997 resultados para intelligent building


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Students experience university as peers. Peer-to-peer interaction offers unique opportunities for fostering the academic, social and emotional wellbeing of students (Kuh, 2008). Peer programs provide a formalisation of this relationship enabling students to partake both as peer leaders and program participants. The success of such programs is reliant on the university having a reserve of motivated and trained peer leaders. From their initial experience of peer programs as participants in first year and their ongoing involvement as peer leaders, students grow their graduate capabilities and employability skills through scaffolded peer leadership and training opportunities. Universities aspire to produce graduates who are inspirational leaders, effective collaborators and competent professionals ready to participate in the global community (DEEWR, 2012; Shook & Keup, 2012). This poster describes a model which scaffolds the development of peer leaders’ graduate capabilities using a university-wide supporting framework to grow a range of peer-to-peer initiatives across a variety of coordinated peer programs underpinned by a social justice framework (Gidley, Hampson, Wheller & Bereded-Samuel, 2010; Nelson & Creagh, 2012).

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In the era of global knowledge economy, urban regions that are seeking to increase their competitive edge, become destinations for talent and investment, and provide prosperity and quality of life to their inhabitants have little chance achieving their development goals without forming effective knowledge-based urban development strategies. This paper aims to shed light on the planning and development of the knowledge-based urban development phenomenon with respect to the construction of knowledge community precincts aimed at building contemporary urban spaces of knowledge and innovation. Following to a thorough review of the literature on knowledge-based urban development, the paper undertakes policy and best practice analyses to learn from the internationally renowned Australian knowledge community precincts, from Sydney, Melbourne and Brisbane, to better understand the dynamics of knowledge community precinct development practices. The paper provides a discussion on the study findings and recommendations for successfully establishing contemporary urban spaces of knowledge and innovation.

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As buildings have become more advanced and complex, our ability to understand how they are operated and managed has diminished. Modern technologies have given us systems to look after us but it appears to have taken away our say in how we like our environment to be managed. The aim of this paper is to discuss our research concerning spaces that are sensitive to changing needs and allow building-users to have a certain level of freedom to understand and control their environment. We discuss why, what we call the Active Layer, is needed in modern buildings; how building inhabitants are to interact with it; and the development of interface prototypes to test consequences of having the Active Layer in our environment.

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This thesis investigated the viability of using Frequency Response Functions in combination with Artificial Neural Network technique in damage assessment of building structures. The proposed approach can help overcome some of limitations associated with previously developed vibration based methods and assist in delivering more accurate and robust damage identification results. Excellent results are obtained for damage identification of the case studies proving that the proposed approach has been developed successfully.

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Teaching introductory programming has challenged educators through the years. Although Intelligent Tutoring Systems that teach programming have been developed to try to reduce the problem, none have been developed to teach web programming. This paper describes the design and evaluation of the PHP Intelligent Tutoring System (PHP ITS) which addresses this problem. The evaluation process showed that students who used the PHP ITS showed a significant improvement in test scores

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The reliability analysis is crucial to reducing unexpected down time, severe failures and ever tightened maintenance budget of engineering assets. Hazard based reliability methods are of particular interest as hazard reflects the current health status of engineering assets and their imminent failure risks. Most existing hazard models were constructed using the statistical methods. However, these methods were established largely based on two assumptions: one is the assumption of baseline failure distributions being accurate to the population concerned and the other is the assumption of effects of covariates on hazards. These two assumptions may be difficult to achieve and therefore compromise the effectiveness of hazard models in the application. To address this issue, a non-linear hazard modelling approach is developed in this research using neural networks (NNs), resulting in neural network hazard models (NNHMs), to deal with limitations due to the two assumptions for statistical models. With the success of failure prevention effort, less failure history becomes available for reliability analysis. Involving condition data or covariates is a natural solution to this challenge. A critical issue for involving covariates in reliability analysis is that complete and consistent covariate data are often unavailable in reality due to inconsistent measuring frequencies of multiple covariates, sensor failure, and sparse intrusive measurements. This problem has not been studied adequately in current reliability applications. This research thus investigates such incomplete covariates problem in reliability analysis. Typical approaches to handling incomplete covariates have been studied to investigate their performance and effects on the reliability analysis results. Since these existing approaches could underestimate the variance in regressions and introduce extra uncertainties to reliability analysis, the developed NNHMs are extended to include handling incomplete covariates as an integral part. The extended versions of NNHMs have been validated using simulated bearing data and real data from a liquefied natural gas pump. The results demonstrate the new approach outperforms the typical incomplete covariates handling approaches. Another problem in reliability analysis is that future covariates of engineering assets are generally unavailable. In existing practices for multi-step reliability analysis, historical covariates were used to estimate the future covariates. Covariates of engineering assets, however, are often subject to substantial fluctuation due to the influence of both engineering degradation and changes in environmental settings. The commonly used covariate extrapolation methods thus would not be suitable because of the error accumulation and uncertainty propagation. To overcome this difficulty, instead of directly extrapolating covariate values, projection of covariate states is conducted in this research. The estimated covariate states and unknown covariate values in future running steps of assets constitute an incomplete covariate set which is then analysed by the extended NNHMs. A new assessment function is also proposed to evaluate risks of underestimated and overestimated reliability analysis results. A case study using field data from a paper and pulp mill has been conducted and it demonstrates that this new multi-step reliability analysis procedure is able to generate more accurate analysis results.

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Trust is widely recognised as one of the key qualities that a successful leader needs to bring about change within their organization. Browning’s study aimed to identify practices which a school leader can effectively use to inspire, build, and maintain trust between themselves, their staff and Chair of governing body. The study was undertaken in two phases. Phase One was the identification of four highly trusted transformational leaders from the Australian independent schooling sector. Phase Two was a multicase study of the four school leaders. The findings provide practical advice for school leaders wishing to have a positive impact on the outcomes of the students in their school.

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This paper discusses computer mediated distance learning on a Master's level course in the UK and student perceptions of this as a quality learning environment.

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Amongst the current reforms in early childhood in Australia is the requirement for four year university degree-qualified teachers to be employed to provide a kindergarten program for four-year-old children in the year prior to school entry. The possibility for long day care to provide a funded kindergarten program, with an early childhood teacher (ECT) presents a change for the field. With this change come challenges, though also opportunities to think in new and different ways about what long day care and working in long day care might look like.

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Purpose A knowledge-based urban development needs to be sustainable and, therefore, requires ecological planning strategies to ensure a better quality of its services. The purpose of this paper is to present an innovative approach for monitoring the sustainability of urban services and help the policy-making authorities to revise the current planning and development practices for more effective solutions. The paper introduces a new assessment tool–Micro-level Urban-ecosystem Sustainability IndeX (MUSIX) – that provides a quantitative measure of urban sustainability in a local context. Design/methodology/approach A multi-method research approach was employed in the construction of the MUSIX. A qualitative research was conducted through an interpretive and critical literature review in developing a theoretical framework and indicator selection. A quantitative research was conducted through statistical and spatial analyses in data collection, processing and model application. Findings/results MUSIX was tested in a pilot study site and provided information referring to the main environmental impacts arising from rapid urban development and population growth. Related to that, some key ecological planning strategies were recommended to guide the preparation and assessment of development and local area plans. Research limitations/implications This study provided fundamental information that assists developers, planners and policy-makers to investigate the multidimensional nature of sustainability at the local level by capturing the environmental pressures and their driving forces in highly developed urban areas. Originality/value This study measures the sustainability of urban development plans through providing data analysis and interpretation of results in a new spatial data unit.

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For construction stakeholders to fully embrace sustainability, its long-term benefits and associated risks need to be identified through holistic approaches. Consensus among key stakeholders is very important to the improvement of the ecological performance of industrialized building systems (IBS), a building construction method gaining momentum in Malaysia. A questionnaire survey examines the relative significance of 16 potentially important sustainability factors for IBS applications. To present possible solutions,semi-structured interviews solicit views from experienced IBS practitioners, representing the professions involved. Three most critical factors agreed by key stakeholders are material consumption, waste generation and waste disposal. Using SWOT analysis, the positive and negative aspects of these factors are investigated, with action plans formulated for IBS design practitioners. The SWOT analysis based guidelines have the potential to become part of IBS design briefing documents against which sustainability solutions are contemplated, selected and implemented. Existing knowledge on ecological performance issues is extended by considering the unique characteristics of IBS and identifying not only the benefits, but also the potential risks and challenges of pursuing sustainability. This is largely missing in previous research efforts. Findings to date focus on providing much-needed assistance to IBS designers, who are at the forefront of decision-making with a significant level of project influence. Ongoing work will be directed towards other project development phases and consider the inherent linkage between design decisions and subsequent sustainability deliverables in the project life cycle.

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Collisions between pedestrians and vehicles continue to be a major problem throughout the world. Pedestrians trying to cross roads and railway tracks without any caution are often highly susceptible to collisions with vehicles and trains. Continuous financial, human and other losses have prompted transport related organizations to come up with various solutions addressing this issue. However, the quest for new and significant improvements in this area is still ongoing. This work addresses this issue by building a general framework using computer vision techniques to automatically monitor pedestrian movements in such high-risk areas to enable better analysis of activity, and the creation of future alerting strategies. As a result of rapid development in the electronics and semi-conductor industry there is extensive deployment of CCTV cameras in public places to capture video footage. This footage can then be used to analyse crowd activities in those particular places. This work seeks to identify the abnormal behaviour of individuals in video footage. In this work we propose using a Semi-2D Hidden Markov Model (HMM), Full-2D HMM and Spatial HMM to model the normal activities of people. The outliers of the model (i.e. those observations with insufficient likelihood) are identified as abnormal activities. Location features, flow features and optical flow textures are used as the features for the model. The proposed approaches are evaluated using the publicly available UCSD datasets, and we demonstrate improved performance using a Semi-2D Hidden Markov Model compared to other state of the art methods. Further we illustrate how our proposed methods can be applied to detect anomalous events at rail level crossings.

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Within-building spatial variability of indoor air quality may influence substantially the reliability of human exposure assessments based on single point samples, but have hitherto been little studied. To investigate and understand the within-building spatial variation of air pollutants, field measurements were conducted in a 7 level office building in Brisbane, Australia. The building consists of 3 sections (A side, Meddler and B side).

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Industrialised building (IB) is considered by many to have an important role to play in China's residential construction industry due to its potential for improved quality, productivity, efficiency, safety and sustainability. It is surprising, therefore, that although a large number of construction programmes have been completed in the country in recent years, very few have been built in this manner. Quite why this situation exists is unknown. The well-known problems with IB, such as the constraints placed on designer freedom, may be the cause. It is equally possible that, as is typical with developing countries such as China, cost or government issues dominate. On the other hand, in comparison with other countries, the construction industry in China has been widely criticised for its lack of modernity. Either way, there is an urgent need to assess and understand the hindrances to the adoption of IB in residential construction in order to identify what corrective measures, if any, need to be taken. Towards this end, we first identify a set of critical factors (CFs) for assessing the hindrances to IB adoption in China. This involves the analysis of research data collected by a questionnaire survey of experienced housing developers and professionals working in China's construction industry sector. Fuzzy set theory is used in the selection of the CFs. These CFs comprise, in rank order: higher initial cost; lack of skilled labour in IB; manufacturing capability and involvement issues and product quality problems; lack of supply chain; lack of codes and standards; and lack of government incentives, directives and promotion. The establishment of the CFs provides a basis for local construction sectors to better equip themselves for future implementation of IB. The findings also indicate a current need for formulating improved policies and strategies to encourage the further development of IB in China at present.

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This thesis investigates the possibility of using an adaptive tutoring system for beginning programming students. The work involved, designing, developing and evaluating such a system and showing that it was effective in increasing the students’ test scores. In doing so, Artificial Intelligence techniques were used to analyse PHP programs written by students and to provide feedback based on any specific errors made by them. Methods were also included to provide students with the next best exercise to suit their particular level of knowledge.