Universities, R&D Groups and Academic Networks

PsyCris (Psycho-Social Support in Crisis Management) is an international multi-disciplinary project funded by the European Union with the overall objective to improve psycho-social support in crisis management. Our main goals are: status quo analysis of support in crises in European countries, improvement of support strategies, contingency planning, development of interventions, providing efficient self-help strategies to communities affected by crises as well as investigation of long-term impact of crises. The results will have a significant impact on public health, community resilience, international cooperation and cost containment. For more information please check http://psycris.eu

Recommendation algorithm is very important for e-commercial websites when it can recommend online customers favorite products, which results out an increase in sale revenue. The project produces the framework of e-commercial recommendation algorithms, named Hudup. This is a middleware framework or “operating system” for e-commercial recommendation software, which support scientists and software developers build up their own recommendation algorithms with low cost, high achievement and fast speed. Concretely, you need to develop a recommendation solution for online-sale website. You, a scientist, invent a new algorithm after researching many years. Your solution is excellent and very useful but you cope with many difficulties relevant to heterogeneous models in recommendation studies, processing data, evaluation metrics, and simulation environment. Hudup supports you to solve perfectly these difficulties via three stages such as base stage – building up your algorithm, evaluation stage – evaluating your algorithm according to pre-defined metrics, and simulation stage – providing a simulator which helps you to test your algorithm in real-time applications. The product introduction is accepted to be published in American Journal of Computer Science and Information Engineering, American Association for Science and Technology (AASCIT). The product is available at
http://www.hudup.net.

The consumption of large amounts of multilingual and multimedia content regardless of its reliability and cross-validation can have important consequences on the society. An indicative example is the current crisis of the financial markets in Europe, which has created an extremely unstable ground for economic transactions and caused insecurity in the population. The fact that the national mass media provide exaggerated and contradictory information and the inaptness to understand local contexts from different countries has a considerable share in the aggravation of the crisis.

To break this spiral, we need multilingual technologies with sentiment, social and spatiotemporal competence that are able to interpret, relate and summarise economic information and news created from various local subjective and biased views and disseminated via TV, radio, mass media websites and social media. To address these challenges, MULTISENSOR will mine heterogeneous data from the aforementioned resources and apply multidimensional content integration.

MULTISENSOR will go beyond the state of the art by proposing the following scientific objectives: a) content distillation of heterogeneous multimedia and multilingual data; b) sentiment and context analysis of content and social interactions; c) semantic integration of heterogeneous multimedia and multilingual data; d) semantic reasoning and intelligent decision support; e) multilingual and multimodal summarisation and presentation of the information to the user. To achieve multidimensional integration of heterogeneous resources, MULTISENSOR proposes a content integration framework that builds upon multimedia mining, knowledge extraction, analysis of computer-mediated interaction, topic detection, semantic and multimodal representation as well as hybrid reasoning. The developed technologies will be validated with the aid of 3 main use cases: i) Journalism, ii) commercial media monitoring and iii) SME internationalisation.

The BMBF research program “IT-Security for Critical Infrastructures” has been initiated as part of the “High Tech Strategy 2020” of the German Federal Government. In order to evaluate and to improve IT Security of critical infrastructures, the project VeSiKi “Networked IT-Security of Critical Infrastructures” (Vernetzte IT-Sicherheit Kritischer Infrastrukturen, acronym “VeSiKi”), accompanies various projects from different critical infrastructure backgrounds to establish a collaborative research process among these projects (see joint research projects: http://vesiki.w3.rz.unibw-muenchen.de).  

It serves as a platform which allows research institutions and providers of critical infrastructures to access results derived within this collaborative process.

From knowledge engineering point of view the VeSiKi project provides an ontology for IT-Security in critical infrastructures. The ontology for IT-Security in critical infrastructures integrates the following subontologies in form of terminological knowledge (TBox concepts) to build up the model:

n  The subontology Project covers a cross sectoral analysis and classification of project information and results like project institution, competence, critical infrastructure and approach.

n  The subontology IT-Security covers the IT-Security relevant aspects like, threats, controls and vulnerabilities and is linked via critical infrastructure to the CRITIS subontology and consequently to the appropriate assets of an organization.

n  The subontology Compliance covers norms and standards, regulations and applicable laws and measurements. The compliance ontology is linked to the it-security ontology to gain first indication of an appropriate threat. The results of the aforementioned various project approaches inter-relate with available measurements or extend the measurements by integrating new approaches.

n  The subontology CRITIS links the cross sectoral classification of the projects with critical infrastructures relevant aspects like Asset, Organization and Critical Infrastructure.