62 research outputs found
A European research roadmap for optimizing societal impact of big data on environment and energy efficiency
We present a roadmap to guide European research efforts towards a socially
responsible big data economy that maximizes the positive impact of big data in
environment and energy efficiency. The goal of the roadmap is to allow
stakeholders and the big data community to identify and meet big data
challenges, and to proceed with a shared understanding of the societal impact,
positive and negative externalities, and concrete problems worth investigating.
It builds upon a case study focused on the impact of big data practices in the
context of Earth Observation that reveals both positive and negative effects in
the areas of economy, society and ethics, legal frameworks and political
issues. The roadmap identifies European technical and non-technical priorities
in research and innovation to be addressed in the upcoming five years in order
to deliver societal impact, develop skills and contribute to standardization.Comment: 6 pages, 2 figures, 1 tabl
Towards an Automated Semantic Data-driven Decision Making Employing Human Brain
[EN] Decision making is time-consuming and costly, as it requires direct intensive
involvement of the human brain. The variety of expertise of highly qualified
experts is very high, and the available experts are mostly not available on a
short notice: they might be physically remotely located, and/or not being able
to address all the problems they could address time-wise. Further, people
tend to base more of their intellectual labour on rapidly increasing volumes
of online data, content and computing resources, and the lack of
corresponding scaling in availability of the human brain resources poses a
bottleneck in the intellectual labour. We discuss enabling direct
interoperability between the Internet and the human brain, developing
"Internet of Brains", similar to "Internet of Things", where one can
semantically model, interoperate and control real life objects. The Web,
"Internet of Things" and "Internet of Brains" will be connected employing the
same kind of semantic structures, and work in interoperation. Applying Brain
Computer Interfaces (BCIs), psychology and behavioural science, we discuss
the feasibility of a possible decion making infrastructure for semantic
transfer of human thoughts, thinking processes, communication directly to
the InternetThis work has been partially funded by project DALICC, supported by the Austrian Research Promotion Agency (FFG) within the program “Future ICT”.Fensel, A. (2018). Towards an Automated Semantic Data-driven Decision Making Employing Human Brain. En 2nd International Conference on Advanced Reserach Methods and Analytics (CARMA 2018). Editorial Universitat Politècnica de València. 167-175. https://doi.org/10.4995/CARMA2018.2018.8338OCS16717
Enabling customers engagement and collaboration for small and medium-sized enterprises in ubiquitous multi-channel ecosystems
Over the last few years, we have encountered an exponential growth in online communication opportunities. Organizations have more and more ways to connect and engage with their current or future customers. The existence of more opportunities in connecting to people can be both an enabler and a burden. Being present at a multitude of different channels requires the effective management of a very large number of adapted contents, formats, and interaction patterns fulfilling the communication and cooperation needs of distributed target groups. In this respect, we integrate existing fragmented communication and monitoring approaches into a full-fledged communication model as a basis for an adequate engagement approach. We describe applications of our approach in both the eTourism and manufacturing domain. In this paper, we introduce an approach that will enable communication, collaboration and value exchange of users through a multitude of online interaction possibilities based on the use of semantic technology. Finally, we also compare our approach with existing solutions with respect to the identified challenges in this subject.European Union (UE) EU FP7 284860 (MSEE
KGTN-ens: Few-Shot Image Classification with Knowledge Graph Ensembles
We propose KGTN-ens, a framework extending the recent Knowledge Graph
Transfer Network (KGTN) in order to incorporate multiple knowledge graph
embeddings at a small cost. We evaluate it with different combinations of
embeddings in a few-shot image classification task. We also construct a new
knowledge source - Wikidata embeddings - and evaluate it with KGTN and
KGTN-ens. Our approach outperforms KGTN in terms of the top-5 accuracy on the
ImageNet-FS dataset for the majority of tested settings
Towards Semantic APIs for Research Data Services
Die schnelle Entwicklung der Internet- und Web-Technologie verändert den Stand der Technik in der Kommunikation von Wissen oder Forschungsergebnissen. Insbesondere werden semantische Technologien, verknüpfte und offene Daten zu entscheidenden Faktoren für einen erfolgreichen und effizienten Forschungsfortschritt. Zuerst definiere ich den Research Data Service (RDS) und diskutiere typische aktuelle und mögliche zukünftige Nutzungsszenarien mit RDS. Darüber hinaus bespreche ich den Stand der Technik in den Bereichen semantische Dienstleistung und Datenanmerkung und API-Konstruktion sowie infrastrukturelle Lösungen, die für die RDS-Realisierung anwendbar sind. Zum Schluss werden noch innovative Methoden der Online-Verbreitung, Förderung und effizienten Kommunikation der Forschung diskutiert.Rapid development of Internet and Web technology is changing the state of the art in communication of knowledge, or results of research activities. Particularly, Semantic technology, linked and open data become key enablers for successful and efficient progress in research. At first, I define the research data service (RDS) and discuss typical current and possible future usage scenarios involving RDS. Further, I discuss the state of the art in the areas of semantic service and data annotation and API construction, as well as infrastructural solutions, applicable for RDS realisation. At last, innovative methods of online dissemination, promotion and efficient communication of research are discussed
Hotel Websites, Web 2.0, Web 3.0 and Online Direct Marketing: The Case of Austria
Abstract Direct communication with customers in order to increase sales has become one of the most important marketing methods used by small, medium and large hotels alike. With the rapid development of ICT technologies, including the Internet, Web, and recently Web 2.0 and 3.0, the number of channels in which hotels can interact directly with customers has grown even larger. Being visible on all these channels and using these technologies has now become a requirement if effective marketing and massive direct sales are to be achieved. In this chapter, we perform a rigorous empirical analysis of the advances towards the employment of Web 2.0 and 3.0 technologies in the tourism domain. We begin by presenting our methodology, including criteria and evaluation metrics, and follow by analysing the uptake of Web 2.0 and 3.0 technologies for Austrian hotels. As this chapter demonstrates, despite the benefits of new Web technology for online marketing, the hotels in Austria are not using these technologies and do not follow the online developments. Since employing their use is a relatively cheap undertaking, a severe competence gap seems to emerge either directly in the touristic service industry, or in the industry providing them with their on-line presence
Polite Teacher: Semi-Supervised Instance Segmentation with Mutual Learning and Pseudo-Label Thresholding
We present Polite Teacher, a simple yet effective method for the task of
semi-supervised instance segmentation. The proposed architecture relies on the
Teacher-Student mutual learning framework. To filter out noisy pseudo-labels,
we use confidence thresholding for bounding boxes and mask scoring for masks.
The approach has been tested with CenterMask, a single-stage anchor-free
detector. Tested on the COCO 2017 val dataset, our architecture significantly
(approx. +8 pp. in mask AP) outperforms the baseline at different supervision
regimes. To the best of our knowledge, this is one of the first works tackling
the problem of semi-supervised instance segmentation and the first one devoted
to an anchor-free detector
Enabling Scalable Multi-channel Communication through Semantic Technologies
With the advance of the Web in the direction Social
Media the number of communication possibilities has
exponentially increased bringing new challenges and
opportunities for companies to build and shape their
reputation online as well as to engage and maintain the
relationships to their customers. In this paper we describe how
semantic technologies enable scalable, effective and efficient
on-line communication. We illustrate four different ways in
which semantics can be used for this purpose. First, we discuss
semantic analysis of communication items based on 'classical'
semantic, such as natural language processing. Second, we look
at semantics as a channel, viewing Linked Open Data
vocabularies not only as terminological assets but as
communication channels. Third, semantics provide the
methodologies and tools for content modeling by means of
ontologies. Finally, semantics through semantic matchmaking
enable semi-automatic assignment and distribution of content
to channels and vice-versa
Data Aggregation, Fusion and Recommendations for Strengthening Citizens Energy-aware Behavioural Profiles
In this paper, ENTROPY platform, an IT ecosystem for supporting energy
efficiency in buildings through behavioural change of the occupants is
provided. The ENTROPY platform targets at providing a set of mechanisms for
accelerating the adoption of energy efficient practices through the increase of
the energy awareness and energy saving potential of the occupants. The platform
takes advantage of novel sensor networking technologies for supporting
efficient sensor data aggregation mechanisms, semantic web technologies for
unified data representation, machine learning mechanisms for getting insights
from the available data and recommendation mechanisms for providing
personalised content to end users. These technologies are combined and provided
through an integrated platform, targeting at leading to occupants' behavioural
change with regards to their energy consumption profiles.Comment: To appear in the proceedings of Global IoT Summit 201
A Survey on Energy Efficiency in Smart Homes and Smart Grids
Empowered by the emergence of novel information and communication technologies (ICTs) such as sensors and high-performance digital communication systems, Europe has adapted its electricity distribution network into a modern infrastructure known as a smart grid (SG). The benefits of this new infrastructure include precise and real-time capacity for measuring and monitoring the different energy-relevant parameters on the various points of the grid and for the remote operation and optimization of distribution. Furthermore, a new user profile is derived from this novel infrastructure, known as a prosumer (a user that can produce and consume energy to/from the grid), who can benefit from the features derived from applying advanced analytics and semantic technologies in the rich amount of big data generated by the different subsystems. However, this novel, highly interconnected infrastructure also presents some significant drawbacks, like those related to information security (IS). We provide a systematic literature survey of the ICT-empowered environments that comprise SGs and homes, and the application of modern artificial intelligence (AI) related technologies with sensor fusion systems and actuators, ensuring energy efficiency in such systems. Furthermore, we outline the current challenges and outlook for this field. These address new developments on microgrids, and data-driven energy efficiency that leads to better knowledge representation and decision-making for smart homes and SGsThis research was co-funded by Interreg Österreich-Bayern 2014–2020 programme project KI-Net: Bausteine für KI-basierte Optimierungen in der industriellen Fertigung (AB 292). This work is also supported by the ITEA3 OPTIMUM project and ITEA3 SCRATCH project, all of them funded by the Centro Tecnológico de Desarrollo Industrial (CDTI), Spain
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