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The problem of vessel collisions or near-collision situations on sea, often caused by human error due to incomplete or overwhelming information, is becoming more and more important with rising maritime traffic. Approaches to supply navigators and Vessel Traffic Services with expert knowledge and suggest trajectories for all vessels to avoid collisions, are often aimed at situations where a single planner guides all vessels with perfect information. In contrast, we suggest a two-part procedure which plans trajectories using a specialised A* and negotiates trajectories until a solution is found, which is acceptable for all vessels. The solution obeys collision avoidance rules, includes a dynamic model of all vessels and negotiates trajectories to optimise globally without a global planner and extensive information disclosure. The procedure combines all components necessary to solve a multi-vessel encounter and is tested currently in simulation and on several test beds. The first results show a fast converging optimisation process which after a few negotiation rounds already produce feasible, collision free trajectories.

Tourist tracking
(2015)

Regarding moral concerns in the business sphere, integrity is often mentioned as one of the core values that guides the behavior of companies. Daimler for instance states: “Acting with integrity is the central requirement for sustainable success and a maxim that Daimler follows in its worldwide business practices.”1 Reference to integrity is mostly supposed to signal that the company acts morally responsibly. Although some companies specify what acting with integrity means for them, it generally remains unclear what the concept of integrity entails – both broadly speaking and referring to business. This conceptual gap shall be filled by developing a concept of integrity that can be transferred to the business context. For this purpose, the main criteria that constitute moral integrity will be discussed before reflecting on how these could be integrated into a practical and comprehensive concept of corporate integrity.

Small vessels or unmanned surface vehicles only have a limited amount of space and energy available. If these vessels require an active sensing collision avoidance system it is often not possible to mount large sensor systems like X-Band radars. Thus, in this paper an energy efficient automotive radar and a laser range sensor are evaluated for tracking surrounding vessels. For these targets, those type of sensors typically generate more than one detection per scan. Therefore, an extended target tracking problem has to be solved to estimate state end extension of the vessels. In this paper, an extended version of the probabilistic data association filter that uses random matrices is applied. The performance of the tracking system using either radar or laser range data is demonstrated in real experiments.

Classification of point clouds by different types of geometric primitives is an essential part in the reconstruction process of CAD geometry. We use support vector machines (SVM) to label patches in point clouds with the class labels tori, ellipsoids, spheres, cones, cylinders or planes. For the classification features based on different geometric properties like point normals, angles, and principal curvatures are used. These geometric features are estimated in the local neighborhood of a point of the point cloud. Computing these geometric features for a random subset of the point cloud yields a feature distribution. Different features are combined for achieving best classification results. To minimize the time consuming training phase of SVMs, the geometric features are first evaluated using linear discriminant analysis (LDA).
LDA and SVM are machine learning approaches that require an initial training phase to allow for a subsequent automatic classification of a new data set. For the training phase point clouds are generated using a simulation of a laser scanning device. Additional noise based on an laser scanner error model is added to the point clouds. The resulting LDA and SVM classifiers are then used to classify geometric primitives in simulated and real laser scanned point clouds.
Compared to other approaches, where all known features are used for classification, we explicitly compare novel against known geometric features to prove their effectiveness.

Knowing the position of the spool in a solenoid valve, without using costly position sensors, is of considerable interest in a lot of industrial applications. In this paper, the problem of position estimation based on state observers for fast-switching solenoids, with sole use of simple voltage and current measurements, is investigated. Due to the short spool traveling time in fast-switching valves, convergence of the observer errors has to be achieved very fast. Moreover, the observer has to be robust against modeling uncertainties and parameter variations. Therefore, different state observer approaches are investigated, and compared to each other regarding possible uncertainties. The investigation covers a High-Gain-Observer approach, a combined High-Gain Sliding-Mode-Observer approach, both based on extended linearization, and a nonlinear Sliding-Mode-Observer based on equivalent output injection. The results are discussed by means of numerical simulations for all approaches, and finally physical experiments on a valve-mock-up are thoroughly discussed for the nonlinear Sliding-Mode-Observer.

Vortrag auf dem Doktorandenkolloquium des Kooperativen Promotionskollegs der HTWG, 09.07.2015

This work investigates soft input decoding for generalized concatenated (GC) codes. The GC codes are constructed from inner nested binary Bose-Chaudhuri-Hocquenghem (BCH)codes and outer Reed-Solomon (RS) codes. In order to enable soft input decoding for the inner BCH block codes, a sequential stack decoding algorithm is used. Ordinary stack decoding of binary block codes requires the complete trellis of the code.
In this work a representation of the block codes based on the trellises of supercodes is proposed in order to reduce the memory requirements for the representation of the BCH codes. Results for the decoding performance of the overall GC code are presented.
Furthermore, an efficient hardware implementation of the GC decoder is proposed.

To evaluate the quality of a person's sleep it is essential to identify the sleep stages and their durations. Currently, the gold standard in terms of sleep analysis is overnight polysomnography (PSG), during which several techniques like EEG (eletroencephalogram), EOG (electrooculogram), EMG (electromyogram), ECG (electrocardiogram), SpO2 (blood oxygen saturation) and for example respiratory airflow and respiratory effort are recorded. These expensive and complex procedures, applied in sleep laboratories, are invasive and unfamiliar for the subjects and it is a reason why it might have an impact on the recorded data. These are the main reasons why low-cost home diagnostic systems are likely to be advantageous. Their aim is to reach a larger population by reducing the number of parameters recorded. Nowadays, many wearable devices promise to measure sleep quality using only the ECG and body-movement signals. This work presents an android application developed in order to proof the accuracy of an algorithm published in the sleep literature. The algorithm uses ECG and body movement recordings to estimate sleep stages. The pre-recorded signals fed into the algorithm have been taken from physionet1 online database. The obtained results have been compared with those of the standard method used in PSG. The mean agreement ratios between the sleep stages REM, Wake, NREM-1, NREM-2 and NREM-3 were 38.1%, 14%, 16%, 75% and 54.3%.

SInCom 2015
(2015)

We consider classes of (Formula presented.)-by-(Formula presented.) sign regular matrices, i.e. of matrices with the property that all their minors of fixed order (Formula presented.) have one specified sign or are allowed also to vanish, (Formula presented.). If the sign is nonpositive for all (Formula presented.), such a matrix is called totally nonpositive. The application of the Cauchon algorithm to nonsingular totally nonpositive matrices is investigated and a new determinantal test for these matrices is derived. Also matrix intervals with respect to the checkerboard ordering are considered. This order is obtained from the usual entry-wise ordering on the set of the (Formula presented.)-by-(Formula presented.) matrices by reversing the inequality sign for each entry in a checkerboard fashion. For some classes of sign regular matrices, it is shown that if the two bound matrices of such a matrix interval are both in the same class then all matrices lying between these two bound matrices are in the same class, too.

Shadow IT risk
(2015)

Sabbatical semester report
(2015)

RELOAD
(2015)

Vortrag auf dem Doktorandenkolloquium des Kooperativen Promotionskollegs der HTWG, 09.07.2015

Digital cameras are subject to physical, electronic and optic effects that result in errors and noise in the image. These effects include for example a temperature dependent dark current, read noise, optical vignetting or different sensitivities of individual pixels. The task of a radiometric calibration is to reduce these errors in the image and thus improve the quality of the overall application. In this work we present an algorithm for radiometric calibration based on Gaussian processes. Gaussian processes are a regression method widely used in machine learning that is particularly useful in our context. Then Gaussian process regression is used to learn a temperature and exposure time dependent mapping from observed gray-scale values to true light intensities for each pixel. Regression models based on the characteristics of single pixels suffer from excessively high runtime and thus are unsuitable for many practical applications. In contrast, a single regression model for an entire image with high spatial resolution leads to a low quality radiometric calibration, which also limits its practical use. The proposed algorithm is predicated on a partitioning of the pixels such that each pixel partition can be represented by one single regression model without quality loss. Partitioning is done by extracting features from the characteristic of each pixel and using them for lexicographic sorting. Splitting the sorted data into partitions with equal size yields the final partitions, each of which is represented by the partition centers. An individual Gaussian process regression and model selection is done for each partition. Calibration is performed by interpolating the gray-scale value of each pixel with the regression model of the respective partition. The experimental comparison of the proposed approach to classical flat field calibration shows a consistently higher reconstruction quality for the same overall number of calibration frames.

Probabilistic data association for tracking extended targets under clutter using random matrices
(2015)

The use of random matrices for tracking extended objects has received high attention in recent years. It is an efficient approach for tracking objects that give rise to more than one measurement per time step. In this paper, the concept of random matrices is used to track surface vessels using highresolution automotive radar sensors. Since the radar also receives a large number of clutter measurements from the water, for the data association problem, a generalized probabilistic data association filter is applied. Additionally, a modification of the filter update step is proposed to incorporate the Doppler velocity measurements. The presented tracking algorithm is validated using Monte Carlo Simulation, and some performance results with real radar data are shown as well.

The improvement of collision avoidance for vessels in close range encounter situations is an important topic for maritime traffic safety. Typical approaches generate evasive trajectories or optimise the trajectories of all involved vessels. Such a collision avoidance system has to produce evasive manoeuvres that do not confuse other navigators. To achieve this behaviour, a probabilistic obstacle handling based on information from a radar sensor with target tracking, that considers measurement and tracking uncertainties is proposed. A grid based path search algorithm, that takes the information from the probabilistic obstacle handling into account, is then used to generate evasive trajectories. The proposed algorithms have been tested and verified in a simulated environment for inland waters.

Post harvest technology
(2015)

The detection of differences between images of a printed reference and a reprinted wood decor often requires an initial image registration step. Depending on the digitalization method, the reprint will be displaced and rotated with respect to the reference. The aim of registration is to match the images as precisely as possible. In our approach, images are first matched globally by extracting feature points from both images and finding corresponding point pairs using the RANSAC algorithm. From these correspondences, we compute a global projective transformation between both images. In order to get a pixel-wise registration, we train a learning machine on the point correspondences found by RANSAC. The learning algorithm (in our case Gaussian process regression) is used to nonlinearly interpolate between the feature points which results in a high precision image registration method on wood decors.

This Chapter introduces parameterized, or parametric, Model Order Reduction (pMOR). The Sections are offered in a prefered order for reading, but can be read independently. Section 5.1, written by Jorge Fernández Villena, L. Miguel Silveira, Wil H.A. Schilders, Gabriela Ciuprina, Daniel Ioan and Sebastian Kula, overviews the basic principles for pMOR. Due to higher integration and increasing frequency-based effects, large, full Electromagnetic Models (EM) are needed for accurate prediction of the real behavior of integrated passives and interconnects. Furthermore, these structures are subject to parametric effects due to small variations of the geometric and physical properties of the inherent materials and manufacturing process. Accuracy requirements lead to huge models, which are expensive to simulate and this cost is increased when parameters and their effects are taken into account. This Section introduces the framework of pMOR, which aims at generating reduced models for systems depending on a set of parameters.

The intentions of the so-called "More Electrical Aircraft" (MEA) are higher efficiency and lower weight. A main topic here is the application of electrical instead of hydraulical, pneumatical and mechanical systems. The necessary power electronic devices have intermediate DC-links, which are typically supplied by a three-phase system with active B6 and passive B12 rectifiers. A possible alternative is the B6 diode bridge in combination with an active power filter (APF). Due to the parallel arrangement, the APF offers a higher power density and is able to compensate for harmonics from several devices. The use of the diode bridge rectifier alone is not permitted due to the highly distorted phase current. The following investigations are dealing with the development of an active power filter for a three-phase supply with variable frequency from 360 to 800 Hz. All relevant components such as inductors, EMC-filters, power modules and DC-link capacitor are designed. A particular focus is put on the customized power module with SiC-MOSFETs and SiC-diodes, which is characterized electrically and thermally. The maximum supply frequency slope has a value of 50 Hz/ms, which requires a high dynamic and robustness on the control algorithm. Furthermore, the content of 5th and 7th harmonics must be reduced to less than 2 %, which demands a high accuracy. To cope with both requirements, a two-stage filter algorithm is developed and implemented in two independent signal processors. Simulations and laboratory experiments confirm the performance and robustness of the control algorithm. This work comprehensively presents the design of aerospace rectifiers. The results were published in conferences and patents.

Reconstruction of hand-held laser scanner data is used in industry primarily for reverse engineering. Traditionally, scanning and reconstruction are separate steps. The operator of the laser scanner has no feedback from the reconstruction results. On-line reconstruction of the CAD geometry allows for such an immediate feedback.
We propose a method for on-line segmentation and reconstruction of CAD geometry from a stream of point data based on means that are updated on-line. These means are combined to define complex local geometric properties, e.g., to radii and center points of spherical regions. Using means of local scores, planar, cylindrical, and spherical segments are detected and extended robustly with region growing. For the on-line computation of the means we use so-called accumulated means. They allow for on-line insertion and removal of values and merging of means. Our results show that this approach can be performed on-line and is robust to noise. We demonstrate that our method reconstructs spherical, cylindrical, and planar segments on real scan data containing typical errors caused by hand-held laser scanners.

Technology-based ventures provide an important route for successful technology transfer [1], [2]. Their founders are supported in successful technology commercialization by innovation intermediaries [3]. Accordingly, the performance of an innovation system, at least to some extent, depends on the efficiency of these intermediaries in terms of the impact of their scarce resources on the survival and growth of technology-based ventures. To increase their efficiency, intermediaries typically optimize their "intake" by requesting a formal business plan to base their selection on as a hygiene factor [4]-[7]. Thus, some scholars argue that written business plans show significant distortion as being produced only to attract support from innovation intermediaries [6], [8]. Accordingly, they rarely serve for these addressees as a source of information for analyzing the strengths and weaknesses of ventures, in order to derive actionable conclusions and more effectively support ventures [9], [10]. Addressees search for different indicators in business plans for their evaluation [11]. The descriptions of these indicators only evince little empirical proof for the performance of technology-based venture's [8], [12]. This gap is herein addressed, in contrast to the lacking empirical insight, as the most frequently produced artifact of early-stage technology ventures is at the same time a written business plan [10], [13]. This paper addresses this gap by conceptualizing transaction relations described in the written business plan as a means for working around the inevitable inaccuracies and uncertainties that delimit the explanatory abilities [14] of the snapshot model [10] presented by a business plan. Using a qualitative content analysis, we derive from the descriptions of transaction relations in a written business plan valid indicators for the maturity of the venture's value-network in different dimensions [15]. To this extent, this paper presents the findings from a pre-study that was conducted based on a sample of forty business plans from an overall population of 800 business plans in a longitudinal sample from one of Europe's most active innovation systems, the regional State of Baden-Württemberg. Such findings may be used by innovation intermediaries to enhance their efficiency, by enabling these to not only derive individual support strategies for business acceleration but also to analyze the impact of support measures by reliably monitoring maturity progress in venture activities.

Codes over quotient rings of Lipschitz integers have recently attracted some attention. This work investigates the performance of Lipschitz integer constellations for transmission over the AWGN channel by means of the constellation figure of merit. A construction of sets of Lipschitz integers is presented that leads to a better constellation figure of merit compared to ordinary Lipschitz integer constellations. In particular, it is demonstrated that the concept of set partitioning can be applied to quotient rings of Lipschitz integers where the number of elements is not a prime number. It is shown that it is always possible to partition such quotient rings into additive subgroups in a manner that the minimum Euclidean distance of each subgroup is strictly larger than in the original set. The resulting signal constellations have a better performance for transmission over an additive white Gaussian noise channel compared to Gaussian integer constellations and to ordinary Lipschitz integer constellations.

Codes over quotient rings of Lipschitz integers have recently attracted some attention. This work investigates the performance of Lipschitz integer constellations for transmission over the AWGN channel by means of the constellation figure of merit. A construction of sets of Lipschitz integers that leads to a better constellation figure of merit compared to ordinary Lipschitz integer constellations is presented. In particular, it is demonstrated that the concept of set partitioning can be applied to quotient rings of Lipschitz integers where the number of elements is not a prime number. It is shown that it is always possible to partition such quotient rings into additive subgroups in a manner that the minimum Euclidean distance of each subgroup is strictly larger than in the original set. The resulting signal constellations have a better performance for transmission over an additive white Gaussian noise channel compared to Gaussian integer constellations and to ordinary Lipschitz integer constellations. In addition, we present multilevel code constructions for the new signal constellations.

Motion safety for vessels
(2015)

The improvement of collision avoidance for vessels in close range encounter situations is an important topic for maritime traffic safety. Typical approaches generate evasive trajectories or optimise the trajectories of all involved vessels. The idea of this work is to validate these trajectories related to guaranteed motion safety, which means that it is not sufficient for a trajectory to be collision-free, but it must additionally ensure that an evasive manoeuvre is performable at any time. An approach using the distance and the evolution of the distance to the other vessels is proposed. The concept of Inevitable Collision States (ICS) is adopted to identify the states for which no evasive manoeuvre exist. Furthermore, it is implemented into a collision avoidance system for recreational crafts to demonstrate the performance.

Model Order Reduction
(2015)

This chapter offers an introduction to Model Order Reduction (MOR). It gives an overview on the methods that are mostly used. It also describes the main concepts behind the methods and the properties that are aimed to be preserved. The sections are in a prefered order for reading, but can be read independentlty. Section 4.1, written by Michael Striebel, E. Jan W. ter Maten, Kasra Mohaghegh and Roland Pulch, overviews the basic material for MOR and its use in circuit simulation. Issues like Stability, Passivity, Structure preservation, Realizability are discussed. Projection based MOR methods include Krylov-space methods (like PRIMA and SPRIM) and POD-methods. Truncation based MOR includes Balanced Truncation, Poor Man’s TBR and Modal Truncation.Section 4.2, written by Joost Rommes and Nelson Martins, focuses on Modal Truncation. Here eigenvalues are the starting point. The eigenvalue problems related to large-scale dynamical systems are usually too large to be solved completely. The algorithms described in this section are efficient and effective methods for the computation of a few specific dominant eigenvalues of these large-scale systems. It is shown how these algorithms can be used for computing reduced-order models with modal approximation and Krylov-based methods.Section 4.3, written by Maryam Saadvandi and Joost Rommes, concerns passivity preserving model order reduction using the spectral zero method. It detailedly discusses two algorithms, one by Antoulas and one by Sorenson. These two approaches are based on a projection method by selecting spectral zeros of the original transfer function to produce a reduced transfer function that has the specified roots as its spectral zeros. The reduced model preserves passivity.Section 4.4, written by Roxana Ionutiu, Joost Rommes and Athanasios C. Antoulas, refines the spectral zero MOR method to dominant spectral zeros. The new model reduction method for circuit simulation preserves passivity by interpolating dominant spectral zeros. These are computed as poles of an associated Hamiltonian system, using an iterative solver: the subspace accelerated dominant pole algorithm (SADPA). Based on a dominance criterion, SADPA finds relevant spectral zeros and the associated invariant subspaces, which are used to construct the passivity preserving projection. RLC netlist equivalents for the reduced models are provided.Section 4.5, written by Roxana Ionutiu and Joost Rommes, deals with synthesis of a reduced model: reformulate it as a netlist for a circuit. A framework for model reduction and synthesis is presented, which greatly enlarges the options for the re-use of reduced order models in circuit simulation by simulators of choice. Especially when model reduction exploits structure preservation, we show that using the model as a current-driven element is possible, and allows for synthesis without controlled sources. Two synthesis techniques are considered: (1) by means of realizing the reduced transfer function into a netlist and (2) by unstamping the reduced system matrices into a circuit representation. The presented framework serves as a basis for reduction of large parasitic R/RC/RCL networks.

Besides energy efficiency, product quality is gaining importance in the design of drying processes for sensitive biological foodstuffs. The influence of drying parameters on the drying kinetics of apples has been extensively investigated; the information about effects on product quality available in literature however, is often contradictory. Furthermore quality changes obtained applying different drying parameters are usually hard to compare. As most quality changes can be expressed as zero, first or second order reactions and mainly depend on drying air temperature and drying time, it would be desirable to cross-check the results in function thereof. This paper introduces a method of quality determination using a new reference value, the cumulated thermal load. It is defined as the time integral of the product surface temperature and improves the comparability of quality changes obtained by different experimental settings in drying of apples and tomatoes. It could be shown that quality parameters like color changes and shrinkage during apple drying and the content of temperature sensitive acids in tomatoes vary linearly with the integral of product temperature over time.

In biomechanics laboratories the ground reaction force time histories of the foot-fall of persons are usually measured using a force plate. The accelerations of the floor, in which the force plate is embedded, have to be limited, as they may influence the accuracy of the force measurements. For the numerical simulation of vibrations induced by humans in biomechanical laboratories, loading scenarios are defined. They include continuous motions of persons (walking, running) as well as jumps, typical for biomechanical investigations on athletes. The modeling of floors has to take into account the influence of floor screed in case of portable force plates. Criteria for the assessment of the measuring error provoked by floor vibrations are given. As an example a floor designed to accommodate a force platform in a biomechanical laboratory of the University Hospital in Tübingen, Germany, has been investi-gated for footfall induced vibrations. The numerical simulation by a finite element analysis has been validated by field measurements. As a result, the measuring error of the force plate installed in the laboratory is obtained for diverse scenarios.

This paper compares the surface morphology of differently finished austenitic stainless steel AISI 316L, also in combination with low temperature carburization. Milled and tumbled surfaces were analyzed by means of corrosion resistance and surface morphology. The results of potentiodynamic measurements show that professional grinding operations with SiC and Al2O3 always lead to a better corrosion resistance of low temperature carburized surfaces compared to the untreated reference in the used acidified chloride solution. Big influence on the corrosion resistance of vibratory ground or tumbled surfaces has the amount of plastic deformation while machining, that has to be kept low for austenitic stainless steels. Due to the high ductility, plastic deformation can lead to the formation of meta stable pits that can be initiation points of corrosion. The formation of meta stable pits can be aggravated by low temperature diffusion processes.

Vortrag auf dem Doktorandenkolloquium des Kooperativen Promotionskollegs der HTWG, 09.07.2015

IGA using subdivision-solids
(2015)

Hot isostatic pressing (HIP) allows the production of complex components geometry. Generally, a high quality of the components is achieved due to the well managed composition of the metal powder and the non-isotropic properties. If a duplex stainless steel is produced, a heat treatment after the HIP-process is necessary to remove precipitations like carbides, nitrides and intermetallic phases. In a new process, the sintering step should be combined with the heat treatment. In this case a high cooling rate is necessary to avoid precipitations in duplex stainless steels. In this work, the influence of the HIP-temperature and the wall thickness on corrosion resistance, microstructure and impact strength were investigated. The results should help to optimize the process parameters like temperature and cooling rate. For the investigation, two HIP-temperatures were tested in a classical HIP-process step with a defined cooling rate. An additional heat treatment was not conducted. The specimens were cut from different sectors of the HIP-block. For investigation of the corrosion resistance, the critical pitting temperature was determined with electrochemical method according to EN ISO 17864. An impact test was used to determine the impact transition temperature. Metallographic investigations show the microstructure in the different sectors of the HIP-block.

Stress is recognized as a factor of predominant disease and in the future the costs for treatment will increase. The presented approach tries to detect stress in a very basic and easy to implement way, so that the cost for the device and effort to wear it remain low. The user should benefit from the fact that the system offers an easy interface reporting the status of his body in real time. In parallel, the system provides interfaces to pass the obtained data forward for further processing and (professional) analyses, in case the user agrees. The system is designed to be used in every day’s activities and it is not restricted to laboratory use or environments. The implementation of the enhanced prototype shows that the detection of stress and the reporting can be managed using correlation plots and automatic pattern recognition even on a very light-weighted microcontroller platform.

In this paper an approach towards databased fault diagnosis of linear electromagnetic actuators is presented. Time and time-frequency-domain methods were applied to extract fault related features from current and voltage measurements. The resulting features were transformed to enhance class separability using either Principal Component Analysis (PCA) or Optimal Transformation. Feature selection and dimensionality reduction was performed employing a modified Fisher-ratio. Fault detection was carried out using a Support-Vector-Machine classifier trained with randomly selected data subsets. Results showed, that not only the used feature sets (time-domain/time-frequency-domain) are crucial for fault detection and classification, but also feature pre-processing. PCA transformed time-domain features allow fault detection and classification without misclassification, relying on current and voltage measurements making two sensors necessary to generate the data. Optimal transformed time-frequency-domain features allow a misclassification free result as well, but as they are calculated from current measurements only, a dedicated voltage sensor is not necessary. Using those features is a promising alternative even for detecting purely supply voltage related faults.

Vortrag auf dem Doktorandenkolloquium des Kooperativen Promotionskollegs der HTWG, 09.07.2015

Effect of cold working on the localized corrosion behavior of CrNi and CrNiMnN metastable austenites
(2015)

Earthquake response spectra as defined by Eurocode 8 (German NAD) are restricted to soils with shear wave velocities greater than 150 m/s. For soft soil layers e.g. of clay underlain by bedrock special investigations are required because resonance effects of the layer significantly influence the shape of the spectrum. Numerical investigations are normally based on a one-dimensional theory of horizontally polarized shear waves propagating in vertical direction. The paper describes a parametric study to define acceleration response spectra for a soft soil over a half-space for a wide range of soil layer heights and material parameters. Based on this study a simplified method to describe response spectra for the model of a soft soil layer underlain by a viscoelastic halfspace is given.

Technology commercialization is described as the most dreadful challenge for technology-based entrepreneurs. The scarcity of resources and limited managerial experience make it a daunting task, putting in danger the whole firm emergence. Prior research has often build upon the resource-based view to propose that the new firms' performance is dependent on their initial resource endowments and configurations. Nevertheless, little is known on how the early-stage decisions of the entrepreneur might influence on the growth of the firm. Scholars have suggested that both technology and market orientation actions could influence the performance and growth of firms in this context; nevertheless, there is limited empirical evidence of the influence of these different orientations in the context of new technology-based firms (NTBFs). In this study we propose to explore the influence of technology and demand creation actions adopting a demand-side view. We use a longitudinal study on a panel dataset (2004-2007) with 249 U.S. new high-technology firms to test our hypothesis. The results point towards a rather limited influence of initial resource configurations, as well as an unexpected influence of market and technology orientation in the growth dimensions of an NTBF. The research holds implications for the management of new technology-based firms and for those interested in supporting the development of technology entrepreneurship.

Differences in the pitting resistance between cold worked CrNi and CrNiMnN metastable austenites
(2015)

Fachvortrag auf dem Kongress CORROSION 2015, 15-19 March, Dallas, Texas, USA. NACE International

Conducting surveillance impact assessment is the first step to solve the "Who monitors the monitor?" problem. Since the surveillance impacts on different dimensions of privacy and society are always changing, measuring compliance and impact through metrics can ensure the negative consequences are minimized to acceptable levels. To develop metrics systematically for surveillance impact assessment, we follow the top-down process of the Goal/Question/Metric paradigm: 1) establish goals through the social impact model, 2) generate questions through the dimensions of surveillance activities, and 3) develop metrics through the scales of measure. With respect to the three factors of impact magnitude: the strength of sources, the immediacy of sources, and the number of sources, we generate questions concerning surveillance activities: by whom, for whom, why, when, where, of what, and how, and develop metrics with the scales of measure: the nominal scale, the ordinal scale, the interval scale, and the ratio scale. In addition to compliance assessment and impact assessment, the developed metrics have the potential to address the power imbalance problem through sousveillance, which employs surveillance to control and redirect the impact exposures.

The proposed approach applies current unsupervised clustering approaches in a different dynamic manner. Instead of taking all the data as input and finding clusters among them, the given approach clusters Holter ECG data (long-term electrocardiography data from a holter monitor) on a given interval which enables a dynamic clustering approach (DCA). Therefore advanced clustering techniques based on the well known Dynamic Time Warping algorithm are used. Having clusters e.g. on a daily basis, clusters can be compared by defining cluster shape properties. Doing this gives a measure for variation in unsupervised cluster shapes and may reveal unknown changes in healthiness. Embedding this approach into wearable devices offers advantages over the current techniques. On the one hand users get feedback if their ECG data characteristic changes unforeseeable over time which makes early detection possible. On the other hand cluster properties like biggest or smallest cluster may help a doctor in making diagnoses or observing several patients. Further, on found clusters known processing techniques like stress detection or arrhythmia classification may be applied.

Nowadays, the number of flexible and fast human to application system interactions is dramatically increasing. For instance, citizens interact with the help of the internet to organize surveys or meetings (in real-time) spontaneously. These interactions are supported by technologies and application systems such as free wireless networks, web -or mobile apps. Smart Cities aim at enabling their citizens to use these digital services, e.g., by providing enhanced networks and application infrastructures maintained by the public administration. However, looking beyond technology, there is still a significant lack of interaction and support between "normal" citizens and the public administration. For instance, democratic decision processes (e.g. how to allocate public disposable budgets) are often discussed by the public administration without citizen involvement. This paper introduces an approach, which describes the design of enhanced interactional web applications for Smart Cities based on dialogical logic process patterns. We demonstrate the approach with the help of a budgeting scenario as well as a summary and outlook on further research.

Atom interferometers have a multitude of proposed applications in space including precise measurements of the Earth's gravitational field, in navigation & ranging, and in fundamental physics such as tests of the weak equivalence principle (WEP) and gravitational wave detection. While atom interferometers are realized routinely in ground-based laboratories, current efforts aim at the development of a space compatible design optimized with respect to dimensions, weight, power consumption, mechanical robustness and radiation hardness. In this paper, we present a design of a high-sensitivity differential dual species 85Rb/87Rb atom interferometer for space, including physics package, laser system, electronics and software. The physics package comprises the atom source consisting of dispensers and a 2D magneto-optical trap (MOT), the science chamber with a 3D-MOT, a magnetic trap based on an atom chip and an optical dipole trap (ODT) used for Bose-Einstein condensate (BEC) creation and interferometry, the detection unit, the vacuum system for 10-11 mbar ultra-high vacuum generation, and the high-suppression factor magnetic shielding as well as the thermal control system.
The laser system is based on a hybrid approach using fiber-based telecom components and high-power laser diode technology and includes all laser sources for 2D-MOT, 3D-MOT, ODT, interferometry and detection. Manipulation and switching of the laser beams is carried out on an optical bench using Zerodur bonding technology. The instrument consists of 9 units with an overall mass of 221 kg, an average power consumption of 608 W (819 W peak), and a volume of 470 liters which would well fit on a satellite to be launched with a Soyuz rocket, as system studies have shown.

This paper proposes a pipelined decoder architecture for generalised concatenated (GC) codes. These codes are constructed from inner binary Bose-Chaudhuri-Hocquenghem (BCH) and outer Reed-Solomon codes. The decoding of the component codes is based on hard decision syndrome decoding algorithms. The concatenated code consists of several small BCH codes. This enables a hardware architecture where the decoding of the component codes is pipelined. A hardware implementation of a GC decoder is presented and the cell area, cycle counts as well as the timing constraints are investigated. The results are compared to a decoder for long BCH codes with similar error correction performance. In comparison, the pipelined GC decoder achieves a higher throughput and has lower area consumption.

Nowadays, there is a continuous need for many corporations to renew their business portfolio strategically in anticipation of changes in the business environment (e.g., technological change). The ongoing booming of founding international start-ups suggests that small entrepreneurial teams are an effective means to develop new businesses. Corporations should be able to benefit from this form of self-organized innovation when entering novel business domains for strategic renewal. However, corporations that establish small entrepreneurial teams (corporate ventures) are facing two obstacles. First, corporate ventures often fail for reasons that are not well explored. Second, it remains unclear how the partial successes may be improved to large successes. Although the key success factors remain ambiguous, there is little hope that corporate ventures will be successful without effective management. Since an empirical model for corporate venture management does not exists so far, the thesis formulates and answers the following problem statement: How can corporate management effectively manage corporate ventures? Building on qualitative and quantitative research methodologies, a model for effective corporate venture management is developed and tested statistically in the German IT consulting industry. The research results reveal some of the essential management principles through which corporate management can increase corporate venture success systematically.

Bernstein polynomials on a simplex V are considered. The expansion of a given polynomial p into these polynomials provides bounds for range of p over V. Bounds for the range of a rational function over V can easily be obtained from the Bernstein expansions of the numerator and denominator polynomials of this function. In this paper it is shown that these bounds converge monotonically and linearly to the range of the rational function if the degree of the Bernstein expansion is elevated. If V is subdivided then the convergence is quadratic with respect to the maximum of the diameters of the subsimplices.

Domain-specific modelling is increasingly adopted in the software development industry. While open source metamodels like Ecore have a wide impact, they still have some problems. The independent storage of nodes (classes) and edges (references) is currently only possible with complex, specific solutions. Furthermore the developed models are stored in the extensible markup language (XML) data format, which leads to problems with large models in terms of scaling. In this paper we describe an approach that solves the problem of independent classes and references in metamodels and we store the models in the JavaScript Object Notation (JSON) data format to support high scalability. First results of our tests show that the developed approach works and classes and references can be defined independently. In addition, our approach reduces the amount of characters per model by a factor of approximately two compared to Ecore. The entire project is made available as open source under the name MoDiGen. This paper focuses on the description of the metamodel definition in terms of scaling.

This work proposes an efficient hardware Implementation of sequential stack decoding of binary block codes. The decoder can be applied for soft input decoding for generalized concatenated (GC) codes. The GC codes are constructed from inner nested binary Bose-Chaudhuri-Hocquenghem (BCH) codes and outer Reed-Solomon (RS) codes. In order to enable soft input decoding for the inner BCH block codes, a sequential stack decoding algorithm is used.

This chapter contains three advanced topics in model order reduction (MOR): nonlinear MOR, MOR for multi-terminals (or multi-ports) and finally an application in deriving a nonlinear macromodel covering phase shift when coupling oscillators. The sections are offered in a preferred order for reading, but can be read independently.

We present a 3d-laser-scan simulation in virtual
reality for creating synthetic scans of CAD models. Consisting of
the virtual reality head-mounted display Oculus Rift and the
motion controller Razer Hydra our system can be used like
common hand-held 3d laser scanners. It supports scanning of
triangular meshes as well as b-spline tensor product surfaces
based on high performance ray-casting algorithms. While point
clouds of known scanning simulations are missing the man-made
structure, our approach overcomes this problem by imitating
real scanning scenarios. Calculation speed, interactivity and the
resulting realistic point clouds are the beneﬁts of this system.

A semilinear distributed parameter approach for solenoid valve control including saturation effects
(2015)

In this paper a semilinear parabolic PDE for the control of solenoid valves is presented. The distributed parameter model of the cylinder becomes nonlinear by the inclusion of saturation effects due to the material's B/H-curve. A flatness based solution of the semilinear PDE is shown as well as a convergence proof of its series solution. By numerical simulation results the adaptability of the approach is demonstrated, and differences between the linear and the nonlinear case are discussed. The major contribution of this paper is the inclusion of saturation effects into the magnetic field governing linear diffusion equation, and the development of a flatness based solution for the resulting semilinear PDE as an extension of previous works [1] and [2].

This contribution presents a data compression scheme for applications in non-volatile flash memories. The objective of the data compression algorithm is to reduce the amount of user data such that the redundancy of the error correction coding can be increased in order to improve the reliability of the data storage system. The data compression is performed on block level considering data blocks of 1 kilobyte. We present an encoder architecture that has low memory requirements and provides a fast data encoding.