2,435 research outputs found
Mixed reality participants in smart meeting rooms and smart home enviroments
Human–computer interaction requires modeling of the user. A user profile typically contains preferences, interests, characteristics, and interaction behavior. However, in its multimodal interaction with a smart environment the user displays characteristics that show how the user, not necessarily consciously, verbally and nonverbally provides the smart environment with useful input and feedback. Especially in ambient intelligence environments we encounter situations where the environment supports interaction between the environment, smart objects (e.g., mobile robots, smart furniture) and human participants in the environment. Therefore it is useful for the profile to contain a physical representation of the user obtained by multi-modal capturing techniques. We discuss the modeling and simulation of interacting participants in a virtual meeting room, we discuss how remote meeting participants can take part in meeting activities and they have some observations on translating research results to smart home environments
Towards Exascale Scientific Metadata Management
Advances in technology and computing hardware are enabling scientists from
all areas of science to produce massive amounts of data using large-scale
simulations or observational facilities. In this era of data deluge, effective
coordination between the data production and the analysis phases hinges on the
availability of metadata that describe the scientific datasets. Existing
workflow engines have been capturing a limited form of metadata to provide
provenance information about the identity and lineage of the data. However,
much of the data produced by simulations, experiments, and analyses still need
to be annotated manually in an ad hoc manner by domain scientists. Systematic
and transparent acquisition of rich metadata becomes a crucial prerequisite to
sustain and accelerate the pace of scientific innovation. Yet, ubiquitous and
domain-agnostic metadata management infrastructure that can meet the demands of
extreme-scale science is notable by its absence.
To address this gap in scientific data management research and practice, we
present our vision for an integrated approach that (1) automatically captures
and manipulates information-rich metadata while the data is being produced or
analyzed and (2) stores metadata within each dataset to permeate
metadata-oblivious processes and to query metadata through established and
standardized data access interfaces. We motivate the need for the proposed
integrated approach using applications from plasma physics, climate modeling
and neuroscience, and then discuss research challenges and possible solutions
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A survey of simulation techniques in commerce and defence
Despite the developments in Modelling and Simulation (M&S) tools and techniques over the past years, there has been a gap in the M&S research and practice in healthcare on developing a toolkit to assist the modellers and simulation practitioners with selecting an appropriate set of techniques. This study is a preliminary step towards this goal. This paper presents some results from a systematic literature survey on applications of M&S in the commerce and defence domains that could inspire some improvements in the healthcare. Interim results show that in the commercial sector Discrete-Event Simulation (DES) has been the most widely used technique with System Dynamics (SD) in second place. However in the defence sector, SD has gained relatively more attention. SD has been found quite useful for qualitative and soft factors analysis. From both the surveys it becomes clear that there is a growing trend towards using hybrid M&S approaches
SOA-RTDBS: A service oriented architecture (SOA) supporting real time database systems
With the increase of complexity in Real-time Database Systems (RTDBS), the amount of data that needs to be managed has also increased. Adoption of a RTDBS as a tightly integrated part of the SOA development process can give significant benefits with respect to data management. However, the variability of data management requirements in different systems, and its heterogeneity may require a distinct database configuration. We addressed the challenges that face RTDB managers who intend to adopt RTDBS in SOA market; we also introduce a service oriented approach to RTDBS analytics and describe how this is used to measure and to monitor the security system. A SOA approach for generating RTDBS configurations suitable for resource-constrained real-time systems using Service Oriented Architecture tools to assist developers with design and analysis of services of developed or new systems was also explored
Outliagnostics: Visualizing Temporal Discrepancy in Outlying Signatures of Data Entries
This paper presents an approach to analyzing two-dimensional temporal
datasets focusing on identifying observations that are significant in
calculating the outliers of a scatterplot. We also propose a prototype, called
Outliagnostics, to guide users when interactively exploring abnormalities in
large time series. Instead of focusing on detecting outliers at each time
point, we monitor and display the discrepant temporal signatures of each data
entry concerning the overall distributions. Our prototype is designed to handle
these tasks in parallel to improve performance. To highlight the benefits and
performance of our approach, we illustrate and validate the use of
Outliagnostics on real-world datasets of various sizes in different parallelism
configurations. This work also discusses how to extend these ideas to handle
time series with a higher number of dimensions and provides a prototype for
this type of datasets.Comment: in IEEE Visualization in Data Science (IEEE VDS) (2019
Web-Based Visualization of Very Large Scientific Astronomy Imagery
Visualizing and navigating through large astronomy images from a remote
location with current astronomy display tools can be a frustrating experience
in terms of speed and ergonomics, especially on mobile devices. In this paper,
we present a high performance, versatile and robust client-server system for
remote visualization and analysis of extremely large scientific images.
Applications of this work include survey image quality control, interactive
data query and exploration, citizen science, as well as public outreach. The
proposed software is entirely open source and is designed to be generic and
applicable to a variety of datasets. It provides access to floating point data
at terabyte scales, with the ability to precisely adjust image settings in
real-time. The proposed clients are light-weight, platform-independent web
applications built on standard HTML5 web technologies and compatible with both
touch and mouse-based devices. We put the system to the test and assess the
performance of the system and show that a single server can comfortably handle
more than a hundred simultaneous users accessing full precision 32 bit
astronomy data.Comment: Published in Astronomy & Computing. IIPImage server available from
http://iipimage.sourceforge.net . Visiomatic code and demos available from
http://www.visiomatic.org
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