348 resultados para INTERRELATIONSHIPS
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The purpose of this paper is to investigate the edge condition between the digital layers and the physical layers of the city and how tangible expressions of the interrelationships between them to create and define new experiences of place, creating hybrid place. To date there has been discussion and investigation into understanding the importance of place, similarly into defining hybrid space. This paper explores principles of place and space to question how they can be applied into defining and proposing the notion of hybrid place in urban environments. The integration of media spaces into architecture provide infrastructure for the development of hybrid place. The physical boundaries of urban spaces become blurred through the integration of media such as computer technologies connecting the physical environment with the digital. Literature and case studies that reflect the current trends of use of technology by people in space and place within urban environments are examined.
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This book provides a general framework for specifying, estimating, and testing time series econometric models. Special emphasis is given to estimation by maximum likelihood, but other methods are also discussed, including quasi-maximum likelihood estimation, generalized method of moments estimation, nonparametric estimation, and estimation by simulation. An important advantage of adopting the principle of maximum likelihood as the unifying framework for the book is that many of the estimators and test statistics proposed in econometrics can be derived within a likelihood framework, thereby providing a coherent vehicle for understanding their properties and interrelationships. In contrast to many existing econometric textbooks, which deal mainly with the theoretical properties of estimators and test statistics through a theorem-proof presentation, this book squarely addresses implementation to provide direct conduits between the theory and applied work.
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The importance of community resilience to natural disasters is being increasingly recognised. This paper presents an approach for the development of surrogate indicators for comprehensive assessment of community resilience, which is crucial in the context of predicted increase in natural disasters resulting from extreme weather events due to climate change. The use of surrogate indicators is advocated because a comprehensive assessment of community resilience across various thematic areas and associated key areas requires the measurement of a large number of resilience indicators which is not always feasible due to time and resource constraints, To overcome this, researchers tend to use secondary data sources, which are easily available but not always reliable. This highlights the need for surrogate indicators that are easy to measure from reliable primary data sources and are adequate to capture the resilience of a community. Firstly, the paper discusses the two approaches for defining and conceptualising community resilience and the need to account for the complex interrelationships between thematic areas, key areas and resilience indicators and their implications for research. Secondly, a comprehensive framework for the assessment of community resilience is proposed and the difficulties associated with the measurement of overall resilience of the community are discussed. Thirdly, the paper explains a two-step approach to develop surrogate indicators highlighting the necessity and challenges associated with it. Finally, the proposed approach is elaborated with a simple example for better understanding.
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1. Expert knowledge continues to gain recognition as a valuable source of information in a wide range of research applications. Despite recent advances in defining expert knowledge, comparatively little attention has been given to how to view expertise as a system of interacting contributory factors, and thereby, to quantify an individual’s expertise. 2. We present a systems approach to describing expertise that accounts for many contributing factors and their interrelationships, and allows quantification of an individual’s expertise. A Bayesian network (BN) was chosen for this purpose. For the purpose of illustration, we focused on taxonomic expertise. The model structure was developed in consultation with professional taxonomists. The relative importance of the factors within the network were determined by a second set of senior taxonomists. This second set of experts (i.e. supra-experts) also provided validation of the model structure. Model performance was then assessed by applying the model to hypothetical career states in the discipline of taxonomy. Hypothetical career states were used to incorporate the greatest possible differences in career states and provide an opportunity to test the model against known inputs. 3. The resulting BN model consisted of 18 primary nodes feeding through one to three higher-order nodes before converging on the target node (Taxonomic Expert). There was strong consistency among node weights provided by the supra-experts for some nodes, but not others. The higher order nodes, “Quality of work” and “Total productivity”, had the greatest weights. Sensitivity analysis indicated that although some factors had stronger influence in the outer nodes of the network, there was relatively equal influence of the factors leading directly into the target node. Despite differences in the node weights provided by our supra-experts, there was remarkably good agreement among assessments of our hypothetical experts that accurately reflected differences we had built into them. 4. This systems approach provides a novel way of assessing the overall level of expertise of individuals, accounting for multiple contributory factors, and their interactions. Our approach is adaptable to other situations where it is desirable to understand components of expertise.
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Digital Human Models (DHM) have been used for over 25 years. They have evolved from simple drawing templates, which are nowadays still used in architecture, to complex and Computer Aided Engineering (CAE) integrated design and analysis tools for various ergonomic tasks. DHM are most frequently used for applications in product design and production planning, with many successful implementations documented. DHM from other domains, as for example computer user interfaces, artificial intelligence, training and education, or the entertainment industry show that there is also an ongoing development towards a comprehensive understanding and holistic modeling of human behavior. While the development of DHM for the game sector has seen significant progress in recent years, advances of DHM in the area of ergonomics have been comparatively modest. As a consequence, we need to question if current DHM systems are fit for the design of future mobile work systems. So far it appears that DHM in Ergonomics are rather limited to some traditional applications. According to Dul et al. (2012), future characteristics of Human Factors and Ergonomics (HFE) can be assigned to six main trends: (1) global change of work systems, (2) cultural diversity, (3) ageing, (4) information and communication technology (ICT), (5) enhanced competiveness and the need for innovation, and; (6) sustainability and corporate social responsibility. Based on a literature review, we systematically investigate the capabilities of current ergonomic DHM systems versus the ‘Future of Ergonomics’ requirements. It is found that DHMs already provide broad functionality in support of trends (1) and (2), and more limited options in regards to trend (3). Today’s DHM provide access to a broad range of national and international databases for correct differentiation and characterization of anthropometry for global populations. Some DHM explicitly address social and cultural modeling of groups of people. In comparison, the trends of growing importance of ICT (4), the need for innovation (5) and sustainability (6) are addressed primarily from a hardware-oriented and engineering perspective and not reflected in DHM. This reflects a persistent separation between hardware design (engineering) and software design (information technology) in the view of DHM – a disconnection which needs to be urgently overcome in the era of software defined user interfaces and mobile devices. The design of a mobile ICT-device is discussed to exemplify the need for a comprehensive future DHM solution. Designing such mobile devices requires an approach that includes organizational aspects as well as technical and cognitive ergonomics. Multiple interrelationships between the different aspects result in a challenging setting for future DHM. In conclusion, the ‘Future of Ergonomics’ pose particular challenges for DHM in regards to the design of mobile work systems, and moreover mobile information access.
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Do you need a practical guide to assessment, curriculum and policy? Are you also looking for a book that is firmly grounded in the theory of this subject? Assessment for Education combines both theory and practice, making it the perfect guide for students, researchers, academics and teachers. This book makes assessment processes transparent for practitioners, and shows how assessment should relate to education. It looks at evidence-informed decision-making and the interrelationships between standards, judgment and moderation practice for improved assessment, teacher quality, schools and systems. The book will provide you with: ' Knowledge about quality assessment and judgement practice ' Understanding of relationships across curriculum, assessment, teaching and learning ' Knowledge of the concept of front-ending assessment based on the learner's needs ' An analysis of practitioner judgement approaches ' Understanding of the conditions under which teacher assessment can be valid ' Principles derived from research of social moderation practices Whether you are studying and researching assessment or working in curriculum and assessment policy, this book will show you how practitioner use of achievement standards can improve learning, equity, social justice and accountability.
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As organizations attempt to become more business process-oriented, existing role descriptions are revised and entire new business process-related roles emerge. A lot of attention is often being paid to the technological aspect of Business Process Management (BPM), but relatively little work has been done concerning the people factor of BPM and the specification of BPM expertise in particular. This study tries to close this gap by proposing a comprehensive BPM expertise model, which consolidates existing theories and related work. This model describes the key attributes characterizing “BPM expertise” and outlines their structure, dynamics, and interrelationships. Understanding BPM expertise is a predecessor to being able to develop and apply it effectively. This is the cornerstone of human capital and talent management in BPM.
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Background. Volitional risky driving behaviours such as drink- and drug-driving (i.e. substance-impaired driving) and speeding contribute to the overrepresentation of young novice drivers in road crash fatalities, and crash risk is greatest during the first year of independent driving in particular. Aims. To explore the: 1) self-reported compliance of drivers with road rules regarding substance-impaired driving and other risky driving behaviours (e.g., speeding, driving while tired), one year after progression from a Learner to a Provisional (intermediate) licence; and 2) interrelationships between substance-impaired driving and other risky driving behaviours (e.g., crashes, offences, and Police avoidance). Methods. Drivers (n = 1,076; 319 males) aged 18-20 years were surveyed regarding their sociodemographics (age, gender) and self-reported driving behaviours including crashes, offences, Police avoidance, and driving intentions. Results. A relatively small proportion of participants reported driving after taking drugs (6.3% of males, 1.3% of females) and drinking alcohol (18.5% of males, 11.8% of females). In comparison, a considerable proportion of participants reported at least occasionally exceeding speed limits (86.7% of novices), and risky behaviours like driving when tired (83.6% of novices). Substance-impaired driving was associated with avoiding Police, speeding, risky driving intentions, and self-reported crashes and offences. Forty-three percent of respondents who drove after taking drugs also reported alcohol-impaired driving. Discussion and Conclusions. Behaviours of concern include drink driving, speeding, novice driving errors such as misjudging the speed of oncoming vehicles, violations of graduated driver licensing passenger restrictions, driving tired, driving faster if in a bad mood, and active punishment avoidance. Given the interrelationships between the risky driving behaviours, a deeper understanding of influential factors is required to inform targeted and general countermeasure implementation and evaluation during this critical driving period. Notwithstanding this, a combination of enforcement, education, and engineering efforts appear necessary to improve the road safety of the young novice driver, and for the drink-driving young novice driver in particular.
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Improved public awareness of the environment and available technologies will continue to highlight the importance of sustainable housing in the coming years. Despite this potential, the majority of new housing development in Australia is still “project homes” with few tangible sustainability measures. Stakeholders tend to have different perceptions and priorities on sustainability. To promote the uptake of sustainable housing products, a study of the critical issues affecting the implementation of sustainable housing is necessary. This research investigates multiple factors that may influence key stakeholders’ decision-making towards sustainable housing adoption. Drawing insights from combined questionnaire and interview studies, 12 critical factors and their interrelationships are identified based on professional views in the Australian housing industry. The mutual influences, or driving force and dependency, of these factors are further investigated via Interpretive Structural Modelling (ISM) to distinguish those requiring prominent and immediate attention. A hierarchical model is developed to help key stakeholders prioritise actions when implementing sustainable housing.
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Drug-dependent individuals commonly report craving, which is an urge to consume a substance to experience pleasure or provide relief. However, the motivation to use drugs is also influenced by the expectancies we hold about drug ingestion. Drug expectancies are among a range of internal and external cues that can elicit craving. Scientific advances in the neurobiology of reward have illuminated individual differences in the neurotransmitter systems involved in associative learning that underpin drug use motivation and expectancies. We have begun to elaborate the interrelationships of these constructs and mechanisms to inform new treatments that incorporate recent models of reward learning.
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It is well known that, for major infrastructure networks such as electricity, gas, railway, road, and urban water networks, disruptions at one point have a knock on effect throughout the network. There is an impressive amount of individual research projects examining the vulnerability of critical infrastructure network. However, there is little understanding of the totality of the contribution made by these projects and their interrelationships. This makes their review a difficult process for both new and existing researchers in the field. To address this issue, a two-step literature review process is used, to provide an overview of the vulnerability of the transportation network in terms of four main themes - research objective, transportation mode, disruption scenario and vulnerability indicator –involving the analysis of related articles from 2001 to 2013. Two limitations of existing research are identified: (1) the limited amount of studies relating to multi-layer transportation network vulnerability analysis, and (2) the lack of evaluation methods to explore the relationship between structure vulnerability and dynamical functional vulnerability. In addition to indicating that more attention needs to be paid to these two aspects in future, the analysis provides a new avenue for the discovery of knowledge, as well as an improved understanding of transportation network vulnerability.
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As Business Process Management (BPM) is evolving and organisations are becoming more process oriented, the need for Expertise in BPM amongst practitioners has increased. Proactively managing Expertise in BPM is essential to unlock the potential of BPM as a management paradigm and competitive advantage. Whilst great attention is being paid by the BPM community to the technological aspects of BPM, relatively little research or work has been done concerning the expertise aspect of BPM. There is a substantial body of knowledge on expertise itself, however there is no common framework in existence at the time of writing, describing the fundamental attributes characterising Expertise in the illustrative context of BPM. There are direct implications of the understanding and characterisation of Expertise in the context of BPM as a key strategic component and success factor of BPM itself, as well as for those involved in BPM. Expertise in the context of BPM needs to be characterised to understand it, and be able to proactively manage it. Given the relative infancy of research into Expertise in the context of BPM, an exploration of the relevance and importance of Expertise in the context of BPM was considered essential, to ensure the study itself was of value to the BPM field. The aims of this research are firstly to address the two research questions 'why is expertise important and relevant in the context of BPM?', and 'how can Expertise in the context of BPM be characterised?', and secondly, the development of a comprehensive and validated A-priori model characterising Expertise in the illustrative context of BPM. The study is theory-guided. It has been undertaken via an extensive literature review across relevant literature domains, and a revelatory case study utilising several methods: informal discussions, an open-ended survey, and participant observation. An a-priori model was then developed which comprised of several Constructs and Sub-constructs, and several overall aspects of Expertise in BPM. This was followed by the conduct of interviews in the validation phase of the revelatory case study. The primary contributions of this study are to the fields of expertise, BPM and research. Contributions to the field of expertise include a comprehensive review of expertise literature in general and synthesised critique on expertise research, characterisation of expertise in an illustrative context as a system, and a comprehensive narrative of the dynamics and interrelationships of the core attributes characterising expertise. Contributions to the field of BPM include firstly, the establishment of the importance of understanding Expertise in the context of BPM, including a comprehensive overview of the role the relevance and importance of Expertise in the context of BPM, through explanation of the effect of Expertise in BPM. Secondly, a model characterising Expertise in the context of BPM, which can be used by BPM practitioners to clearly articulate and illuminate the state of Expertise in BPM in organisations. Contributions to the field of research include an extended view of Systems Theory developed, reflecting the importance of the system context in systems thinking, and a narrative on ontological innovation through the positioning of ontology as a meta-model of Expertise in the context of BPM.
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Vehicle speed is an important attribute for analysing the utility of a transport mode. The speed relationship between multiple modes of transport is of interest to traffic planners and operators. This paper quantifies the relationship between bus speed and average car speed by integrating Bluetooth data and Transit Signal Priority data from the urban network in Brisbane, Australia. The method proposed in this paper is the first of its kind to relate bus speed and average car speed by integrating multi-source traffic data in a corridor-based method. Three transferable regression models relating not-in-service bus, in-service bus during peak periods, and in-service bus during off-peak periods with average car speed are proposed. The models are cross-validated and the interrelationships are significant.
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Dried plant food products are increasing in demand in the consumer market, leading to continuing research to develop better products and processing techniques. Plant materials are porous structures, which undergo large deformations during drying. For any given food material, porosity and other cellular parameters have a direct influence on the level of shrinkage and deformation characteristics during drying, which involve complex mechanisms. In order to better understand such mechanisms and their interrelationships, numerical modelling can be used as a tool. In contrast to conventional grid-based modelling techniques, it is considered that meshfree methods may have a higher potential for modelling large deformations of multiphase problem domains. This work uses a meshfree based microscale plant tissue drying model, which was recently developed by the authors. Here, the effects of porosity have been newly accounted for in the model with the objective of studying porosity development during drying and its influence on shrinkage at the cellular level. For simplicity, only open pores are modelled and in order to investigate the influence of different cellular parameters, both apple and grape tissues were used in the study. The simulation results indicated that the porosity negatively influences shrinkage during drying and the porosity decreases as the moisture content reduces (when open pores are considered). Also, there is a clear difference in the deformations of cells, tissues and pores, which is mainly influenced by the cell wall contraction effects during drying.
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As cities are rapidly developing new interventions against climate change, embedding renewable energy in public spaces is an important strategy. However, most interventions primarily include environmental sustainability while neglecting the social and economic interrelationships of electricity production. Although there is a growing interest in sustainability within environmental design and landscape architecture, public spaces are still awaiting viable energy-conscious design and assessment interventions. The purpose of this paper is to investigate this issue in a renowned public space—Ballast Point Park in Sydney—using a triple bottom line (TBL) case study approach. The emerging factors and relationships of each component of TBL, within the context of public open space, are identified and discussed. With specific focus on renewable energy distribution in and around Ballast Point Park, the paper concludes with a general design framework, which conceptualizes an optimal distribution of onsite electricity produced from renewable sources embedded in public open spaces.