54,838 research outputs found
From Artifacts to Aggregations: Modeling Scientific Life Cycles on the Semantic Web
In the process of scientific research, many information objects are
generated, all of which may remain valuable indefinitely. However, artifacts
such as instrument data and associated calibration information may have little
value in isolation; their meaning is derived from their relationships to each
other. Individual artifacts are best represented as components of a life cycle
that is specific to a scientific research domain or project. Current cataloging
practices do not describe objects at a sufficient level of granularity nor do
they offer the globally persistent identifiers necessary to discover and manage
scholarly products with World Wide Web standards. The Open Archives
Initiative's Object Reuse and Exchange data model (OAI-ORE) meets these
requirements. We demonstrate a conceptual implementation of OAI-ORE to
represent the scientific life cycles of embedded networked sensor applications
in seismology and environmental sciences. By establishing relationships between
publications, data, and contextual research information, we illustrate how to
obtain a richer and more realistic view of scientific practices. That view can
facilitate new forms of scientific research and learning. Our analysis is
framed by studies of scientific practices in a large, multi-disciplinary,
multi-university science and engineering research center, the Center for
Embedded Networked Sensing (CENS).Comment: 28 pages. To appear in the Journal of the American Society for
Information Science and Technology (JASIST
Oceans of Tomorrow sensor interoperability for in-situ ocean monitoring
The Oceans of Tomorrow (OoT) projects,
funded by the European Commissionâs FP7 program, are
developing a new generation of sensors supporting physical,
biogeochemical and biological oceanographic monitoring.
The sensors range from acoustic to optical fluorometers to
labs on a chip. The result is that the outputs are diverse in a
variety of formats and communication methodologies. The
interfaces with platforms such as floats, gliders and cable
observatories are each different. Thus, sensorPeer ReviewedPostprint (author's final draft
Finding Academic Experts on a MultiSensor Approach using Shannon's Entropy
Expert finding is an information retrieval task concerned with the search for
the most knowledgeable people, in some topic, with basis on documents
describing peoples activities. The task involves taking a user query as input
and returning a list of people sorted by their level of expertise regarding the
user query. This paper introduces a novel approach for combining multiple
estimators of expertise based on a multisensor data fusion framework together
with the Dempster-Shafer theory of evidence and Shannon's entropy. More
specifically, we defined three sensors which detect heterogeneous information
derived from the textual contents, from the graph structure of the citation
patterns for the community of experts, and from profile information about the
academic experts. Given the evidences collected, each sensor may define
different candidates as experts and consequently do not agree in a final
ranking decision. To deal with these conflicts, we applied the Dempster-Shafer
theory of evidence combined with Shannon's Entropy formula to fuse this
information and come up with a more accurate and reliable final ranking list.
Experiments made over two datasets of academic publications from the Computer
Science domain attest for the adequacy of the proposed approach over the
traditional state of the art approaches. We also made experiments against
representative supervised state of the art algorithms. Results revealed that
the proposed method achieved a similar performance when compared to these
supervised techniques, confirming the capabilities of the proposed framework
SciRecSys: A Recommendation System for Scientific Publication by Discovering Keyword Relationships
In this work, we propose a new approach for discovering various relationships
among keywords over the scientific publications based on a Markov Chain model.
It is an important problem since keywords are the basic elements for
representing abstract objects such as documents, user profiles, topics and many
things else. Our model is very effective since it combines four important
factors in scientific publications: content, publicity, impact and randomness.
Particularly, a recommendation system (called SciRecSys) has been presented to
support users to efficiently find out relevant articles
From Sensor to Observation Web with Environmental Enablers in the Future Internet
This paper outlines the grand challenges in global sustainability research and the objectives of the FP7 Future Internet PPP program within the Digital Agenda for Europe. Large user communities are generating significant amounts of valuable environmental observations at local and regional scales using the devices and services of the Future Internet. These communitiesâ environmental observations represent a wealth of information which is currently hardly used or used only in isolation and therefore in need of integration with other information sources. Indeed, this very integration will lead to a paradigm shift from a mere Sensor Web to an Observation Web with semantically enriched content emanating from sensors, environmental simulations and citizens. The paper also describes the research challenges to realize the Observation Web and the associated environmental enablers for the Future Internet. Such an environmental enabler could for instance be an electronic sensing device, a web-service application, or even a social networking group affording or facilitating the capability of the Future Internet applications to consume, produce, and use environmental observations in cross-domain applications. The term ?envirofied? Future Internet is coined to describe this overall target that forms a cornerstone of work in the Environmental Usage Area within the Future Internet PPP program. Relevant trends described in the paper are the usage of ubiquitous sensors (anywhere), the provision and generation of information by citizens, and the convergence of real and virtual realities to convey understanding of environmental observations. The paper addresses the technical challenges in the Environmental Usage Area and the need for designing multi-style service oriented architecture. Key topics are the mapping of requirements to capabilities, providing scalability and robustness with implementing context aware information retrieval. Another essential research topic is handling data fusion and model based computation, and the related propagation of information uncertainty. Approaches to security, standardization and harmonization, all essential for sustainable solutions, are summarized from the perspective of the Environmental Usage Area. The paper concludes with an overview of emerging, high impact applications in the environmental areas concerning land ecosystems (biodiversity), air quality (atmospheric conditions) and water ecosystems (marine asset management)
The use of gliders for oceanographic science: the data processing gap
Autonomous gliders represent a step change in the way oceanographic data can be collected and as such they are increasingly seen as valuable tools in the oceanographerâs arsenal. However, their increase in use has left a gap regarding the conversion of the signals that their sensors collect into scientifically useable data.At present the novelty of gliders means that only a few research groups within the UK are capable of processing glider data whilst the wider oceanographic community is often unaware that requesting deployment of a glider by MARS does not mean that they will be provided with fully processed and calibrated data following the deployment. This is not a failing of MARS â it is not in their remit â but it does mean that a solution is needed at the UK community level. The solution is also needed quickly given the rapidly growing glider fleet and requests to use it.To illustrate the far from trivial resources and issues needed to solve this problem at a community level, this document briefly summarises the resources and steps involved in carrying glider data through from collection to final product, for the glider owning research groups within the UK which have the capability.This report does not provide a recommendation on whether such a community facility should be the responsibility of NOC, BODC or MARS but does provide information on possible protocols and available software that could be part of a solution.This report does, however, recommend that, to support the growing use of the MARS gliders, a permanently staffed group is needed as a priority, to provide data processing and calibration necessary to allow the translation of glider missions into high impact scientific publications
The status of textile-based dry EEG electrodes
Electroencephalogram (EEG) is the biopotential recording of electrical signals generated by brain activity. It is useful for monitoring sleep quality and alertness, clinical applications, diagnosis, and treatment of patients with epilepsy, disease of Parkinson and other neurological disorders, as well as continuous monitoring of tiredness/ alertness in the field. We provide a review of textile-based EEG. Most of the developed textile-based EEGs remain on shelves only as published research results due to a limitation of flexibility, stickability, and washability, although the respective authors of the works reported that signals were obtained comparable to standard EEG. In addition, nearly all published works were not quantitatively compared and contrasted with conventional wet electrodes to prove feasibility for the actual application. This scenario would probably continue to give a publication credit, but does not add to the growth of the specific field, unless otherwise new integration approaches and new conductive polymer composites are evolved to make the application of textile-based EEG happen for bio-potential monitoring
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Sensor, Signal, and Imaging Informatics in 2017.
ObjectiveâTo summarize significant contributions to sensor, signal, and imaging informatics literature published in 2017.MethodsâPubMedÂŽ and Web of ScienceÂŽ were searched to identify the scientific publications published in 2017 that addressed sensors, signals, and imaging in medical informatics. Fifteen papers were selected by consensus as candidate best papers. Each candidate article was reviewed by section editors and at least two other external reviewers. The final selection of the four best papers was conducted by the editorial board of the International Medical Informatics Association (IMIA) Yearbook.ResultsâThe selected papers of 2017 demonstrate the important scientific advances in management and analysis of sensor, signal, and imaging information.ConclusionThe growth of signal and imaging data and the increasing power of machine learning techniques have engendered new opportunities for research in medical informatics. This synopsis highlights cutting-edge contributions to the science of Sensor, Signal, and Imaging Informatics
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