703 resultados para turf visual quality
Resumo:
Experience plays an important role in building management. “How often will this asset need repair?” or “How much time is this repair going to take?” are types of questions that project and facility managers face daily in planning activities. Failure or success in developing good schedules, budgets and other project management tasks depend on the project manager's ability to obtain reliable information to be able to answer these types of questions. Young practitioners tend to rely on information that is based on regional averages and provided by publishing companies. This is in contrast to experienced project managers who tend to rely heavily on personal experience. Another aspect of building management is that many practitioners are seeking to improve available scheduling algorithms, estimating spreadsheets and other project management tools. Such “micro-scale” levels of research are important in providing the required tools for the project manager's tasks. However, even with such tools, low quality input information will produce inaccurate schedules and budgets as output. Thus, it is also important to have a broad approach to research at a more “macro-scale.” Recent trends show that the Architectural, Engineering, Construction (AEC) industry is experiencing explosive growth in its capabilities to generate and collect data. There is a great deal of valuable knowledge that can be obtained from the appropriate use of this data and therefore the need has arisen to analyse this increasing amount of available data. Data Mining can be applied as a powerful tool to extract relevant and useful information from this sea of data. Knowledge Discovery in Databases (KDD) and Data Mining (DM) are tools that allow identification of valid, useful, and previously unknown patterns so large amounts of project data may be analysed. These technologies combine techniques from machine learning, artificial intelligence, pattern recognition, statistics, databases, and visualization to automatically extract concepts, interrelationships, and patterns of interest from large databases. The project involves the development of a prototype tool to support facility managers, building owners and designers. This Industry focused report presents the AIMMTM prototype system and documents how and what data mining techniques can be applied, the results of their application and the benefits gained from the system. The AIMMTM system is capable of searching for useful patterns of knowledge and correlations within the existing building maintenance data to support decision making about future maintenance operations. The application of the AIMMTM prototype system on building models and their maintenance data (supplied by industry partners) utilises various data mining algorithms and the maintenance data is analysed using interactive visual tools. The application of the AIMMTM prototype system to help in improving maintenance management and building life cycle includes: (i) data preparation and cleaning, (ii) integrating meaningful domain attributes, (iii) performing extensive data mining experiments in which visual analysis (using stacked histograms), classification and clustering techniques, associative rule mining algorithm such as “Apriori” and (iv) filtering and refining data mining results, including the potential implications of these results for improving maintenance management. Maintenance data of a variety of asset types were selected for demonstration with the aim of discovering meaningful patterns to assist facility managers in strategic planning and provide a knowledge base to help shape future requirements and design briefing. Utilising the prototype system developed here, positive and interesting results regarding patterns and structures of data have been obtained.
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“SOH see significant benefit in digitising its drawings and operation and maintenance manuals. Since SOH do not currently have digital models of the Opera House structure or other components, there is an opportunity for this national case study to promote the application of Digital Facility Modelling using standardized Building Information Models (BIM)”. The digital modelling element of this project examined the potential of building information models for Facility Management focusing on the following areas: • The re-usability of building information for FM purposes • BIM as an Integrated information model for facility management • Extendibility of the BIM to cope with business specific requirements • Commercial facility management software using standardised building information models • The ability to add (organisation specific) intelligence to the model • A roadmap for SOH to adopt BIM for FM The project has established that BIM – building information modelling - is an appropriate and potentially beneficial technology for the storage of integrated building, maintenance and management data for SOH. Based on the attributes of a BIM, several advantages can be envisioned: consistency in the data, intelligence in the model, multiple representations, source of information for intelligent programs and intelligent queries. The IFC – open building exchange standard – specification provides comprehensive support for asset and facility management functions, and offers new management, collaboration and procurement relationships based on sharing of intelligent building data. The major advantages of using an open standard are: information can be read and manipulated by any compliant software, reduced user “lock in” to proprietary solutions, third party software can be the “best of breed” to suit the process and scope at hand, standardised BIM solutions consider the wider implications of information exchange outside the scope of any particular vendor, information can be archived as ASCII files for archival purposes, and data quality can be enhanced as the now single source of users’ information has improved accuracy, correctness, currency, completeness and relevance. SOH current building standards have been successfully drafted for a BIM environment and are confidently expected to be fully developed when BIM is adopted operationally by SOH. There have been remarkably few technical difficulties in converting the House’s existing conventions and standards to the new model based environment. This demonstrates that the IFC model represents world practice for building data representation and management (see Sydney Opera House – FM Exemplar Project Report Number 2005-001-C-3, Open Specification for BIM: Sydney Opera House Case Study). Availability of FM applications based on BIM is in its infancy but focussed systems are already in operation internationally and show excellent prospects for implementation systems at SOH. In addition to the generic benefits of standardised BIM described above, the following FM specific advantages can be expected from this new integrated facilities management environment: faster and more effective processes, controlled whole life costs and environmental data, better customer service, common operational picture for current and strategic planning, visual decision-making and a total ownership cost model. Tests with partial BIM data – provided by several of SOH’s current consultants – show that the creation of a SOH complete model is realistic, but subject to resolution of compliance and detailed functional support by participating software applications. The showcase has demonstrated successfully that IFC based exchange is possible with several common BIM based applications through the creation of a new partial model of the building. Data exchanged has been geometrically accurate (the SOH building structure represents some of the most complex building elements) and supports rich information describing the types of objects, with their properties and relationships.
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This paper reviews the means by which teacher quality has been measured. It considers data sources such as students, peers, experts, and examines the psychometrics and scaleproperties of teacher quality assessment instruments with respect to reliability and validity. A list of items for possible inclusion in an elementary student focussed instrument is considered, together with the potential use of such an instrument in measuring teacher quality.
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This report is for one of the four Tasks of the CRC project ‘Regenerating Construction to Enhance Sustainability’. The report specifically addresses Task 2 ‘Design guidelines for delivering high quality indoor environments’.
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This paper describes the operation of a microgrid that contains a custom power park (CPP). The park may contain an unbalanced and/or nonlinear load and the microgrid may contain many dis-tributed generators (DGs). One of the DGs in the microgrid is used as a compensator to achieve load compensation. A new method is proposed for current reference generation for load compensation, which takes into account the real and reactive power to be supplied by the DG connected to the compensator. The real and reactive power from the DGs and the utility source is tightly regulated assuming that dedicated communication channels are available. Therefore this scheme is most suitable in cases where the loads in CPP and DGs are physically located close to each other. The proposal is validated through extensive simulation studies using EMTDC/PSCAD software package (version 4.2).
Resumo:
The indoor air quality (IAQ) in buildings is currently assessed by measurement of pollutants during building operation for comparison with air quality standards. Current practice at the design stage tries to minimise potential indoor air quality impacts of new building materials and contents by selecting low-emission materials. However low-emission materials are not always available, and even when used the aggregated pollutant concentrations from such materials are generally overlooked. This paper presents an innovative tool for estimating indoor air pollutant concentrations at the design stage, based on emissions over time from large area building materials, furniture and office equipment. The estimator considers volatile organic compounds, formaldehyde and airborne particles from indoor materials and office equipment and the contribution of outdoor urban air pollutants affected by urban location and ventilation system filtration. The estimated pollutants are for a single, fully mixed and ventilated zone in an office building with acceptable levels derived from Australian and international health-based standards. The model acquires its dimensional data for the indoor spaces from a 3D CAD model via IFC files and the emission data from a building products/contents emissions database. This paper describes the underlying approach to estimating indoor air quality and discusses the benefits of such an approach for designers and the occupants of buildings.
Resumo:
The quality of office indoor environments is considered to consist of those factors that impact the occupants according to their health and well-being and (by consequence) their productivity. Indoor Environment Quality (IEQ) can be characterized by four indicators: • Indoor air quality indicators • Thermal comfort indicators • Lighting indicators • Noise indicators. Within each indicator, there are specific metrics that can be utilized in determining an acceptable quality of an indoor environment based on existing knowledge and best practice. Examples of these metrics are: indoor air levels of pollutants or odorants; operative temperature and its control; radiant asymmetry; task lighting; glare; ambient noise. The way in which these metrics impact occupants is not fully understood, especially when multiple metrics may interact in their impacts. It can be estimated that the potential cost of lost productivity from poor IEQ may be much in excess of other operating costs of a building. However, the relative productivity impacts of each of the four indicators is largely unknown. The CRC Project ‘Regenerating Construction to Enhance Sustainability’ has a focus on IEQ impacts before and after building refurbishment. This paper provides an overview of IEQ impacts and criteria and the implementation of a CRC project that is currently researching these factors during the refurbishment of a Melbourne office building. IEQ measurements and their impacts will be reported in a future paper
Resumo:
The quality of office indoor environments is considered to consist of those factors that impact occupants according to their health and well-being and (by consequence) their productivity. Indoor Environment Quality (IEQ) can be characterized by four indicators: • Indoor air quality indicators • Thermal comfort indicators • Lighting indicators • Noise indicators. Within each indicator, there are specific metrics that can be utilized in determining an acceptable quality of an indoor environment based on existing knowledge and best practice. Examples of these metrics are: indoor air levels of pollutants or odorants; operative temperature and its control; radiant asymmetry; task lighting; glare; ambient noise. The way in which these metrics impact occupants is not fully understood, especially when multiple metrics may interact in their impacts. While the potential cost of lost productivity from poor IEQ has been estimated to exceed building operation costs, the level of impact and the relative significance of the above four indicators are largely unknown. However, they are key factors in the sustainable operation or refurbishment of office buildings. This paper presents a methodology for assessing indoor environment quality (IEQ) in office buildings, and indicators with related metrics for high performance and occupant comfort. These are intended for integration into the specification of sustainable office buildings as key factors to ensure a high degree of occupant habitability, without this being impaired by other sustainability factors. The assessment methodology was applied in a case study on IEQ in Australia’s first ‘six star’ sustainable office building, Council House 2 (CH2), located in the centre of Melbourne. The CH2 building was designed and built with specific focus on sustainability and the provision of a high quality indoor environment for occupants. Actual IEQ performance was assessed in this study by field assessment after construction and occupancy. For comparison, the methodology was applied to a 30 year old conventional building adjacent to CH2 which housed the same or similar occupants and activities. The impact of IEQ on occupant productivity will be reported in a separate future paper
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The practice of displaying children's artwork in early childhood classrooms poses a number of questions about the child and his or her visual artwork. This paper focuses on young children’s experiences with the display of their own visual artwork. Following Giorgi's (1985a; 1985b) approach to conducting phenomenological psychological research, 13 children between the ages of 4 and 6 years attending an independent school outside metropolitan Detroit, Michigan (USA) participated in semi-structured interviews as a way of uncovering their lived experiences of seeing their artwork displayed. The study yielded 12 essential themes and from these three key issues and their implications for early childhood art education are explored.
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The field of research training (for students and supervisors) is becoming more heavily regulated by the Federal Government. At the same time, quality improvement imperatives are requiring staff across the University to have better access to information and knowledge about a wider range of activities each year. Within the Creative Industries Faculty at the Queensland University of Technology (QUT), the training provided to academic and research staff is organised differently and individually. This session will involve discussion of the dichotomies found in this differentiated approach to staff training, and begin a search for best practice through interaction and input from the audience.
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The purpose of this study was to examine the impact of pain on functioning across multiple quality of life (QOL) domains among individuals with multiple sclerosis (MS). A total of 219 people were recruited from a regional MS society membership database to serve as the community-based study sample. All participants completed a questionnaire containing items about their demographic and clinical characteristics, validated measures of QOL and MS-related disability, and a question on whether or not they had experienced clinically significant pain in the preceding 2 weeks. Respondents who reported pain then completed an in-person structured pain interview assessing pain characteristics (intensity, quality, location, extent, and duration). Comparisons between participants with and without MS-related pain demonstrated that pain prevalence and intensity were strongly correlated with QOL: physical health, psychological health, level of independence, and global QOL were more likely to be impaired among people with MS when pain was present, and the extent of impairment was associated with the intensity of pain. Moreover, these relationships remained significant even after statistically controlling for multiple demographic and clinical covariates associated with self-reported QOL. These findings suggest that for people with MS, pain is an important source of distress and disability beyond that caused by neurologic impairments.
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To date, automatic recognition of semantic information such as salient objects and mid-level concepts from images is a challenging task. Since real-world objects tend to exist in a context within their environment, the computer vision researchers have increasingly incorporated contextual information for improving object recognition. In this paper, we present a method to build a visual contextual ontology from salient objects descriptions for image annotation. The ontologies include not only partOf/kindOf relations, but also spatial and co-occurrence relations. A two-step image annotation algorithm is also proposed based on ontology relations and probabilistic inference. Different from most of the existing work, we specially exploit how to combine representation of ontology, contextual knowledge and probabilistic inference. The experiments show that image annotation results are improved in the LabelMe dataset.
Resumo:
It is widely acknowledged that “quality of life” (QoL) is an imprecise concept, which is difficult to define (Arnold, 1991; Ball et al., 2000; Bury & Holme, 1993; Byrne & MacLean, 1997; Guse & Masesar, 1999; McDowell & Newell, 1996). McDowell and Newell (1996) described the term as “intuitively familiar” (p.382), suggesting that everyone believes that they know what it means; while, in reality its meaning differs from person to person. Recent years, have seen steadily increasing interest in the study and measurement of QoL related to human services, which reflects greater importance being attached to accountability in its widest sense. Anecdotally, many care staff will indicate that ensuring good QoL for their clients is important to them, but how can we ascertain whether we are achieving positive QoL outcomes, and given the complexities of the concept and its measurement, how can we best incorporate QoL assessment into everyday practice? This chapter will explore the issues of QoL definition and measurement, particularly as they pertain to aged care. It will consider many measurement tool options, and provide advice on how to choose an appropriate instrument for your circumstances. Issues of quality of care and their relationship to QoL will also be considered, and the chapter will conclude with a discussion on the integration of QoL assessment into practice. Because residential aged care constitutes a living environment as well as a care environment, QoL is considered particularly pertinent in this context, and as such, it will provide much of the focus for the chapter
The relationship between clinical outcomes and quality of life for residents of aged care facilities
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Objectives It is widely assumed improving care in residential facilities will improve quality of life (QoL), but little research has explored this relationship. The Clinical Care Indicators (CCI) Tool was developed to fill an existing gap in quality assessment within Australian residential aged care facilities and it was used to explore potential links between clinical outcomes and QoL. Design and Setting Clinical outcome and QoL data were collected within four residential facilities from the same aged care provider. Subjects Subjects were 82 residents of four facilities. Outcome Measures Clinical outcomes were measured using the CCI Tool and QoL data was obtained using the Australian WHOQOL‑100. Results Independent t‑test analyses were calculated to compare individual CCIs with each domain of the WHOQOL‑100, while Pearson’s product moment coefficients (r) were calculated between the total number of problem indicators and QoL scores. Significant results suggested poorer clinical outcomes adversely affected QoL. Social and spiritual QoL were particularly affected by clinical outcomes and poorer status in hydration, falls and depression were most strongly associated with lower QoL scores. Poorer clinical status as a whole was also significantly correlated with poorer QoL. Conclusions Hydration, falls and depression were most often associated with poorer resident QoL and as such appear to be key areas for clinical management in residential aged care. However, poor clinical outcomes overall also adversely affected QoL, which suggests maintaining optimum clinical status through high quality nursing care, would not only be important for resident health but also for enhancing general life quality.