Senior Scientist ohne Doktorat (w/m) am Institut für Unterrichts- und Schulentwicklung (IUS) – Kennung 634H/18

Stellenausschreibung Wissenschaftliches Personal| Foto: kasto/

Die Alpen-Adria-Universität Klagenfurt schreibt folgende Stelle zur Besetzung aus:

Senior Scientist ohne Doktorat (w/m)

an der Fakultät für Interdisziplinäre Forschung und Fortbildung, Institut für Unterrichts- und Schulentwicklung (IUS), im Rahmen der Koordinationsstelle Lehramtsausbildung, im Beschäftigungsausmaß von 100 {c8db3f4443fb2f1c80e20e2e8420a201d47393e6b007c83f4847286f4b955a35} (40 Wochenstunden, Uni-KV: B1, ) vorerst befristet auf ein Jahr, mit der Option auf Überleitung in ein unbefristetes Dienstverhältnis. Das monatliche Mindestentgelt für diese Verwendung beträgt € 2.794,60 brutto (14 x jährlich) und kann sich durch die Anrechnung tätigkeitsspezifischer Vorerfahren erhöhen. Voraussichtlicher Beginn des Angestelltenverhältnisses ist 1. Jänner 2019.

Der Aufgabenbereich umfasst:

  • Koordination der bildungswissenschaftlichen Lehrveranstaltungen
  • Mitarbeit an der LehrerInnenausbildung im Rahmen des Entwicklungsverbunds Süd/Ost und bei der Kooperation mit der Pädagogischen Hochschule Kärnten
  • Organisation, Koordination und Durchführung des Aufnahmeverfahrens für die LehramtskandidatInnen
  • Beratung von Lehramtsstudierenden, Lehramtsinteressierten und Lehrkräften
  • Mitwirkung in den Lehramtsstudiengängen und an den Aufgaben der School of Education, Beiträge zu den Forschungsschwerpunkten des Instituts, der Fakultät und der School of Education sowie Bereitschaft zur interdisziplinären Kooperation
  • Selbstständige Lehrtätigkeit und entsprechende Prüfungstätigkeit in den bildungswissenschaflichen Anteilen des Lehramtsstudiums
  • Selbstständige Konzeption von Forschungsprojekten inkl. Antragstellung und Mitwirkung in bestehenden lehramtsbezogenen Forschungsprojekten
  • Mitarbeit an allgemeinen administrativen und organisatorischen Aufgaben des Instituts


  • Abgeschlossenes Diplom- oder Masterstudium im Bereich der Sozial-, Kultur- oder Erziehungswissenschaften oder abgeschlossenes Lehramtsstudium an einer in- oder ausländischen Hochschule
  • Gute Kenntnisse des österreichischen Schulwesens
  • Erfahrungen im universitären Lehr- und Forschungsbetrieb
  • Kompetenzen im Bereich quantitativer oder/und qualitativer Forschungsmethoden
  • Ausgewiesene Kompetenzen und Erfahrungen im Organisieren und Koordinieren
  • Hohe Kommunikations- und Teamfähigkeit

Der Nachweis für die Erfüllung aller Voraussetzungen für die Einstellung muss bis spätestens 24. Oktober 2018 vorliegen.

Erwünscht sind:

  • Gute Englischkenntnisse
  • Erfahrungen im Bereich der Unterrichts-, Schul- oder Bildungssystementwicklung
  • Erfahrungen in der Schulpraxis
  • Erfahrungen in der LehrerInnenaus- und -weiterbildung
  • Erfahrungen in der Kooperation mit Institutionen der Bildungspolitik und –verwaltung (Pädagogische Hochschulen, Bildungsdirektionen, Ministerium)

Die Universität strebt eine Erhöhung des Frauenanteils beim wissenschaftlichen Personal an und fordert daher qualifizierte Frauen zur Bewerbung auf. Frauen werden bei gleicher Qualifikation vorrangig aufgenommen.

Menschen mit Behinderungen oder chronischen Erkrankungen, die die geforderten Qualifikationskriterien erfüllen, werden ausdrücklich zur Bewerbung aufgefordert.

Allgemeine Informationen finden BewerberInnen unter

Bewerbungen sind mit den üblichen Unterlagen bis spätestens 24. Oktober 2018 unter der Kennung 634H/18 an die Alpen-Adria-Universität Klagenfurt, Dekanatekanzlei / Recruiting, ausschließlich über das Online-Bewerbungsformular unter zu richten.

Es besteht kein Anspruch auf Abgeltung von Reise- und Aufenthaltskosten, die aus Anlass des Aufnahmeverfahrens entstehen.

Der Beitrag Senior Scientist ohne Doktorat (w/m) am Institut für Unterrichts- und Schulentwicklung (IUS) – Kennung 634H/18 erschien zuerst auf Alpen-Adria-Universität Klagenfurt.

Source: AAU TEWI

Presentation of research results at the 34th IEEE International Conference on Software Maintenance and Evolution

Symbolfoto Forschungsgruppe SERG

Veit Frick, Christoph Wedenig, and Martin Pinzger from the software engineering research group (ISYS/SERG) are presenting their results on helping software developers to better understand changes in the source code and their impact at the 34th IEEE International Conference on Software Maintenance and Evolution, in Madrid, Spain. The two publications are „Generating Accurate and Compact Edit Scripts using Tree Differencing“ and „DiffViz: A Diff Algorithm Independent Visualization Tool for Edit Scripts“. Preprints of the publications are available at:

Der Beitrag Presentation of research results at the 34th IEEE International Conference on Software Maintenance and Evolution erschien zuerst auf Alpen-Adria-Universität Klagenfurt.

Source: AAU TEWI

The MIM Department at the annual conference of the research group Konsum & Verhalten in Lüneburg

Last week, the annual conference of the research group Konsum & Verhalten took place at Leuphana Universität Lüneburg. As every year, the MIM Department’s attendance was numerous – this year Ralf Terlutter, Sonja Bidmon, Svenja Diegelmann and Anita Paggitz attended. At this conference, current research findings from the area of consumer behaviour are presented and discussed and the relations to the German-speaking research community are strengthened and extended. As always, the K&V conference was a highlight in the conference calendar of our staff. Many thanks to the organizers!

Der Beitrag The MIM Department at the annual conference of the research group Konsum & Verhalten in Lüneburg erschien zuerst auf Alpen-Adria-Universität Klagenfurt.

Source: AAU TEWI

Efficiency in the great big data cloud

Radu Prodan | Foto: aau/Waschnig

Every minute, video material amounting to roughly 400 hours of viewing time is uploaded to YouTube. Users watch one billion hours’ worth of videos every single day, according to the channel’s own statistics. This data traffic between the YouTube “cloud” and the terminal devices, more than half of which are mobile devices, requires efficient organisation. The computer scientist Radu Prodan specialises in the efficiency aspects of these distributed and parallel systems. In the following interview, he discusses the possibilities and impossibilities that still lie ahead and that present enormous challenges for technology, humankind, and nature.

In June, the fastest supercomputer commenced operation in the USA, boasting a performance capacity of 200 petaflops (one quadrillion floating point operations per second). You examine how well these vast systems function. What challenges do you perceive?
These computers consist of millions of heterogeneous components, combined in a highly complex and hierarchical structure. The efficient programming of supercomputers of this vast size represents a considerable challenge, as the necessary communication between the components, the synchronisation, and many other inevitable overheads tend to result in inefficiency. Many of these computers have an actual utilization of only 15 to 20 per cent compared to the peak performance they could theoretically achieve. This translates into a performance problem for not only numerous applications, but also for the operator, who is not making full use of computing infrastructure that was acquired at great cost.

What is the main problem?
In many cases, it is the inability to reach the theoretical peak performance. Supercomputers are steadily growing in size in the attempt to achieve speeds above one quadrillion operations per second. If you gain mass, you sacrifice velocity, as happens when the communication between the individual components is too frequent or involves excessively high data volumes. “Extreme data” is the byword of the big data concept, which is characterised by vast volumes of data that need to be retrieved, communicated and analysed at a speed approximating real time. This is the issue we are currently addressing in the context of a new European research project.

Why is this necessary?
Nowadays, there are many scientific and commercial applications that need to generate, store, filter, and analyse data at a rate of hundreds of gigabits per second. One contemporary example is the simultaneous analysis of millions of images each day, which involves a real-time database scan of one billion social data posts. Conventional hard drives and commercial storage systems are not up to this task. What we are trying to do, is to improve existing concepts and technologies, and our particular focus is on data-intensive applications running on systems that consist of millions of computing elements. These are the so-called exascale computing systems, which can manage one quadrillion operations per second.

What is your contribution and what will the new project contribute to improving these exascale systems?
We aim to develop new programming paradigms, interfaces, runtime tools, and methods to efficiently deploy data-intensive tasks on exascale systems, which will pave the way for the future utilisation of massive parallelism through a simplified model of the system architecture. This should facilitate advanced performance and efficiency, and provide powerful operations and mechanisms to facilitate the processing of extremely large data sources at high speed and/ or in real time.

Many of the numbers mentioned sound like superlatives. Nonetheless, it seems that we are still far from achieving genuine superlatives in terms of the demand for computing capacity. What is your view?
Gordon Moore, co-founder of Intel, formulated Moore’s Law in 1965, which essentially states that the speed of computing systems will double every 18 months. This law still holds true today. Certainly, the rates of increase are not nearly adequate to cope with the growing volume of data. There are estimates that claim that each human being in the world will be generating around 1.5 to 2 megabytes per second by 2020. We can neither store nor process such vast volumes of data. That is why it is important to interpret and filter the data in such a way that only the important information is used for further processing.

Which approaches might be able to deliver a solution?
That depends very much on the application. The trend today is towards edge computing. On the one side, we have a vast cloud, where numerous parallel computers form a common unit, which processes data in a centralised manner. We now know that the cloud is not sufficient to cope with the sheer volume of data. The distance between the terminal device and the server farm – which might be located on the other side of the world – leads to latency issues. Even though it may only be a matter of a few milliseconds, humans are very sensitive when it comes to having to wait for data to be retrieved. This is especially critical in the case of highly-interactive user interfaces such as computer games. It is important that we manage to bring the cloud closer to the end user, which means processing the data at the edge of the Internet. That is the fundamental idea of edge computing.

Can you describe how this might work in practice?
People dynamically and adaptively plug a small network-compatible computer into an electrical socket in the vicinity of the application. This provides every individual with their own small “cloud”, which manages the data and permits significantly faster communication, at a speed that is much closer to real time. The management of such distributed edge/ cloud computers still needs a lot of development effort to ensure that they are automated, transparent, adaptive, and flexible. Still, we can expect to see them on the market in the next few years.

Does this mean that the advantages of the cloud are lost, i.e. the unlimited resources, access to data anytime and anywhere, scalability, outsourcing and with it the confidence that the data are securely stored elsewhere?
No, not at all, because it basically supplements the existing cloud. Security will certainly remain a big issue, as long as our data are stored on an ever-increasing number of third-party devices, particularly in view of today’s new European data protection regulations.

All these giant computers and server farms also consume energy. To what extent do they endanger our environment?
This is the dark side of the cloud: they consume vast amounts of resources. Looking back, a few years ago, the data processing centres of the world already consumed around three per cent of the world’s total energy supply, and this value is rising drastically. There is also a massive effect on greenhouse gas emissions. As cloud computing expands, be it in the shape of large clouds or in the form of many small individual clouds, we urgently have to consider the environmental issues as well. That is why our work on energy efficiency is so vital, both in terms of computer design and in relation to the hardware technology.

Can the concept of edge computing offer assistance here?
Yes, the idea is to take the large red hotspot that greedily devours energy and to cool it down using numerous small green units distributed across the globe. This follows precisely the same line as the notion to harness the many terminal devices, which are used throughout the world and are now very powerful, by using them more intensively for data processing. This concept of peer-to-peer computing first emerged in the 1990s. At the time, it was mainly used for file sharing, for instance to upload and download music or movies, often drifting into illegal practices. Today, we can take this one step further by considering, in particular, how to harness the computing power of these many devices.

Does anyone ever think about “tidying up” within the data bulge, performing a thorough clean-up and discarding data?
Storage space is inexpensive nowadays, especially if the speed of reading and writing is of no great concern. No-one here is thinking about a clean-up. Once the data are either uploaded to the Internet or when they are leaked online inadvertently, it is practically impossible to delete them.

Considering the susceptibility to errors, what is better: one big cloud or countless small clouds?
In the case of individual computers we have a “single point of failure”, as we say in computer science. Here, it is possible to implement very strict security measures and to ensure that the core is well guarded. Where we have many decentralised units, the damage that affects one of the entities in the case of a security issue is naturally much less severe. At the same time, however, it is far less simple to implement requisite safety measures. Numerous small devices also lead to the problem of cheating, which means that we distribute the status from one point to several members. If everyone functioned properly, this would not present a problem. But that is not how the world works.

You are 44 years old. What problem would you like to see solved in your field of work by the time you retire? Or, to put it differently: If you were to achieve fame as a scientist, what would you like to be famous for?
The programming languages are still very primitive, especially in the case of high-performance computers. The way we programme today has hardly changed since the 1970s, and we have not yet been able to develop a higher-level programming language.

Why not?
It’s a translation problem. The translation from a higher-level programming language to an application involves so many layers and steps which need to be overcome that the problem seems insurmountable for now. We are also still dealing with high levels of inefficiency.

Will it ever be possible to use a natural language to programme computers?
There are many students who express that wish during the early semesters of their studies. (laughs) The holy grail of programming is to be able to use the natural – German, English, or Romanian – language to do more than merely issue orders. That much has been achieved already: “Call Thomas!” But programming also means developing new, innovative programmes, and from today’s perspective, it is not yet conceivable how we could manage this with natural language. What might be feasible is a simpler language that is also accessible for a greater number of people.

There are some voices that say that programming – along with writing and arithmetic – will soon be one of the fundamental skills of human beings. Do you agree?
It depends what is meant by “programming”. If the interface is easily accessible, a person can programme without realizing it. However, I do not believe that everyone is capable of algorithmic thinking, and neither do I believe that everyone has to be capable. After all, not everyone needs to be able to paint at the level of an accomplished artist. Thinking back to my university days, there was a definite moment when things simply clicked into place, and I understood what it means to think, structure and develop in this way. From that point on, things were much easier.

for ad astra: Romy Müller

About the person

Radu Prodan joined Alpen-Adria-Universität Klagenfurt in March 2018 as Professor for Distributed Systems at the Department of Information Technology. Born in Romania, he completed his engineering degree at the Technical University of Cluj-Napoca. Having gained his doctoral degree at Vienna Technical University (TU Wien), he was granted the venia docendi for Informatics by the University of Innsbruck in 2009. He has worked at ETH Zurich, the University of Basel, and the Swiss Scientific Computing Centre. From 2004, until his appointment as professor at AAU, he lectured at the Department of Informatics at the University of Innsbruck, and participated as lead scientist in several FWF, FFG, and EU projects. The EUH2020-FET project “ASPIDE”, also run by Radu Prodan, was recently approved, with the aim to improve exascale systems. His key research areas are: parallel and distributed systems, cloud computing, high-performance scientific computing, performance analysis and tools, scheduling and optimization, compiler technology, and energy efficiency.

Radu Prodan | Foto: aau/Waschnig

Gerald Hochegger | Foto: aau/Müller

Behind the scenes

The photo shoot for the ad astra cover story took place in the Data Center of the University of Klagenfurt. The Data Center is managed by Central Computing Services (ZID). It is run by the head of the Department of Server and Communication Systems, Gerald Hochegger (pictured here). The Data Center hosts the complete range of the university’s IT services (such as Moodle, the online staff portal, or the university’s website) along with the bespoke servers of numerous departments.

Der Beitrag Efficiency in the great big data cloud erschien zuerst auf Alpen-Adria-Universität Klagenfurt.

Source: AAU TEWI

“Drones Are Here to Stay. Get Used to It.”

Drohne | Foto: THANANIT/

This was the title of a TIME article, which was included in the magazine’s special report on “The Drone Age”. We asked Christian Bettstetter to tell us what today’s drones can do and what drone(swarms) are not yet capable of. One thing is certain: Our airspace is going to be much busier in the future.

Mr Bettstetter, would you board an autonomous flying taxi drone in Dubai?
(without hesitation) Yes, I would. I trust this technology. Anyway, nowadays it is already the case that most airplanes switch to autonomous flying mode once they are in the air.

For ten years, scientist have been conducting drone research at Alpen-Adria-Universität. You have been here slightly longer, since 2005. What were drones unable to do then, which they can manage now?
The quadcopters we use are much cheaper today. The price is now barely a tenth of the price ten years ago. There has also been a significant increase in software functionality. It is, more or less, possible to purchase a drone from an electronics store, which is automatically capable of flying across a certain area. When we started, drones were specifically designed for a niche market and for research purposes; today, pretty much anyone can own a drone.

Does it seem sensible to you that private individuals can own drones?
To be honest, I am not sure that it does make complete sense. One negative example are the selfie-drones that are threatening to buzz over the heads of tourists everywhere. Having said that, in the past I have sometimes misjudged these kinds of predictions: In the case of the mobile phone and the tablet PC I honestly did not believe that they would find their way into every private home. I have learned to be more cautious with predictions.

Do you consider the current regulations to be adequate?
The prevailing impression is that the respective legal framework tends to lag behind the technical developments. The challenge I see is how to integrate autonomous aerial vehicles in traditional air traffic in general.

Which professional purposes could drones usefully fulfil?
These might include the maintenance of industrial installations or operational planning on the part of the emergency services. A very recent addition is the use in entertainment shows, where drones with light effects are deployed as an entertaining (environmentally friendly) alternative to fireworks. During the Super Bowl halftime interval Intel presented just such a show. Transport services by drones are also up and coming, for example ferrying blood or lab samples between hospitals. This kind of use makes sense in locations where the infrastructure on the ground is poorly developed or cannot be used due to environmental impacts such as heavy rainfall. This is no longer a fiction: This type of system is currently being operated in Rwanda.

How realistic is the notion that private parcels might be delivered by drone in the future?
Once the regulations have been set out accordingly, firms will start to offer this service. Technically, there has been a lot of progress: Drones can start up autonomously, they can reach a target, and they can land. Nonetheless, in reality, numerous difficulties still need to be resolved: Thunderstorms and strong winds, for instance, represent a huge problem. Maybe we can compare the current status with that of the automobile about 100 years ago. The basic technology works, but we still have far to go before it can be described as an advanced technology.

What contributions have you and your colleagues made to the development of drones over the past ten years?
Our very first research project involved getting drones to fly across an area and take photos from the air, which would subsequently be joined together to form an overall picture. The compilation process and the wireless communication presented a big challenge. To achieve the best possible results, we collaborated with the emergency forces and the fire service, who also went on to test the technology. Today, this works pretty well. Next, we worked on the coordination between the drones, i.e. we explored the idea that drones – much like a flock of birds in nature – should be able to fly in a self-organised manner and without central pre-programming. There is still a lot of active research in this area, but it has not yet produced a marketable product. Most recently, camera-based navigation entered the scene. Here, a drone will observe its surroundings and use this information for orientation purposes.

You have offered many positive examples of how to use drones. However, it cannot be ignored that drones also have military applications. How do you distance yourself from this aspect?
I once received an informal inquiry from a US customer with links to the military, which we declined. In any case, I suspect that military research in this area is already miles ahead of the civil scientific world. The military is involved in numerous developments that we are not even aware of. After all, they do not publish their results. Generally speaking, much good can be done with drones, but they can also be used to kill. Military drones usually tend to be very large aerial vehicles, which cannot really be compared with our small quadcopters. But quadcopters, too, can cause problems: they can irritate the neighbour who is enjoying his garden, they can be used to spy on people, and they can introduce a significant level of risk in the case of large-scale events. We need regulations to address these aspects, and technology can do its part as well. Geoblocking, for instance, can be used to prevent drones from lifting off in the vicinity of a stadium.

What are the particular challenges in drone research?
First of all, the setting is rather complex: It is not possible to casually experiment with new algorithms once the drone is airborne. If a problem occurs, the drone might simply drop from the sky, or crash into someone or something. This makes things far more complicated for us than for those who work with ground-level robots. And secondly, the topic of swarm intelligence still features many sticking points, which need to be resolved: These include the ability of groups of drones to adapt smoothly to changes in the environment.

for ad astra: Romy Müller

About the person

Christian Bettstetter is professor and head of the Institute of Networked and Embedded Systems. He is also founding scientific director of Lakeside Labs GmbH. He has published his research work on wireless communications technology and autonomous and self-organizing systems in more than 140 scientific articles. Christian Bettstetter is a member of the core faculty of the Karl Popper Doktorats- und Wissenschaftskolleg in the field of “Networked Autonomous Aerial Vehicles” at the University of Klagenfurt.

Christian Bettstetter | Foto: aau/Waschnig

Der Beitrag “Drones Are Here to Stay. Get Used to It.” erschien zuerst auf Alpen-Adria-Universität Klagenfurt.

Source: AAU TEWI

“I worked hard for this”

Jennifer Simonjan | Foto: Daniel Bruckner

Jennifer Simonjan’s work focuses on camera networks. In conversation with ad astra she tells us why she does not fear ubiquitous camera surveillance, what she recently learned in Atlanta about nano cameras, and what it took for her, a first-generation student from an environment that was hardly technologically-minded, to gain her current position.

For a long time, there was nothing to indicate that Jennifer Simonjan might one day become an engineer, the predoc scientist tells us during the interview. She was not one of those children who owned a computer from an early age or who spent a lot of time playing computer games. Her parents, the Bulgarian father lives in Germany and the Austrian mother lives in Carinthia, do not have an academic background. Nonetheless, at school Simonjan was quick to notice: “Maths is easy for me.” Once she had completed her secondary vocational school (HBLA), she opted for a degree in Information Technology in Klagenfurt. What followed was “hard work”: “During the first three semesters, I barely understood a word in the courses that were also attended by numerous people who had completed a secondary technical school (HTL). But finally, the famous knot unravelled, and I suddenly understood the bigger picture. Since then, I have really enjoyed my subject and I cannot imagine doing anything else.”

Today, Jennifer Simonjan works at the university as predoc scientist and is a member of the working group assembled by Bernhard Rinner at the Institute of Networked and Embedded Systems. She specialises in camera networks, where cameras communicate with each other in order to achieve shared goals. “Let’s use an animal park as an example. The park management wants to know where the animals tend to be at which times. To help us establish the facts, we can install 50 cameras throughout the animal park. The objective of my work in relation to localisation in camera networks is to ensure that the cameras work things out by themselves: Who is my neighbour? Who can I transfer tasks to? Who is looking in which direction? These technologies should help to simplify the installation of camera networks.”

In order to pursue her work, Simonjan has built a simulator, which allows her to test algorithms for the camera networks. Over the past year she has worked on the so-called calibration algorithm, which calculates the ideal relations to the respective neighbours within the camera network. When we ask whether she finds the idea of a world full of camera surveillance unsettling, she states: “I do not feel threatened by it. Our research group is working on the protection of the private sphere in cameras. The idea is to ensure that the images do not leave the camera, and instead the camera simply files a report when something is conspicuous. This could have a beneficial application in technologies that allow the elderly to remain in their own homes for longer without putting themselves at risk. If someone were to stumble and remain lying on the floor for some time, the camera could transmit this information to family members.”

Recently, Jennifer Simonjan added a further area of research to her list of interests, after spending three months at the elite university Georgia Institute of Technology in Atlanta. She found the institution fascinating, not only due to its size, but also due to its comprehensive fee-funded offer for students. The research team she was assigned to in Atlanta worked, among other things, on nano cameras: cameras that are thinner than a single hair. Currently, nothing in this field is ready for the market. However, Simonjan firmly believes that the medical future, in particular, will belong to these extremely small cameras.

Jennifer Simonjan expects to conclude her doctoral degree within the next 12 months. What might follow is currently wide open: “I am not entirely sure what I want to do next. I do know that I would like to stay involved with research – either at a university or at an external institute.” The available opportunities always partially depend on one’s willingness to relocate to almost anywhere in the world. Simonjan knows: “For a limited period, I’d be happy to go absolutely anywhere. I love the international exchange, and it is unbelievably exciting to get to know the boundless academic world. But: At some point I want to build a home here in Carinthia.”

In her field of research, there seem to be limitless possibilities waiting to be discovered. Yet those who think that things are easier for a young woman in a setting where the technical faculties perpetually strive to meet quotas (for women), are mistaken: “Some believe that everything is simply dropped into your lap. I worked hard for this. And unfortunately, I sometimes find myself doubting: Are they addressing me as an engineer or as a female engineer? Ultimately, the only thing that should count is good scientific work.”

for ad astra: Romy Müller

A few words with … Jennifer Simonjan

What career would you have chosen, if you had not become a scientist?
Probably something in the world of the arts (e.g. drama) or organisation (e.g. event management).

Do your parents understand what it is you are working on?
I think they do, on an abstract level. If not, I will smuggle in this article, hidden amongst the morning papers.

What is the first thing you do when you arrive at the office in the morning?
I drink coffee and read my e-mails.

Do you have proper holidays? Without thinking about your work?
I don’t manage to shut out work completely; I still think about work, about my doctoral thesis, and I remain available to colleagues and students via e-mail. Still, I manage to relax and enjoy my holidays.

What makes you furious?
Bad coffee and miscommunication.

What calms you down?
Spending time with friends and family.

Who do you regard as the greatest scientist in history, and why?
There are many outstanding scientists who fascinated me when I first learned about them at school. To me, the most remarkable ones are those who managed great things despite having few means, and who managed to retain their humanity despite everything.

What are you embarrassed about?
My fear of negative responses.

What are you afraid of?
Losing people who are important to me and making poor decisions.

What are you looking forward to?
Exploring the world, making fascinating new acquaintances, and finding out what life has in store for me.

Der Beitrag “I worked hard for this” erschien zuerst auf Alpen-Adria-Universität Klagenfurt.

Source: AAU TEWI

Automatic log-loading at sawmills

Holzwirtschaft | Foto: adobe-stock

Sawmills can already transform wooden logs into planks at lightning speed. In contrast, the process of unloading the logs from the truck and transferring them to the sawmill is relatively slow. A project funded by the FFG is now exploring ways to automate this step.

In the forest, trees are loaded onto trucks with the help of timber cranes and are subsequently transferred to sawmills. The trucks equipped with timber cranes drive up as close as possible to the start of the production line in the sawmill and then the logs are heaved into place for the next processing step – in a process that is manually controlled by a human. From then on, things move very quickly: Once the logs are on the conveyer belt, it is just a matter of minutes before the final planks are produced.

Springer Maschinenfabrik GmbH in Friesach, a company that specialises in innovative solutions for the timber industry, is working to optimise this stage of the process. The international company is a partner in a joint project together with Graz University of Technology (Institute of Computer Graphics and Vision) and the University of Klagenfurt (Institute of Smart Systems Technologies). The research project bears the title Auto-LOG (Automated Log Ordering through robotic Grasper) and has been designed to find a solution for this loading problem.

The project is managed by Stephan Weiss, Professor for the Control of Networked Systems at the University of Klagenfurt (AAU). He explains the challenges as follows: “Trees are not uniform, not in their consistency and not in the way in which they travel to the start of the production chain, lying on the bed of a truck. We aim to write the algorithms and design the methods in such a way that the system can comfortably manage these discrepancies.” The work plan has been organised to comprise several stages.

„Trees are not uniform, not in their consistency and not in the way in which they travel to the start of the production chain, lying on the bed of a truck.“

In a first step, the participating company will provide the researchers with a scaled model (1:5), which will be used to test various situations. Next, the team hopes to define the navigation or regulation of the timber crane’s gripping arm. This requires artificial intelligence (AI), as Stephan Weiss explains: “Under the leadership of Friedrich Fraundorfer, the team at TU Graz will take a closer look at the timber load with the help of AI and will place 3D markers at points where the gripper can be positioned.” In the second phase, the objective will be the robust task accomplishment. “This is where the expertise of the sensor technology team managed by Hubert Zangl at AAU will come into play: The sensors should be able to recognise whether the gripper can properly grasp and hold the log. One way to measure this is by checking the weight distribution.” The measurements retrieved by the sensors are subsequently transferred to the control system, which should then be able to perform the correct actions.

„The gripping arm should be able to perform in a human-like manner and should know how to competently grasp the log in order to transfer it to the onward production chain.“

But what precisely does the control system do? Stephan Weiss explains: “The control system has to recognise where the crane is at any given moment and has to steer it in such a way that it can move from A to B in a meaningful way.” The associated research is similar to Stephan Weiss’ work on drones: That, too, involves a movable object, which must be continuously observed in terms of its condition, in order to facilitate the intended movement. Just as drones cannot rely on GPS-based navigation in many areas, the GPS signal does not work to control gripping arms, as it is far too imprecise. But that is not where the challenges end: Looking ahead, the gripping arm attached to the innovative timber crane should be able to solve problems autonomously. If, for instance, despite all precautions, a log did drop to the ground between the truck and the sawmill, the crane should automatically solve the problem and pick up the log. This also requires Artificial Intelligence: “The gripping arm should be able to perform in a human-like manner and should know how to competently grasp the log in order to transfer it to the onward production chain.”

Similar technologies already exist elsewhere, for instance in the USA. “The dimensions are completely different there. In this country, the companies working with these kinds of machines are much smaller in relative terms, and the conditions tend to be much more heterogenous”, Stephan Weiss elaborates. The AI-based understanding, the control system, and the navigation as well as self-sufficient sensors allow the utilisation of this technology by smaller companies in a wide range of existing production lines and sectors. The versatility of the approach provides high flexibility, strong performance, and the dynamic adaptability of a production line. The results of the project, which is funded by the Austrian Research Promotion Agency (FFG), are expected in 2021.

The local Institute of Smart Systems Technologies has already gained experience in forestry in recent years with the Forest-iMate project. The objective of this project is to use small, unmanned helicopters to conduct parameter readings for forest inventory tasks. Information such as the diameter of a tree at chest level, the shape of the trunk, and the position of the individual trees are gathered by drones, allowing scientists to extrapolate the volume, quality, and distribution of the timber. Issues remaining to be solved include object recognition, route planning, navigation, and the avoidance of obstacles. The project is now in the final phase.

for ad astra: Romy Müller

About the person

Stephan M. Weiss, born in Caracas (Venezuela) in 1981, grew up in Switzerland. He studied electrical engineering and information technology at ETH Zurich, where he completed his doctoral degree at the Autonomous Systems Lab in 2012. His career then took him to NASA’s Jet Propulsion Laboratory (JPL) in California, where he continued to work in the area of camera-based navigation for unmanned helicopters. An adapted version of the drone-flight technology developed by Weiss will be used during the 2020 Mars Mission.

Stephan Weiss | Foto: aau/

Der Beitrag Automatic log-loading at sawmills erschien zuerst auf Alpen-Adria-Universität Klagenfurt.

Source: AAU TEWI