DAS develops methods for automatic analysis of data (sensor data...) for the purpose of knowledge discovery, model refinement and optimization. The spectrum of applications encompasses process data analysis, process optimization, condition monitoring, fault detection and diagnosis, virtual sensors, fault prediction and optimal control systems in the process industry and production, in machine manufacture and maintenance and in energy management.
Prognose,prognosis,Steuerung und Optimierung,control and optimization,Datenanalyse,data analytics,Datenzentrierte Technologien,data centric technologies,Wissensrepräsentation und Semantik,knowledge representation and semantics,Big Data,big data,Wissensrepräsentation,knowledge representation,Datenmanagement,data management
Google, Facebook, Netflix or Amazon are already relying on machine learning. These technologies can also be used in a broad range of industrial environments - but companies are reluctant to do so. It is important not to lose any time, as a look at the state of the art reveals. The SCCH experts and a COMET partner in the current issue of "Computer & Automation" explain what is important.
The Data Analysis Systems (DAS) group and the FLLL of the Johannes Kepler University Linz cooperate in the field of dissertations. The paper on Machine Learing/Deep Learning, which was presented at the ICLR 2017, originates from this cooperation.
The second event of the event series for IT experts at Softwarepark Hagenberg on "Automotive Computing" was a complete success! On June 22, 2017, around 60 industry experts took the opportunity to address the question: "What are the opportunities for data analysis in the automotive sector?"
In order to boost the digital transformation in Upper Austria, the government is encouraging 14 innovative research projects in the field of digitization with a total funding volume of EUR 5.68 million. The Software Competence Center Hagenberg is involved in two projects.
The Automotive Cluster Upper Austria organized the Innovation Workshop at MAGNA in Graz. The experts from the research focus Data Analysis Systems (DAS) showed how predictive maintenance works and how the "Early Warning Point" can be found.
In modern enterprises a mass of data is available in many formats and qualities. An automated analysis of this data promises an increase of knowledge and thus the opportunity to optimize different systems.
Host, Mr. Dirk Lukaschik, CEO of T-Systems, presented the winners of the E-Award 2016. The submitted projects impressively showed the importance of digitization and how it affects all economic and living areas. This circumstance effects many companies, but also the entire society", says Lukaschik. "In order to line up for the digital transformation, IT organizations need completely new skills, technologies and management approaches.
Following on from the highly successful EU ParaPhrase project, the University of St Andrews has obtained substantial further funding from the Europeon Union under the Horizon 2020 programme to study advanced computing. The 3.5M Euro RePhrase project is coordinated by Professor Kevin Hammond of the University of St Andrews, and brings together 8 leading academic and industry partners from the UK, Austria, Italy, Spain, Hungary and Israel. It aims to tackle one of the most pressing problems in computer science: how to produce effective software for emerging "parallel" computer platforms, that promise significantly increased performance at significantly reduced cost and energy usage.
For small and medium enterprises, the question arises, how much effort they can drive sensibly to systematically develop their data. To evaluate them and to make them productive in the sense of the company. The questions are many and varied: What is Big Data for small and medium-sized businesses? Which areas of application have already proved, that could be developed? Where are the problems and where are the solutions?
The RePhrase project aims to produce new software engineering tools, techniques and methodologies for developing data-intensive applications in C++, targeting heterogeneous multicore/manycore systems that combine CPUs and GPUs into a coherent parallel platform.
A world-leading team of academic researchers and industrial experts from across Europe are celebrating the conclusion of a four year research collaboration tackling the challenges posed by the fastest and most powerful computing systems on the planet.The € 4.2M ParaPhrase project brought together academic and industrial experts from across Europe to improve the programmability and performance of modern parallel computing technologies.
On December 1st, 2014 the 2.5-year research project PROSAM (Intelligent fault prognosis systems for anticipative maintenance strategies) has been started under the coordination of the Software Competence Center Hagenberg. The project is funded by the FFG under the funding program “ICT for the future”.