their prevention. However, current safety training methods/tools are unable to provide trainees with the hands-on practice needed. Game technology-based safety training platforms have the potential to overcome this problem in a virtual environment. One such platform is described in this paper - its characteristics are analysed and its possible contribution to safety training identified. This is developed and tested by means of a case study involving three major pieces of construction plant, which successfully demonstrates that the platform can improve the process and performance of the safety training involved in their operation. This research not only presents a new and useful solution to the safety training of construction operations, but illustrates the potential use of advanced technologies in solving construction industry problems in general.

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The goal of this research project is to develop specific BIM objects for temporary construction activities which are fully integrated with object design, construction efficiency and safety parameters. Specifically, the project will deliver modularised electronic scaffolding and formwork objects that will allow designers to easily incorporate them into BIM models to facilitate smarter and safer infrastructure and building construction. This research first identified there is currently a distinct lack of BIM objects for temporary construction works resulting in productivity loss during design and construction, and opportunities for improved consideration of safety standards and practices with the design of scaffolding and formwork. This is particularly relevant in Australia, given the “harmonisation” of OHS legislation across all states and territories from 1 January 2012, meaning that enhancements to Queensland practices will have direct application across Australia. Thus, in conjunction with government and industry partners in Queensland, Australia, the research team developed a strategic three-phase research methodology: (1) the preliminary review phase on industrial scaffolding and formwork practices and BIM implementation; (2) the BIM object development phase with specific safety and productivity functions; and (3) the Queensland-wide workshop phase for product dissemination and training. This paper discusses background review findings, details of the developed methodology, and expected research outcomes and their contributions to the Australian construction industry.

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Data mining techniques extract repeated and useful patterns from a large data set that in turn are utilized to predict the outcome of future events. The main purpose of the research presented in this paper is to investigate data mining strategies and develop an efficient framework for multi-attribute project information analysis to predict the performance of construction projects. The research team first reviewed existing data mining algorithms, applied them to systematically analyze a large project data set collected by the survey, and finally proposed a data-mining-based decision support framework for project performance prediction. To evaluate the potential of the framework, a case study was conducted using data collected from 139 capital projects and analyzed the relationship between use of information technology and project cost performance. The study results showed that the proposed framework has potential to promote fast, easy to use, interpretable, and accurate project data analysis.

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Clients and Design-build (DB) contractors are two key stakeholders in DB projects, and contribute significantly to the successful project performance. This study aims to identify and compare such key competences in the construction market of the PRC. After the survey of available literature and face-to-face interviews, a two-round Delphi questionnaire survey was conducted to identify the key competences of clients and DB contractors in DB projects. Relative importance of these identified competences were ranked and compared. The questionnaire results indicated distinct differences between the key competences of clients and that of contractors. The contractor’s key competences emphasize on DB experience, corporate management capability, building and design expertise, financial capability, enterprise qualification and reputation. While the client’s competences focus on the ability to clearly define the project scope & requirements, financial capacity, contract management ability, adequate staff, effective coordination with DB contractor and similar DB experience. Both clients and DB contractors should clearly understand the competence requirements in DB projects and possess all the necessary competences for the successful outcome of DB projects. The identification of these key competences provides clients and DB contractors with indicators to assess their capabilities before going for the DB option. Furthermore, the comparison of competences for clients and DB contractors will result in better understanding of DB system and improve the communication between these stakeholders.

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IT-supported field data management benefits on-site construction management by improving accessibility to the information and promoting efficient communication between project team members. However, most of on-site safety inspections still heavily rely on subjective judgment and manual reporting processes and thus observers’ experiences often determine the quality of risk identification and control. This study aims to develop a methodology to efficiently retrieve safety-related information so that the safety inspectors can easily access to the relevant site safety information for safer decision making. The proposed methodology consists of three stages: (1) development of a comprehensive safety database which contains information of risk factors, accident types, impact of accidents and safety regulations; (2) identification of relationships among different risk factors based on statistical analysis methods; and (3) user-specified information retrieval using data mining techniques for safety management. This paper presents an overall methodology and preliminary results of the first stage research conducted with 101 accident investigation reports.

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This article is based on an analysis of narratives of 26 offenders with mental health problems living in the United Kingdom. It explores the impact of an ascribed dangerous status and the construction of the self as moral and responsible in response to this label with reference to the literature on denial, deviance disavowal and other “techniques of neutralization” and Goffman's presentation of self. Two dominant strands are identified in relation to the construction of moral self-hood: “Not my fault” and “Good at heart” narratives. “Techniques of neutralization” are widely drawn on, particularly denial of responsibility in the “Not my fault” narratives that seek to explain anti-social behavior with reference to external forces such as a hostile environment inhibiting their ability to control their lives. In contrast, “Good at heart” narratives draw on the essentially good and moral nature of the inner-self. Both are used as evidence of sharing and adhering to moral norms in order to present an acceptable and credible self.