980 resultados para RADIO - PROGRAMAS - RATING
Resumo:
Bangkok Metropolitan Region (BMR) is the centre for various major activities in Thailand including political, industry, agriculture, and commerce. Consequently, the BMR is the highest and most densely populated area in Thailand. Thus, the demand for houses in the BMR is also the largest, especially in subdivision developments. For these reasons, the subdivision development in the BMR has increased substantially in the past 20 years and generated large numbers of subdivision developments (AREA, 2009; Kridakorn Na Ayutthaya & Tochaiwat, 2010). However, this dramatic growth of subdivision development has caused several problems including unsustainable development, especially for subdivision neighbourhoods, in the BMR. There have been rating tools that encourage the sustainability of neighbourhood design in subdivision development, but they still have practical problems. Such rating tools do not cover the scale of the development entirely; and they concentrate more on the social and environmental conservation aspects, which have not been totally accepted by the developers (Boonprakub, 2011; Tongcumpou & Harvey, 1994). These factors strongly confirm the need for an appropriate rating tool for sustainable subdivision neighbourhood design in the BMR. To improve level of acceptance from all stakeholders in subdivision developments industry, the new rating tool should be developed based on an approach that unites the social, environmental, and economic approaches, such as eco-efficiency principle. Eco-efficiency is the sustainability indicator introduced by the World Business Council for Sustainable Development (WBCSD) since 1992. The eco-efficiency is defined as the ratio of the product or service value according to its environmental impact (Lehni & Pepper, 2000; Sorvari et al., 2009). Eco-efficiency indicator is concerned to the business, while simultaneously, is concerned with to social and the environment impact. This study aims to develop a new rating tool named "Rating for sustainable subdivision neighbourhood design (RSSND)". The RSSND methodology is developed by a combination of literature reviews, field surveys, the eco-efficiency model development, trial-and-error technique, and the tool validation process. All required data has been collected by the field surveys from July to November 2010. The ecoefficiency model is a combination of three different mathematical models; the neighbourhood property price (NPP) model, the neighbourhood development cost (NDC) model, and the neighbourhood occupancy cost (NOC) model which are attributable to the neighbourhood subdivision design. The NPP model is formulated by hedonic price model approach, while the NDC model and NOC model are formulated by the multiple regression analysis approach. The trial-and-error technique is adopted for simplifying the complex mathematic eco-efficiency model to a user-friendly rating tool format. Credibility of the RSSND has been validated by using both rated and non-rated of eight subdivisions. It is expected to meet the requirements of all stakeholders which support the social activities of the residents, maintain the environmental condition of the development and surrounding areas, and meet the economic requirements of the developers.
Rating defence major project success : the role of personal attributes and stakeholder relationships
Resumo:
In this paper we develop and test a model of the associations between major project managers' personal attributes and project success in the context of the Australian Defence industry. In our model, emotional intelligence, cognitive flexibility and systemic thinking were hypothesised to relate to project success, mediated by internal and external stakeholder relationships. The model was tested in an online survey with 373 major project managers. Emotional intelligence and cognitive flexibility were found to be related to the development, quality and effectiveness of major project managers' relationships with both internal and external stakeholders; and these in turn were associated with their ratings of project success. Systemic thinking, however, had no relationship with either stakeholder relationships or project success. Additional research is needed to examine the contribution of a wider range of personal attributes to stakeholder relationships and project success, and to assess whether this model is applicable in other industries and types of projects.
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Recent research at the Queensland University of Technology has investigated the structural and thermal behaviour of load bearing Light gauge Steel Frame (LSF) wall systems made of 1.15 mm G500 steel studs and varying plasterboard and insulation configurations (cavity and external insulation) using full scale fire tests. Suitable finite element models of LSF walls were then developed and validated by comparing with test results. In this study, the validated finite element models of LSF wall panels subject to standard fire conditions were used in a detailed parametric study to investigate the effects of important parameters such as steel grade and thickness, plasterboard screw spacing, plasterboard lateral restraint, insulation materials and load ratio on their performance under standard fire conditions. Suitable equations were proposed to predict the time–temperature profiles of LSF wall studs with eight different plasterboard-insulation configurations, and used in the finite element analyses. Finite element parametric studies produced extensive fire performance data for the LSF wall panels in the form of load ratio versus time and critical hot flange (failure) temperature curves for eight wall configurations. This data demonstrated the superior fire performance of externally insulated LSF wall panels made of different steel grades and thicknesses. It also led to the development of a set of equations to predict the important relationship between the load ratio and the critical hot flange temperature of LSF wall studs. Finally this paper proposes a simplified method to predict the fire resistance rating of LSF walls based on the two proposed set of equations for the load ratio–hot flange temperature and the time–temperature relationships.
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Interview with Mr Kaan Ozgun, PhD Candidate at Queensland University of Technology, about clean energy in Australia.
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One of the most important parts of any Bridge Management System (BMS) is the condition assessment and rating of bridges. This paper, introduces a procedure for condition assessment, based on criticality and vulnerability analysis. According to this procedure, new rating equations are developed. The inventory data is used to determine the contribution of different critical factors such as environmental effects, flood, earthquake, wind, and vehicle impacts. The criticality of the components to live load and vulnerability of the components to the above critical factors are identified. Based on the criticality and the vulnerability of the components and criticality of factors, and by using the new rating equations, the condition assessment and the rating of the railway bridges and their components at the network level will be conducted. This method for the first time incorporates structural analysis, available knowledge of risk assessment in structural engineering standards, and the experience of structural engineers in a practical way to enhance the reliability of the condition assessment and rating a network of bridges.
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The construction and operation of infrastructure assets can have significant impact on society and the region. Using a sustainability assessment framework can be an effective means to build sustainability aspects into the design, construction and operation of infrastructure assets. The conventional evaluation processes and procedures for infrastructure projects do not necessarily measure the qualitative/quantitative effectiveness of all aspects of sustainability: environment, social wellbeing and economy. As a result, a few infrastructure sustainability rating schemes have been developed with a view to assess the level of sustainability attained in the infrastructure projects. These include: Infrastructure Sustainability (Australia); CEEQUAL (UK); and Envision (USA). In addition, road sector specific sustainability rating schemes such as Greenroads (USA) and Invest (Australia) have also been developed. These schemes address several aspects of sustainability with varying emphasis (weightings) on areas such as: use of resources; emission, pollution and waste; ecology; people and place; management and governance; and innovation. The attainment of sustainability of an infrastructure project depends largely on addressing the whole-of-life environmental issues. This study has analysed the rating schemes’ coverage of different environmental components for the road infrastructure under the five phases of a project: material, construction, use, maintenance and end-of-life. This is based on a comprehensive life cycle assessment (LCA) system boundary. The findings indicate that there is a need for the schemes to consider key (high impact) life cycle environmental components such as traffic congestion during construction, rolling resistance due to surface roughness and structural stiffness of the pavement, albedo, lighting, and end-of-life management (recycling) to deliver sustainable road projects.
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Smartphone technology provides free or inexpensive access to mental health and wellbeing resources. As a result the use of mobile applications for these purposes has increased significantly in recent years. Yet, there is currently no app quality assessment alternative to the popular ‘star’-ratings, which are often unreliable. This presentation describes the development of the Mobile Application Rating Scale (MARS) a new measure for classifying and rating the quality of mobile applications. A review of existing literature on app and web quality identified 25 published papers, conference proceedings, and online resources (published since 1999), which identified 372 explicit quality criteria. Qualitative analysis identified five broad categories of app quality rating criteria: engagement, functionality, aesthetics, information quality, and overall satisfaction, which were refined into the 23-item MARS. Independent ratings of 50 randomly selected mental health and wellbeing mobile apps indicated the MARS had excellent levels of internal consistency (α = 0.92) and inter-rater reliability (ICC = 0.85). The MARS provides practitioners and researchers with an easy-to-use, simple, objective and reliable tool for assessing mobile app quality. It also provides mHealth professionals with a checklist for the design and development of high quality apps.
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This paper presents the details of research undertaken on the development of an energy based time equivalent approach for light gauge steel frame (LSF) walls. This research utilized an energy based time equivalent approach to obtain the fire resistance ratings (FRR) of LSF walls exposed to realistic design fires with respect to standard fire exposure [1]. It is based on the equal area concept of fire severity and relates to the amount of energy transferred to the member. The proposed method was used to predict the fire resistance of single and double plasterboard lined and externally insulated LSF walls. The predicted fire resistance ratings were compared with the results from finite element analyses and fire design rules for three different wall configurations. This paper presents the review of the available time equivalent approaches and the development of energy based time equivalent approach for the prediction of fire resistance ratings of LSF walls exposed to realistic design fires.
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The charge of an isolated dust grain and ion drag forces on the grain in a collisionless, high-voltage, capacitive rf sheath are studied theoretically. The studies are carried out assuming that the positive ions are monoenergetic, as well as in more realistic approximation, assuming that the time-averaged energy distribution of ions impinging on the dust grain has a double-peaked hollow profile. For the nonmonoenergetic case, an analytical expression for the ion flux to the dust grain is obtained. It is studied how the dust charge and ion drag forces depend on the rf frequency, electron density at plasma-sheath boundary, electron temperature and ratio of the effective oscillation amplitude of rf current to the electron Debye length. It is shown that the dust charge and ion drag forces obtained in the monoenergetic ion approximation may differ from those calculated assuming that the ions are nonmonoenergetic. The difference increases with increasing the width of the ion energy spread in the ion distribution. © 2009 American Institute of Physics.
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Radial and axial distributions of magnetic fields in a low-frequency (∼460 kHz)inductively coupled plasmasource with two internal crossed planar rf current sheets are reported. The internal antenna configuration comprises two orthogonal sets of eight alternately reconnected parallel and equidistant copper litz wires in quartz enclosures and generates three magnetic (H z, H r, and H φ) and two electric (E φ and E r) field components at the fundamental frequency. The measurements have been performed in rarefied and dense plasmas generated in the electrostatic(E) and electromagnetic (H)discharge modes using two miniature magnetic probes. It is shown that the radial uniformity and depth of the rf power deposition can be improved as compared with conventional sources of inductively coupled plasmas with external flat spiral (“pancake”) antennas. Relatively deeper rf power deposition in the plasma source results in more uniform profiles of the optical emission intensity, which indicates on the improvement of the plasma uniformity over large chamber volumes. The results of the numerical modeling of the radial magnetic field profiles are found in a reasonable agreement with the experimental data.
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Many websites offer the opportunity for customers to rate items and then use customers' ratings to generate items reputation, which can be used later by other users for decision making purposes. The aggregated value of the ratings per item represents the reputation of this item. The accuracy of the reputation scores is important as it is used to rank items. Most of the aggregation methods didn't consider the frequency of distinct ratings and they didn't test how accurate their reputation scores over different datasets with different sparsity. In this work we propose a new aggregation method which can be described as a weighted average, where weights are generated using the normal distribution. The evaluation result shows that the proposed method outperforms state-of-the-art methods over different sparsity datasets.
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This thesis developed a condition assessment and rating method to identify those bridges in a network which are in most need of repair for an effective life cycle management. The method estimates the contribution of critical factors towards bridge deterioration and uses structural analysis to overcome the subjectivity of traditional current condition assessment methods. This research was a part of the CRC project titled 'Life Cycle Management of Railway Bridges'. Efficient usage of resources and enhancing the safety and serviceability of railway bridges are the significant outcomes of using the proposed method.
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With the extensive use of rating systems in the web, and their significance in decision making process by users, the need for more accurate aggregation methods has emerged. The Naïve aggregation method, using the simple mean, is not adequate anymore in providing accurate reputation scores for items [6 ], hence, several researches where conducted in order to provide more accurate alternative aggregation methods. Most of the current reputation models do not consider the distribution of ratings across the different possible ratings values. In this paper, we propose a novel reputation model, which generates more accurate reputation scores for items by deploying the normal distribution over ratings. Experiments show promising results for our proposed model over state-of-the-art ones on sparse and dense datasets.
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Background The use of mobile apps for health and well being promotion has grown exponentially in recent years. Yet, there is currently no app-quality assessment tool beyond “star”-ratings. Objective The objective of this study was to develop a reliable, multidimensional measure for trialling, classifying, and rating the quality of mobile health apps. Methods A literature search was conducted to identify articles containing explicit Web or app quality rating criteria published between January 2000 and January 2013. Existing criteria for the assessment of app quality were categorized by an expert panel to develop the new Mobile App Rating Scale (MARS) subscales, items, descriptors, and anchors. There were sixty well being apps that were randomly selected using an iTunes search for MARS rating. There were ten that were used to pilot the rating procedure, and the remaining 50 provided data on interrater reliability. Results There were 372 explicit criteria for assessing Web or app quality that were extracted from 25 published papers, conference proceedings, and Internet resources. There were five broad categories of criteria that were identified including four objective quality scales: engagement, functionality, aesthetics, and information quality; and one subjective quality scale; which were refined into the 23-item MARS. The MARS demonstrated excellent internal consistency (alpha = .90) and interrater reliability intraclass correlation coefficient (ICC = .79). Conclusions The MARS is a simple, objective, and reliable tool for classifying and assessing the quality of mobile health apps. It can also be used to provide a checklist for the design and development of new high quality health apps.