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We present GEM-NI -- a graph-based generative-design tool that supports parallel exploration of alternative designs. Producing alternatives is a key feature of creative work, yet it is not strongly supported in most extant tools. GEM-NI enables various forms of exploration with alternatives such as parallel editing, recalling history, branching, merging, comparing, and Cartesian products of and for alternatives. Further, GEM-NI provides a modal graphical user interface and a design gallery, which both allow designers to control and manage their design exploration. We conducted an exploratory user study followed by in-depth one-on-one interviews with moderately and highly skills participants and obtained positive feedback for the system features, showing that GEM-NI supports creative design work well.
Binary relations with certain properties such as biorders, equivalences or difunctional relations can be represented as particular matrices. In order for these properties to be identified usually a rearrangement of rows and columns is required in order to reshape it into a recognisable normal form. Most algorithms performing these transformations are working on binary matrix representations of the underlying relations. This paper presents an approach to use the RLE-compressed matrix representation as a data structure for storing relations to test whether they are biorders in a hopefully more efficient way.
Work in progress: Starter-project for first semester students to survey their engineering studies
(2015)
The central theme of the 2014 Annual Report is human thinking.
In an interview, University President Hartmut Ihne and 3Sat moderator Gert Scobel discuss the concept of thought: "Should we be allowed to give up our autonomy voluntarily?"
Our university’s Language Centre Director James Chamberlain examines to what extent thinking varies in different languages.
Professor Paul Plöger from the Department of Computer Science explains why robots have tremendous problems understanding complex relationships in open environments.
Rather than focusing solely on our university’s future, the Annual Report links the fascinating theme to the enormous variety of life, research and tuition offered by H-BRS.
Advanced driver assistance systems (ADAS) are technology systems and devices designed as an aid to the driver of a vehicle. One of the critical components of any ADAS is the traffic sign recognition module. For this module to achieve real-time performance, some preprocessing of input images must be done, which consists of a traffic sign detection (TSD) algorithm to reduce the possible hypothesis space. Performance of TSD algorithm is critical.
One of the best algorithms used for TSD is the Radial Symmetry Detector (RSD), which can detect both Circular [7] and Polygonal traffic signs [5]. This algorithm runs in real-time on high end personal computers, but computational performance of must be improved in order to be able to run in real-time in embedded computer platforms.
To improve the computational performance of the RSD, we propose a multiscale approach and the removal of a gaussian smoothing filter used in this algorithm. We evaluate the performance on both computation times, detection and false positive rates on a synthetic image dataset and on the german traffic sign detection benchmark [29].
We observed significant speedups compared to the original algorithm. Our Improved Radial Symmetry Detector is up to 5.8 times faster than the original on detecting Circles, up to 3.8 times faster on Triangle detection, 2.9 times faster on Square detection and 2.4 times faster on Octagon detection. All of this measurements were observed with better detection and false positive rates than the original RSD.
When evaluated on the GTSDB, we observed smaller speedups, in the range of 1.6 to 2.3 times faster for Circle and Regular Polygon detection, but for Circle detection we observed a decreased detection rate than the original algorithm, while for Regular Polygon detection we always observed better detection rates. False positive rates were high, in the range of 80% to 90%.
We conclude that our Improved Radial Symmetry Detector is a significant improvement of the Radial Symmetry Detector, both for Circle and Regular polygon detection. We expect that our improved algorithm will lead the way to obtain real-time traffic sign detection and recognition in embedded computer platforms.
Communicating Sequential Processes (CSP) [7] is a calculus for concurrent systems that has been the basis of subject-oriented business process management (S-BPM) [4]. We use CSPm -- a machine readable dialect of CSP -- to create a sequence of models for a case study on an "Automated Teller Machine" [1]. We use the refinement checker FDR2 to prove that certain models are correct implementations of specifications.
Comparison of the subject-oriented and the Petri net based approach for business process automation
(2015)
The subject-oriented modelling approach [5] significally differs from the classic Petri net based approach of many business process modeling languages like EPC [9], Business Process Model and Notation (BPMN) [11], and also Yet Another Workflow Language (YAWL) [10]. In this work, we compare the two approaches by modeling a case study called "Procure to Pay"[3], a typical business process where some equipment for a construction site is rented and finally paid. The case study is not only modelled but also automated using the Metasonic Suite for the subject-oriented and YAWL for the Petri net based approach.
Extraction of text information from visual sources is an important component of many modern applications, for example, extracting the text from traffic signs on a road scene in an autonomous vehicle. For natural images or road scenes this is a unsolved problem. In this thesis the use of histogram of stroke widths (HSW) for character and noncharacter region classification is presented. Stroke widths are extracted using two methods. One is based on the Stroke Width Transform and another based on run lengths. The HSW is combined with two simple region features– aspect and occupancy ratios– and then a linear SVM is used as classifier. One advantage of our method over the state of the art is that it is script-independent and can also be used to verify detected text regions with the purpose of reducing false positives. Our experiments on generated datasets of Latin, CJK, Hiragana and Katakana characters show that the HSW is able to correctly classify at least 90% of the character regions, a similar figure is obtained for non-character regions. This performance is also obtained when training the HSW with one script and testing with a different one, and even when characters are rotated. On the English and Kannada portions of the Chars74K dataset we obtained over 95% correctly classified character regions. The use of raycasting for text line grouping is also proposed. By combining it with our HSW-based character classifier, a text detector based on Maximally Stable Extremal Regions (MSER) was implemented. The text detector was evaluated on our own dataset of road scenes from the German Autobahn, where 65% precision, 72% recall with a f-score of 69% was obtained. Using the HSW as a text verifier increases precision while slightly reducing recall. Our HSW feature allows the building of a script-independent and low parameter count classifier for character and non-character regions.
This book chapter describes application examples of gas chromatography/mass spectrometry and pyrolysis – gas chromatography/mass spectrometry in failure analysis for the identification of chemical materials like mineral oils and nitrile rubber gaskets. Furthermore, failure cases demanding identification of polymers/copolymers in fouling on the compressor wall of a car air conditioner and identification of fouling on the surface of a bearing race from the automotive industry are demonstrated. The obtained analytical results were then used for troubleshooting and remedial action of the technological process.
In the fermentation process sugars are transformed into lactic acid. pH meters have traditionally been used for fermentation process monitoring based on acidity. More recently, near infrared (NIR) spectroscopy has proven to provide an accurate and non-invasive method to detect when the transformation of sugars into lactic acid is finished. The fermentation process when sugars are transformed into lactic acid. This research proposes the use of simplified NIR spectroscopy using multispectral optical sensors as a simpler and less expensive measure to end the fermentation process. The NIR spectrum of milk and yogurt is compared to find and extract features that can be used to design a simple sensor to monitor the yogurt fermentation process. Multispectral images in four selected wavebands within the NIR spectrum are captured and show different spectral remission characteristics for milk, yogurt and water, which support the selection of these wavebands for milk and yogurt classification.
The latest advances in the field of smart card technologies allow modern cards to be more than just simple security tokens. Recent developments facilitate the use of interactive components like buttons, displays or even touch-sensors within the card's body thus conquering whole new areas of application. With interactive functionalities the usability aspect becomes the most important one for designing secure and popularly accepted products. Unfortunately, the usability can only be tested fully with completely integrated hence expensive smart card prototypes. This restricts severely application specific research, case studies of new smart card user interfaces and the optimization of design aspects, as well as hardware requirements by making usability and acceptance tests in smart card development very costly and time-consuming. Rapid development and simulation of smart card interfaces and applications can help to avoid this restriction. This paper presents a rapid development process for new smart card interfaces and applications based on common smartphone technology using a tool called SCUID^Sim. We will demonstrate the variety of usability aspects that can be analyzed with such a simulator by discussing some selected example projects.
We present a system that combines voxel and polygonal representations into a single octree acceleration structure that can be used for ray tracing. Voxels are well-suited to create good level-of-detail for high-frequency models where polygonal simplifications usually fail due to the complex structure of the model. However, polygonal descriptions provide the higher visual fidelity. In addition, voxel representations often oversample the geometric domain especially for large triangles, whereas a few polygons can be tested for intersection more quickly.
We propose a high-performance GPU implementation of Ray Histogram Fusion (RHF), a denoising method for stochastic global illumination rendering. Based on the CPU implementation of the original algorithm, we present a naive GPU implementation and the necessary optimization steps. Eventually, we show that our optimizations increase the performance of RHF by two orders of magnitude when compared to the original CPU implementation and one order of magnitude compared to the naive GPU implementation. We show how the quality for identical rendering times relates to unfiltered path tracing and how much time is needed to achieve identical quality when compared to an unfiltered path traced result. Finally, we summarize our work and describe possible future applications and research based on this.
The study of locomotion in virtual environments is a diverse and rewarding research area. Yet, creating effective and intuitive locomotion techniques is challenging, especially when users cannot move around freely. While using handheld input devices for navigation may often be good enough, it does not match our natural experience of motion in the real world. Frequently, there are strong arguments for supporting body-centered self-motion cues as they may improve orientation and spatial judgments, and reduce motion sickness. Yet, how these cues can be introduced while the user is not moving around physically is not well understood. Actuated solutions such as motion platforms can be an option, but they are expensive and difficult to maintain. Alternatively, within this article we focus on the effect of upper-body tilt while users are seated, as previous work has indicated positive effects on self-motion perception. We report on two studies that investigated the effects of static and dynamic upper body leaning on perceived distances traveled and self-motion perception (vection). Static leaning (i.e., keeping a constant forward torso inclination) had a positive effect on self-motion, while dynamic torso leaning showed mixed results. We discuss these results and identify further steps necessary to design improved embodied locomotion control techniques that do not require actuated motion platforms.
Over the last 50 years, the controlled motion of robots has become a very mature domain of expertise. It can deal with all sorts of topologies and types of joints and actuators, with kinematic as well as dynamic models of devices, and with one or several tools or sensors attached to the mechanical structure. Nevertheless, the domain has not succeeded in standardizing the modelling of robot devices (including such fundamental entities as “reference frames”!), let alone the semantics of their motion specification and control. This thesis aims to solve this long-standing problem, from three different sides: semantic models for robot kinematics and dynamics, semantic models of all possible motion specification and control problems, and software that can support the latter while being configured by a systematic use of the former.
Virtual reality environments are increasingly being used to encourage individuals to exercise more regularly, including as part of treatment in those with mental health or neurological disorders. The success of virtual environments likely depends on whether a sense of presence can be established, where participants become fully immersed in the virtual environment. Exposure to virtual environments is associated with physiological responses, including cortical activation changes. Whether the addition of a real exercise within a virtual environment alters sense of presence perception, or the accompanying physiological changes, is not known. In a randomized and controlled study design, trials of moderate-intensity exercise (i.e. self-paced cycling) and no-exercise (i.e. automatic propulsion) were performed within three levels of virtual environment exposure. Each trial was 5-min in duration and was followed by post-trial assessments of heart rate, perceived sense of presence, EEG, and mental state. Changes in psychological strain and physical state were generally mirrored by neural activation patterns. Furthermore these change indicated that exercise augments the demands of virtual environment exposures and this likely contributed to an enhanced sense of presence.
Annual Report 2013 - 2014
(2015)
The steadily decreasing prices of display technologies and computer graphics hardware contribute to the increasing popularity of multiple-display environments, like large, high-resolution displays. It is therefore necessary that educational organizations give the new generation of computer scientists an opportunity to become familiar with this kind of technology. However, there is a lack of tools that allow for getting started easily. Existing frameworks and libraries that provide support for multi-display rendering are often complex in understanding, configuration and extension. This is critical especially in educational context where the time that students have for their projects is limited and quite short. These tools are also rather known and used in research communities only, thus providing less benefit for future non-scientists. In this work we present an extension for the Unity game engine. The extension allows – with a small overhead – for implementation of applications that are apt to run on both single-display and multi-display systems. It takes care of the most common issues in the context of distributed and multi-display rendering like frame, camera and animation synchronization, thus reducing and simplifying the first steps into the topic. In conjunction with Unity, which significantly simplifies the creation of different kinds of virtual environments, the extension affords students to build mock-up virtual reality applications for large, high-resolution displays, and to implement and evaluate new interaction techniques and metaphors and visualization concepts. Unity itself, in our experience, is very popular among computer graphics students and therefore familiar to most of them. It is also often employed in projects of both research institutions and commercial organizations; so learning it will provide students with qualification in high demand.
Sustainable development needs sustainable production and sustainable consumption. During the last decades the encouragement of sustainable production has been the focus of research and policy makers under the implicit assumption that the observable increasing ‘green’ values of consumers would also entail a growing sustainable consumption. However, it has been found that the actual purchasing behaviour often deviates from ‘green’ attitudes. This phenomenon is called the attitude-behaviour gap. It is influenced by individual, social and situational factors. The main purchasing barriers for sustainable (organic) food are price, lack of immediate availability, sensory criteria, lack or overload of information as well as the low-involvement feature of food products in conjunction with well-established consumption routines, lack of transparency and trust towards labels and certifications.
The phenomenon of the deviation between purchase attitudes and actual buying behaviour of responsible consumers is called the attitude-behaviour gap. It is influenced by individual, social and situational factors. The main purchasing barriers for sustainable (organic) food are price, lack of immediate availability, sensory criteria, lack or overload of information as well as the low-involvement feature of food products in conjunction with well-established consumption routines, lack of transparency and trust towards labels and certifications. The last three barriers are mainly of a psychological nature. Especially the low-involvement feature of food products due to daily purchase routines and relatively low prices tends to result in fast, automatic and subconscious decisions based on a so-called human mental system 1, derived from Daniel Kahneman’s (Nobel-Prize laureate in Behavioural Economics) model in behavioural psychology. In contrast, the human mental system 2 is especially important for the transformations of individual behaviour towards a more sustainable consumption. Decisions based on the human mental system 2 are slow, logical, rational, conscious and arduous. This so-called dual action model also influences the reliability of responses in consumer surveys. It seems that the consumer behaviour is the most unstable and unpredictable part of the entire supply chain and requires special attention. Concrete measures to influence consumer behaviour towards sustainable consumption are highly complex. Reviews of interdisciplinary research literature on behavioural psychology, behavioural economics and consumer behaviour and an empirical analysis of selected countries worldwide with a view to sustainable food are presented. The example of Denmark serves as a ‘best practice’ case study to illustrate how sustainable food consumption can be encouraged. It demonstrates that common efforts and a shared responsibility of consumers, business, interdisciplinary researchers, mass media and policy are needed. It takes pioneers of change who succeed in assembling a ‘critical mass’ willing to increase its ‘sustainable’ behaviour. Considering the strong psychological barriers of consumers and the continuing low market share of organic food, proactive policy measures would be conducive to foster the personal responsibility of the consumers and offer incentives towards a sustainable production. Also, further self-obligations of companies (Corporate Social Responsibility – CSR) as well as more transparency and simplification of reliable labels and certifications are needed to encourage the process towards a sustainable development.
Secure vehicular communication has been discussed over a long period of time. Now,- this technology is implemented in different Intelligent Transportation System (ITS) projects in europe. In most of these projects a suitable Public Key Infrastructure (PKI) for a secure communication between involved entities in a Vehicular Ad hoc Network (VANET) is needed. A first proposal for a PKI architecture for Intelligent Vehicular Systems (IVS PKI) is given by the car2car communication consortium. This architecture however mainly deals with inter vehicular communication and is less focused on the needs of Road Side Units. Here, we propose a multi-domain PKI architecture for Intelligent Transportation Systems, which considers the necessities of road infrastructure authorities and vehicle manufacturers, today. The PKI domains are cryptographically linked based on local trust lists. In addition, a crypto agility concept is suggested, which takes adaptation of key length and cryptographic algorithms during PKI operation into account.
Simultaneous multifrequency radio observations of the Galactic Centre magnetar SGR J1745-2900
(2015)
Reducing energy consumption is one of the most pursued economic and ecologic challenges concerning societies as a whole, individuals and organizations alike. While politics start taking measures for energy turnaround and smart home energy monitors are becoming popular, few studies have touched on sustainability in office environments so far, though they account for almost every second workplace in modern economics. In this paper, we present findings of two parallel studies in an organizational context using behavioral change oriented strategies to raise energy awareness. Next to demonstrating potentials, it shows that energy feedback needs must fit to the local organizational context to succeed and should consider typical work patterns to foster accountability of consumption.
Reducing energy consumption is one of the most pursued economic and ecologic challenges concerning societies as a whole, individuals and organizations alike. While politics start taking measures for energy turnaround and smart home energy monitors are becoming popular, few studies have touched on sustainability in office environments so far, though they account for almost every second workplace in modern economics. In this paper, we present findings of two parallel studies in an organizational context using behavioral change oriented strategies to raise energy awareness. Next to demonstrating potentials, it shows that energy feedback needs must fit to the local organizational context to succeed and should consider typical work patterns to foster accountability of consumption.
Although much effort is made to prevent risks arising from food, food-borne diseases are an ever present-threat to the consumers’ health. The consumption of fresh food that is contaminated with pathogens like fungi, viruses or bacteria can cause food poisoning that leads to severe health damages or even death. The outbreak of Shiga Toxin-producing enterohemorrhagic E. coli (EHEC) in Germany and neighbouring countries in 2011 has shown this dramatically. Nearly 4.000 people were reported of being affected and more than 50 people died during the so called EHEC-crisis. As a result the consumers’ trust in the safety of fruits and vegetables decreased sharply.
Although much effort is made to prevent risks arising from food, food-borne diseases are an ever-present threat to the consumers’ health. The consumption of fresh food that is contaminated with pathogens like fungi, viruses or bacteria can cause food poisoning that leads to severe health damages or even death. The outbreak of Shiga Toxin-producing enterohemorrhagic E. coli (EHEC) in Germany and neighbouring countries in 2011 has shown this dramatically. Nearly 4.000 people were reported of being affected and more than 50 people died during the so called EHEC-crisis. As a result the consumers’ trust in the safety of fruits and vegetables decreased sharply.
Fundamentals of Energy Meteorology - Influence of atmospheric parameters on solar energy production
(2015)
So far, sustainable HCI has mainly focused on the domestic context, but there is a growing body of work looking at the organizational context. As in the domestic context, these works still rest on psychological theories for behaviour change used for the domestic context. We supplement this view with an organizational theory-informed approach that adopts organizational roles as a key element. We will show how a role-based analysis could be applied to uncover information needs and to give em-ployee’s eco-feedback, which is linked to their tasks at hand. We illustrate the approach on a qualitative case study that was part of a broader, ongoing action research conducted in a German production company.
With the increasing average age of the population in many developed countries, afflictions like cardiovascular diseases have also increased. Exercising has a proven therapeutic effect on the cardiovascular system and can counteract this development. To avoid overstrain, determining an optimal training dose is crucial. In previous research, heart rate has been shown to be a good measure for cardiovascular behavior. Hence, prediction of the heart rate from work load information is an essential part in models used for training control. Most heart-rate-based models are described in the context of specific scenarios, and have been evaluated on unique datasets only. In this paper, we conduct a joint evaluation of existing approaches to model the cardiovascular system under a certain strain, and compare their predictive performance. For this purpose, we investigated some analytical models as well as some machine learning approaches in two scenarios: prediction over a certain time horizon into the future, and estimation of the relation between work load and heart rate over a whole training session.