1,448 research outputs found
The renormalized stress tensor in Kerr space-time: general results
We derive constraints on the form of the renormalized stress tensor for
states on Kerr space-time based on general physical principles: symmetry, the
conservation equations, the trace anomaly and regularity on (sections of) the
event horizon. This is then applied to the physical vacua of interest. We
introduce the concept of past and future Boulware vacua and discuss the
non-existence of a state empty at both scri- and scri+. By calculating the
stress tensor for the Unruh vacuum at the event horizon and at infinity, we are
able to check our earlier conditions. We also discuss the difficulties of
defining a state equivalent to the Hartle-Hawking vacuum and comment on the
properties of two candidates for this state.Comment: 24 pages, no figures, revtex, minor changes to conclusion
The global rotating scalar field vacuum on anti-de Sitter space-time
We consider the definition of the global vacuum state of a quantum scalar field on n-dimensional antide
Sitter space–time as seen by an observer rotating about the polar axis. Since positive (or negative)
frequency scalar field modes must have positive (or negative) Klein–Gordon norm respectively, we find
that the only sensible choice of positive frequency corresponds to positive frequency as seen by a static
observer. This means that the global rotating vacuum is identical to the global nonrotating vacuum. For
n ≥ 4, if the angular velocity of the rotating observer is smaller than the inverse of the anti-de Sitter
radius of curvature, then modes with positive Klein–Gordon norm also have positive frequency as seen
by the rotating observer. We comment on the implications of this result for the construction of global
rotating thermal states
Scalar field Hadamard renormalisation in AdSn
We outline an analytic method for computing the renormalised vacuum expectation value of the quadratic fluctuations and stress-energy tensor associated with a quantised scalar field propagating on . Explicit results have been obtained using Hadamard renormalisation in the case of a massive neutral scalar field with arbitrary coupling to the curvature, for to inclusive
A descriptive literature review of Recognition of Prior Learning for vocational learners in emergency medical care in South Africa
Radical advances in emergency medical care education in South Africa have resulted in both advancements and suppression. After short-course vocational training, the emergency care provider could seek employment in an emergency service. With the realignment of emergency medical care programmes to the National Qualifications Framework (NQF), these short vocational courses were phased out by 2018. Although necessary for educational advancement, these changes prevented vocationally trained emergency care providers from articulating into higher education without returning to full-time academia. Moreover, despite recognition of prior learning (RPL) policies in higher education, few institutes offering emergency medical care programmes offered this as an access option.
This descriptive literature review aimed to analyse the RPL processes in South Africa and globally. Additionally, insight into RPL candidates” support requirements for postgraduate studies was gained. A systematic search of peer-reviewed journal articles, periodicals, dissertations, and governmental reports from 2000 to 2021 was conducted. Various databases were accessed, including Proquest, EBSCOhost, LearnTechLib, JSTOR, ERIC, Google Scholar, and the Thesis Repository. The lack of literature focusing on the prehospital RPL system in South Africa prompted search expansions into the field of health science internationally. Of the 401 screened sources, 19 met the researcher’s inclusion criteria. Two additional articles were sourced in a repeated search in February 2022. The findings revealed enablers and barriers for RPL students and expanded on their personal and academic transitions. The themes identified through the enablers and barriers can assist in identifying additional support for RPL students during their educational journey. Ultimately, despite vital institutional transitions in RPL processes, intrinsic motivation inspired these students to embrace the challenges they faced, and their process of personal transition and lifelong learning began
On the existence of dyons and dyonic black holes in Einstein-Yang-Mills theory
We study dyonic soliton and black hole solutions of the
Einstein-Yang-Mills equations in asymptotically anti-de Sitter space. We prove
the existence of non-trivial dyonic soliton and black hole solutions in a
neighbourhood of the trivial solution. For these solutions the magnetic gauge
field function has no zeros and we conjecture that at least some of these
non-trivial solutions will be stable. The global existence proof uses local
existence results and a non-linear perturbation argument based on the (Banach
space) implicit function theorem.Comment: 23 pages, 2 figures. Minor revisions; references adde
Understanding temporal rhythms and travel behaviour at destinations: Potential ways to achieve more sustainable travel
This paper analyses the roles played by time in destination-based travel behaviour. It contrasts clock time's linear view of time with fragmented time, instantaneous time, fluid time and flow, time out and the multiple temporalities of tourism experiences. It explores temporal issues in a destination travel context, using qualitative techniques. Data were captured using diary photography, diary-interview method with tourists at a rural destination; their spatial and temporal patterns were captured using a purpose built smartphone app. The analysis revealed three temporal themes influencing travel behaviour: time fluidity; daily and place-related rhythms; and control of time. Three key messages emerge for future sustainable tourist destination-based travel systems. Given the strong desire for temporal fluidity, transport systems should evolve beyond clock-time regimes. Second, temporal forces favour personal modes of transport (car, walk, cycle), especially in rural areas where public transport cannot offer flexibility. Third, the car is personalised and perceived to optimise travel fluidity and speed, but is currently unsustainable. Imaginative initiatives, using new mobile media technology can offer new positive and proactive car travel, utilising spare public and private vehicle capacity. Research is needed to implement mechanisms for individualised space-time scheduling and collective vehicle use strategies. © 2013 Copyright Taylor and Francis Group, LLC
Issues in the Cognition and Representation of Internet Based Public Transport Maps
Spatial content and maps are no longer unusual on the Internet. Public transport operators
have realised that the Internet is currently the most powerful medium for the
dissemination of up-to-date scheduling and timetabling information. Transportation
information is now of vital interest in our daily lives. Journey planning systems are
innovative uses of the WWW providing geospatial information about transportation with
maps and schematic routing diagrams being used in these systems. Transportation maps
are now amongst the most important and influential cartographic works in the world
[Thrower]. A public transport journey planning system ptInfo [Mooney] has been
developed to allow users to plan journeys on public transport systems. The system returns
detailed journey itinerary specifications including interchange points. ptInfo uses digital
maps as its principal means of journey specification and user interaction
Topographic Object Recognition Through Shape
Automatic structuring (feature coding and object recognition) of topographic data, such as that derived from air survey or raster scanning large-scale paper maps, requires the classification of objects such as buildings, roads, rivers, fields and railways. The recognition of objects in computer vision is largely based on the matching of descriptions of shapes. Fourier descriptors, moment invariants, boundary chain coding and scalar descriptors are methods that have been widely used and have been developed to describe shape irrespective of position, orientation and scale. The applicability of the above four methods to topographic shapes is described and their usefulness evaluated.
All methods derive descriptors consisting of a small number of real values from the object's polygonal boundary. Two large corpora representing data sets from Ordnance Survey maps of Purbeck and Plymouth were available. The effectiveness of each description technique was evaluated by using one corpus as a training-set to derive distributions for the values for supervised learning. This was then used to reclassify the objects in both data sets using each individual descriptor to evaluate their effectiveness. No individual descriptor or method produced consistent correct classification.
Various models for the fusion of the classification results from individual descriptors were implemented. These were used to experiment with different combinations of descriptors in order to improve results. Overall results show that Moment Invariants fused with the minfusion rule gave the best performance with the two data sets. Much further work remains to be done as enumerated in the concluding section
Data Fusion for Topographic Object Classification
This paper presents research conducted into the automatic recognition of features and objects on topographic maps (for example, buildings, roads, land parcels etc.) using a selection of shape description methods developed mostly in the field of computer vision. In particular the work here focuses on the proposal and evaluation of fusion techniques (at the decision level of representation) for the classification of topographic data. A set of Ordnance Survey large-scale digital data (1:1250 and 1:2500) was used to evaluate the classification performance of the shape recognition methods used. Each technique proved partially successful in distinguishing classes of objects, however, no one technique provided a general solution to the problem. Further outlined experiments combine these techniques, using a data fusion methodology, on the real-world problem of checking and assigning feature codes in large-scale Ordnance Survey digital data
Using moment invariants for classifying shapes on large scale maps
Automated feature extraction and object recognition are large research areas in the field of image processing and computer vision. Recognition is largely based on the matching of descriptions of shapes. Numerous shapes description techniques have been developed, such as scalar features (dimension, area, number of corners etc.), Fourier descriptors and moment invariants. These techniques numerically describe shapes independent of translation, scale and rotation and can be easily applied to topographical data. The applicability of the moment invariants technique to classify objects on large-scale maps is described. From the test data used, moments are fairly reliable at distinguishing certain classes of topographic object. However, their effectiveness will increase when fused with the results of other techniques
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