956 resultados para Anatomy taxonomy


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This paper contributes to the literature on subjective well-being (SWB) by taking into account different aspects of life, called domains, such as health, financial situation, job, leisure, housing, and environment. We postulate a two-layer model where individual total SWB depends on the different subjective domain satisfactions. A distinction is made between long-term and short-term effects. The individual domain satisfactions depend on objectively measurable variables, such as income. The model is estimated using a large German panel data set.

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Delegation, from the technical point of view, is widely considered as a potential approach in addressing the problem of providing dynamic access control decisions in activities with a high level of collaboration, either within a single security domain or across multiple security domains. Although delegation continues to attract significant attention from the research community, presently, there is no published work that presents a taxonomy of delegation concepts and models. This paper intends to address this gap by presenting a set of taxonomic criteria relevant to the concept of delegation and applies the taxonomy to a selection of significant delegation models published in the literature.

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Delegation, from a technical point of view, is widely considered as a potential approach in addressing the problem of providing dynamic access control decisions in activities with a high level of collaboration, either within a single security domain or across multiple security domains. Although delegation continues to attract significant attention from the research community, presently, there is no published work that presents a taxonomy of delegation concepts and models. This article intends to address this gap by presenting a set of taxonomic criteria relevant to the concept of delegation. This article also applies the taxonomy to a selection of significant delegation models published in the literature.

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Stereo vision is a method of depth perception, in which depth information is inferred from two (or more) images of a scene, taken from different perspectives. Applications of stereo vision include aerial photogrammetry, autonomous vehicle guidance, robotics, industrial automation and stereomicroscopy. A key issue in stereo vision is that of image matching, or identifying corresponding points in a stereo pair. The difference in the positions of corresponding points in image coordinates is termed the parallax or disparity. When the orientation of the two cameras is known, corresponding points may be projected back to find the location of the original object point in world coordinates. Matching techniques are typically categorised according to the nature of the matching primitives they use and the matching strategy they employ. This report provides a detailed taxonomy of image matching techniques, including area based, transform based, feature based, phase based, hybrid, relaxation based, dynamic programming and object space methods. A number of area based matching metrics as well as the rank and census transforms were implemented, in order to investigate their suitability for a real-time stereo sensor for mining automation applications. The requirements of this sensor were speed, robustness, and the ability to produce a dense depth map. The Sum of Absolute Differences matching metric was the least computationally expensive; however, this metric was the most sensitive to radiometric distortion. Metrics such as the Zero Mean Sum of Absolute Differences and Normalised Cross Correlation were the most robust to this type of distortion but introduced additional computational complexity. The rank and census transforms were found to be robust to radiometric distortion, in addition to having low computational complexity. They are therefore prime candidates for a matching algorithm for a stereo sensor for real-time mining applications. A number of issues came to light during this investigation which may merit further work. These include devising a means to evaluate and compare disparity results of different matching algorithms, and finding a method of assigning a level of confidence to a match. Another issue of interest is the possibility of statistically combining the results of different matching algorithms, in order to improve robustness.

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Item folksonomy or tag information is popularly available on the web now. However, since tags are arbitrary words given by users, they contain a lot of noise such as tag synonyms, semantic ambiguities and personal tags. Such noise brings difficulties to improve the accuracy of item recommendations. In this paper, we propose to combine item taxonomy and folksonomy to reduce the noise of tags and make personalized item recommendations. The experiments conducted on the dataset collected from Amazon.com demonstrated the effectiveness of the proposed approaches. The results suggested that the recommendation accuracy can be further improved if we consider the viewpoints and the vocabularies of both experts and users.

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Item folksonomy or tag information is a kind of typical and prevalent web 2.0 information. Item folksonmy contains rich opinion information of users on item classifications and descriptions. It can be used as another important information source to conduct opinion mining. On the other hand, each item is associated with taxonomy information that reflects the viewpoints of experts. In this paper, we propose to mine for users’ opinions on items based on item taxonomy developed by experts and folksonomy contributed by users. In addition, we explore how to make personalized item recommendations based on users’ opinions. The experiments conducted on real word datasets collected from Amazon.com and CiteULike demonstrated the effectiveness of the proposed approaches.

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A survey was completed by 122 case managers describing the types of homework assignments commonly used with individuals diagnosed with severe mental illness (SMI). Homework types were categorized using a 12-item homework description taxonomy and in relation to the 22 domains of the Camberwell Assessment of Need (CAN). Case managers predominately reported using behaviourally based homework tasks such as scheduling activities and the development of personal hygiene skills. Homework focused on CAN areas of need in relation to Company, Psychological Distress, Psychotic Symptoms and Daytime Activities. The applications of the taxonomy for both researchers and case managers are discussed.

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Zero energy buildings (ZEB) and zero energy homes (ZEH) are a current hot topic globally for policy makers (what are the benefits and costs), designers (how do we design them), the construction industry (can we build them), marketing (will consumers buy them) and researchers (do they work and what are the implications). This paper presents initial findings from actual measured data from a 9 star (as built), off-ground detached family home constructed in south-east Queensland in 2008. The integrated systems approach to the design of the house is analysed in each of its three main goals: maximising the thermal performance of the building envelope, minimising energy demand whilst maintaining energy service levels, and implementing a multi-pronged low carbon approach to energy supply. The performance outcomes of each of these stages are evaluated against definitions of Net Zero Carbon / Net Zero Emissions (Site and Source) and Net Zero Energy (onsite generation vs primary energy imports). The paper will conclude with a summary of the multiple benefits of combining very high efficiency building envelopes with diverse energy management strategies: a robustness, resilience, affordability and autonomy not generally seen in housing.

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There is limited understanding about business strategies related to parliamentary government's departments. This study focuses on the strategies of departments of two state governments in Australia. The strategies are derived from department strategic plans available in public domain and collected from respective websites. The results of this research indicate that strategies fall into seven categories: internal, development, political, partnership, environment, reorientation and status quo. The strategies of the departments are mainly internal or development where development strategy is mainly the focus of departments such as transport, and infrastructure. Political strategy is prevalent for departments related to communities, and education and training. Further three layers of strategies are identified as kernel, cluster and individual, which are mapped to the developed taxonomy.

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Conventional rainfall classification for modelling and prediction is quantity based. This approach can lead to inaccuracies in stormwater quality modelling due to the assignment of stochastic pollutant parameters to a rainfall event. A taxonomy for natural rainfall events in the context of stormwater quality is presented based on an in-depth investigation of the influence of rainfall characteristics on stormwater quality. In the research study, the natural rainfall events were classified into three types based on average rainfall intensity and rainfall duration and the classification was found to be independent of the catchment characteristics. The proposed taxonomy provides an innovative concept in stormwater quality modelling and prediction and will contribute to enhancing treatment design for stormwater quality mitigation.

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The 12 to 13 July 2003 andesite lava dome collapse at the Soufrière Hills volcano, Montserrat, provides the first opportunity to document comprehensively both the sub-aerial and submarine sequence of events for an eruption. Numerous pyroclastic flows entered the ocean during the collapse, depositing approximately 90% of the total material into the submarine environment. During peak collapse conditions, as the main flow penetrated the air–ocean interface, phreatic explosions were observed and a surge cloud decoupled from the main flow body to travel 2 to 3 km over the ocean surface before settling. The bulk of the flow was submerged and rapidly mixed with sea water forming a water-saturated mass flow. Efficient sorting and physical differentiation occurred within the flow before initial deposition at 500 m water depth. The coarsest components (∼60% of the total volume) were deposited proximally from a dense granular flow, while the finer components (∼40%) were efficiently elutriated into the overlying part of the flow, which evolved into a far-reaching turbidity current.

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Airports are vital sources of income to a country and city. Airports are often understood from a management perspective, rather than a passenger perspective. As passengers are a vital customer of airports, a passenger perspective can provide a novel approach in understanding and improving the airport experience. This paper focuses on the study of passenger experiences at airports. This research is built on recent investigations of passenger discretionary activities in airports by the authors, which have provided a new perspective on understanding the airport experience. The research reported in this paper involves field studies at three Australian airports. Seventy one people who had impending travel were recruited to take part in the field study. Data collection methods included video-recorded observation and post-travel interviews. Observations were coded and a list of activities performed was developed. These activities were then classified into an activity taxonomy, depending on the activity location and context. The study demonstrates that there is a wide range of activities performed by passengers as they navigate through the airport. The emerging activity taxonomy consists of eight categories. They include: (i) processing (ii) preparatory (iii) consumptive (iv) social (v) entertainment (vi) passive (vii) queuing and (viii) moving. The research provides a novel perspective to understand the experience of passenger at international airports. It has been applied in airports to improve passenger processing and reduce waiting times. The significance of the taxonomy lies in its potential application to airport terminal design and how it can be utilised to understand and improve the passenger experience.

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The social tags in Web 2.0 are becoming another important information source to profile users' interests and preferences to make personalized recommendations. To solve the problem of low information sharing caused by the free-style vocabulary of tags and the long tails of the distribution of tags and items, this paper proposes an approach to integrate the social tags given by users and the item taxonomy with standard vocabulary and hierarchical structure provided by experts to make personalized recommendations. The experimental results show that the proposed approach can effectively improve the information sharing and recommendation accuracy.