521 research outputs found
Clustering of vacancy defects in high-purity semi-insulating SiC
Positron lifetime spectroscopy was used to study native vacancy defects in
semi-insulating silicon carbide. The material is shown to contain (i) vacancy
clusters consisting of 4--5 missing atoms and (ii) Si vacancy related
negatively charged defects. The total open volume bound to the clusters
anticorrelates with the electrical resistivity both in as-grown and annealed
material. Our results suggest that Si vacancy related complexes compensate
electrically the as-grown material, but migrate to increase the size of the
clusters during annealing, leading to loss of resistivity.Comment: 8 pages, 5 figure
A framework for deriving semantic web services
Web service-based development represents an emerging approach for the development of distributed information systems. Web services have been mainly applied by software practitioners as a means to modularize system functionality that can be offered across a network (e.g., intranet and/or the Internet). Although web services have been
predominantly developed as a technical solution for integrating software systems, there is a more business-oriented aspect that developers and enterprises need to deal with in order to benefit from the full potential of web services in an electronic market. This ‘ignored’ aspect is the representation of the semantics underlying the services themselves as well as the ‘things’ that the services manage. Currently languages like the Web Services Description Language (WSDL) provide the syntactic means to describe web services, but
lack in providing a semantic underpinning. In order to harvest all the benefits of web services technology, a framework has been developed for deriving business semantics from syntactic descriptions of web services. The benefits of such a framework are two-fold. Firstly, the framework provides a way to gradually construct domain ontologies from previously defined technical services. Secondly, the framework enables the
migration of syntactically defined web services toward semantic web services. The study follows a design research approach which (1) identifies the problem area and its relevance from an industrial case study and previous research, (2) develops the
framework as a design artifact and (3) evaluates the application of the framework through a relevant scenario
A Survey of Volunteered Open Geo-Knowledge Bases in the Semantic Web
Over the past decade, rapid advances in web technologies, coupled with
innovative models of spatial data collection and consumption, have generated a
robust growth in geo-referenced information, resulting in spatial information
overload. Increasing 'geographic intelligence' in traditional text-based
information retrieval has become a prominent approach to respond to this issue
and to fulfill users' spatial information needs. Numerous efforts in the
Semantic Geospatial Web, Volunteered Geographic Information (VGI), and the
Linking Open Data initiative have converged in a constellation of open
knowledge bases, freely available online. In this article, we survey these open
knowledge bases, focusing on their geospatial dimension. Particular attention
is devoted to the crucial issue of the quality of geo-knowledge bases, as well
as of crowdsourced data. A new knowledge base, the OpenStreetMap Semantic
Network, is outlined as our contribution to this area. Research directions in
information integration and Geographic Information Retrieval (GIR) are then
reviewed, with a critical discussion of their current limitations and future
prospects
First-principles study of As interstitials in GaAs: Convergence, relaxation, and formation energy
Convergence of density-functional supercell calculations for defect formation
energies, charge transition levels, localized defect state properties, and
defect atomic structure and relaxation is investigated using the arsenic split
interstitial in GaAs as an example. Supercells containing up to 217 atoms and a
variety of {\bf k}-space sampling schemes are considered. It is shown that a
good description of the localized defect state dispersion and charge state
transition levels requires at least a 217-atom supercell, although the defect
structure and atomic relaxations can be well converged in a 65-atom cell.
Formation energies are calculated for the As split interstitial, Ga vacancy,
and As antisite defects in GaAs, taking into account the dependence upon
chemical potential and Fermi energy. It is found that equilibrium
concentrations of As interstitials will be much lower than equilibrium
concentrations of As antisites in As-rich, -type or semi-insulating GaAs.Comment: 10 pages, 5 figure
Models of Star-Planet Magnetic Interaction
Magnetic interactions between a planet and its environment are known to lead
to phenomena such as aurorae and shocks in the solar system. The large number
of close-in exoplanets that were discovered triggered a renewed interest in
magnetic interactions in star-planet systems. Multiple other magnetic effects
were then unveiled, such as planet inflation or heating, planet migration,
planetary material escape, and even modification of the host star properties.
We review here the recent efforts in modelling and understanding magnetic
interactions between stars and planets in the context of compact systems. We
first provide simple estimates of the effects of magnetic interactions and then
detail analytical and numerical models for different representative scenarii.
We finally lay out a series of future developments that are needed today to
better understand and constrain these fascinating interactions.Comment: 23 pages, 10 figures, accepted as a chapter in the Handbook of
Exoplanet
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Bias in data-driven artificial intelligence systems - An introductory survey
Artificial Intelligence (AI)-based systems are widely employed nowadays to make decisions that have far-reaching impact on individuals and society. Their decisions might affect everyone, everywhere, and anytime, entailing concerns about potential human rights issues. Therefore, it is necessary to move beyond traditional AI algorithms optimized for predictive performance and embed ethical and legal principles in their design, training, and deployment to ensure social good while still benefiting from the huge potential of the AI technology. The goal of this survey is to provide a broad multidisciplinary overview of the area of bias in AI systems, focusing on technical challenges and solutions as well as to suggest new research directions towards approaches well-grounded in a legal frame. In this survey, we focus on data-driven AI, as a large part of AI is powered nowadays by (big) data and powerful machine learning algorithms. If otherwise not specified, we use the general term bias to describe problems related to the gathering or processing of data that might result in prejudiced decisions on the bases of demographic features such as race, sex, and so forth. This article is categorized under: Commercial, Legal, and Ethical Issues > Fairness in Data Mining Commercial, Legal, and Ethical Issues > Ethical Considerations Commercial, Legal, and Ethical Issues > Legal Issues
Bias in data-driven artificial intelligence systems—An introductory survey
Artificial Intelligence (AI)-based systems are widely employed nowadays to make decisions that have far-reaching impact on individuals and society. Their decisions might affect everyone, everywhere, and anytime, entailing concerns about potential human rights issues. Therefore, it is necessary to move beyond traditional AI algorithms optimized for predictive performance and embed ethical and legal principles in their design, training, and deployment to ensure social good while still benefiting from the huge potential of the AI technology. The goal of this survey is to provide a broad multidisciplinary overview of the area of bias in AI systems, focusing on technical challenges and solutions as well as to suggest new research directions towards approaches well-grounded in a legal frame. In this survey, we focus on data-driven AI, as a large part of AI is powered nowadays by (big) data and powerful machine learning algorithms. If otherwise not specified, we use the general term bias to describe problems related to the gathering or processing of data that might result in prejudiced decisions on the bases of demographic features such as race, sex, and so forth. This article is categorized under: Commercial, Legal, and Ethical Issues > Fairness in Data Mining Commercial, Legal, and Ethical Issues > Ethical Considerations Commercial, Legal, and Ethical Issues > Legal Issues
Microbial Spy Games and Host Response: Roles of a Pseudomonas aeruginosa Small Molecule in Communication with Other Species
Influence of defects on the lattice constant of GaMnAs
We study the influence of main compensating defects: As antisites and Mn
interstitials, known to occur in GaMnAs ferromagnetic semiconductor, on its
structural properties. Our experimental results show that there is a balance
between Mn interstitial and As antisite defects, leading to the reduced density
of one type of defect upon increased density of another defect. The significant
differences in the lattice parameters of GaMnAs with the different balance
between these two types of defects were observed. The annealing induced
reduction of GaMnAs lattice constant is inhibited in the samples with large
density of As antisites.Comment: 17 pages, 4 figure
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