Agency: Cordis | Branch: H2020 | Program: RIA | Phase: ICT-01-2014 | Award Amount: 3.71M | Year: 2015
Uncertainty is intrinsic in Cyber-Physical Systems (CPSs) due to novel interactions of embedded systems, networking equipment, cloud infrastructures, and humans. CPSs have become predominant in critical domains and necessitate the implementation of proper mechanisms to deal with uncertainty during their operation at an acceptable cost avoiding unwarranted threats to its users and environment. One way to guarantee the correct implementation of such mechanisms is via automated and systematic Model-Based Testing (MBT)a way of improving dependability. U-Test will improve the dependability of CPSs by defining extensible MBT frameworks supporting holistic MBT of CPSs under uncertainty in a cost-effective manner. More specifically our objectives are: 1) Provide a comprehensive and extensible taxonomy of uncertainties classifying uncertainties, their properties, and relationships; 2) An Uncertainty Modelling Framework (UMF) to support modelling uncertainties at various levels relying on exiting modelling/testing standards; 3) Defining an intelligent way to evolve uncertainty models developed using UMF towards realistic unknown uncertainty models using search algorithms (e.g., Genetic Algorithms); 4) Generating cost-effective test cases from uncertainty and evolved models. U-Test consortium encompasses domain experts from various facets of CPSs, i.e., software, embedded systems, distributed systems, and cloud infrastructure. We have chosen two case studies from diverse domains including Handling Systems and Geo Sports to assess the cost-effectiveness of U-Test. The solutions will be integrated into two key commercial tools available in the market: ModelBus/Fokus!MBT and CertifyIt. Moreover, the solutions will be deployed into the actual practise in addition to standardization to achieve a wider impact within Logistics, Geo Sports, and Healthcare domains and further facilitate interoperability among tools and technologies.
Agency: Cordis | Branch: H2020 | Program: RIA | Phase: ICT-12-2015 | Award Amount: 2.90M | Year: 2016
Recent revelations about large-scale pervasive surveillance of Internet traffic have led to a rapidly expanding deployment of encryption in order to protect end-user privacy. At the same time, network operators and access providers rely on increasing use of in-network functionality provided by middleboxes and network function virtualization (NFV) approaches to improve network operations and management, and to provide additional value for their customers. In addition, new applications such as interactive video make new demands on the transport layer, requiring the deployment of new protocols and extensions, the deployment of which is impaired by the proliferation of middleboxes that cause them to fail. These three trends are on a collision course. The MAMI project seeks to restore balance among end-user privacy concerns in the face of pervasive surveillance, innovation in network protocols in the face of increasing ossification, and the provision of in-network functionality in a cooperative way. We aim to do this through the development and experimental deployment of a middlebox cooperation protocol (MCP) embedded in a more flexible transport layer, to be used together with ubiquitously deployed encryption. To ensure the applicability of the protocol, we will develop it on a background of middlebox behaviour models, derived from large-scale measurements of middleboxes in the public Internet conducted on top of a FIRE\ testbed. We will then evaluate the fitness of our proposed MCP to purpose by evaluating its applicability to a set of real-world use cases for transport layer evolution, focusing on incremental deployability in the presence of both cooperative and uncooperative middleboxes by experimentation in the Internet utilising the facilities provided by FIRE\ testbeds.
Agency: Cordis | Branch: H2020 | Program: IA | Phase: ICT-18-2014 | Award Amount: 1.30M | Year: 2015
European film makers are well-known for their creative innovation in selecting themes, their original way of storytelling and their art of cinematography. Like elsewhere in the world, they use computer-generated visual effects to achieve the intended visual experience and quality. To achieve the best interaction between the creative team on set and the post-production team, it is important to achieve the best common understanding between the team filming real scenes and the team working on visual effects. For this, previz has been developed. Previz today contributes to film making from the planning stage to filming with actors on set, where the final composition of mixed reality scenes can be reviewed during and right after the shoot. Large film studios that produce films with the highest budgets take the final step and integrate previz with the final post-production. For this, they develop in-house tools or cooperate with a company that is dedicated to the previz concept. This integration remains unavailable to most film makers and provides a strong competitive advantage. Without the integration, a gap remains between the team filming real scenes and the team working on visual effects in post-production. POPART will introduce an affordable and highly customizable solution that will disrupt the market and overcome this lack of competition. It will democratize the access to a complete previz solution integrated into the pipeline from shooting preparation to post-production, that doesnt exist on the market. In contrast to the market lock-in solutions, all core elements required for real-time previz will be released in open source and will be based on open standards to provide an highly customizable solution. The product released by POPART will comprise hard- and software components. It will be available at an affordable price, help improve the processes for creative teams in Europe directly, and will stimulate research by providing core libraries in open source.
Agency: Cordis | Branch: H2020 | Program: RIA | Phase: BIOTEC-2-2015 | Award Amount: 10.71M | Year: 2016
Recent developments in omics technologies demand implementation of systems biology approaches to facilitate analysis and interpretation of the generated complex datasets.This is essential for biotechnological as well as preclinical and clinical applications. In comparison to previous approaches, most cancer relevant studies are confined to pattern recognition or at best modelling of single pathways, rather than the complex pathways and cross-talk determining cancer progression and drug response. Systematic tools that evaluate and validate personalised medicine approaches on a preclinical level are missing; an important prerequisite for translation into clinical practice. The overall objective of CanPathPro is to build and validate a new biotechnological application: a combined experimental and systems biology platform, which will be utilized in testing cancer signaling hypotheses in biomedical research and life sciences. Thus, the proposed project will focus on developing and refining bioinformatic and experimental tools for the evaluation of systems biology modelling predictions. Components comprise a highly controlled mouse experimental system, NGS, a quantitative proteomics based read-out of changes in pathway signalling and an integrative systems biology model for data integration. Testable hypotheses about biological systems will be generated and experimentally validated. The developed system tools will be made available to researchers, SMEs and industry for practical applications. Following this project, a commercial platform for interpretation and analysis of complex omics data and for deriving and testing new hypotheses will be set up by the participating companies and academic partners. CanPathPro will enhance the competitive potential of the SMEs involved expanding in the field of biotechnology, personalised medicine and drug development and also provide new opportunities for other SMEs working in the field of bioinformatics and biomedical applications.
Agency: Cordis | Branch: H2020 | Program: MSCA-RISE | Phase: MSCA-RISE-2014 | Award Amount: 207.00K | Year: 2015
Central venous catheters (CVCs) play a critical role in healthcare and few medical devices are more important and widespread in modern medicine. Catheter-related bloodstream infection (CRBSI) is the most common life-threatening complication of CVCs. Reducing the risk of CRBSI among patients would save costs, reduce length of stay and improve mortality and morbidity. The major challenge of UNICAT is thus to develop a new CVC solution to prevent infection and thrombosis. The project partners will introduce a whole new way of thinking by introducing a disruptive approach which is more than just a coating of devices. A new material will, for the first time, combine ultra-biocompatibility with chemical resistance and desired mechanical properties, to effectively prevent adverse host response, inflammation and infection. A major problem in biomaterials science is that bioresistant materials are inevitably also chemically inert and hence highly difficult to manipulate by traditional wet chemistry. If manipulation (e.g. coating) is achieved, the solution is often unstable and fragile. UNICAT will address this problem by combining two materials using a novel method based on super critical CO2-chemistry. It will result in a hybrid material which is stably formed and combines the best properties of two or more materials. The success criterion is to exceed performance of coatings by producing the first fully biocompatible material to be used as sole robust bulk material of vascular access lines. UNICAT is an international and inter-sector collaborative project comprising R&D activities and secondments between the SME BioModics (BM), the University of Minho (UMinho), the Bar-Ilan University (BIU) and the Simula Research Laboratory (Simula). The consortium has identified the RISE programme as a suitable vehicle for overcoming the identified major challenges and for bridging the knowledge gap, while helping to overcome the financial, technological and intersectoral barriers.