Past projects

The European Green Deal defines 4 key elements for a sustainable mobility and automotive industry, namely: climate neutrality, zero pollution Europe, sustainable transport, and the transition to a circular economy. Digital technologies are a significant enabler for attaining the sustainability goals in mobility and transportation. The EC is taking initiatives to ensure that digital technologies such as AI, 5G, IoT and cloud/edge computing can accelerate the transition of the automotive industry to electrical, autonomous, connected, and shared vehicles. The current COVID-19 situation accelerates this trend. The AI4CSM project will develop advanced electronic components and systems (ECS) and architectures for future massmarket ECAS vehicles. This fuels the digital transformation in the automotive sector to support the mobility trends and accelerate the transition towards a sustainable green and digital economy. Having assembled some of Europe’s best partners from industry, research and academia, AI4CSM will deliver key innovations in technical areas including: sensor fusion and perception platforms; efficient propulsion and energy modules; advanced connectivity for cooperative mobility applications; vehicle/edge/cloud computing integration concepts; new digital platforms for efficient and federated computing; and intelligent components based on trustworthy AI techniques and methods. ECAS vehicles enabled by embedded intelligence and functional integration for future mobility, becomes the pivotal factor for the automotive sector to address the Green Deal principles. AI4CSM consists of 8 collaborative R&D clusters, gathering 41 partners from 10 countries. AI4CSM will reinforce user acceptance and affordability by convenience and services for the major transition to a diverse mobility. AI4CSM addresses the increasing demand of mobility, supporting future traffic concepts and strengthen the European automotive manufacturing base as a global industry leader.

The overall project goal is the availability of validated vehicle control algorithms for autonomous driving under military conditions. This is an essential contribution to the few researched solutions to the complex requirements of military automated driving. It is particularly important for nations the size of Austria to be involved in forward-looking high-tech military technology and to try to seize opportunities for niche products. In addition to the immediate technical solution, this should be particularly emphasized as a programmatic goal.

At present, the building stock in the EU remains energy intensive and mostly inefficient; it is responsible for 40% of final energy consumption and 36% of CO2 emissions. In order to increase the share of renewable energy and reduce energy consumption, future systems must have a high degree of flexibility and efficiency. On the one hand, this requires the systematic embedding of cyber technologies in order to monitor the physical systems and enable communication between different subsystems. On the other hand, innovative energy services such as demand-side management or model-predictive control are required to reduce the energy consumption of buildings and to transform buildings into active, intelligent players in higher-level energy systems. Studies have shown that artificial intelligence (AI - Artificial Intelligence) is the backbone and enabler of many energy services. Key Message 1: Applications of artificial intelligence are the backbone and enabler of many energy services. Innovative Energy Services are built on a bi-directional, real-time interaction with real buildings. Innovative solutions are required for the generation, provision and evaluation of these large amounts of data. Internet of Things (IoT) technologies are the backbone and an enabler of these intelligent systems. Computing paradigms Current IoT implementation depends almost entirely on cloud infrastructure and cloud-based services. Cloud computing offers numerous advantages such as cost efficiency, high availability, inexpensive software and enhanced security [6]. However, cloud-based services also have serious disadvantages: reliability, trustworthiness, or security and data protection. These disadvantages result, among other things, from the fact that the data provider (end user) and the data consumer (cloud provider) often have conflicting interests. Key Message 2: In the area of ​​energy services for intelligent buildings, cloud computing has serious weaknesses in the areas of reliability, trustworthiness, and data protection/security. Edge computing is an alternative IoT implementation and refers to computing taking place at the edge of networks; the "edge" is where end devices access the rest of the network. Edge computing increases availability, accessibility and reliability and improves latency for many services compared to cloud computing applications. Users usually own the end devices and have physical access on site to control them. This also increases user trust as data migration becomes optional for many use cases, which in turn leads to a lower risk of data breaches. Key Message 3: In principle, edge computing can overcome the main problems and limitations of cloud computing. Edge devices have power consumption limitations and therefore have limited computing resources. Cloud-based AI applications usually consume a lot of energy and cannot (or only to a very limited extent) be used on resource-constrained devices. A central challenge for edge applications in the field of intelligent buildings is to "bring AI to the edge". Key Message 4: In order to use the full potential of edge computing for intelligent buildings, "AI must be brought to the edge" of networks.

The Quality Assurance Methodologies for autonomous Cyber-Physical Systems (QAMCAS) aims at methods for enabling substantial quality improvements of interacting communicating systems that interact with humans and the physical environment. QAMCAS is intended to carry out research improving quality assurance methods during development together with methods that assure quality criteria like safety as well as reliability and also robustness during operation. The latter deals with fail-operational methodologies based on artifacts obtained during development and also measurements gained from previous similar systems during operation. In QAMCAS we treat quality assurance from a holistic point of view investigating methods to be used at development time as well as methods to be applied during operation of the cyber-physical system. To solve the challenges corresponding to the holistic view, we suggest to integrate testing methodologies like combinatorial testing and model-based testing and to combine them with machine learning approaches for model and test data generation. Furthermore, we carry out research for transferring development artifacts like models to fail-operational systems that follow the model-based reasoning paradigm. For this purpose, we have to work on smart monitoring systems that are capable of identifying failures and triggering fault localization and repair procedures for obtaining truly fail-operational systems. Although, the main ingredients are available, their integration is challenging and requires several research issues to be solved. In this proposal we discuss these issues in detail. In order to show that the proposed methods and techniques contribute to quality assurance of cyberphysical systems, we carry out the development of prototypical implementations that are further on used for providing an experimental evaluation in the context of autonomous driving and other mobile and autonomous systems.

When recommending videos, the current context of the user plays an important role. The first task in the context of the project is to identify those recommendation approaches that best help to support contextual recommendation of videos. A context is composed of different data sources, such as current search strings of the user, search strings in similar situations, search strings of the "Nearest Neighbors" (users with similar interaction behavior) etc. Analysis and design are carried out in the work package "On-Demand-Clipping" , Implementation and evaluation of a context-based recommendation approach. The solutions developed for "on-demand clipping" form the basis for further developments with the aim of supporting the synthesis of videos ("on-demand clip merging"). On the basis of information such as available time, keywords describing the context and other information (so-called company-related information parameters in the context of the use of knowlede graphs), the system should identify (synthesize) a sequence of partial videos, which the user sees as a "solution video "represents. A simple application is eLearning: here, for example, a corresponding video can be generated by the system on the basis of the learning requirements of a user.

The overall idea of AIDOaRT is to efficiently support requirements, monitoring, modelling, coding, and testing activities during the software development process. AIDOaRT can be used as a platform to extend existing tools. To this intent, the project proposes the use of Model-Driven Engineering (MDE) principles and techniques to provide a model-based framework offering proper methods and related tooling. The projects’ framework will enable the observation and analysis of collected data from both runtime and design time to provide dedicated AI-augmented solutions that will then be validated in concrete industrial cases involving complex CPSs.

SMART2B aims to 1) upgrade smartness levels of existing buildings through coordinated control of legacy equipment and smart appliances, 2) implement interoperability in two existing cloud-based platforms that are currently available in the European market and, as a result of this project, will be integrated into a single building management platform, 3) create a user-centric ecosystem that empowers citizens by simplifying equipment and device control and providing information about overall energy performance. The cloud-based platform will facilitate smartness upgrades of existing buildings, enabling their transition from passive buildings to active elements of the energy system by offering new energy and non-energy services such as increased energy efficiency, improved indoor comfort to the occupants and flexibility to various stakeholders including DSOs, building managers and other third-parties. Thereupon, specifically tailored to the needs of the user, SMART2B will provide new business models for the building energy market combining the savings from energy efficiency measures and gains from the active contribution of the building through flexibility services by exploiting the maximum level of smartness. The experience and maturity of solutions from the consortium partners will ensure market uptake through sound exploitation and replication activities carried out by the strong commercial backbone of SMART2B. SMART2B will develop and deploy non-intrusive IoT sensors and actuators in existing buildings aiming to solve one of the main problems of improving buildings’ indoor comfort and energy efficiency: the structural (physical and financial) limits of installing, monitoring, automating and control existing devices in buildings, by proposing plug & play devices able to interact with the appliances and legacy equipment already installed and communicate the collected data to the cloud for remote monitoring, data analysis based on AI and machine learning and control.

The construction sector accounts for around 40% of the total final energy consumption and has enormous potential for saving energy and reducing CO2 emissions at low cost. The latest developments in digitization and the establishment of cyber-physical systems have the potential to significantly reduce the costs of building operations. Intelligent systems could access large amounts of data in order to reduce the energy consumption of buildings through optimized regulations that are adapted to actual needs. So far, this potential has only rarely been exploited. The overarching goal of the annex is to improve access to low-cost, high-quality data from buildings and to support the development of data-driven energy efficiency applications and analyzes. This enables the building controls to be optimized in real time and provides energy efficiency data and decision-making aids for building management. In order to achieve the overarching goal of the annex, the annex contains a number of specific goals on the subjects of (i) data acquisition, (ii) digital characterization of buildings, (iii) coding of knowledge in intelligent energy efficiency applications and (iv) support the use of data-driven products and services. These additional goals are 1) Providing knowledge, standards, protocols and procedures for the cost-effective collection and sharing of high quality data in buildings 2) Developing a methodology for creating control-oriented building models that enable testing, development and evaluation of the effects of alternative energy efficient strategies for HVAC - Facilitate control of buildings in a digital environment 3) Develop building energy efficiency (and related) software applications that can be used to reduce energy consumption in buildings and ideally commercialized. 4)Promotion of the transfer of the annex results through case studies, business model innovation and dissemination of results. The aim of Austrian participation in Annex 81 is to network with international project partners in the field of IT and building technology to identify global developments in this field, to actively participate in the cooperative technology development and thus to enhance Austria's competence (on the company side as well as on Side of the research). Through targeted dissemination activities and the involvement of relevant sectors and industries, this knowledge should also be shared with the relevant actors and stakeholders in Austria (control and smart home providers, real estate companies, building technology planners, facility management, IT sectors, architects, etc. ) to get redirected. Subsequently, the aim is to use the international networks gained from the annex, in particular to strengthen Austrian companies, such as permanent cooperation with annex partners in the area of ​​cooperative technology development, possible partnerships in the area of ​​Horizon Europe or at the level of classic business cooperation.

(1) C programmes that adhere to the current C standard (ISO/IEC 9899:2018) should be converted into translatable assembler programmes (assembler dfyasm) for the Dragonfly CPU. TU Graz will provide expertise in the creation of creation of a compiler and software development. (2) Graz University of Technology provides a test framework for the compiler including test programmes and a test protocol.

Automatic tests allow software developers to detect a considerable amount of bugs before a software is released. However, the step after the detection of a bug, i.e. debugging, is still done manually in most software companies. This requires many man-hours of expensive developers. While there exist numerous academic approaches to ease the debugging process, these approaches are rarely used in practice. Therefore, automatic debugging has the potential to reduce time and costs of the software development cycle. This project aims to close the gap between academic research and debugging in practice. We will focus our research on the improvement of existing academic debugging techniques (in particular Slicing, Model-based Software Debugging, and Spectrum-based Fault Localization) in order to prepare them for use in practice. Thereby, we will address the scalability, accuracy and practicability of the approaches. The project is divided into three phases: the assessment phase, the improvement phase, and the integration phase. In the assessment phase, we examine the reasons for the lack of acceptance of academic debugging approaches in practice. This phase includes observations of software developers when they are debugging a program and follow-up interviews. This observational study is used to develop hypotheses about the current state of debugging in practice. The obtained hypotheses are tested with the data we will collect through a large-scale online survey. We will furthermore identify the weaknesses of the individual debugging approaches and identify possible improvements by laboratory experiments. These experiments include both evaluations of approaches with existing benchmarks and user studies where participants have to use the different debugging approaches to find bugs in given programs. In the next phase, we will use the insights gained from the assessment phase to improve the individual debugging approaches. There are two particularly interesting research questions in this project phase: (1) Can the combination of debugging approaches help to improve the overall debugging experience? (2) Is it possible to automatically select the best suited debugging method for a given program and test suite? In the third phase, we will focus on the practical integration of the approaches into development environments and processes. Essential parts of this phase are (1) the integration of the academic debugging approaches into IDEs (e.g. Eclipse), (2) the co-evolution of tests for a given debugging program, and (3) the implementation of additional debugging support (e.g. Cause-Effect-Chains). We plan to conduct extensive laboratory experiments to evaluate the usefulness of the developed debugging tools.

In the NextGES project, domain-informed machine learning methods and a user-centred approach are applied to develop energy services. The developed energy services will be tested in two Styrian demonstrators - "My Smart City Graz" and "Stanz" - improved and adapted to the needs of the local users. In the process, care will be taken to ensure that, through cooperation with the associated spin-off of Graz University of Technology, further development and research steps can be used. The creation of a roadmap necessary for this for the time after the project and for the further commercial utilisation of the project results will take place within the framework of the project.

The project COOL-QUARTER-PLUS was developed to counteract the current trend towards inefficient individual units with coordinated cooling concepts at neighbourhood level. The focus is on office and research quarters, because here central measures are more likely to be implemented than in heterogeneous residential or mixed-use quarters due to the ownership structure and central management.

The project UserGRIDs develops two user-centred energy services at city district level, be¬ne¬fit-ting from active user participation and large amounts of real-time data. An ICT platform acts as a mid¬dleware providing seamless interoperability and standardized protocols. The first service is an energy management system (EMS) for districts with strongly fluctuating con¬sump¬tion and generation characteristics. The aim is to minimize emissions through optimal mana¬ge¬ment of en-ergy storage and supply from volatile sources. Various building controllers are ex¬ten¬ded to form a comprehensive, self-learning control system for the entire district. Its de¬vel¬opment is based on detailed thermo-electrical models also used by the second service, energy structure planning. It supports decisions on the transition of the district energy system towards zero greenhouse gas emissions. EMS, ICT-platform and energy structure planning will be im¬ple¬men¬ted, tested and further developed at the INNOVATION DISTRICT INFFELD of TU Graz.

Objectives and Motivation: • The estimation of energy consumption of a driver moving along some road currently is based on statistical methods that give good but not very precise forecasts. Within this Project, these forecasts shall be made much more precise without losing explainability or reliability. Methodology: • Based on real-driver data and combinations of automata-learning and machine learning methods, more accurate models of driver behaviour shall be constructed that give more precise forecasts. For comparison purposes a purely deep-learning approach also is followed. Expected Results: • More precise driver models that are able to predict the energy usage over arbitrary roads and given a certain driving “style” more precisely, while still retaining modest computational overhead and being “real-time” (i.e., no GPUs required, couple of minutes for the computation).

With the Renewable Expansion Act (EAG), the goal set by the federal government to cover 100% of total electricity consumption from 2030 on a national balance sheet from renewable energy sources is to be implemented. For this purpose, the annual electricity generation from renewable sources is to be increased by 27 TWh by 2030 through new construction, expansion and revitalization, with 11 TWh being realized by means of photovoltaic systems (PV). In 2019, the installed PV capacity in Austria was 1.7 GWp (1.7 TWh of generated energy). The annual growth rates in the years 2014-2018 were 150-180 MWp / a. Only in 2019 was it possible to achieve a higher value of 250 MWp / a. To achieve the target of 11 TWh by 2030, an annual expansion rate of 1,000 MWp / a would have to be achieved. Current studies show that the available roof areas with an expansion potential of 3.5 TWh are not sufficient and therefore alternative PV systems are required. For the reasons mentioned above, in addition to the planned roof systems, innovative alternative area potentials for PV systems must be tapped. The reports from other projects show the available space and energy potential, but these were determined using statistical methods, so that no statement is made regarding the actual suitability. Alternative PV areas / yields in a city were specified, but no methodically systematic localization of these places was carried out. The motivation of PV4EAG is to close this gap and to develop a process for the automated discovery of alternative PV areas. This addresses the sub-topic "Creation of a freely accessible data platform with energy-relevant forecasts" In the PV4EAG project, alternative PV areas are to be analyzed using methods from the field of Geographic Information Science & Technology and artificial intelligence for their suitability in terms of shading, yield potential, construction costs, and grid connection options. The starting point is the existing GIS data (digital building heights, vegetation models, terrain models from airborne laser scanning data, cadastral data), in combination with other publicly available data (Open Governmental Data) and other open data sources (OpenStreetMap, Corine Landcover, etc.), as well as remote sensing data and products (ie orthophotos and satellite image data) are used. By using smart data fusion, semantic annotation of the data (for semantic data integration), and spatial analysis techniques paired with artificial intelligence (GeoAI in the broadest sense), the data should be suitable for large-scale facade-integrated systems on high-rise buildings, sealed parking spaces in shopping centers and residential areas , Traffic areas and rail systems as well as floating PV are analyzed. For the development and testing of the analysis method, the project is limited to selected locations in Styria, with the aim of scaling it up. For these locations, a plausibility check is carried out using the existing VR installation in the EAS lab using a virtual 3D process, and detailed project planning is used to specify the realistic PV yield to be expected.

The aim of KI-SecAssist is the development of autonomous assistance modules based on cooperative task management and various UAV and UGV systems with integrated multi-sensor Payload. The development of AI-based solution approaches enables cooperative multimodal interaction strategies between several UAVs ("Fixed Wing" and "Multi-Rotor" systems) and UGVs and thus an intelligent interaction of the individual systems into one Optimized assistance for emergency services geared towards special application scenarios. The UAV- / UGV- Systems have different performance parameters as well as one different sensors, geared to the requirements of the individual scenarios and enable near real-time on-board Situation analysis. A cooperative task management is administered Tasks and goals, prioritized and generated on the basis of situation Changes to new tasks and delegates the autonomous processing of tasks to the UAV / UGV systems. The result from KI-SecAssist is a modular proof-of-concept functional demonstrator, incl. Tests, exercises and evaluation related to the functional, Performance and practical suitability for an optimized assistance service for emergency services in crisis and disaster scenarios.

The aim is to develop an IoT platform for the smart city. The first implementation takes place in the VS Graz - Leopoldinum. This IoT platform is the prerequisite for developments in the projects ANSERS and NextGES; in these projects (a) the user: interior comfort are collected, (b) through (machine learning-based) data analysis of heating, cooling & ventilation can be quantified, whether this can be increased, and (c) the energy consumption (electrical and thermal) can be analyzed and optimized.

In order to increase trust in robot systems and reduce cognitive load, the project aims to develop well-founded methods for measuring trust in assistance systems and the cognitive load caused by their use. Furthermore, options for intervention in (1) the design of the user interface for input and output, (2) the degree of autonomy and (3) the transparency of decisions by the robot that allow an improvement of these parameters are to be examined. The primary innovation of the project is that trust and the cognitive load as well as measures to improve them are thoroughly investigated in an interdisciplinary team (psychologists, visualization experts, robotics, emergency services). The planned direct coupling of the assessment of trust and cognitive load with possible changes in the interaction design and the behavior of the robot will provide new insights into the nature of trust in assistance robots and enable the development of improved assistance systems. The immediate practical benefit of this knowledge is evaluated in realistic field tests with emergency services.

The goal of I-GReta is to develop solutions for planning and operation of highly flexible energy systems benefitting from storage capacities. I-GReta will connect 5 trial sites in 4 countries via a professional ICT platform benefitting from FIWARE components and thereby build a real-world digitalized and decentralized energy system. In recent years, studies and hands-on experience have concluded that the integration and participation of end-users are crucial for the energy transition. Occupants, owners and system operators as key need owners will participate and evaluate the operation of the respective systems in a Virtual Smart Grid which is based on the developed platform. A key use case will be the trading of storage capacities via the platform. The Austrian partners will contribute methodological expertise in the field of psychological and technical aspects of active user participation in smart energy systems with high shares of storages of different energy carriers. Furthermore, they provide mathematical and computational methods to enable large-scale modelling, simulation and optimization of cyber-physical systems. Prototypical developments will be tested and evaluated under laboratory conditions in the Austrian pilots.

Digital twins are very useful for answering or completing inquiries about the past or future behaviour of a complex cyber-physical system (of systems), which is either not yet fully implemented or is used remotely, whereby the creation of a physicallocal copy is not possible or economical. Digital twins are relatively inexpensive to create when they can be derived and simulated directly from artefacts created during development. However, these optimal conditions are often not (yet) given in practice. An automated creation, e.g. by learning methods, would remedy this. In addition, for successful use, the applied models and the insights derived from them must sufficiently reflect the properties of the real system. If this is not the case, they are even counterproductive as they lead to wrong conclusions. Therefore, one must be able to trust digital twins. Hence, they must be correct and reliable and at the same time cost-effective in their creation and maintenance. The use of a new technology is often accompanied by doubts about its reliability and concerns about possible side effects. If digital twins are created automatically, e.g. by learning methods, the process behind it is not easy to understand for the user. For acceptance of the technology by the affected user group, instruments must be available to correctly assess the reliability, traceability and limitations of digital twins and to establish trust. LearnTwins addresses these mentioned challenges by using a combined learn-based testing method. This is based on the insight that the properties of complex systems often cannot be captured concisely in a single model (type). Therefore, the project aims to combine different learning methods to create the digital twin (automatic learning, classical machine learning and deep learning). In addition to already existing data sources, learning data will be gained by executing test cases on the real system, whereby the test cases, in turn, will be created automatically from the (learned) digital twin. The technical work will be embedded in a foresight process. For this purpose, the involvement of stakeholders is planned, who actively work out desired futures and strategies regarding the developed technology. The results of the project will enable the faster and more economical creation of high-quality and reliable digital twins and accelerate the necessary digital transformation of product artefacts. The results on the understandability of automatically learned models should contribute to a higher acceptance and a more focussed use of learning-based methods. The developed methods will be tested and evaluated in three realistic use cases from different domains.

Industrial energy systems for manufacturing are mainly designed for single supply technologies, not designed for the fluctuation of energy demand and energy supply and thus can only react to a volatile demand and supply (thermal and electric) to a limited extent. From this, the need for the best possible support in optimizing the operation of the industrial energy system (demand and supply), the interaction of different renewable (volatile) and conventional energy sources and the design for industrial energy systems can be derived. The demand for products from the printed circuit board industry is continuously on the rise. Besides the increase of companies in Austria have to face the challenge of frequent change and adaptation to end-user requirements, causing significant changes in the energy demand and supply and by this, energy capacity limits onsite. This will be further increased by digitalisation and in terms of site security the need to increase productivity. The flexibility of the system makes it almost impossible for industry to plan and assess necessary adaptations and investment in the process and supply system and these challenges will increase significantly in the upcoming years. The overall objective of DigitalEnergyTwin is to support the industry with the development of a methodology and software tool to optimize the operation and design of industrial energy systems. The core of the project is the development of a holistic optimization approach, based on (near-) real production data, historical and predictions of the existing system, both the process demand and supply level. By this, industry will be supported for the first time with reliable solutions in terms of fluctuating, volatile and renewable energy supply well designed for efficient process technologies. The methodology of the digital twin will be developed and validated for single use cases and more importantly implemented in the manufacturing industry (PCB industry). For selected processes (energy relevant) and renewable as well as conventional supply technologies also the product quality will be addressed within this approach. Simplification and the development of technical standard solutions will lead to costeffective exploitation in other industrial sectors. Thus, the DigitalEnergyTwin builds on other areas of digitisation that are currently being developed. The use of the digital twin methodology will also make it possible to use the augmented and virtual reality (AR/VR) approach, which enables efficient production and system monitoring as well training and will support the EnergyManager4.0 in the future. By this, a maximum impact and multiplication in other industrial companies and sectors will be achieved and the industry benefits from a reduction of costs and risk of investment decision, which will lead to a significant increase of the implementation of renewable energy technologies as well as technologies for higher energy efficiency in industrial production.

GENDER STI will innovatively contribute to solve complex problems associated to the integration of the gender perspective in STI dialogues with third countries. By adopting a design thinking human-centric problem-solving approach, GENDER STI will investigate how gender equality is taken into consideration at different levels of international cooperation dialogues in the area of STI, between the EU Member States and Associated Countries, and a selected set of 10 third countries, including Canada, the United States, Mexico, Brazil, Chile, Argentina, South Africa, India, South Korea and China. This one of a kind consortium of EU and third countries partners will have a meaningful impact in accelerating the integration of gender equality in STI dialogues with third countries. The investigation will be conducted along the three objectives of the Gender Equality strategy in EU R&I, i.e. gender equality in scientific careers, gender in decision making, and gender in R&I content. Built on the work done by ERA-related groups on gender equality and international cooperation, as well as EU funded projects, GENDER STI will provide a mapping and comparative analysis on gender equality in STI bilateral and multilateral agreements with the selected third countries. In addition, the project will deploy a series of Co-Design Lab workshops to create the environment to co-design solutions regarding gender inequalities in STI dialogues. As a result, the project will create the GENDER STI Community of Practice that will help to scale up the experience of gender equality in STI at a European and international level, and the European Observatory on Gender in STI, which is unique of its kind in Europe and will serve as a hub for gender equality in STI dialogues, incorporating all knowledge and materials resulting from the project. These actionable insights will feed the process to formulate recommendations to enhance the integration of gender equality in STI dialogues with third countries.

The Austrian government is committed to accelerating the transition of its energy system and achieving CO2 neutrality by 2040. To achieve this goal, Austria must significantly step up its efforts to decarbonise all parts of its energy sector. Buildings account for about a third of the total energy demand. The government plans to phase out oil and coal heating systems by 2035 and limit the use of natural gas for heating in new buildings from 2025. Energy services such as predictive maintenance, demand-side management and model predictive control are central components for reducing the energy consumption of build-ings and transforming buildings into active, intelligent actors in higher-level energy sys-tems. The aim of BEYOND is to develop the technological foundation for “Next Generation En-ergy Services”, which is made possible by the interplay of the following technolo-gies: Virtual Reality for visualization and real-time interaction with the real building; Machine learning and physical simulation to show the real-life effects of interven-tions and decisions. IoT platforms for bidirectional real-time communication be-tween the building and its users. The technological developments are tested and evaluated on the basis of two use cases “Predictive Maintenance and Error Diagnosis” and “Human Aspects in Buildings”. Innovative companies in the field of energy services, building automation, simulation software and VR technology will benefit from the developments in BEYOND. Political decision-makers and end users will also benefit from the new possibilities of actively engaging with these next generation Energy Services.

In ParXCel, we will focus on the development of synthesis (e.g., configuration) and analysis algorithms (e.g., conflict detection and diagnosis) that help to tackle the above mentioned challenges. The overall idea of ParXCel is 1) to develop machine learning techniques for boosting the performance and prediction quality of constraint solving and 2) to develop parallelized approaches for efficient analysis operations (conflict detection and diagnosis). Major research contributions of ParXCel will be the following. First, we will focus on the integration of machine learning techniques with adaptive search heuristics. This will make it possible to transfer machine learning based prediction approaches to configuration scenarios and optimize the prediction of future user preferences. Second, we will parallelize existing algorithmic approaches especially in conflict detection and direct diagnosis [JUN2004, FSZ2012]. Parallelization on the algorithmic level, for example, on the level of conflict detection, provides the possibility of exploiting environments such as Java ForkJoin that support the implementation of parallelized algorithms.

Spreadsheets are omnipresent in organizations. They are used for a variety of purposes and in many cases, calculations in spreadsheets directly serve as a basis for reporting and for subsequent managerial decision making. One reason for the widespread use of spreadsheets is that they can be developed (“programmed”) by end users, e.g., an employee in the controlling department. Being able to develop one’s own data aggregation and decision support tools increases the flexibility for the end users. However, one potential problem with spreadsheets is that they are typically not subject to quality assurance (QA) processes that are common in traditional software development, like code inspections or systematic testing. In many cases, spreadsheet developers also lack the awareness regarding the importance of software testing. Moreover, today’s spreadsheet environments provide only limited functionality for fault avoidance, detection, and removal. As a result, faults are not uncommon in spreadsheets and numerous cases have been reported where such faults led to substantial financial losses for companies1 or to miscalculations in scientific investigations, for a prominent example in the field of economics. Due to the risks that can arise from faulty spreadsheets, researchers have proposed a variety of approaches to provide better tool support for spreadsheet developers. These techniques range from advanced spreadsheet visualizations, over algorithmic spreadsheet testing and debugging methods, to solutions that aim at the automated repair of erroneous spreadsheets. The proposed project continues these lines of research and specifically focuses on improved debugging support for spreadsheets. While existing work in that area often focused on algorithmic fault localization, recent research indicates that to be truly helpful for users, debuggers should offer more functionality than only providing ranked lists of fault candidates. In this project, we will therefore explore novel mechanisms for interactive spreadsheet debugging, which, for example, proactively guide the user to the true location of the fault. From a methodological perspective, one key aspect of our joint research project is that we follow a dual approach. Besides traditional computational experiments that, e.g., compare the fault ranking performance and the computation times of different techniques, we plan to run different controlled user studies, where study participants solve debugging tasks with the help of the tools that will be developed in the project.

Automated robot systems that are able to navigate in remote and challenging environments like alpine regions be a significant help end users mountain or constructors or of infrastructure (e.g paths or installation for protection). Such robots can perform automated transport of materials, tools, and persons as well as the automated execution of construction or maintenance actions (although the development of the actual manipulation actions is beyond the scope of this project). Endurance and payload issues renders the deployment of ground robots more realistically. Two main issues arise when deploying such robots in remote and difficult terrain. First in contrast to humans robots usually need a rather detailed maps of their environment to perform navigation; deriving and execution an efficient and safe path to a given goal. In engineered environments like urban areas or highways such detailed maps are available. In remote or unstructured areas these maps needed to be generated beforehand either by the robot itself or by other means like airborne systems. The fact that detailed maps for remote areas do not exist and the expensive pre-mapping step are obstacle for fast and efficient deployment. Second humans are capable to navigate in a challenging environment even with a less detailed map and a rough given route because of their superior perception and motion skills. Robots in contrat still need very detailed map and a high accuracy in their localization to perform challenging navigation task. In order to allow a ground robot to navigate efficiently and safely in remote areas to support end use activities RoboNav will aim at three main goals. First in close cooperation with the end users use cases will be defined that are relevant for the users but are also realistic and helpful for the participating users. The definition of promising use cases andrealistic requirements will maintain realistic expectations and acceptance by the users. The second goal of RoboNav is the development of a pipeline to convert earth observation data into routing data that can be used for the navigation. The important goal is here to avoid extensive preparation campaigns such as detailed mapping of the environment with the robot system itself or other systems like UAVs. Animportant innovation is here that the obtained routing data will be generated depending on the robot’s locomotion capabilities in order to allow broad and easy application of the approach. The third goal of RoboNav is to develop an integrated navigation concept that is suitable for automated navigation of a robot in the envisioned challenging environments. In order to achieve this goal the views and competences of two research disciplinesneed to be combined: geodesy and robotics. A suitable navigation concept including localization, routing and guidance will be replicated for the purpose of an automatically moving robot. The proposed navigation system will be implemented and integrated into a robot platform demonstrator. The integrated system will be evaluated in realistic field trials defined in cooperation with the end users. Deployments in the field but will also form a base for an economic exploitation by young participating companies from both disciplines.

Independent validation is fundamental to emphasise the capability and safety of any solution in the electric, connected and automated (ECA) vehicles space. It is vital that appropriate and audited testing takes place in a controlled environment before any deployment takes place. As the software and hardware components come from multiple vendors and integrate in numerous ways, the various levels of validation required must be fully understood and integration with primary and secondary parts must be considered. The key targets of ArchitectECA2030 are - the robust mission-validated traceable design of electronic components and systems (ECS) - the quantification of an accepted residual risk of ECS for ECA vehicles to enable type approval, and - an increased end-user acceptance due to more reliable and robust ECS. The proposed methods include automatic built-in safety measures in the electronic circuit design, accelerated testing, residual risk quantification, virtual validation, and multi-physical and stochastic simulations. The project will implement a unique in-vehicle monitoring device able to measure the health status and degradation of the functional electronics empowering model-based safety prediction, fault diagnosis, and anomaly detection. A validation framework comprised of harmonized methods and tools able to handle quantification of residual risks using data different sources (e.g. monitoring devices, sensor/actuators, fleet observators) is provided to ultimately design safe, secure, and reliable ECA vehicles with a well-defined, quantified, and acceptable residual risk across all ECS levels. The project brings together stakeholders from ECS industry, standardization and certification bodies, test field operators, insurance companies, and academia closely interacting with ECSEL lighthouse initiative Mobility.E to align and influence emerging standards and validation procedures for ECA vehicles.

Concepts for future, sustainable energy systems are characterized by a radical change in the entire system. Future intelligent energy systems will merge into an integrated overall system that must intelligently connect different sectors, (decentralized) generation plants and energy storage with each other. The growing availability of various energy-related data holds great potential for operating existing systems more economically and ecologically. This requires an infrastructure in which energy and information are transmitted seamlessly in real time to enable a reliable and economically viable energy supply. Furthermore, innovative solutions based on artificial intelligence, statistical methods and traditional physical modeling are required for the generation, provision and evaluation of these large amounts of data. Internet of Things (IoT) technologies are the backbone and an enabler of these intelligent systems. The IoT is a network of uniquely identifiable entities that exchange data and commands with minimal human intervention. Universal standards and IoT middleware platforms Many entities in the IoT are only compatible with those from the same provider. This results in a central difficulty in the IoT. Successful machine-to-machine communication requires that the collaborators use a common language. There are two ways to achieve interoperability: (i) establishing a universal standard, or (ii) using middleware as a translator. Universal standards are difficult to define and enforce. An example is sockets: for a century, different regions have had different standards. Middleware sits between entities and mediates between incompatible devices and applications. In the literature, IoT middleware is also referred to as an IoT middleware platform, IoT data platform or IoT platform. security and privacy The data generated in IoT applications not only includes control and control data, but potentially also personal data. This requires measures to ensure IT security (security) and privacy protection (privacy). In existing technologies, these points are often insufficiently addressed. There is currently a lack of analyzes that analyze measures that anchor security and privacy in the form of "security by design" and "privacy by design" directly in the middleware. In addition, it must be examined whether the data processing steps of the middleware can be abstracted to such an extent that sensitive data can be reliably identified as such in the middleware, regardless of the selected use cases, in order to be able to implement the corresponding methods for privacy and security.

The digitization of integrated, regional energy systems leads to the emergence of so-called cyber-physical energy systems, which are based on the integration of software components and physical processes. In the analysis and optimization of these systems, modeling and simulation methods and tools are of central importance. New requirements for modeling and simulation are due to a steadily growing amount of operating data from Internet-of-Things (IoT) sensors and the blurring of the sector boundaries between electricity, gas, heating, cooling and mobility. Data-based machine learning (ML) methods are successfully used for the simulation and modeling of physical systems. However, traditional methods of machine learning reach their limits, especially with dynamic physical processes 5 7. Especially in situations in which data acquisition is complicated or expensive, it is often difficult to learn complex relationships from sparse or incomplete data. Furthermore, the physical plausibility of the results is a central framework condition for many ML applications. Techniques and methods that can meaningfully combine established physical modeling as well as existing specialist and domain knowledge with machine learning (e.g. in the architecture of deep learning networks that are influenced by the equations of the underlying physics) are promising candidates for this problem to solve. The development of domain-informed, interpretable and robust ML methods and algorithms were defined as a central research requirement in the field of artificial intelligence 6. Machine learning and physical modeling models are very often in direct competition. While it is unlikely that purely physical models will be completely replaced by data-driven models, the combination of the two modeling paradigms opens up new possibilities.

Analysis of the current status, interviews with strategic technology, evaluation of the technologies/architectures, evaluation of the process model, elaboration of additions/improvements, reports/recommendations.

In the area of digital transformation, when Flexibility in manufacturing of complex products becomes the key competitive advantage, Artificial Intelligence (AI) is the accepted method to drive the digitalization for the transformation of the industry and their industrial prod-ucts. These products with highest complexity based on multi-dimensional requirements need flexible and adaptive manufacturing lines as well as flexible com-ponents. One of the examples is the automotive indus-try and the products based on high semiconductor con-tent for functional integration, such as highly auto-mated cars, aircrafts, and also the related industrial and manufacturing itself. This change will enable new in-novative industrial and manufacturing models. New process management approaches emerge with the use of data science as a core strategy in the organization and management of these networking manufacturing sites. With deterministic data, the classical approach performs best. However, when only empirical data are available, AI be-comes the option of choice, especially in networking manufacturing sites which are typical in the semiconductor manufacturing and the novel ISLAND approach of the automotive industry away from the linear production with less potential for further flexibility and faster response times.

The increasing digitalization and automation through the use of Artificial Intelligence (AI) of the working world (industry 4.0, Smart Logistics, Big Data, etc.) and our everyday life(assistance systems, smart devices, social media, etc.) posts great challenges for society and education. This ranges from building awareness, increasing acceptance and teaching thefoundations of the technology, to fostering a meaningful, creative usage as well as an assessment of threats, risks as well as opportunities and potentials. The program area ischaracterized by a few urban centers and a large number of rural regions. To prevent a brain drain from the program area as well as to ensure a sustainable and responsible usageof technology, young people with skills to understand and use these new technologies are required. AI applications in particular allow an added value away from urban centers orwithout access to natural resources. Stimulating enthusiasm as well as facilitating a basic understanding has to be done at an early age. This provides a sound basis for youngpeople’s decision to pursue a career (job, training, study) in an AI related sector. The project addresses these challenges at two levels: On the one hand, fostering young people’s(aged 10-14) interest in AI and facilitating a basic technical understanding at an early age. In this context, the integration of teachers and instructors, using a train-the-trainerapproach is the key and ensures a broad and sustainable dissemination. On the other hand, building awareness regarding social, economic and technical aspects and potentials of AIamong the general public (children, parents, apprentices, working persons, etc.) using open, low-threshold activities. Since the described challenges concern the entire program area,a cross-border project implementation is vital.

An urgent task for future energy systems is the design and operation of systems that integrate a large proportion of renewable energies and at the same time improve the overall efficiency of the system. In this context, buildings are of central importance: buildings are responsible for 32% of total global final energy consumption and 19% of energy-related greenhouse gas emissions; In the European Union, buildings are responsible for 40% of total energy consumption. The optimization and design of energy systems for residential and office buildings as well as buildings in a network (city districts, energy communities, etc.) is therefore of great importance within the sustainable energy transition. An essential goal of such intelligent energy systems is not only decentralized, locally produced and sustainable energy to match the requirements of the higher-level network (electricity, heat, cooling) as best as possible, but also to actively involve users in the energy system. In contrast to an outdated energy system, in which users were viewed as passive, ignorant consumers, the energy transition requires active participation and participation by everyone. Energy systems have to be developed and optimized with and for the user. The provision and use of data by users plays a crucial role in this process. The omnipresence of data is said to have great potential for operating buildings and energy systems more economically and ecologically. Technical developments enable ever faster and more comprehensive data acquisition, data transmission and data processing. These systemic changes provide an ideal breeding ground for innovations that use this data for new energy services. The data from and about users play a central role. Although a substantial part of the data can be automatically recorded and processed (e.g. with sensors, smart meters or web scraping), the direct involvement of users and the direct query of personal preferences, behavioral intentions and system assessments (for example with regard to the perceived comfort) Great potential for the development and optimization of innovative energy services to support the energy transition. In the ANSERS project, we combine psychological insights into user activation and user participation with cutting-edge software technologies. This interaction is of central importance for future intelligent energy systems, which promote the reduction of energy consumption and enable energy services such as demand response, peer-2-peer trading or the optimal control of interconnected energy systems. To do this, however, it is necessary, on the one hand, to fundamentally understand and optimally address the psychological determinants of user participation in Energy Services and, on the other hand, to make the best possible use of the data and the system both with regard to the requirements of the higher-level network and with regard to the Optimize user requirements.

The aim of ROBO-MOLE is to increase the safety for responder and civilians in tunnels or other sub-terrain buildings by the detection and identification of hazard materials, providing an actual situation map and to improve the efficiency of disaster response missions. For instance after a accident with a dangerous goods transporter in a tunnel responder are faced with severe and dangerous challenges due to heat, structural danger, smoke or exposure to hazard material. Thus, a semi-autonomous robot for supporting analyzing tasks will be developed, that is equipped with a broad range of sensors (position, imaging, hazard material). The information of these sensors will be fused to allow safe navigation and control of the robot under challenging conditions (smoke, heat, debris) and to detect and map hazards.

IntelliServ is an AI and recommender-based platform that offers intelligent support for the service processes of systems and devices: Service processes must be planned in the office and then carried out on site in the form of maintenance, tests and repairs on devices and systems. The system offers "intelligent" support by analyzing and aggregating all available data in the background in order to process them using technologies from the field of AI and recommender systems. The aim is on the one hand to support those responsible in the office and on the other hand to support the implementation staff in making their work more efficient.

Networks are present in our lives in numerous different environments: to name just a few, networks can model social relationships, they can model the Internet and links between web pages, they might model the spread of a virus infection between people, and they might represent computer processors/sensors that have to exchange information. This project aims to obtain new insights into the behaviour of networks, which are studied from a geometric and computational perspective. Thereto, the project brings together researchers from different areas such as computational geometry, discrete mathematics, graph drawing, and probability. Among of the topics of research are enumerative problems on geometric networks, crossing numbers, random networks, imprecise models of data, restricted orientation geometry. Combinatorial approaches are combined with algorithms. Algorithmic applications of networks are also studied in the context of unmanned aerial vehicles (UAVs) and in the context of musical information retrieval (MIR). The project contains the work packages: “Geometric networks”, "Stochastic Geometry and Networks", “Restricted orientation geometry”, “Graph-based algorithms for UAVs and for MIR”, and “Dissemination and gender equality promotion”. The project connects researchers from 14 universities located in Austria, Belgium, Canada, Chile, Czech Republic, Italy, Mexico, and Spain, who will collaborate and share their different expertise in order to obtain new knowledge on the combinatorics of networks and applications.

The SurveyHub project aims to develop a modern web application for the evaluation, visualisation and further work with the results of employee surveys. The main aim is to support large companies in overcoming the content-related and logistical hurdles of national and international employee surveys. SurveyHub pursues the following 5 core objectives. 1: 1. to create a DSGVO-compliant and user-friendly online platform for the evaluation and presentation of employee survey results that takes into account Austrian and Central European specifics. 2. to make results data from any online survey system accessible and retrievable via API. SurveyHub is not a "survey platform" but a survey-neutral "evaluation platform". 3. The quantitative result data of employee surveys should not only be presented statistically, but should also be prepared didactically and visually for the target group "managers and employees" in companies. The target groups should be guided through the results in order to better understand their meaning. 4. The qualitative result data in the sense of open comments should be evaluated by content-analytical algorithms and processed in the same way. We want to make accessible the rich wealth of experience and opinion in companies that otherwise lies fallow. 5. We want to digitalise the process of collecting and working with the results and thus accelerate it. It should be possible for clients to receive the results of surveys in hours, not weeks. Managers in client companies should be able to quickly capture the core content of their surveys and process them in a time-saving manner.

It is predicted that over 50 billion intelligent objects - smart things - will communicate with each other in the Internet of Things by 2020, allowing for numerous everyday applications. For example, cars will be able to communicate with each other on the streets to prevent accidents, and tailor-made furniture will be able to tell industrial production machines what exactly needs to be done to them. One day, the Internet of Things will be as important as the power grid is today. There is, however, still much research to be done, especially regarding the reliability of the Internet of Things. In particular, critical applications in health, traffic and production need to function perfectly at all times. Lead project researchers in the Field of Expertise Information, Communication & Computing at TU Graz are working on fundamental aspects that will enable computers embedded into everyday objects to function reliably, even under the most difficult conditions.

In this project, research will be carried out to document thermal engineering applications in which system improvements can be achieved through innovative control approaches. In doing so, not only methods known from control and system engineering will be considered, but also artificial intelligence (AI) methods in particular. To substantiate the potential for further research activities regarding AI in thermal engineering, a comparison between conventional control strategies and AI-based methods is aimed at.

Future intelligent and integrated energy systems must have a high degree of flexibility and efficiency to ensurereliable and sustainable operation. Along with the rapid expansion of renewable energy, this degree of flexibility and efficiency can be achieved by overcoming the clear separation between different sectors and by increasing connectivity and the associated data availability through the integration of sensors and edge/fog computing. All of these developments drivethe transition from towardsso-called Cyber Physical Energy Systems. The cyber technologies (sensors, edge/fog computing, IoT networks, etc.) areable to monitor the physical systems, to enable communication between different subsystems and to control them.Modelling and simulation tools are of central importance for the optimal operation of integrated energy systems. Due to the above-mentionedcharacteristics of future intelligent energy systems, the requirements for modelling and simulation have heightened. Project results and findings in the literature have shown that in the field of modelling and simulation, the combination of three paradigms is of major importance: the description of physical components by differential-algebraic equations, the description of discrete systems by discrete-event models and learning from data by means of machine-learning algorithms. The arguments for the "why" in the field of intelligent, integrated energy systems have been clearly established; however,the "how" remains an open research question. The exploratory project NextHyb2 addresses this research gap by exploring the concept of hybrid-hybrid system simulations for integrated energy systems. Methods, tools and systemic solutions will be developed and evaluated together with experts. Furthermore, the solution will be implemented and tested on the basis of a proof of concept.It can be assumed that in most future research and development projects in the field of integrated energy systems, the tools of modelling and simulation will playan integral part. Their role will assit in optimisingthesetup and operation of energy communities or for building models for prediction and diagnosis in the field of energy networks. The project results should serve to ensure that these future projects can be based on an objective and rationally comprehensible evaluation of the possibilities and fundamental limitations in the field of hybrid-hybrid system simulations. Thus, the project serves as preparation for future research and development projects in the field of intelligent, integrated energy systems.

Micro-structured surfaces (riblet surfaces) reduce drag, and as a consequence, allow increasing efficiency in various flow applications. Therefore, riblet surfaces can save fuel consumption substantially in industrial applications like aircrafts and high-speed trains or to increase energy output of wind turbines and lower noise emission. In the last ten years industry did massive investments in the development, production and application of riblet surfaces. Efficiency gains depend on the quality of the riblet surface. Therefore, it is very important to make use of special inspection equipment in order to assure the quality of the riblet surface in terms of their expected reduced drag behavior. Unfortunately, the current inspection processes being used are very timeand cost- intensive. Thus, there is a need for easy to use and inexpensive inspection devices allowing to estimate the riblet surface’s properties during maintenance processes on several applications (aircrafts, wind turbines, etc.). RiSPECT proposes to apply machine learning and in particular deep neural networks for classifying and predicting the quality of riblet surfaces for the first time. The proposed approach makes use of example images obtained from available riblet surfaces and simulations for this purpose. Because of the need for having a larger number of labelled images comprising riblet surfaces with and without defects, RiSPECT will provide a database of such images that are acquired using a tailored machine vision system to be developed as part of the project. The images stored in a database rely on EASA certified riblet test bench, high precise SEM pictures and CFD simulations. Because of the fact that machine learning applications based on neural networks are vulnerable, verification & validation becomes a critical issue of RiSPECT. In particular, the focus will be on how to prevent small image changes that lead to misclassification and erroneous quality predictions. This will increase the robustness of the overall application. The main objective of RiSPECT is to come up with the foundations behind an automated system for estimating the quality of riblet surfaces based on image data that reduces the overall costs for quality assurance measures within the riblet surface maintenance. For this purpose, RiSPECT also includes a sophisticated case study to be carried out at the end of the project.

This project aims to investigate the possibilities for a passive infrastructure-less self-localization by vehicles for navigation purposes. Such localization is an essential precondition for the half-autonomous control of convoys, which was raised by the military user. Up to here autonomous car navigation in nearly all variants is supported by global navigation satellite systems (GNSS) and / or active sensors (radar, lidar). For reasons of defilade active means must be waived. Off-road driving conditions do not offer any infrastructure. And GNSS must be waived, too, since it aggressively may be jammed or spoofed. The remaining means are mainly camera based localization, inertial navigation and the evaluation of the vehicle’s sensor data. It is now necessary to investigate by which algorithms and methods a reliable localization is possible, based on only these reduced means. These are now the goals of the project, to reach an automated vehicle’s localization under the above mentioned conditions. Firstly it is necessary to obtain realistic data sets from cameras, inertial measurement unit (IMU) and from the vehicle’s sensors and to emulate autonomous driving conditions. For this purpose drive-by-wire capabilities of the test vehicles will be implemented, which up to here is prohibited in road traffic. Using drive-by-wire omits those characteristics of the vehicle’s control, which are generated by the driver’s subjective impressions. Especially in off- road conditions reflexive reactions by the driver may be significant. In a totally new approach the data from the cameras, from the IMU and from the vehicle’s sensors will be used to generate a map of the driven path and to estimate the vehicle’s location with respect to the map. Obstacles will be recognized and the vehicle will be stopped. Technology readiness level 1 (TRL 1), the proof of the basic principle, is already given and is the starting point of the project. With the successful experimental proof finally TRL 3 will be prepared and reached. According to the low TRL, some simplifying conditions will be established, like a speed limit of 30 kilometers per hour or constant vegetation conditions. Target goals and findings are the successful implementation of a demonstrator of principle. For validation purposes a reference trajectory with all available means (GNSS, etc.) will be acquired, too. The found trajectory in comparison with the reference trajectory finally shall reach an accuracy which is acceptable for the targeted application. Challenges in the methods shall be recognized and shall be accordingly be addressed. Visual localization, inertial navigation and also the evaluation of the vehicle’s sensor data are affected by systematic inaccuracies, which is to be eliminated by data fusion techniques as much as possible. The concrete project results are the algorithms for determining the trajectory, which are openly explained and documented in the project’s reports. Further the acquired data sets and their analyses are part of the project results and the documentation of the experimental setup.

The development of 3D city models enables the integration of city and building levels into a single model that contains both semantic and geometric information. These models can be used to help stakeholders such as policymakers, city planners, energy providers and suppliers, and citizens make decisions and improve communication and public relations. The highest form of visualization in this area is the use of virtual reality technology. CityGML is an international, widespread standard of the Open Geospatial Consortium for the modeling, storage and exchange of 3D city models; the Open Geospatial Consortiums regards the connection between virtual reality and CityGML as one of the greatest challenges in research and development. In this project two central research aspects in the area of ​​3D city models are addressed. (i) How can virtual reality be used as the highest form of visualization in the area of ​​3D city models? What use cases are there for virtual reality in the area of ​​3D city models? Answers to these questions are developed together with stakeholders and users; the focus is on energy-relevant applications. In the project, a methodology is being developed that enables automatic creation of virtual reality content from CityGML models in combination with energy-relevant extensions such as Energy ADE; Furthermore, the results of dynamic simulation results of energetic analyzes such as the electricity, heating and cooling requirements of a district are shown virtually. Finally, possibilities and limits of virtual reality in the field of 3D city modeling are explored in coordination with relevant stakeholders. (ii) The modeling of the energy structure of larger urban units is characterized by a lack of descriptive input data. In many cases, data sets are incomplete or certain use cases require additional information that is not represented in the corresponding data model; Furthermore, it can be assumed that virtual reality applications require additional data that is neither contained in the current CityGML format nor in ADE extensions. In all of these cases, an "enrichment" of the original data record is necessary in order to provide all the necessary data. Artificial intelligence and statistical methods are promising here: Missing information is calculated using other attributes and heuristic approaches. The planned project is embedded in international developments and projects in the CityGML and Energy ADE area as well as in the BIM2Sim and BIM2CityGML area.

Arrangements of geometric objects and drawings of graphs lie at the core of modern Discrete and Computational Geometry. They serve as a exible tool in applications in both mathematics and computer science, since many important problems that involve geometric information may be modeled as problems on arrangements or graphs. Therefore, the study of these structures and a better understanding of their properties impacts a wide variety of problem domains. This DACH project \Arrangements and Drawings" connects groups that have already cooperated successfully in the European collaborative research programme EuroGIGA. In this follow-up project, we plan to investigate the relationships between different types of drawings and arrangements, as well as their abstract representations and their algorithmic properties. We have composed a list of challenging problems from the following four focus areas: (A) Arrangements of lines and pseudolines, (B) Drawings of graphs, (C) Structure of intersection, and (D) Planar and near-planar structures. The goal of this project is to gain insights in order to broaden our understanding of these areas and to jointly attack some of their long-standing open questions. These questions are notoriously diffcult though important, so that even partial solutions are expected to have impact.

Children between the ages of 7 and 15 are very interested and inquisitive in MINT topics (mathematics, computer science, natural sciences and technology). Primarily in elementary school age or before puberty, girls are just as interested in MINT topics as boys. It is important to maintain and strengthen this interest, especially that of the girls. The world of technology, computer science, natural science and mathematics is fascinating for children and young people. And we want to promote this fascination. The children and young people want to learn the basics of computer science and programming / coding in a playful and creative way. It is very important for this target group that they are playfully accompanied through the learning process. The children and adolescents respond particularly well to young adults as trainers, who bring the content closer to them in age-appropriate language. In our courses, a pair of trainers is always used and the content is chosen so that there is something suitable and interesting for everyone. The children experience the world of programming and robotics through self-programmed games and animations and learn that programming is creative and exciting. This increases our motivation and enthusiasm for the MINT area. Programming languages ​​and robotics have only recently become part of the current curricula for grades 3 to 8 at Austrian schools. This also means that the training of pedagogues in this area is still in its infancy. Additional offers for interested students are usually only available in large cities, children and young people in rural areas are less accessible. The pandemic also makes it more difficult (lockdown or temporary closure individual classes / schools) holding on-site workshops since March of this year. The Austrian labor market urgently needs (young) specialists from the MINT area. The need for skilled workers in these areas is high and continues to grow. Early promotion of enthusiasm for MINT subjects, the anchoring of interdisciplinary and digital skills in all training courses are important levers for securing the future of Austria.

In the project "Alert" we investigate and analyse intrusion-detection systems (IDS) appropriate for the control-networks of (nationwide) high voltage power grids. A special focus in this project will be on anomaly-detection techniques and their integration with other methods. This will allow us to detect also unknown attacks, so that a security information and event management system (SIEM) can raise the appropriate alerts as soon as possible, and so that we can use such data also in the context of prevention mechanisms in order to mitigate arising issues (IDPS).

The central goal is the development of a mobile application that enables the energy optimization and planning of buildings, neighborhoods and higher-level energy systems through the participation of the user and the user as a new source of data and information. The development of the application is strongly transdisciplinary and integrates mathematical methods of simulation and optimization as well as psychological aspects of user behavior in order to develop new business models and open up new markets.

Automated driving is a disruptive technology which opens the door to future multi-billion markets providing business opportunities to value chains in automotive and semiconductor industry.The European industry has leading competitive strength in the development and manufacturing of highly reliable electro-mechanical systems. In order to preserve this capability Europe needs to setup European standards for high level control such as real-time computing or big data processing. In order to respond on the global challenge AutoDrive has gathered Europe’s leading semiconductor companies, suppliers, OEMs, and research institutes committed to create a pan-European eco-system, which has the critical mass to initiate standards and provides the components and subsystems for automated driving. Currently, even the most sophisticated vehicle automation technology on the road is not able to surpass human driving capabilities – especially considering context awareness in any situation. Moreover, there is no common agreement on quantifiable dependability measures which hardware and embedded software have to achieve to allow safe automated driving for SAE Levels 3-5. AutoDrive aims for the design of (i) fail-aware (self-diagnostics), (ii) fail-safe, (iii) fail-operational (HW and SW redundancy) electronic components and systems architecture that enable the introduction of automated driving in all car categories. AutoDrive results will significantly contribute to safer and more efficient mobility. It will raise end-user acceptance and comfort by supporting drivers in highly challenging situations (active safety) as well as in regular driving situations. Combining both will reduce the number of road fatalities especially in rural scenarios and under adverse weather conditions. AutoDrive will contribute to Europe’s Vision Zero and to improved efficiency. This will sustain Leadership and even grow the market position of all AutoDrive partners.

Over the next 10 years, lower birth rate students born in 1999-2010 will graduate and enter their professional career or university. The retiring workforce will not be completely replaceable by those. If nothing changes, the Austrian workforce will drop to 77% in the next 20 years and to even 65% among the under 40s. At the same time, the demand for IT professionals will be increasing, with a dramatic impact on the industrial and economic region. To counteract this, we want to inspire young women and men with playful coding activities to choose IT related jobs or studies. The number of young people and women in particular choosing to study in ICT fields is decreasing dramatically. To address this gender bias at an early stage, one of the goals of this proposal is to make coding more accessible and attractive for young females. Therefore, we will use our educational app Pocket Code, which is developed by the Austrian free and open source project Catrobat, initiated at Graz University of Technology. The app Pocket Code allows the creation of programs in a playful way and directly on phones. To make the app more interesting and attractive for our target group of young women between 12 and 15 years old, we are planning to extend the app with the option to program embroidery machines. In this way, self-created patterns and designs can be stitched on t-shirts, pants or even bags. With Pocket Code, the embroidery machines will get programmable. Patterns and different forms can be created using a visual programming language. As a result, teenagers have something they can be proud of, something they can wear, and they can show to others. For this purpose, a new version of Pocket Code for pattern embroidery will be developed, which should attract especially young women and girls. Furthermore, appropriate stitch/coding courses will be offered at schools. A special emphasis will be given to a gender-equitable conception to consider different requirements, needs and interests of our target group. These courses will be realized together with our partner "bits4kids". On the one hand they are intended to show young women new ways of using technology, with a lot of fun in a sustainable way. On the other hand, young men get inspired through this digital design process to take part in textile handicraft lessons. The cooperation with the fashion shop "Apflbutzn" will help us to picture the whole workflow. The Apflbutzn team will take part in the last units and bring their embroidery machine. Thus, the teenagers are able to see how their programmed patterns are directly embroidered on T-shirts and bags. In addition, “Apflbutzn” will create an economical and sustainable concept, which can be integrated into existing (web-)shops and processes. In future, the pattern-files can be sent via mail and the embroidered products can be picked up or shipped. The project’s outcomes will be 1) a new version of the Pocket Code app, which includes the stitch extension, 2) a gender-equitable framework for stitch/coding courses, and 3) insights into the practical implementation for shops. As a result, the new Pocket Code Stitch App and the published gender-appropriate "guidelines" should show how young women could be motivated and, thus, they should serve as a guideline for others (Fab-Labs, schools, etc.).

Significant efforts are made, during spacecraft development activities, to build discipline models, e.g. thermal mathematical models. Yet, a large effort is spent during operations for anomaly root cause analysis as these already existing models are not used in fault identification. The main aim of the project is to combine models and flight data, acquired during the operation of a spacecraft mission to improve spacecraft and mission fault analysis, prediction of spacecraft behaviour, and discipline models.

In this project, we seek to develop new security testing concepts for web technologies in general, suitable for black-box testing as well as integration into development workflows. XSS is only one form of injection; we want to explore a variety of other possibilities such as Content Injection on the client side (which has very different requirements regarding its output context; it also allows us to examine new delivery methods like HTTP Header Injection) and SQL injections on the server side. Both lend themselves to be the focus of research due to their popularity, high impact and oftentimes slow adaption and low quality of countermeasures. We will further advance the underlying methodology by improving both the generation/selection of attack vectors (test cases) and the localization of sanitization bugs. Ultimately, we plan to create a prototype combinatorial security testing framework for web technologies to validate our approach.

The future development of the economy, prosperity and quality of life in Europe will strongly depend on the following factors. Modern processes and methods are crucial for competitive products on a global scale. Smart production as the interplay of robotics, computer science and artificial intelligence (AI) will become more and more important. Furthermore, novel and innovative products and services will be necessary to develop the economy sustainably. In order to enable such products young people with knowledge and skills in robotics and AI will be needed. An appropriate developed labour market will significantly contribute to the strategic goals (smart, sustainable, inclusive growth) given by the underlying cooperation programme. Novel ideas and improved human capital enable companies to generate qualitative jobs in the project region. All this will contribute to the strategic goals as well as the operative goal of strengthening the labour market. In order to achieve this we propose to establish a standardized training and certification system for young people in the areas of robotics and AI. The training will be on a high professional level allowing the young people to develop an exceptional and satisfying career. A professional certification system similar to the ECDL as well as the involvement of stakeholders (educational institutions, public institutions, companies, …) in the project development will foster a great acceptance of the provided training system and will also allow companies and educational institutions to recognize the obtained skills of young people. The "train the trainer" approach will allow to roll out the system in the entire project region. Because the above problems exist in all areas of the project region such a project needs to be developed in a cross-border fashion.

Requirements Engineering is a key activity in ICT projects: What are current user needs and what requirements satisfy them? How much effort would a requirement cost and in which release should it be delivered? Which requirements can be reused from similar projects? Are there hidden dependencies or inconsistencies? What trade-offs are acceptable for users and other stakeholders? A satisfactory, efficient answer to these questions is essential for the success for nowadays software projects. OPENREQ leverages modern recommender algorithms, semantic technologies and data-mining to provide intelligent, proactive support for stakeholders survey alternatives and make individual or group decisions. OPENREQ focuses on complex, community-driven ICT projects with various dependencies and stakeholders as in the Telecom, Transportation, and Cross-Platform-Software domain covered in our trials. We will develop, evaluate and disseminate a fully integrated open-source requirements management platform and a set of connectors with the following decision-making capabilities: Requirements Intelligence: monitors the actual software usage, collects stakeholders’ and users’ feedback (e.g. from social media), aggregates and visualizes this information as predictive analytics. Stakeholder’s Personal Recommender: implements advanced recommendation and machine-learning algorithms to assist requirements work, improve a requirement’s quality, estimate its properties or predict relevant stakeholders. Group Decision Support: enables the stakeholders’ participation, the resolution of preference conflicts, and the identification of consensus, e.g. during release planning. Dependency Management: semi-automatically identifies requirements dependencies, supports requirements reasoning and reuse of requirements knowledge. With the OPENREQ Interfaces, these capabilities will be integrated

Analysis of status, assessment of technologies and architectures as well as process models, elaboration of amendments and improvements.

The main goal for the planned SMF project is to prepare competitive and comprehensive proposals for the EU funded project to submit under H2020 call or similar large-scale transnational calls (e.g Interreg SI-AT cooperation programme Austria-Slovenia, Interreg Central Europe, AMIF, DG calls). In relation to this, the SMF project aims to develop a strategic and transnational project that builds on the project DRIM's (Danube Region Information Platform for Economic Integration of Migrants) main outputs, specifically a) Danube Compass information platform with information designed specifically for migrants and public authorities working with migrants in the region, as well as b) Strategy for effective information sharing for migrants in the Danube region. The objective of this SMF project is to prepare a proposal that will use the vast database collected for Danube Compass information platform (information for migrants in 8 countries and 12 migrant languages) and create an interactive format that allows upgrading of skills of users aiming to improve employability and entrepreneurial abilities of our main target groups (refugees and migrants). By developing a technologically advanced information dissemination tool that will be more user-oriented (through personalized content recommendations) we want to establish a sustainable ICT-tool for efficient interaction between public authorities and private users (by including concepts like "wisdom of the crowd"). The main planned activities of the SMF project are to prepare a plan how to reach an innovative yet sustainable output by finding ICT solutions for facilitating refugee integration through: - innovative learning and artificial intelligence systems - to build a multidisciplinary consortium (IT, knowledge providers, user researchers, NGOs, public authorities) - to prepare a viable and detailed budget that reflects the real needs of the partners to achieve the project goals.

Currently, a tourist cannot get the desired information in an integrated way from both the humans and Web services, and much less the joint Austrian-Slovenian services. Typically, Slovenian or Austrian tourist office will provide only predefined national tours and not user-centric cross-border tours. As a consequence, tourists may miss locations they might be interested in visiting and tourist locations get less visits. The goal of the project is to create a joint Austrian-Slovenian center - an ICT supported network of service providers and tourist offices, municipalities, tourists and citizens to enhance continuous cooperation between them. Thus, cross-border tourist exchange, collaboration and expertise transfer between providers will largely increase with respect to the current state. The main project output will be the operational center with humans involved, having support of the following tools: Virtual assistant (providing automatic answering in natural language to the questions and performing services) according to demands from tourists, Communication service (ICT solution that will enable conversation between the tourists, virtual assistants, tourist information workers and local communities), Information sources (inclusion of existing information sources), Recommender system for tour planning, Network of tourist services and services from local communities. The system will help tourists better plan their cross-border visits, discover less popular sites that would otherwise be missed, stay longer and better satisfy their needs. Local communities will easily offer local services and information to visitors, e.g. a tour might include visiting a specialized craftsman and boost selling local products. Tourist officers will get better access to tourists. Project provides the integration of virtual and human services from Austria and Slovenia with the uniform functionality - to provide most relevant information, attract the tourists, and prolong their stay.

Technologies to support recommendations in financial services scenarios.

We propose a research project in the field of computational geometry, a sub-field of mathematics and theoretical computer science that focuses on the theoretical backgrounds of how computer programs can process geometric entities. Our research has applications in extremal combinatorial geometry, where we are interested in estimating the numbers of different “networks” defined by straight-line connections drawn between sites (represented by points) on a flat surface, similar to straight routes connecting cities on a map. Such drawings are called geometric graphs. Geometric graphs can be classified in various ways, for example whether or not they contain crossings or cycles. For many classes without crossings, it is known that the number of different geometric graphs (obtained by connecting given points) is minimized when the points are placed on a circle. Analogously, arranging the points in that way maximizes the number of such graphs for many geometric graph classes with crossings. One objective of our work is to characterize point sets that maximize or minimize the number of geometric graphs for certain classes. For such problems, we are usually not interested in the exact position of the points, but how they are placed relative to each other, since, in general, our problem does not change if we slightly move a few points. The “order type” of a point set tells us in which order we encounter three points of the set when walking along the boundary of the triangle defined by these points in counterclockwise direction; that is, we get the orientation of each triple of points. In previous work, we defined a relation on order types by comparing the set of crossing-free geometric graphs each order type admits. We characterized order types among which there are point sets that have the most or the least number of certain classes of geometric graphs. However, this characterization is rather general. We plan to obtain relations between order types that provide more insight into the structure of maximizing and minimizing point sets. In particular, we are interested in bounding the number of triangulations (geometric graphs in which each bounded area is a triangle). We will attempt to prove a longstanding conjecture stating that the number of triangulations is minimized by a certain order type, using the insights obtained from different relations and local transformations (for example changing the orientation of a single point triple). Apart from bounding the number of geometric graphs, we are interested in relations between different order types in its own right. We will analyze different types of local operations that allow transforming one order type into another.

ENABLE-S3 will pave the way for accelerated application of highly automated and autonomous systems in the mobility domains automotive, aerospace, rail, maritime and health, through provision of highly effective test and validation methodology and platforms that will save significant fractions of field tests. Virtual testing and verification and coverage-oriented test selection methods will enable certification of these systems with reasonable efforts and project results will be considered for standardization of such systems. This overall goal is founded on following technical Objectives: 1. ENABLE-S3 will provide a modular verification and validation framework that proves the functionality, safety and security of ACPS. 2. ENABLE-S3 promotes a new technique for testing sensor-based ACPS with physical sensor signal stimuli generators, which will be demonstrated within the use-cases. 3. ENABLE-S3 aims to significantly raise the level of dependability of automated systems and minimizing the risk of design or implementation faults by the provision of a modular comprehensive verification and validation platform and systematic coverage measures. 4. ENABLE-S3 will provide a validation environment for rapid re-qualification, which will allow reuse of validation scenarios in at least 3 development stages. 5. ENABLE-S3 will promote and extend existing standards as well as establish new open standards to speed up the adoption of the new verification and validation methods and tools for ACPS. 6. ENABLE-S3 aims at developing validation and verification bricks applicable across 6 industrial domains (Automotive, Aerospace, Rail, Maritime, Health, Farming). 7. ENABLE-S3 aims for the creation of an eco-system (incl. LEs, SMEs, NGOs and academia) for the validation and verification of automated systems within the European industry.

In the study to be developed we are tackling the case of testing HSU circuits and systems.

AGILE project aims to create an open, flexible and widely usable IoT solution at disposal of industries (startups, SMEs, techcompanies) and individuals (researchers, makers, entrepreneurs) as a framework that consists of: • A modular IoT gateway enabling various types of devices (wearables, home appliances, sensors, actuators, etc.) to be connected with each other and to the Internet; • Data management and device control maximizing security and privacy, at local level and in the cloud, technologies and methodologies to better manage data privacy and ownership in the IoT; • Support of various open and private clouds; • Recommender and visual developer’s interfaces enabling easy creation of applications to manage connected devices and data; • Support of mainstream IoT/M2M protocols, and SDKs from different standardization bodies for device discovery and communication; • Two separate gateway hardware versions: a) the ‘maker’s version, based on the popular RaspberryPi platform for easily prototyping and attracting the current community; b) the ‘industrial’ version for more industrial and production-ready applications; • An ecosystem of IoT applications shareable among users and developers leveraging on existing initiatives by key stakeholders in this domain, like Canonical and Ubuntu Snappy IoT ecosystem. Piloted in relevant open areas (fields and in a port) for field & cattle monitoring through drones, air quality & pollution monitoring and in smart retail, AGILE will be easily adaptable and usable in different contexts serving as an horizontal technology for fast IoT prototyping and engineering in different domains. Following an open hardware/software approach, harnessing the power of IoT developers and entrepreneurs communities, AGILE aims to offer tools to overcome limitations imposed by closed and vertical walled gardens for IoT apps development,

High Performance Sailing (HPS) is an international initiative of TU Graz together with other universities, research groups, the industry and other associations related to sailing. The main objective of HPS is the development and evaluation of methods, techniques and processes in the area of sailing regatta, where the aim is to provide tools well suited during races in order to support sailing teams drawing decisions. In addition HPS is intended to support other activities in the area of high performance sailing. HPS at TU Graz is organized in a multidisciplinary fashion working across faculties. The steering committee comprises Christof Sommitsch (Institute of Materials Science and Welding), Siegfried Vössner (Institute of Engineering and Business Informatics), and Franz Wotawa (Institute for Software Technology). This multidisciplinary approach combining different core competences ensures a holistic view on the topic and thus solutions of high quality. In addition, HPS aims at bringing together all students and employees having interest in sailing in order to bring in their technical expertise for solving challenges related to support tools for sailing. Sailing in this context stands for both, the technological innovation as well as for a sustainable and clean mean for transportation and thus nicely fits into the research agenda of TU Graz.

Geometric objects such as points, lines and polygons are the key elements of a big variety of interesting research problems in computer science. With the rise of modern technologies, more and more of these tasks are solved by computers, as opposed to the classic pen-and-paper approach. Over the last thirty years, researchers around the world have developed different techniques and algorithms that take advantage of the structure provided by geometry to sIn this thesis we consider triangles in the colored Euclidean plane. We call a triangle monochromatic if all its vertices have the same color. First, we study how many colors are needed so that for every triangle we can color the Euclidean plane in such a way, that there does not exist a monochromatic rotated copy of the triangle or a monochromatic translated copy of the triangle. Furthermore, we show that for every triangle every coloring of the Euclidean plane in finitely many colors contains a monochromatic triangle, which is similar to the given triangle. Then we study the problem, for which triangles there exists a 6-coloring, such that the triangle is nonmonochromatic in this 6-coloring. We also show, that for every triangle there exists a 2-coloring of the rational plane, such that the triangle is nonmonochromatic. Finally we give a 5-coloring of a strip with height 1, such that there do not exist two points with distance 1, which have the same color. olve these problems. This area of research, in between mathematics and computer science, is known as discrete and computational geometry. In this joint seminar we plan to use tools from discrete aIn this thesis we consider triangles in the colored Euclidean plane. We call a triangle monochromatic if all its vertices have the same color. First, we study how many colors are needed so that for every triangle we can color the Euclidean plane in such a way, that there does not exist a monochromatic rotated copy of the triangle or a monochromatic translated copy of the triangle. Furthermore, we show that for every triangle every coloring of the Euclidean plane in finitely many colors contains a monochromatic triangle, which is similar to the given triangle. Then we study the problem, for which triangles there exists a 6-coloring, such that the triangle is nonmonochromatic in this 6-coloring. We also show, that for every triangle there exists a 2-coloring of the rational plane, such that the triangle is nonmonochromatic. Finally we give a 5-coloring of a strip with height 1, such that there do not exist two points with distance 1, which have the same color. Computational geometry (such as order-type-like properties, see below) and apply them to problems that come motivated from the field of sensor networks.

Spreadsheets are the most successful example of the End User Programming approach to software development. Today, spreadsheet applications, e.g., based on Microsoft Excel, can be found nearly everywhere in companies and are used for a variety of purposes. Studies showed for example that in over 80% of the examined companies spreadsheets are used for financial reporting. Furthermore, companies often use dozens or even hundreds of spreadsheet applications which often tend to be large and complex comprising hundreds or even thousands of formulas. Despite the fact that in many cases business-critical decisions depend on spreadsheets, a complete lack of quality control measures for this type of software applications can be observed in many companies. Not surprisingly, spreadsheets - which are usually developed by nonprogrammers-contain errors of various types. In some studies, researchers found at least one error in every single spreadsheet they analyzed. However, when business decisions are based on spreadsheets, such errors can lead to a significant financial loss or to other business risks as reported by the European Spreadsheet Risk Interest Group. Over the last decades, academics from different fields as well as industry have produced a rich set of methods, techniques and tools to ensure or improve the quality of traditional software artifacts. Only in recent years, the question of how to improve the quality of End User Programs and in particular spreadsheets has gained more attention in research and in practice. These developments led to a number of first proposals ranging, e.g., from process-related measures over visualization and software testing approaches to debugging techniques. In this project, we focus on the debugging stages of the spreadsheet development cycle. Therefore, our goal is to provide the spreadsheet developer with tools that support him or her in identifying the possible problem causes (error localization). These possible causes are called diagnoses and represent subsets of all formulas used in a spreadsheet that should be modified in order to make a spreadsheet application work as expected. In particular, we will analyze and systematically evaluate in which ways various existing approaches to software debugging can be applied, extended or combined to cope with the particularities of spreadsheet debugging. Based on these technical and algorithmic contributions, we aim to develop a classification system that helps us understand which error-spotting techniques are particularly well suited for which types of programs and application settings. Furthermore, we plan to conduct laboratory studies with real users at different stages of the project, in which we want to obtain a better understanding of how and to which extent the participants profit from using the provided debugging tools and how the interaction with an intelligent debugger for end users should be designed.

The 3Ccar project will provide highly integrated ECS Components for Complexity Control in thereby affordable electrified cars. The new semiconductors for Complexity management (Control, reduction) will offer the next level of energy efficiency in transportation systems. 3Ccar’s impact is maximizing pragmatic strategy: Use semiconductor technology innovations to manage functionality & complexity increase. This leads also to cheaper, efficient, robust, comfortable, reliable and usable automotive systems. The task of TU Graz is to provide means for automated testing of developed componentes and systems.

The Project RoboCar aims at a new approach in the development of autonomous driving vehicles based on the integration of an existing highly flexible prototype research vehicle as well as object recognition and vehicle control algorithms from robotic science. The prototype vehicle is driven by four independent hub motors that provide manoeuvrability and driving function far beyond automotive standards. Enhanced Know-how from robotic disciplines comprises sensor technology, navigation algorithms and the autonomous vehicle control system. With the integrated research vehicle, several autonomous driving testing scenarios will be carried out at a university campus to enable comprehensive evaluation and potential assessment of the technology. In this way, the potentials of new technological approaches are assessed and analysed by support of objective and rational evaluation of strengths and weaknesses to facilitate decision-making processes for strategic technological determinations in view of future R&D projects.

Existing configuration systems assume single users. In many domains group-based configuration support is needed (e.g., architectural design and software release planning). The overall goal of We-Want is to develop technologies that enable group-based configuration processes.

Most of today's protocols for secure communication have not been thoroughly tested and we have witnessed some astonishing discoveries regarding flaws or backdoors in their implementations (e.g. Heartbleed bug, NSA BULLRUN project). The main research question of this proposal is whether model-based and combinatorial interaction testing can advance the state of the art of secure software development, e.g. security testing, in terms of finding and exploiting new vulnerabilities within the context of information security. For this purpose we consider mainly security protocols, like TLS/SSL, SSH and IKE. For carrying out the SPLIT project the aims of the team as a whole are i) to develop new approaches and methods in model-based testing and combinatorial testing, and ii) to use and combine these methods to automate security testing in the context of software development This project will contribute substantially towards protecting the information of communicating parties in a digitally connected society by providing quality assurance of security protocols and thus ensuring the privacy of the respective users. Moreover, the project will also contribute to the international efforts currently being carried out by the academic and industrial community to provide bug-free and secure communication protocols for society.

Right-to-left language support for Pocket Code. Young refugees from Syria or Afghanistan, where languages are used that are written from right to left such as Arabic, Pashto or Dari, can learn how to program their own apps directly on their smartphones. Since most teenage refugees own smartphones, and because no additional hardware is required, Pocket Code provides a sustainable, long-term and thus pragmatic way to let them acquire economically significant skills in a fun and easy way. The challenges posed by the project come, on the one hand, from the required long-term collaboration of developers who do not know about right-to-left languages with developers who are native speakers of Arabic, Pashto, or Dari, and on the other hand because right-to-left languages are not sufficiently supported on mobile phones compared to other languages.

TRUCONF sets out to increase trust in and reliability of systems of systems, going beyond the standard notion of functional correctness. It will focus on emergent non-functional properties of complex composed systems and extend - as well as adopt - well-established modelling, verification and testing techniques. In closing the modelling-testing loop, TRUCONF will also explore automated nonfunctional property learning techniques. Outcome of TRUCONF will be a language for rigorous system design, backed by theory and tools that allow the thorough, systematic and efficient validation of diverse non-functional properties of a system of systems. TRUCONF was motivated by the real-world needs of the industry partner and will, once successful, help increasing its competitiveness in a global market.

Technology and process development for remote diagnosis and optimization of wind-turbine maintenance in order to sustainably reduce the cost of wind energy. Required maintenance activities on wind turbines are identified via remote detection of deviating system behavior, root-cause diagnosis and evaluation of remaining life. Based on these results necessary activities to grant for maximum availability and lifetime of turbines are derived. The required methods, the know-how basis and the processes for wind energy are designed, developed and tested. The change process for condition based maintenance will be developed, tested and assessed for an onshore as well as an offshore wind park.

TU Graz works togehter in Styria to evaluate the possibility of autonomous driving on streets in downtown Graz.

Graz University of Technology has been successfully involved in the field of educational robotics (the use of robots as an educational tool for teaching maths, computer science, natural sciences and technology) since 2007. In addition to the successful organisation of international robotics tournaments (RoboCup World Championship 2009, RoboCupJunior Austrian Open 2013), Graz University of Technology offers a range of support measures for schools, teachers and pupils. The steadily growing number of schools integrating robotics into lessons, the positive feedback from pupils and teachers, the excellent cooperation with schools and other educational institutions in Styria, the success stories and careers of former participants in robotics competitions for young talents and the continuously growing number of participants in these annual competitions are proof of the success of the Educational Robotics Initiative, which is largely supported by TU Graz. The aim now is to continue on this successful path, to realise concrete plans for the coming years and to develop new concepts and ideas in the field of educational robotics.

No One Left Behind has been created to take advantages of the opportunities and the potential of digital games to tackle challenges in the education sector. This project will create a new generation of Pocket Code (a mobile media-rich programming environment for children) to unlock inclusive gaming creation and experiences in formal learning situations, underpin meaningful learning and support children to realise their full potential; by transferring game mechanics, dynamics, assets and in-game analytics from nonleisure digital games SMEs, into Pocket Code, which also will be adapted to academic curricula.

In this project we investigate how automated testing and diagnosis can be used to improve the dependability of service robots in industrial envinronments. In particular the project focuses on the reuse of models and the integration into the development process.

Vision+ is dedicated to narrow the gap between customer needs or unsolved challenges a. technological availability by research activities focusing on integrating vision systems with additional knowledge from multi-modal sensors, spatio-temporal investigations, but also humans.

The Applied MOdel-based Reasoning (AMOR) project deals with providing a methodology and a framework for diagnosis in the industrial domain. This includes the objective to further provide support for bringing model-based diagnosis into daily industrial practice. Diagnosis as a process comprises the following activities: (1) to detect a failure, which is a deviation between the expected and the observed behavior of a system, (2) to localize the root cause for the failure, and (3) to correct the fault, which either be a replacement of system components or any other action that brings the system back into a well-defined desired state. Note that in AMOR we only focus on detection and localization. For fault correction we assume that knowledge of the root cause can be directly mapped to correcting actions. In general this would be a restriction. However, in the proposed domain where maintenance staff has access to the system and where replacement units are available this assumption is reasonable.

Mobility is a major enabler for our wealth in modern societies. The aim of this project, is to enable energy sources and consumers in electric vehicles including electrical, thermal and mechanical energy to cooperate as an energy network and to optimally control this network to minimise the impact of external factors in order to achieve predictable, trustworthy and reliable mileage.

For sustainable applications of knowledge-based recommender technologies it is essential to integrate end users into the development and maitenance process.

CRYSTAL aims at fostering Europes leading edge position in embedded systems engineering in particular regarding quality and cost effectiveness of safety-critical embedded systems and architecture plattforms. Its overall goal is to enable sustainable paths to speed up the maturation, integration, and cross-sectoral reusability of technological and methodological bricks of the factories for safty-critical embedded systems engineering in the areas of transportation (aerospace, automotive, and rail) and healthcare providing a critical mass of European technology providers.

ComPoSe — Combinatorics of Point Sets and Arrangements of Objects

This CRP focuses on combinatorial properties of discrete sets of points and other simple geometric objects primarily in the plane. In general, geometric graphs are a central topic in discrete and computational geometry, and many important questions in mathematics and computer science can be formulated as problems on geometric graphs. In the current context, several families of geometric graphs, such as proximity and skeletal structures, constitute useful abstractions for the study of combinatorial properties of the point sets on which they are defined. For arrangements of other objects, such as lines or convex sets, their combinatorial properties are usually also described via an underlying graph structure.

The following four tasks are well-known hard problems in this area and will form the backbone of the current project. We will consider the intriguing class of Erdős-Szekeres type problems, variants of graph problems with colored vertices, counting and enumeration problems for specific classes of geometric graphs, and generalizations of order types as a versatile tool to investigate the combinatorics of point sets. All these problems are combinatorial problems on geometric graphs and are interrelated in the sense that approaches developed for one of them will also be useful for the others. Moreover, progress in one direction might provide a better understanding for related questions. Our main objective is to gain deeper insight into the structure of this type of problems and to contribute major steps towards their final solution.

Erdős-Szekeres problems. We will investigate specific variants of this famous group of problems, such as colored versions, and use newly developed techniques, such as a recent generalized notion of convexity, to progress on this topic. A typical example is the convex monochromatic quadrilateral problem in Section (iv) of the Call for Outline Proposals: Prove or disprove that every (sufficiently large) bichromatic point set contains an empty convex monochromatic quadrilateral. Recent progress on this and other Erdős-Szekeres type problems has been made by the PIs Aichholzer, Hurtado, Pach, Valtr, and Welzl.

Colored point sets. An interesting family of questions is the existence of constrained colorings of point sets. We may consider, for instance, the problem of coloring a set of points in a way such that any unit disk with sufficiently many points contains all colors. Also, colored versions of classical Helly-type results continue to be a source of fundamental problems, requiring the use of combinatorial and topological tools. In particular we are interested in colored versions of Tverberg-type results and their generalization of Tverberg-Vrećica-type. Pach founded the class of ‘covering colored sets’ problems and will cooperate on these problems with Cardinal and Felsner in particular, but also with all other PIs.

Counting, enumerating, and sampling of crossing-free configurations. Planar graphs are a core topic in abstract graph theory. Their counterpart in geometric graph theory are crossing-free (plane) graphs. Interesting questions arise from considering specific classes of plane graphs, such as triangulations, spanning cycles, spanning trees, and matchings. For example, the flip-graph of the set of all graphs of a given class allows a fast enumeration of all elements from this class and even efficient optimization with respect to certain criteria. But when it comes to more intricate demands, like counting or sampling a random element, very little is understood. We will put emphasis on counting, enumerating, and sampling methods for several of the mentioned graph classes. Related extremal results (e.g. upper bounds on the number of triangulations) will also be considered for other classes, like string graphs of a fixed order k (intersection graphs of curves in the plane with at most k intersections per pair) or visibility graphs in the presence of at most k connected obstacles. Aichholzer, Hurtado, and Welzl have been involved in recent progress on lower and upper bounds for the number of several mentioned classes of geometric graphs and will cooperate with Pach (intersection graphs), Valtr, and Felsner (higher dimensions) on enumerating and counting.

Order types (rank 3 oriented matroids). Order types play a central role in the above mentioned problems, and constitute a useful tool to investigate the combinatorics of point sets. This is done, e.g., by providing small instances of vertex sets for extremal geometric graphs in enumeration problems. Our goal is to generalize, and at the same time specialize, this concept. For example, we plan to investigate the k-set problem as well as a generalization of the Erdős-Szekeres theorem for families of convex bodies in the plane. Typically, progress on the k-set problem has frequently been achieved in the language of pseudoline arrangements, which are dual to order types. In particular we are interested in combinatorial results ranging from Sylvester-type results to counting certain cells, and the number and structure of arrangements of n pseudo-lines. Felsner is an expert on pseudo-line arrangements and will collaborate here with Valtr, Pach, Welzl and Aichholzer on order types. Moreover all PIs have been working on the kset problem individually and will make a joint afford.

This CRP tackles fundamental questions at the intersection of mathematics and theoretical computer science. It is well known that in this area some problems require only days to be solved, others may take decades or even more. Thus, the working schedule with respect to obtaining the desired theoretical results must follow the standard approach: Continuation of work in progress, evaluation of the results obtained by other authors and groups, and continuous identification of new directions for progress and exploration, hence always advancing the frontiers of knowledge. Since it is infeasible to impose a proper temporal order on the objectives and milestones to be attained - the conceptual implications are manifold, and many of the stated objectives are strongly interrelated - it will be the very progress of research and the obtained results that mark our progress in time. This is guaranteed by the competence of the team. The major 'visible' milestones will be the regular presentations of joint papers in the main conferences of the field, the corresponding submissions to journals, and a series of progress reports that will help in keeping a clear and consistent guidance and interaction with the other teams.

Several of the mentioned problems are long-standing open questions and known to be hard. Therefore we will consider several specific variants of them to determine how far state-of-the-art methods can be used and where new approaches have to be found. This will definitely improve our understanding of the structure of these problems, with the goal of making major contributions towards their solution or, in the ideal case, to finally settle them. Most of our approaches will be of theoretical nature. But we will also make intensive use of computers for enumeration and experiments, to get initial insights into the structure of problems, or to support or refute conjectures.

It is well known that the mentioned problems have resisted several previous attacks and therefore require the cooperation of researchers with strong and complementary expertise. We consider large-scale collaboration on these topics as one of the main ingredients for success. Thus we will not have individual projects running in parallel, but all participants will jointly work on the topics, in a massive collaborative effort. To guarantee a strong interaction between the members of the group we will maintain regular exchanges of senior researchers and students, regular joint research workshops (1-2 per year), and frequent visits.

Computational Geometry is a relatively young and very active field of research in the intersection of mathematics and theoretical computer science. Studying algorithms and data structures have been main objectives of this growing discipline. Although geometric graphs are structures defined by geometric properties, like x- and y-coordinates, they have a highly discrete nature. Straight lines spanned by a finite set of discrete points give rise to simple and memory efficient data structures. While not loosing the geometric information, geometric graphs additionally provide combinatorial context (like neighborhood information) that is sufficient for many applications and allows for very efficient and stable algorithms. Moreover, for many problems the geometric information is not needed for their solution. In these cases, point sets, geometric in principle, can be stored and used in a purely combinatorial way. A simple example is the construction of the convex hull of a point set, which is an intrinsic task of countless algorithms. For this it is sufficient to know for any triple a,b,c of points whether c is to the left or to the right of the straight line spanned by a and b. A data structure that stores this information is the so called order type.

Not to be forced to rely on geometric information has one major advantage: It enables for simple, exact, and robust algorithms. For these reasons, Computational Geometry has become highly interweaved with fields of Discrete Geometry like Combinatorial Geometry. In the proposed project we want to explore a group of interrelated questions that can be reduced to purely combinatorial problems.

One exception from this group of purely combinatorial problems is the question of blocking Delaunay triangulations on bi-colored point sets. The order type does not provide the Delaunay property for quadruples of points, an in-circle property needed for Delaunay triangulation construction. An extended order type, for instance, a “Delaunay order type” mapping the Delaunay property to purely combinatorial data, could help solving this and many other problems on Delaunay triangulations by answering how many different Delaunay triangulation exist for a given “classical” order type.

But even though not of pure combinatorial nature, this subproblem is related to the other proposed problems. General methods on bi-colored point sets can be applied to the problems on compatible geometric graphs, isomorphic plane geometric graphs, questions on k-convexity, and also, of course, the Erdős-Szekeres type problems on bi-colored point sets. Further, new insights and results on any of these problems will have implications on the whole project and also to many other problems from Discrete & Computational Geometry.

In the context of this project, examples for interesting classes of geometric graphs are triangulations, pseudo-triangulations, spanning trees, spanning circles, spanning paths, and (perfect) matchings. As already mentioned, the proposed problems are interrelated parts of one project. It is our strong belief that attacking these problems in a combined attempt will have synergetic effects to all parts. This will help to make considerable progress on the presented questions, to gain additional insight into their structure, and to finally answer at least some of them.

First Responder frequently face critical situations whose reconnaissance and handling is significantly afflicted with personal risks. Modern robot technology can help to reduce these risks. Because of different technical and economic reasons such technology is hardly used by first responder nowadays. The aim of this project is to develop a model that allows first responder to request robot technology and experts easily and quickly in a crisis situation. The advantage of this model is that first responder to not have to hold available such complex and expensive technology and that it remains with an external specialized organization for training, maintenance and operation. First Responder frequently face critical situations whose reconnaissance and handling is significantly afflicted with personal risks. Moreover, due to critical weather situations and increased use of technology in daily life there are situation in which even response experts do not have access anymore (mudslide, hazard materials). Modern robot technology can help to reduce these risks and restrictions. Because of different technical and economic reasons such technology is hardly used by first responder nowadays. The aim of this project is to develop a model that allows first responder to request robot technology and experts easily and quickly in a crisis situation. Similar models already exist to request experts in chemistry or geology. The advantage of this model is that first responder to not have to hold available such complex and expensive technology and that it remains with an external specialized organization like an university or a company for training, maintenance and operation. In order to establish such a model realistic use cases have to be identified in cooperation with first responder. Based on these use cases tactical, technical and juridical requirements have to be defined to allow for an effective and save integration of external robots and experts into daily routine. Moreover, regulations for the external technology partner in terms of maintenance, documentation, training and standby service have to be defined in order to guarantee continuous technical quality and fast response times. The declared aim of the project is to develop a workable and well-founded model for the provision of robot technology to first responder. Moreover, the model has to be mature in order to be deployed in real missions without further development.

With globalization and the resulting worldwide competition, high quality systems have crystallized as one way to compete with business rivals. Using a formal temporal language to state the behavioral specification of a protocol, component, or entire system, is a first step towards a high quality product and an efficient development process: It makes subtle questions explicit that otherwise might be hidden in the ambiguity of natural language, and it enables automatic tools. Obviously, a formal notation is not enough to ensure the quality of a specification. Current research, however, mainly focuses on the verification phase, where for example a chip design is verified against its behavioral specification, and not on assisting the designer when writing the specification itself. This is somewhat surprising, as industrial data show that about 50 percent of product defects and about 80 percent of rework efforts can be traced back to flawed specifications. With this project, we face the challenge to provide diagnostic information in the process of developing or verifying formal temporal specifications. Specifically, we will tackle the questions of why a specific trace is a counterexample or witness, and that of what is wrong with a specification if a specific behavior should or should not have been contained by it, and also that of how to properly explain (complex) formal temporal properties. For this purpose, we will integrate the concept of model-based diagnosis from the artificial intelligence community with ideas and techniques that are well-known in the context of temporal logics and verification, like model-checking. Model-based diagnosis will allow us to diagnose the cause of encountered problems during formal specification development, so that we will be able to meet important needs of involved scientists and designers. A general aim of ours will be to provide the scientist or designer with information directly related to the specification, rather than information related to a derived automaton. In order to offer an attractive platform, we will consider the well-known Linear Temporal Logic (LTL) and also extensions suggested by newer languages like the Property Specification Language (PSL). Although LTL and PSL have their origin in the design of programs and electronic hardware, LTL has, for instance, also been used in other applications like the maintenance of knowledge-bases. Thus we will provide a solution that is usable in any application that draws from formal temporal specifications. With our focus on providing diagnostic information which eases the development, maintenance, and application of formal temporal specifications, as well as increases their quality, we expect this project to leverage the incorporation of formal temporal descriptions in industry and also scientific projects. In our vision, we expect that our integration of ideas and technologies from multiple research communities will provide new stimuli for future research.

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The project objectives are summarised as follows: to promote cooperation, training, research and visibility in the field of search and rescue robots at the level of pupils, students, researchers, emergency services, disaster control authorities and the general public.

Todays dependable computer-based infrastructures rapidly grow in complexity due to a continuous evolution towards very large, heterogeneous, highly dynamic and ubiquitous computer systems. This trend of a growing complexity is a serious challenge to the task of engineering trustworthy systems: the more complex a system is, the more difficult is the verification of the fulfilment of its dependability requirements. It seems that despite the many advances in automated verification, the demand for new features and flexibility always creates systems that provide the next barrier for auto- mated verification. Where verification is not possible to establish trust, Sir Popper proposed falsification. TRUFAL will implement this idea by applying mutation analysis to the modelling level, leading to a new form of fault-oriented model-based testing. Mutation testing is strongly related to safety and security testing. Today, no commercial tools exist that combine mutation testing and model-based testing. One reason is the complexity of the algorithms behind mutation testing (equivalent mutant problem). The aim is to develop such a new test case generator that is able to handle models of industrial scale. We will exploit the newest results and techniques from formal methods: formal intermediate models, model decomposition and concolic (concrete and symbolic) execution. This tool, together with domain specific fault models, will be integrated in the quality assurance process of our industrial partners in the safety-critical transportation domain: automotive and railways, which in a mid-term range can lead to improvement of their development processes. The objective is to reduce their testing efforts by at least 10% while providing a measurable and scientifically defendable statement of trust in their systems in terms of fault coverage. All techniques will be well-founded in scientific theory.

The principles of Service-Oriented Architectures (SOAs) have been receiving high attention lately, and are nowadays widely established in the software industry for the application in many domains. The fast evolution of available technology entails the development of new complex domains, and in turn enables and drives active research in fields such as self-optimizing distributed systems, autonomic computing, adaptive systems, or cloud computing. Nowadays SOA-based systems consist of a multitude of Web services, registries/brokers, mediators, message buses, monitors, governance systems and many more components. This ever-growing complexity leads however to a rather high error-proneness, due to the large amount of components and complex as well as subtle links and dependencies between individual system parts. Today there exist numerous solutions that assist designers in testing single Web services. We are however faced with a lack of options that enable methodical system-wide runtime tests of complex SOA systems. We argue that a system-wide high-quality assessment in real conditions is an essential factor in the process of facing today's complexity of SOAs and assure the quality of related prototypes and production systems while keeping development time within manageable bounds. With this project, we face the challenge to provide a methodology and related technologies for a high-quality development environment for SOAs. Specifically we will facilitate the development of SOA models that enable an automated construction of realistic testbeds and high-quality test-suites for system-wide runtime tests. These runtime tests will enable the assessment of important system traits like performance, stability, robustness, scalability, and other functional and non-functional properties in real world scenarios and conditions. Furthermore, we will integrate diagnostic reasoning in the model itself and the testing process. Developed models will thus also contain diagnostic reasoning aspects, so that for failing tests we will provide engineers and researchers with the means to isolate faults using model-based diagnosis techniques. The integration of ideas from the testing as well as model-based diagnosis communities in an active diagnosis'' step will enable us to derive additional tests for the discrimination between ambiguous diagnoses, an essential factor in our proposed work-flow. The diagnostic aspects of the model will also act as additional and interesting criteria for the test-suite generation process. With our focus on providing a methodology and related technologies for a high-quality assessment of SOA traits under realistic conditions, we address current needs of researchers and engineers in this area. We will enable them to assure the quality of their prototypes and products by finding errors with high quality system-wide runtime tests and the option to isolate corresponding faults using diagnostic reasoning. The models will also allow very early design assessment. In the course of the extensive research necessary to achieve our aims, we will integrate the know-how from multiple communities (SOA, testing, model-based diagnosis). As a consequence, in our vision, we expect to give these communities new impulses by the know-how transfer resulting from this project, which, besides our achievements, will sparkle additional research by other groups.

At the moment, Europe is leader in the area of high-quality embedded systems. To boost and further extend this leading position, effective and efficient technologies for developing and validating embedded systems are of utmost importance. One of the most important enablers to assure the requested quality of embedded systems is the application of powerful validation and verification (V&V) technologies accompanying the embedded systems development process. Unfortunately, the V&V technologies already in industrial use are still too expensive while often not effective enough. MBAT will provide Europe with a new leading-edge Reference Technology Platform for effective and cost-reducing validation and verification, focussing primarily on transportation domain, but also to be used in further domains. Developed by European industrial key players (large companies and SMEs) in this domain and supported by leading research partners, this MBAT RTP will be of high value for the European industry, providing very effective means to assure utmost quality embedded systems at reduced costs. With this, MBAT will also strongly support the EU vision of zero traffic fatalities by 2020. As this project is clearly industrial-driven it will be assured that the MBAT RTP will provide solutions for real-life development challenges existing in the European industry as this is also the goal of ARTEMIS projects.

The project Simulation and Configuration of Mobile Networks for M2M Applications (SIMOA) aims in providing foundations for simulation, configuration, and optimization of mobile phone networks considering new application areas of machine-2-machine (M2M) communication. SIMOA focuses on developing a modeling language that allows for stating the problem domain as well as future user behavior in order to forecast changes in the network structure and functionality. The main challenge is the ability to state temporal and spatial knowledge. The FFG, Kapsch CarrierCom, and Kapsch BusinessCom fund SIMOA, which started in 2010.

Casa Vecchia aims to evaluate and improve AAL solutions with regard to their suitability for daily use. Therefore a representative system will be installed in 20 households of elderly and will be thoroughly evaluated during three years. Central points of interest are the usability, the integration of end-users and the acquisition of long-term data based on real life conditions. Results will be made available to the scientific community.

Ziel ist, die Frage zu beantworten, wie Recommender Technologien im Rahmen von Requirements Engineering Prozessen gewinnbringend eingesetzt werden können. Viele Softwareprojekte sind durch eine hohe Anzahl von Anforderungen (Requirements) charakterisiert, die mit den vorhandenen Ressourcen nicht vollständig umgesetzt werden können. Effektives Requirements Engineering wird von immer höherer Bedeutung bei Partnern.

http://www.ist.tugraz.at/icone.html

15% - 40% of the overall costs of a configurator project are related to configuration knowledge base (KB) development and maintenance. Therefore, one of the most important challenges in the development and maintenance of knowledge bases is the effective support of knowledge engineering tasks. The basis of effective knowledge base development and maintenance operations is the understanding of the KB and the support of fault identification and repair. These issues are within the major focus of the ICONE project. The ICONE knowledge acquisition environment will include the following functionalities: Preferred diagnoses: based on a given set of test cases and complexity metrics, preferred diagnoses are calculated and presented to the knowledge engineer. Redundancy detection: in addition to detection of inconsistencies in the knowledge base, ICONE components will support the identification of redundancies which can deteriorate the performance of search algorithms and increase knowledge acquisition overheads. Automated generation of test cases: in the context of diagnosis, test cases will be automatically generated and used in regression tests. Intelligent quality management: complexity metrics and refactoring rules which are especially developed for configuration scenarios will help to improve the quality of (configuration) knowledge bases. Intelligent analysis and navigation: knowledge engineers will be supported by recommender algorithms in the analysis, development, and maintenance of knowledge bases.

Das Forschungsprogramm Softnet II adressiert qualitäts-bezogene Herausforderungen in der modernen Software Entwicklung dies reicht vom Nutzbarmachen von implizitem Ingenieurswissen über Methoden, Techniken und Tools, der kundenspezifischen Adaption von Testautomatisierung, der tool-gestützten Überwachung von Qualitätszielen und der Entwicklung des Software-Qualitätsstatus, bis hin zur Wiederverwendbarkeit von QS-Methoden im Kontext von Software- Produktlinien und neuerdings aufkommenden Vehicle-to-Vehicle Architekturen. Das Herzstück von Softnet II, das Continuos Defect Forecasting and Detection Projekt, integriert Modelle zur Fehlervorhersage mit modernen Testtechniken. (Weiterführung des K-net Softnet Austria (1.05.2006-31.12.2010))

If an autonomous robot has to robustly act in a dynamic real world environment, it has to be able to autonomously cope with unexpected, unforeseen or ambiguous situations. A common reason for such situations is that the current state of the world is inconsistent with the internal belief or knowledge base of the robot. For instance the robot believes that it is in a different office as it is in reality. Usually this is caused by uncertainties in the robots acting and sensing or by exogenous events the robot is not able to perceive or to control. If a robot is not aware of such situations it is doomed to fail in fulfill its task because the decision making of the robot relies on a consistent belief. Due to its reasoning capabilities humans are very good in handling such phenomena. They use common sense reasoning to detect such inconsistencies. Moreover, they are able to perform actions in order to reduce inconsistencies. For instance if a person does not exactly know in which floor of a building it may go back to the elevator or stair case and look for the right floor. In the project we propose a reasoning approach which allows a robot to detect inconsistencies in its belief (abstract knowledge base) and to derive repair actions which remove or at least reduce inconsistencies in its belief. The approach uses a background model (common sense knowledge) about how the robot and its environment should work and methods of model-based diagnosis to detect inconsistencies in the belief and to locate the root cause for the inconsistency, e.g., facts which are wrong or uncertain. Furthermore, the approach automatically generates repair plans the robot is able to perform in order to reduce the inconsistency by confirming or deleting facts from the knowledge base.

The ISAC-project is a research and development project at the Institute for Software Technology of the Graz University of Technology. The ISAC-system establishes new base-technology for a novel kind of interactive and web-based transparent software for applied mathematics. The novelty is given by the human-readable knowledge base including Isabelles HOL-theories and by the transparently working knowledge interpreter (a generalization of 'single stepping' algebra systems). Research within the ISAC-project goes alongside the development of the ISAC-system and concerns issues, which reach from technological ones like 'math on the (semantic) web' down to foundamental ones like a 'rigorous formal semantics of tools for applied mathematcs'. The background to both, development and research, is given by actual needs in math education as well as by foundamental questions about 'the mechanization of thinking' as an essential aspect in mathematics and in technology. The ISAC-system under construction comprises a tutoring-system and an authoring-system. The latter provides for adaption to various needs of individual users and educational institutions and for extensions to arbitrary fields of applied mathematics.

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Computational Geometry is dedicated to the algorithmic study of elementary geometric questions. Traditionally it deals with basic geometric objects like points, lines, and planes. For real world applications, however, often reliable techniques for advanced geometric primitives like surfaces and location query structures are needed. The role of this project is twofold. On one hand it will provide the theoretical background for advanced geometric algorithms and data structures for several other projects within this joint research project (JRP). These include geometric structures for fast information retrieval, the generation and manipulation of triangular meshes, the computation of suitable distance functions to multidimensional objects, and the representation of advanced geometric objects. Another aim of this project is to develop novel techniques for the manipulation and optimization of geometric structures. Here the emphasis is on geometric graphs (triangulation-like and Voronoi diagram-like structures, spanning trees). Properties of these structures will be investigated, with the goal of designing more efficient geometric algorithms and data structures. Existing geometric algorithms libraries (CGAL, LEDA) will be used to guarantee robustness of the developed algorithms.

Using sources from the internet and semantic data provided by user communities in Web2.0 style, a system that can intelligently extract information for user needs will be analyzed, designed and a prototype implemented

The low quality of customer support/service in the financial services domain requires new solutions. Such solutions should enable customers to easily (re-)design financial portfolios on their own. Existing software solutions are product-centered and thus lack an integrated view on the financial situation of the customer. The research project WECARE focuses on the development of new configuration and recommendation technologies that help to provide an integrated view on the customer situation. Key technologies in this context are intelligent recommendation and repair mechanisms that support customers in the design of their portfolio. On a technical level, the goals of WECARE are: - Development of domain-independent algorithms for the personalized recommendation of feature values and configurations. - Development of domain-independent algorithms for the recommendation of reconfigurations (in the case of inconsistent configurations/portfolios). - Evaluation of the developed software components in the context of empirical studies.

Project for coordination, planning, reporting all reference projects in SoftNet Austria K-Ind-network

Analyse bestehender Softwarearchitekturen hinsichtlich Sicherheit und Erweiterbarkeit Bereitstellung von Verfahrensmodellen und Softwarearchitekturen für den Bereich Mobiltelephonie Analyse zukünftiger Entwicklung im Bereich Next Generation Intelligent Networks Bereitstellung von Methoden und Tools zur Sicherung der Softwarequalität unter Berücksichtigung der Applikationsdomänen Mobile IP, Multimedia, Web und Mobiltelephonie Testumgebungen Verifikationstechniken Last- und Zuverlässigkeitstests Analyse von Sicherheitsaspekten

Eine wesentliche Herausforderung bei der Entwicklung von Standardsoftware ist die Erreichung einer bestimmten Softwarequalität. Dazu wird das (vermeintlich) fertige Softwareprodukt getestet, wobei versucht werden muss, eine möglichst vollständige Überdeckung der Funktionalitäten durch Testfälle zu erreichen. Dadurch können bei komplexen Softwaresystemen (wie der von Hyperwave) mehrere tausend Testfälle entstehen. Die Organisation dieser Tests, der daraus resultierenden Fehlerbehebungen und neuerlichen Tests der betroffenen Funktionen stellt daher eine Herausforderung dar.

Ziel des Projektes ist es für die Zeitressourcenplanung in Dienstleistungsunternehmen, Modelle, Methoden und Softwarewerkzeuge zu entwickeln, die es erlauben aufbauend auf Standardbausteinen einfach an die jeweilige Situation angepasste Werkzeuge zu entwickeln; bei der Weiterentwicklung der Standardbausteine sicherzustellen, dass diese Adaptionen mitgepflegt werden, um eine neuerliche Anpassung überflüssig zu machen; auf die jeweils adaptierten Bausteine handlungsrelevant Wissen für die Planer zur Verfügung stellen, um auch komplexe Planungsaufgaben auch praktisch bewältigbar zu machen.

MOGENTES aims at significantly enhancing testing and verification of dependable embedded systems by means of automated generation of test-cases relying on development of new approaches as well as innovative integration of state-of-the-art techniques. Driven by the needs of its industrial partners, it will address both testing of non-functional issues like reliability, by e.g. system stress and overload tests, and functional safety tests, meeting the requirements of standards such as IEC 61508, ISO WD 26262, or AUTOSAR. MOGENTES will demonstrate that different domains with a wide variety of requirements can significantly benefit from a common model-based approach for achieving automated generation of efficient test-cases and for verifying system safety correctness using formal methods and fault injection, as this approach increases system development productivity while achieving predictable system dependability properties. For that purpose, proof-of-concept demonstrations will show the applicability of the developed technologies in two application domains: railway and automotive. In particular, MOGENTES aims at the application of these technologies in large industrial systems, simultaneously enabling application domain experts (with rather little knowledge and experience in usage of formal methods) to use them with minimal learning effort. All in all, MOGENTES will increase knowledge and develop new techniques and tools in the area of verification and validation of dependable embedded systems which can be applied in model-based development processes also by non-experts in formal methods.

The aim of this project is to develop methods and models which enable autonomous and possibly mobile systems like robots to adapt their behaviour after internal faults and unexpected interactions with the environment. (http://www.fwf.ac.at/de/abstracts/abstract.asp?L=D&PROJ=P20199)

Als Anwendungs- und Testobjekt soll ein Multi-Media-Replayer für Mobile Endgeräte entwickelt werden: Radio und TV Sendungen (aktuelle oder vor kurzem ausgestrahlte News, Interviews, Dokumentationen, Talkshows, Musiksendungen wie Starmania, ...) sind über eine Suche in den Wörtern, die von den Personen der Sendung ausgesprochen wurden oder im Titel der Sendung vorgekommen sind, auf einem Mobiltelefon abrufbar. Motto: Google für TV und Radio am Handy.

The general topic of this project is the investigation of geometric graphs, i.e., graphs where the vertex set is a point set in the plane and the edges are straight line segments spanned by these points. Throughout we assume the points to be in general position, that is no three of them lie on a common line, and to be labeled. Geometric graphs are a versatile data structure, as they include triangulations, Euclidean spanning trees, spanning paths, polygonalizations, plane perfect matchings and so on. The investigation of geometric graphs belongs to the field of (combinatorial) mathematics, graph theory, as well as to discrete and computational geometry. The alliance of our two research groups will perfectly cover these fields. For example this will allow us to use an interesting combination of enumerative investigations (lead by the Austrian team) and theoretical research (coordinated by the Spanish group). Let us point out that this combination of theoretical knowledge and practical experience, which is perfectly provided by the combination of these two teams, will be essential for the success of this project. There are many classic as well as new tantalizing problems on geometric graphs, and the investigation of seemingly unrelated questions often leads to new relations and deeper structural insight. So the focus of this project is to investigate several classes of problems with the common goal of optimizing properties of geometric graphs.

Diagnose von Förderanlagen

Zentrales Thema dieser gemeinsamen Forschung ist die Untersuchung grundlegender Datenstrukturen aus dem Bereich der rechnerischen Geometrie (Computational Geometry), einem relativ jungen Teilgebiet der (theoretischen) Informatik. Dabei sollen sowohl theoretische Aspekte untersucht werden, als auch deren konkrete Umsetzung im Rahmen einer allgemein verwendbaren Programmbibliothek. Auf Seite der theoretischen Untersuchungen sollen sowohl klassische Datenstrukturen, wie Voronoi-Diagramme oder Triangulierungen, aber auch relativ neue Datenstrukturen, wie Pseudo-Triangulierungen oder Straight-Skeletons, untersucht werden. Genauere Einzelheiten werden in den nachfolgenden Abschnitten beschrieben. Gleichzeitig soll aber auch für alle untersuchten Strukturen deren tatsächliche Verwendbarkeit in der Praxis berücksichtigt werden. So ist es geplant, jeweils spezielle Aspekte dieser Strukturen in konkreten Implementationen umzusetzen. Um einen bestmöglichen Nutzen der erzielten Ergebnisse zu gewährleisten, sollen die Implementationen in einer standardisierten Bibliothek der gesamten CG-Community zur Verfügung gestellt werden. Dazu ist die Umsetzung in CGAL (Computational Geometry Algorithms Library, siehe { www.cgal.org}) geplant. Es handelt sich dabei um ein ursprünglich von der EU gefördertes Projekt, das insbesondere von unserem französichen Projektpartner an zentraler Stelle mitbetrieben wird.

The Self Properties in Automomous Systems project (SEPIAS) focusses on the development process of mobile systems which comprises hardware and software. The goal is to provide tools and techniques for enabling the mobile systems to react to environmental changes and internal faults in an intelligent way such that they can still fulfil their tasks. Because of limited possibilities for human intervention and even interaction during operation autonomous systems need to solve the problems and unexpected situations by their own. As a consequence, the autonomous system has to have knowledge about the surrounding environment, its task, and itself. Moreover, the system has to be able to reason about its state and if necessary to draw conclusions which even have an effect on its structure and behaviour. For the capabilities of reflection and self-healing capabilities the required knowledge has to be accessible by the system development of hardware and software of a system for a specific task. Although malfunctions are considered partially within the process, the resulting system has no explicit knowledge about itself. To overcome this situation, there has to be a knowledge acquisition phase during the development process which integrates smoothly within a traditional development process. For the purpose of knowledge representation and reasoning this project uses the techniques that are used in model-based reasoning. They have to be adapted and smoothly integrated. An additional requirement is the available computational power of autonomous systems since reflection has to be performed during operation. Hence, the algorithms and knowledge representation have to be adapted to perform well under given computational restrictions.

In this project we explore new extraction in fault detection and localization of java programs. In particular we discover the modificaition of verification techniques of ASPECT to localize fault. Prototype implementation and experimental evaluation should be available at the end of the project.

The Model-based Runtime Diagnosis for Autonomous Mobile Systems (MoRDAMS) project focuses an the modeling of hardware and soflware of mobile robots to allow for autonomous diagnosis and reconfiguration without human interaction. Automated diagnosis and reconfiguration of mobile robots would ensure their potential of use in real-world environments over a longer period of time. Currently, mobile robots require a lot of maintenance work which has to be provided online and offline. By introducing a self-repair capability a mobile robot would less sensitive to errors and malfunctioning. In order to use the developed models directly for diagnosis and reconfiguration the MoRDAMS project uses model-based reasoning techniques which has been successfully applied to diagnosis and reconfiguration in different domains, including software debugging and the automotive industry. The models which will be developed during the project will also be evaluated with respect to real-world test-cases. The obtained data from the realworld test-cases will be published in order to provide test-cases to the community for further studies. Hence, MoRDAMS will have an impact to the model-based reasoning field not only in modeling but also in providing real-world data. In summary the MoRDAMS project investigates: (1) modeling for diagnosis and reconfiguration of systems comprising hardware and Software, (2) how to apply model-based diagnosis and reconfiguration at runtime within a given time and given computational resources, and (3) extracting observations for diagnosis and reconfiguration from raw Sensor data.

The development of safety-critical distributed embedded systems requires adequate testing methods to ensure a low failure rate of the system. Within this project it is the goal to develop a testing framework for safety-critical distributed embedded systems that may have both, event-triggered and time-triggered behavior. As the primary application domain of this framework is the automotive industry, the framework will support the V-model for software development. To ensure a sufficient quality of the generated test data, a correlation between the safety-requirements for the safety-integrity levels (SIL) of the standard IEC 65108 and adequate test suites has to be defined. The testing framework should generate the test cases automatically. Therefore, a formal specification of the application is required. Finding an adequate formal specification language that matches the required expressiveness for the intended application domain will be an important prerequisite for the development of the test case generation techniques. Since this testing framework is targeted to real time embedded systems the underlying formal techniques for test case generation will support a precise notion of time in the application model. The testing framework will support multiple test techniques to provide efficient techniques for different abstraction levels.

Multimedia data has a rich and complex structure in terms of inter- and intra-document references and can be an extremely valuable source of information. However, this potential is severely limited until and unless effective methods for semantic extraction and semantic-based cross-media exploration and retrieval can be devised. Today’s leading-edge techniques in this area are working well for low-level feature extraction (e.g. colour histograms), are focussing on narrow aspects of isolated collections of multimedia data, and are dealing only with single media types. MISTRAL follows the following lines of radically new research: MISTRAL will extract a large variety of semantically relevant metadata from one media type and integrate it closely with semantic concepts derived from other media types. Eventually, the results from this cross-media semantic integration will also be fed back to the semantic extraction processes of the different media types so as to enhance the quality of the results of these processes. MISTRAL will focus on most innovative, semantic-based cross-media exploration and retrieval techniques employing concepts at different semantic levels. MISTRAL addresses the specifics of multimedia data in the global, networked context employing semantic web technologies. The MISTRAL results for semantic-based multimedia retrieval will contribute to a significant improvement of today’s human-computer interaction in multimedia retrieval applications.

The goal of the PROSYD project is to significantly increase the competitiveness and efficiency of the European IT industry through the establishment of a standard, integrated property-based paradigm for the design of electronic systems. This paradigm will integrate and unify the many phases of system development, including requirement definition, design, implementation, and verification, into one coherent design flow, building on the emerging standard property specification language PSL/Sugar, which has been recently selected as a basis for an IEEE standard. The new paradigm will enable the development of electronic systems of higher quality within shorter design cycles and with lower costs. The prime deliverable of the PROSYD project will be a reference methodology and a set of coherent PSL/Sugar-based tools for property-based system design. Using these tools, we aim to demonstrate an improvement of at least 30% in design productivity. In addition, we expect to see an increase in the quality of the finished product, resulting in a significant decrease in the number of design flaws that make it through the verification phase.

Ontology Engineering in the Context of Data Extraction In this part studies and research on approaches to ontology engineering are investigated to generate a basic framework that is designed for further reuse. Ontology-based Intelligent Extraction New methods for data extraction from non-HTML documents, in particular on non-structured formats, are studied. The research is mainly conducted on two formats, namely PDF and plain text, the latter mainly in the context of 3270 applications. Novel Semantic Technologies in Wrapping In this part the main goal is to map data instances that have been extracted from e.g. HTML documents to ontologies such as RDF-Schema or OWL. The declarative logic-based language Elog of the Visual Wrapper is ideally suited for tight integration with ontology repositories. Existing RDF repositories like Jena, Sesame and KAON and various existing RDF query languages are analyzed, and the APIs of the libraries are studied to explore ways how to connect the Lixto Visual Wrapper to these repositories. Wrapper Adaptation In this part the goal is to study automatic and semi-automatic repair technologies that change a wrapper accordingly to major structural changes on the underlying Web sites. Human-Machine Communication: htmlButler htmlButler is intended to be a commodity client server based tool through which general web users can visually specify to be informed via Email about changes in a certain area of interest on a Web page.

The VoIP project deals with improving the software quality for commercial products in the area of the telecommunication industry. In particular, the project focuses on fault detection in VoIP server software comprising concurrent programming language constructs. An important objective is to provide tools and techniques for analyzing the software and to prevent bugs related to concurrency like data races and deadlocks.

The project JADE Extensions (JADE-X) project aims at developing an intelligent debugging environment that improves the software engineering process by providing assistance in locating and (if possible) correcting bugs in Java programs. Considering the size and complexity of recent computer programs, this is generally a very expensive and time-consuming task. Therefore, research has developed several approaches that deal with debugging and verification of computer programs, each of them using proprietary methodologies and requiring different amount of knowledge. Unlike those approaches, our approach does not deal with formal verification of programs, the debugging tool to be developed during JADE-X adapts model-based diagnosis (MBD) for debugging. MBD has been developed for finding and fixing faults in hardware and is based on a componentoriented model of the system describing its functionality. This approach can also be used for software debugging. In this domain, the components are constructed from various elements of the program, such as statements or expressions. The connections are derived from the used and modified variables. However, it is not easy to develop a general model that can be used to locate different kinds of faults efficiently, as the model influences e.g. the number of bug candidates. Hence, the development of suitable models for program debugging depends on multiple aspects and has to be investigated carefully. JADE-X is based on the results obtained during the previous project (JADE) and extends the results in order to provide better results. Multiple models representing different abstractions of programs are to be developed in order to provide better results for different kinds of faults without an increased amount of user interaction. Combinations of such models are expected to considerably enhance the debugging process, as a reduction in bug candidates, diagnosis time and user interaction can be achieved. Project JADE-X is expected to deliver multiple models of Java programs (including object-oriented features), knowledge about when to apply which models, an improvement of available diagnosis algorithms and an empirical evaluation of the results using a collection of realworld examples. Finally, a debugging tool for Java programs is to be implemented that includes multiple models, diagnosis algorithms and mechanisms to express the desired behavior of a program.

Erstellung von prototypischer Software, die für die Erfüllung der Machbarkeitsstudie notwendig ist. Durchführung praktischer Tests der Software basierend auf bereitgestellter Hardware. Spezifikation von Sensoren

Erstellung von prototypischer Software, die für die Erfüllung der Machbarkeitsstudie notwendig ist. Durchführung praktischer Tests der Software basierend auf bereitgestellter Hardware. Spezifikation von Sensoren

The DEV Project aims at supporting and automating software debugging of VHDL programs, i.e., locating and (if possible) correcting bugs. The debugging tool to be developed during DEV adapts model-based diagnosis (MBD) for debugging. Project DEV should be a next step in providing models of VHDL programs in order to make the application of MBD to debugging more application oriented. During DEV the development of logical models of VHDL programs considering practical requirements regarding debugging time, the user interface, and coupling debugging with simulation and verification tools, is a main issue. Project DEV is expected to deliver multiple models of programs, means for allowing to handle those models, an empirically evaluation of the obtained results using real-world VHDL programs, an improvement of available diagnosis algorithms, and finally, the foundations of using a planning system for controlling and optimizing the whole debugging process.

Effort and cost estimations are the basis for project management to calculate the costs of software projects in order to create a budget offer long before the project's realization starts. At this time details about the project are rarely good enough for correct estimations. The basic requirement for a good estimation is the knowledge of the cost driving factors within the software development cycle. The outcome of an analysis regarding the cost driving factors are the expected demands for an effort estimation. A recalculation of project effort estimations using data from previous projects can provide pros and cons of current estimation procedures. In my thesis I work in this direction. For this purpose data from the LOGIM GesmbH company were taken. Function Point methods like IFPUG, Mark II and Full Function Points were tested. Furthermore, the Object Point and the COCOMO II method were analyzed with respect to the available data. This data comprises time recordings and source lines of code for various projects and thus yield to a comparison of the different methods with respect to their ability of computing good cost estimations. The analysis in my work leads to the main conclusion that the used method itself does not have an huge influence of the quality of estimation. More important is the handling of the chosen method which can be ensured by using clear definitions, a well educated personal, pre-adjusted parameters, and influence factors.

Network of Excellence in Model Based Systems and Qualitative Reasoning (MONET 2)

SEAL is a research project which was started in January 1998 at the Institute for Software Technology of the Technical University Graz, Austria. The goal of the project is to design and implement an interactive teaching and learning environment to be used as a tool in computing lectures. The main focus is not primarily the software as a product. The main target lies in research activities at the very edge of computer supported learning environments. The project is thematically bound to the support of teaching and learning computing, i.e. the teaching of methods and principles of programming and software engineering.