Czech Technical University in Prague (České vysoké učení technické v Praze – ČVUT in Czech, is one of the largest universities in the Czech Republic, and is one of the oldest institutes of technology in Central Europe. It is also the oldest non-military technical university in Europe.In the academic year 2012/2013 8 faculties and 1 university institute of Czech Technical University offered 105 degree programs and 419 fields of study, which enrolled more than 24,500 students. Wikipedia.
Czech Technical University | Date: 2017-01-09
An apparatus for an accurate automated non-invasive measurement of blood pressure waveform using brachial (occlusion) cuff pressurized above systolic pressure and using differential pressure sensor. The methodology involves measurement in suprasystolic mode and in utilization and construction of the device followed by algorithms for processing and analysis of measured blood pressure pulse waves and assessment of hemodynamic parameters of human cardiovascular system. The device includes an electro-pump connected to the collar device, a differential pressure sensor, pressure senor A, pressure sensor B, valve, closing a valve and the air reservoir. The cuff is wrapped around a persons arm. The values of the instantaneous pressure in the pneumatic portion of the device are converted into an electric signal by the pressure sensor A, pressure sensor B and the differential pressure sensor. These signals are then filtered using a set of passive RC elements for filtering out high frequency interference, and fed to the microprocessor with a computing unit, analog to digital converter. The sampling frequency is sensed signal at least 200 Hz. The control algorithm in the microprocessor, according to signals from the pressure sensor A further controls the course of cuff pressurization, controls the control valve, and finally determines the closing and opening of the closing valve. A microprocessor further controls a display and the data may be transmitted to the PC.
Samsung and Czech Technical University | Date: 2017-01-11
A graphics processing method and apparatus includes determining locations of primitives in a 3-dimensional (3D) space from graphics data for the 3D space in a memory, determining sizes of the primitives, generating Morton codes comprising a piece of information indicating the locations of the primitives and a piece of information indicating the sizes of the primitives, classifying the primitives into bounding boxes using the piece of information indicating the sizes of the primitives, and generating the acceleration structure indicating an inclusion relationship between the bounding boxes.
Agency: European Commission | Branch: H2020 | Program: IA | Phase: GV-6-2015 | Award Amount: 9.95M | Year: 2016
Fuel economy is a key aspect to reduce operating costs and improve efficiency of freight traffic, thus increasing truck competitiveness. The main objective of the IMPERIUM project (IMplementation of Powertrain Control for Economic and Clean Real driving EmIssion and ConsUMption) is to achieve fuel consumption reduction by 20% (diesel and urea) whilst keeping the vehicle within the legal limits for pollutant emissions. The approach relies on three stages targeting the improvement of the control strategy: * Direct optimisation of the control of the main components (engine, exhaust after-treatment, transmission, waste heat recovery, e-drive) to maximize their performances. * Global powertrain energy manager to coordinate the different energy sources and optimize their use depending on the current driving situation. * Providing a more comprehensive understanding of the mission (eHorizon, mission-based learning) such that the different energy sources can be planned and optimized on a long term. The IMPERIUM consortium consist of major European actors and is able to provide a 100% European value chain for the development of future powertrain control strategies for trucks.
Agency: European Commission | Branch: H2020 | Program: RIA | Phase: LCE-17-2015 | Award Amount: 9.63M | Year: 2016
The share of renewable energy is growing rapidly driven by the objective to reduce greenhouse gas emissions. The amount of electric power which can be supplied to the grid depends on the time of the day and weather conditions. A conventional fleet of thermal power plants is required to compensate for these fluctuations before large scale energy storage technologies will be mature and economically viable. All power market projections expect this to be the case for the next 50 years at least. For a strong expansion of renewables, this fleet has to operate flexibly at competitive cost. Current power plants cannot fill this role immediately without impeding their efficiency and engine lifetime through increased wear and damage induced by the higher number of (shorter) operating/loading cycles. New technologies need to be introduced to balance demand peaks with renewable output fluctuations at minimal fuel consumption and emissions without negative effects on cycling operation. The FLEXTURBINE partners have developed a medium to long term technology roadmap addressing future and existing power plants. The FLEXTURBINE project presented hereafter is the first step in such technology roadmap and consists of: (1) new solutions for extended operating ranges to predict and control flutter, (2) improved sealing and bearing designs to increase turbine lifetime and efficiency by reducing degradation/damages, and (3) an improved lifecycle management through better control and prediction of critical parts to improve competitive costs by more flexible service intervals and planned downtime, and by reducing unplanned outages. In all areas, individual technologies will be developed from TRL 3 to TRL 4-6. FLEXTURBINE brings together the main European turbine manufacturers, renowned research institutes and universities. It involves plant and transmission system operators to include user feedback and to prepare the take-up of the FLEXTURBINE technologies in power plants world-wide.
Agency: European Commission | Branch: H2020 | Program: ECSEL-IA | Phase: ECSEL-17-2015 | Award Amount: 64.82M | Year: 2016
ENABLE-S3 will pave the way for accelerated application of highly automated and autonomous systems in the mobility domains automotive, aerospace, rail and maritime as well as in the health care domain. Virtual testing, verification and coverage-oriented test selection methods will enable validation with reasonable efforts. The resulting validation framework will ensure Europeans Industry competitiveness in the global race of automated systems with an expected market potential of 60B in 2025. Project results will be used to propose standardized validation procedures for highly automated systems (ACPS). The technical objectives addressed are: 1. Provision of a test and validation framework that proves the functionality, safety and security of ACPS with at least 50% less test effort than required in classical testing. 2. Promotion of a new technique for testing of automated systems with physical sensor signal stimuli generators, which will be demonstrated for at least 3 physical stimuli generators. 3. Raising significantly the level of dependability of automated systems due to provision of a holistic test and validation platform and systematic coverage measures, which will reduce the probability of malfunction behavior of automated systems to 10E-9/h. 4. Provision of a validation environment for rapid re-qualification, which will allow reuse of validation scenarios in at least 3 development stages. 5. Establish open standards to speed up the adoption of the new validation tools and methods for ACPS. 6. Enabling safe, secure and functional ACPS across domains. 7. Creation of an eco-system for the validation and verification of automated systems in the European industry. ENABLE-S3 is strongly industry-driven. Realistic and relevant industrial use-cases from smart mobility and smart health will define the requirements to be addressed and assess the benefits of the technological progress.
Agency: European Commission | Branch: H2020 | Program: CSA | Phase: GV-11-2016 | Award Amount: 3.50M | Year: 2017
The FUTURE-RADAR project will support the European Technology Platform ERTRAC (the European Road Transport Research Advisory Council) and the European Green Vehicle Initiative PPP to create and implement the needed research and innovation strategies for a sustainable and competitive European road transport system. Linking all relevant stakeholders FUTURE-RADAR will provide the consensus-based plans and roadmaps addressing the key societal, environmental, economic and technological challenges in areas such as road transport safety, urban mobility, long distance freight transport, automated road transport, global competitiveness and all issues related to energy and environment. FUTURE-RADAR will also facilitate exchange between cities in Europa, Asia and Latin America on urban electric mobility solutions. The FUTURE-RADAR activities include project monitoring, strategic research agendas, international assessments and recommendations for innovation deployment as well as twinning of international projects and comprehensive dissemination and awareness activities. Overall it can be stated that FUTURE-RADAR provides the best opportunity to maintain, strengthen and widen the activities to further develop the multi-stakeholder road transport research area, for the high-quality research of societal and industrial relevance in Europe.
Agency: European Commission | Branch: H2020 | Program: ECSEL-IA | Phase: ECSEL-18-2015 | Award Amount: 82.27M | Year: 2016
The goal of EnSO is to develop and consolidate a unique European ecosystem in the field of autonomous micro energy sources (AMES) supporting Electronic European industry to develop innovative products, in particular in IoT markets. In summary, EnSO multi-KET objectives are: Objective 1: demonstrate the competitiveness of EnSO energy solutions of the targeted Smart Society, Smart Health, and Smart Energy key applications Objective 2: disseminate EnSO energy solutions to foster the take-up of emerging markets. Objective 3: develop high reliability assembly technologies of shapeable micro batteries, energy harvester and power management building blocks Objective 4: Develop and demonstrate high density, low profile, shapeable, long life time, rechargeable micro battery product family. Objective 5: develop customizable smart recharge and energy harvesting enabling technologies for Autonomous Micro Energy Source AMES. Objective 6: demonstrate EnSO Pilot Line capability and investigate and assess the upscale of AMES manufacturing for competitive very high volume production. EnSO will bring to market innovative energy solutions inducing definitive differentiation to the electronic smart systems. Generic building block technologies will be customizable. EnSO manufacturing challenges will develop high throughput processes. The ENSo ecosystem will involve all the value chain from key materials and tools to many demonstrators in different fields of application. EnSO work scope addresses the market replication, demonstration and technological introduction activities of ECSEL Innovation Action work program. EnSO relates to several of the Strategic Thrusts of ECSEL MASP. EnSO innovations in terms of advanced materials, advanced equipment and multi-physics co-design of heterogeneous smart systems will contribute to the Semiconductor Process, Equipment and Materials thrust. The AMES will be a key enabling technology of Smart Energy key applications.
Agency: European Commission | Branch: H2020 | Program: RIA | Phase: NMBP-23-2016 | Award Amount: 3.90M | Year: 2017
The mission of COMPOSELECTOR is to develop a Business Decision Support System (BDSS), which integrates materials modelling, business tools and databases into a single workflow to support the complex decision process involved in the selection and design of polymer-matrix composites (PMCs). This will be achieved by means of an open integration platform which enables interoperability and information management of materials models and data and connects a rich materials modelling layer with industry standard business process models. In order to satisfy the need for effectively designing and producing increasingly sophisticated materials, components and systems with advanced performance on a competitive time scale there is a particular need in industry for chemistry/physics-based materials models and modelling workflows which capture the performance of materials, accounting for material internal microstructure and effects of processing, provide accuracy/validation of predicted data, and relevant management of uncertainty and assemble knowledge ready for decision makers to act upon. COMPOSELECTOR will address these needs by integration of (discrete and continuum) materials models and process models as well as structured and unstructured data into a standards-based, open integration framework, implementing uncertainty management and multi-criteria optimisation in order to provide actionable choices, and building tailored knowledge apps to support decision makers. The human interface of COMPOSELECTOR will be supported by Visual Analytics capable of integrating qualitative, quantitative and cognitive aspects for a user-friendly management of the vast quantity of available data. The COMPOSELECTOR BDSS will be applied to and validated by end users targeting accurate, reliable, efficient and cost effective decision-making and management of polymer matrix composite (PMC) materials in the transport and aerospace value chains.
Agency: European Commission | Branch: H2020 | Program: MSCA-ITN-ETN | Phase: MSCA-ITN-2016 | Award Amount: 3.51M | Year: 2017
SOLUTION will provide research and training program for 14 early stage researchers (ESR) pursuing their PhD in various disciplines covering the broadly defined area of solid lubricant coatings. The project combines theoretical approaches represented by advanced nanoscale simulations, laboratory design and fabrication of novel solid lubricants supported by simulations, and the up-scaling of promising solutions and their application in selected emerging engineering applications. SOLUTION will link industries from various areas dealing with similar issues through intensive training and knowledge sharing. Three topics driven by industrial partners have been selected to demonstrate the added value of simultaneous development and training. The use of modern solid lubricants underlines the transformation of industry towards smart design, which is based on predictive models and cross-communication throughout the entire production chain. Fellows supported by the project will have a unique opportunity to gain competence ranging from simulation, characterization and processing, to industrial processes and entrepreneurship. Highly individualized multidisciplinary training reflecting actual market needs, together with scientific excellence, will generate an open-mind generation able to harvest multidisciplinary knowledge and to successfully face challenges represented by the design of competitive solid lubricants.
Agency: European Commission | Branch: H2020 | Program: RIA | Phase: FOF-11-2016 | Award Amount: 7.99M | Year: 2016
European manufacturing competes in a global knowledge-driven economy, and thus increasingly seeks competitive advantage through quality, agility and personalisation based on latest advances in IT. Increasing utilisation of IT in mission-critical elements of the production brings opportunities for consistency, transparency and flexibility, bringing the lot size of 1 closer to reality even for mass-production industries. Most relevant to achieve the expected increase of production performance for highly customized products is to master the complexity of the supply chain and logistics in the global production networks. Ad-hoc collaboration and setup of production coalitions with a wide spectrum of suppliers and service providers is necessary to answer the customization wishes of customers for their individual products in short time, high quality, and at affordable costs. Innovations from small high-tech companies requested by customers have to be integrated into the traditional industrial processes using novel organisational concepts and setups. DIGICOR will address the development of a collaboration platform, tools, and services for the setup and coordination of production networks and in particular the integration of non-traditional, small, yet innovative companies (SMEs) and logistics providers into the supply chain of large manufacturers (OEMs). The solution is based on an open platform integrating tools and services and implementing case specific governance rules and procedures for collaboration, knowledge protection, and security. The open platform will provide services creating a marketplace for the collaboration partners, for planning and control of the collaborative production and the logistics and risk management. It will be open to third parties to add services for advanced analytics, simulation, or optimization etc. The platform will provide seamless connectivity to the automation solutions, smart objects, and real-time data sources across the network