64,395 research outputs found
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Steve McDowell and Phil Race, 500 Computing Tips for Trainers, London: Kogan Page, ISBN: 0–7494–2675–6. Paperback, 160 pages, £15.99
Algorithms as scores: coding live music
The author discusses live coding as a new path in the evolution of the musical score. Live-coding practice accentu- ates the score, and whilst it is the perfect vehicle for the performance of algorithmic music it also transforms the compositional process itself into a live event. As a continuation of 20th-century artistic developments of the musical score, live-coding systems often embrace graphical elements and language syntaxes foreign to standard programming languages. The author presents live coding as a highly technologized artistic practice, shedding light on how non-linearity, play and generativity will become prominent in future creative media productions
Building Knowledge Bases for the Generation of Software Documentation
Automated text generation requires a underlying knowledge base from which to
generate, which is often difficult to produce. Software documentation is one
domain in which parts of this knowledge base may be derived automatically. In
this paper, we describe \drafter, an authoring support tool for generating
user-centred software documentation, and in particular, we describe how parts
of its required knowledge base can be obtained automatically.Comment: 6 pages, from COLING-9
eMoto - Affectively Involving both Body and Mind
It is known that emotions are experienced by both body and mind. Oftentimes, emotions are evoked by sub-symbolic stimuli, such as colors, shapes, gestures, or music. We have built eMoto, a mobile service for sending affective mes-sages to others, with the explicit aim of addressing such sensing. Through combining affective gestures for input with affective expressions that make use of colors, shapes and animations for the background of messages, the interac-tion pulls the user into an embodied ‘affective loop’. We present a user study of eMoto where 12 out of 18 subjects got both physically and emotionally involved in the interac-tion. The study also shows that the designed ‘openness’ and ambiguity of the expressions, was appreciated and under-stood by our subjects
BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models
Background: Quantitative models of biochemical and cellular systems are used to answer a variety of questions in the
biological sciences. The number of published quantitative models is growing steadily thanks to increasing interest in
the use of models as well as the development of improved software systems and the availability of better, cheaper
computer hardware. To maximise the benefits of this growing body of models, the field needs centralised model
repositories that will encourage, facilitate and promote model dissemination and reuse. Ideally, the models stored in
these repositories should be extensively tested and encoded in community-supported and standardised formats. In
addition, the models and their components should be cross-referenced with other resources in order to allow their
unambiguous identification.
Description: BioModels Database http://www.ebi.ac.uk/biomodels/ is aimed at addressing exactly these needs. It is a
freely-accessible online resource for storing, viewing, retrieving, and analysing published, peer-reviewed quantitative
models of biochemical and cellular systems. The structure and behaviour of each simulation model distributed by
BioModels Database are thoroughly checked; in addition, model elements are annotated with terms from controlled
vocabularies as well as linked to relevant data resources. Models can be examined online or downloaded in various
formats. Reaction network diagrams generated from the models are also available in several formats. BioModels
Database also provides features such as online simulation and the extraction of components from large scale models
into smaller submodels. Finally, the system provides a range of web services that external software systems can use to
access up-to-date data from the database.
Conclusions: BioModels Database has become a recognised reference resource for systems biology. It is being used by
the community in a variety of ways; for example, it is used to benchmark different simulation systems, and to study the
clustering of models based upon their annotations. Model deposition to the database today is advised by several
publishers of scientific journals. The models in BioModels Database are freely distributed and reusable; the underlying
software infrastructure is also available from SourceForge https://sourceforge.net/projects/biomodels/ under the GNU
General Public License
Visual exploration and retrieval of XML document collections with the generic system X2
This article reports on the XML retrieval system X2 which has been developed at the University of Munich over the last five years. In a typical session with X2, the user
first browses a structural summary of the XML database in order to select interesting elements and keywords occurring in documents. Using this intermediate result, queries combining structure and textual references are composed semiautomatically.
After query evaluation, the full set of answers is presented in a visual and structured way. X2 largely exploits the structure found in documents, queries and answers to enable new interactive visualization and exploration techniques that support mixed IR and database-oriented querying, thus bridging the gap between these three views on the data to be retrieved. Another salient characteristic of X2 which distinguishes it from other visual query systems for XML is that it supports various degrees of detailedness in the presentation of answers, as well as techniques for dynamically reordering and grouping retrieved elements once the complete answer set has been computed
Dialogue Act Recognition via CRF-Attentive Structured Network
Dialogue Act Recognition (DAR) is a challenging problem in dialogue
interpretation, which aims to attach semantic labels to utterances and
characterize the speaker's intention. Currently, many existing approaches
formulate the DAR problem ranging from multi-classification to structured
prediction, which suffer from handcrafted feature extensions and attentive
contextual structural dependencies. In this paper, we consider the problem of
DAR from the viewpoint of extending richer Conditional Random Field (CRF)
structural dependencies without abandoning end-to-end training. We incorporate
hierarchical semantic inference with memory mechanism on the utterance
modeling. We then extend structured attention network to the linear-chain
conditional random field layer which takes into account both contextual
utterances and corresponding dialogue acts. The extensive experiments on two
major benchmark datasets Switchboard Dialogue Act (SWDA) and Meeting Recorder
Dialogue Act (MRDA) datasets show that our method achieves better performance
than other state-of-the-art solutions to the problem. It is a remarkable fact
that our method is nearly close to the human annotator's performance on SWDA
within 2% gap.Comment: 10 pages, 4figure
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Visualising Discourse Structure in Interactive Documents
In this paper we introduce a method for generating interactive documents which exploits the visual features of hypertext to represent discourse structure. We explore the consistent and principled use of graphics and animation to support navigation and comprehension of non-linear text, where textual discourse markers do not always work effectively
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