212 resultados para domestic fiction


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The data covers the timing and frequency for composing in the passenger screening process at Melbourne Airport, Victoria. Composing is defined as the process of collecting personal items after the screening process.

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The data covers the timing and frequency for composing in the passenger screening process at Sydney Airport, New South Wales. Composing is defined as the process of collecting personal items after the screening process.

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The data covers the timing and frequency for composing in the passenger screening process at Adelaide Airport, South Australia. Composing is defined as the process of collecting personal items after the screening process.

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The data covers the timing and frequency for passengers walking through the metal detectors as part of the screening process at Melbourne Airport, Victoria.

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The data covers the timing and frequency for passengers walking through the metal detectors as part of the screening process at Sydney Airport, New South Wales.

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The data covers the timing and frequency for passengers walking through the metal detectors as part of the screening process at Adelaide Airport, South Australia.

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The data covers the speed at which passengers walk through Australian domestic airport terminals, based on their group size.

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We present methods for automatically constructing representations of fiction books in a range of modalities: audibly, graphically and as 3D virtual environments. The correspondence between the sequential ordering of events against the order of events presented in the text is used to correctly resolve the dynamic interactions for each representation. Synthesised audio created from the fiction text is used to calibrate the base time-line against which the other forms of media are correctly aligned. The audio stream is based on speech synthesis using the text of the book, and is enhanced using distinct voices for the different characters in a book. Sound effects are included automatically. The graphical representation represents the text (as subtitles), identifies active characters and provides visual feedback of the content of the story. Dynamic virtual environments conform to the constraints implied by the story, and are used as a source of further visual content. These representations are all aligned to a common time-line, and combined using sequencing facilities to provide a multimodal version of the original text.

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This paper describes a strategy for automatically converting fiction text into 3D animations. It assumes the existence of fiction text annotated with avatar, object, setting, transition and relation annotations, and presents a transformation process that converts annotated text into quantified constraint systems, the solutions to which are used in the population of 3D environments. Constraint solutions are valid over temporal intervals, ensuring that consistent dynamic behaviour is produced. A substantial level of automation is achieved, while providing opportunities for creative manual intervention in animation process. The process is demonstrated using annotated examples drawn from popular fiction text that are converted into animation sequences, confirming that the desired results can be achieved with only high-level human direction.

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This paper presents a salience-based technique for the annotation of directly quoted speech from fiction text. In particular, this paper determines to what extent a naïve (without the use of complex machine learning or knowledge-based techniques) scoring technique can be used for the identification of the speaker of speech quotes. The presented technique makes use of a scoring technique, similar to that commonly found in knowledge-poor anaphora resolution research, as well as a set of hand-coded rules for the final identification of the speaker of each quote in the text. Speaker identification is shown to be achieved using three tasks: the identification of a speech-verb associated with a quote with a recall of 94.41%; the identification of the actor associated with a quote with a recall of 88.22%; and the selection of a speaker with an accuracy of 79.40%.

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This paper presents a method for converting unrestricted fiction text into a time-based graphical form. Key concepts extracted from the text are used to formulate constraints describing the interaction of entities in a scene. The solution of these constraints over their respective time intervals provides the trajectories for these entities in a graphical representation.

Three types of entity are extracted from fiction books to describe the scene, namely Avatars, Areas and Objects. We present a novel method for modeling the temporal aspect of a fiction story using multiple time-line representations after which the information extracted regarding entities and time-lines is used to formulate constraints. A constraint solving technique based on interval arithmetic is used to ensure that the behaviour of the entities satisfies the constraints over multiple universally quantified time intervals. This approach is demonstrated by finding solutions to multiple time-based constraints, and represents a new contribution to the field of Text-to-Scene conversion. An example of the automatically produced graphical output is provided in support of our constraint-based conversion scheme.

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This paper presents a hierarchical pattern matching and generalisation technique which is applied to the problem of locating the correct speaker of quoted speech found in fiction books. Patterns from a training set are generalised to create a small number of rules, which can be used to identify items of interest within the text. The pattern matching technique is applied to finding the Speech-Verb, Actor and Speaker of quotes found in ction books. The technique performs well over the training data, resulting in rule-sets many times smaller than the training set, but providing very high accuracy. While the rule-set generalised from one book is less effective when applied to different books than an approach based on hand coded heuristics, performance is comparable when testing on data closely related to the training set.

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Recent advancements in Text-to-Scene research have lead to the development of systems which automatically extract key concepts from the text of a fiction book and generate computer animated movies depicting the story. Extracting such annotations from raw fiction text is a laborious process and so in this work we evaluate appropriate candidates to serve as the basis for the required annotations for generating interactive virtual worlds.

We validate our choice by generating adventure games: inter-active virtual worlds which create a stylized representation of the environment described in the text, populate it with characters related to the story and define game goals related to the plot of the fiction story. Our prototype produces a fully playable game, making use of an existing open-source game engine.

The process is evaluated using user tests in which participants are asked to measure the accuracy with which the game represents the events, characters and goals described in the story. The response indicates that the chosen annotation set is sufficient to define a game that is a plausibly acceptable representation of the text.

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This paper describes a strategy for automatically converting fiction text into 3D animations. It assumes the existence of fiction text annotated with avatar, object, setting, transition and relation annotations, and presents a transformation process that converts annotated text into quantified constraint systems, the solutions to which are used in the population of 3D environments. Constraint solutions are valid over temporal intervals, ensuring that consistent dynamic behaviour is produced. A substantial level of automation is achieved, while providing opportunities for creative manual intervention in animation process. The process is demonstrated using annotated examples drawn from popular fiction text that are converted into animation sequences, confirming that the desired results can be achieved with only highlevel human direction.

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A three stage-treatment of domestic wastewater including anaerobic, anoxic and aerobic phases is employed in this study while a clarifier unit is replaced with a submerged membrane in the aerobic unit. The effects of operational parameters on the performance of a pilot scale submerged membrane bioreactor (SMBR) namely hydraulic retention time (HRT), ratio of return activated sludge (QRS), ratio of internal recycle (QIR), solid retention time (SRT) and dissolved oxygen (DO) are evaluated by simulations, using a hybrid model composed of TUDP model, oxygen transfer model, biofouling model due to extra-cellular polymeric substances (EPS) and turbulent shear model. The results showed that anaerobic HRT of 3 hours, anoxic HRT of 6 hours, QRS of 20% and QIR of 300 % are satisfactory in obtaining a high removal efficiency (>90%) of COD, NH4-N, P04-P as well as a less sludge production. An increase of sludge production causes an increase in EPS, which fouls the membrane surface and increase the cleaning cycle of membrane. Operation of 5MBR system at 2 mg/I of DO and 30 days of SRT can extend the membrane cleaning cycle dramatically. The membrane cleaning cycle however is strongly dependent on the initial and terminal specific fluxes and displays inverse power relationships to those fluxes.