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Institute
- Fakultät Architektur und Gestaltung (41)
- Fakultät Bauingenieurwesen (105)
- Fakultät Elektrotechnik und Informationstechnik (34)
- Fakultät Informatik (121)
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- Institut für Angewandte Forschung - IAF (115)
- Institut für Naturwissenschaften und Mathematik - INM (3)
- Institut für Optische Systeme - IOS (40)
- Institut für Strategische Innovation und Technologiemanagement - IST (60)
In 3D extended object tracking (EOT), well-established models exist for tracking the object extent using various shape priors. A single update, however, has to be performed for every measurement using these models leading to a high computational runtime for high-resolution sensors. In this paper, we address this problem by using various model-independent downsampling schemes based on distance heuristics and random sampling as pre-processing before the update. We investigate the methods in a simulated and real-world tracking scenario using two different measurement models with measurements gathered from a LiDAR sensor. We found that there is a huge potential for speeding up 3D EOT by dropping up to 95\% of the measurements in our investigated scenarios when using random sampling. Since random sampling, however, can also result in a subset that does not represent the total set very well, leading to a poor tracking performance, there is still a high demand for further research.
We quantify the effects of GATT/WTO membership on trade and welfare. Using an extensive database covering manufacturing trade for 186 countries over the period 1980–2016, we find that the average partial equilibrium impact of GATT/WTO membership on trade among member countries is large, positive, and significant. We contribute to the literature by estimating country-specific estimates and find them to vary widely across the countries in our sample with poorer members benefitting more. Using these estimates, we simulate the general equilibrium effects of GATT/WTO on welfare, which are sizable and heterogeneous across members. We show that countries not experiencing positive trade effects from joining GATT/WTO can still gain in terms of welfare, due to lower import prices and higher export demand.
We examine to what extent a transaction relation-based value network maturity status of New Technology-Based Firms (NTBFs) is related to their survival. A specific challenge of NTBFs is their lack of market-orientation, which is why the maturity of the ties they form towards the market in terms of customers, financiers, personnel and partners is supposed to be a strong indicator for survival. We analyze a sample of 170 NTBFs by capturing their value network status from business plans and defining their survival status using secondary research. Simple statistical tests and regressions suggest that the official registration of the business is a pre-step for survival that requires industry-specific value network dimension strengths. A sub-sample survival analysis shows that for all NTBFs that have reached registration, regardless of their industry, a stronger customer value network maturity dimension prevents from failure and is thus a significant predictor for survival. Moreover, the analyses partly support the idea that NTBFs from the IT sector are less dependent on a strong value network in the financier dimension to survive. The results are of relevance for both practitioners and researchers in the innovation system: a better understanding of the factors impacting on NTBF survival can help to provide more tailored support services for young firms, increase the effectiveness of resource allocations, and provide a basis for further research.
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.
The IETF, concerned with the evolution of the Internet architecture, nowadays also looks into industrial automation processes. The contributions of a variety of IETF activities, initiated during the last ten years, enable now the replacement of proprietary standards by an open standardized protocol stack. This stack, denoted in the following as 6TiSCH-stack, is tailored for industrial internet of things (IIoTs). The suitability of 6TiSCH-stack for Industry 4.0 is yet to explore. In this paper, we identify four challenges that, in our opinion, may delay or hinder its adoption. As a prime example of that, we focus on the initial 6TiSCHnetwork
formation, highlighting the shortcomings of the default procedure and introducing our current work for a fast and reliable formation of dense network.
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.
We present an approach to reduce the complexity of adjusting privacy preferences for multiple online social networks. To achieve this, we quantify the effect on privacy for choices that users make, and simplify configuration by introducing privacy configuration as a service. We present an algorithm that effectively measures privacy and adjusts privacy settings across social networks. The aim is to configure privacy with one click.
Die Hochschule Konstanz Technik Wirtschaft und Gestaltung (HTWG) leistet sich einen technologischen Think-Tank: Das Open Innovation Lab. Es ist ein Labor, welches über Hierarchien und Fakultätsgrenzen hinweg für die Hochschulangehörigen geöffnet ist. Es leistet seinen Beitrag zu Lehre, Forschung und Transfer. Bezogen auf das Lernen ermöglicht das Labor, für den allgegenwärtigen Prozess der Digitalisierung soziale Verantwortung zu übernehmen und Kreativität im Umfeld technologischer Möglichkeiten zu entwickeln. Drei Ebenen wirken hier zusammen: das Individuum, das Miteinander und die übergreifende Organisationsstruktur.
Optical surface inspection
(2016)
Optical surface inspection: A novelty detection approach based on CNN-encoded texture features
(2018)
In inspection systems for textured surfaces, a reference texture is typically known before novel examples are inspected. Mostly, the reference is only available in a digital format. As a consequence, there is no dataset of defective examples available that could be used to train a classifier. We propose a texture model approach to novelty detection. The texture model uses features encoded by a convolutional neural network (CNN) trained on natural image data. The CNN activations represent the specific characteristics of the digital reference texture which are learned by a one-class classifier. We evaluate our novelty detector in a digital print inspection scenario. The inspection unit is based on a camera array and a flashing light illumination which allows for inline capturing of multichannel images at a high rate. In order to compare our results to manual inspection, we integrated our inspection unit into an industrial single-pass printing system.
Diese Bachelorarbeit behandelt die Prozessoptimierung des Bemusterungsprozesses mithilfe Lean und agilen Methoden. Die Arbeit orientiert sich dabei an dem Unternehmen Ed. Züblin AG und deren vorhandenen Möglichkeiten. Das Konzept lässt sich jedoch mindestens zu teilen mit den nötigen Anpassungen auf andere Unternehmen und Projekte übertragen. Mithilfe einer Wertstromanalyse und Interviews wurde der Ist-Prozess aufgezeigt. Dabei kamen verschiedene Durchführungen der Bemusterungen im Unternehmen mit unterschiedlichen Problemen zum Vorschein. Unter anderem gab es durch fehlende oder falsche Planung ständige Anforderungsänderungen, Lücken in der Durchführung und Einschränkungen in der Kommunikation. Eine Umstrukturierung des Prozessablaufes, Anpassungen in der Planung mithilfe von Sprints und Überlegungen zur Organisation und den Mitarbeitern sollen die Probleme in den Griff bekommen. Dieser Beitrag soll somit eine Aufklärung zur Bemusterung sein und Anreize und Ideen zur Verbesserung liefern.
Projekte aus dem Hochbau, wie z.B. Schulgebäude sind eine klassische Aufgabe der Tragwerksplanung. Dabei steht eine Vielzahl an unterschiedlichen Bauweisen zur Verfügung. Vor dem Hintergrund der Klimakrise und den damit verbundenen Klimaschutzzielen von Paris besteht akuter Handlungsbedarf in allen Bereichen des Lebens, besonders aber im Bausektor, welcher maßgeblich zu den gesamten Treibhausgasemissionen beiträgt. Deshalb wird momentan vermehrt auf Lösungen in Holzbauweise zurückgegriffen. Neben der Gründung nehmen die Geschossdecken den größten Anteil an den Umweltwirkungen ein. Dieser Anteil steigt mit zunehmender Deckenfläche an. Dadurch besteht ein großes Potenzial bei der Verringerung der Treibhausgasemissionen durch geeignete Auswahl des Deckensystems und Optimierung der Tragstruktur.
In Diskussionen über den Klimawandel wird oft eine nachhaltige Entwicklung thematisiert. Für den Vergleich wurde eine Optimierung durchgeführt zur Beurteilung des CO2-Einsparpotenziales. Um alle Aspekte der Nachhaltigkeit zu erfüllen, wurden die gefundenen Varianten auf Basis gängiger Zertifizierungssysteme für Nachhaltigkeit bewertet. Jede Variante erfüllt dabei die Anforderungen an maximale Spannungen und Verformungen. Durch die Optimierung und den folgenden Vergleich wurde das Optimierungspotenzial verdeutlicht. Gleichzeitig entstehen teilweise nutzungsbedingte Konflikte aus der Optimierung und Anforderungen aus dem Schallschutz.
Optimierungsansätze zur Verbesserung der Leistungsbeschreibungen bei öffentlichen Bauvorhaben
(2021)
Elbphilharmonie, BER, Bischofsresistenz Limburg, Stuttgart 21, Alter Elbtunnel Hamburg. Alles bekannte deutsche Bauprojekte der letzten 20 Jahre. Alle mit einer Gemeinsamkeit: Exorbitante Kostenexplosionen und Bauzeitenverzögerungen.
In dieser Arbeit wird aufgezeigt, weshalb solche Kostenexplosionen auch aufgrund von Unklarheiten bzw. Fehlern in Leistungsbeschreibungen entstehen und welches enorme Potential klare und erschöpfende Leistungsbeschreibungen haben, um bereits im Vorfeld eines Bauvorhabens die Weichen für einen reibungslosen und erfolgreichen Projektverlauf zu stellen.
According to the World Food Organization, nearly half of all root and tuber crops worldwide are not consumed, but are lost due to inappropriate storage and post-harvest losses. In developing countries such as Ethiopia, potatoes have not been dried, but are traditionally stored in potato clamps. So far, dried potatoes have not been converted into usable foods.
The aim of the present work is to convert potatoes - perishable rootlets and tubers - into stable products by hot air drying. Hot air dryers are economical to operate in industrialized countries. In Africa, this is reserved for larger industrial companies only. In regions with a tropical climate, however, the use of solar tunnel dryers is worthwhile. These are a good choice for farming and small industries and wherever electrical energy is difficult or impossible to obtain.
In a first part of the work, the drying process of potatoes was investigated, in particular with regard to the change of thermal, mechanical and chemical quality parameters. In an evaluation of the literature it was found that potatoes are not subject to quality changes if the water activityis below a value of 0.2. In order to determine the water content associated with this value at storage temperature, the known equations for the sorption equilibrium were evaluated and verified with own experimental investigations. This determined the end point of the drying process.
The following experimental investigations showed a process-dependent change of the quality criteria such as color, shrinkage, and mechanical properties as well as the content of valuedetermining substances such as vitamin C and starch. The differences in the course and magnitude of the quality changes were attributed to the glass transition that takes place during the drying process. For the determination of the glass transition temperature a new, simple method based on the measurement of mechanical properties could be developed. The knowledge of the glass transition temperature allowed optimizing the drying process. The drying process could be carried out in the rubbery or glassy region, depending on the expected quality changes. Thus, all information was available to produce high quality dried potatoes in an industrial process.
Since the production of potato products in less industrialized regions without sufficient supply of electrical energy should be included, potatoes were dried with a solar tunnel dryer. Examination of the quality properties mentioned above confirmed the process-dependent quality changes.
Finally, the dried product was ground and with the flour thus produced, wheat flour was replaced for baking bread. An evaluation of the finished bread by a panel showed that the acceptance of the bread according to the new recipe was high, also with regard to baking volume, taste, texture and color.
This work shows that by drying potatoes can be transformed a well accepted, storable and easily transportable product. The risk of losses or degradation is minimized. It can be produced on an industrial as well as on farm level. If the influence of the glass transition is taken into account, it is possible to optimize the quality of the product.
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.
Organisation und Sprache
(2004)
Der radikale Wandel im Unternehmensumfeld bringt Unsicherheit und Komplexität mit sich. Daher ist ein Paradigmenwechsel im Management gefordert, denn scheinbar bewährte Rezepte funktionieren nicht mehr. Dieses Kapitel zeigt dazu, wie Führung 4.0 oder Digital Leadership die notwendigen dynamischen Fähigkeiten in der Organisation implementiert. Darüber hinaus wird dargestellt, wie eine Kernherausforderung der digitalen Transformation für etablierte Unternehmen gelingen kann – Ambidextrie (Beidhändigkeit) umzusetzen. Anhand zahlreicher Praxisbeispiele wird beschrieben, wie diese Beidhändigkeit – gleichzeitig das Kerngeschäft effizient zu optimieren und durch strategische Innovation in neue Geschäfte zu wachsen – strategische Erneuerung und digitale Transformation ermöglicht. Es wird aufgezeigt, wie die notwendige Unternehmerorientierung (Entrepreneur Orientation) gestärkt und Corporate Entrepreneurship erfolgreich umgesetzt werden kann. Als konkrete Option der Implementierung werden dazu unternehmerische, agile Teams – sogenannte eingebettete Unternehmerteams oder Corporate Start-ups – beschrieben. Auf Basis unserer Befragung von ca. 2000 Tech-Unternehmen und der Auswertung von mehr als 5000 Interviewminuten mit Geschäftsführern und Innovationsverantwortlichen in über 40 Unternehmen werden Empfehlungen zu Aufbau und Führung dieser Teams sowie kritische Erfolgsfaktoren erläutert.
Im Mittelpunkt des Forschungsprojekts steht die Intention, dem Management von Unternehmen (in Deutschland meist Vorstand oder Geschäftsführer) Empfehlungen zu geben, mit welchen unternehmerischen Maßnahmen sie die Erfüllung der an sie gestellten Organisations- und Aufsichtspflichten angemessen erfüllen können. Dabei wird der Fokus auf solche Maßnahmen gelegt, die im Rahmen eines umfassenden Compliance Management Systems implementiert werden, die dazu dienen, Fehlverhalten der Mitglieder eines Unternehmens zu verhindern und eine redliche und regelgetreue Führung der Geschäfte zu ermöglichen und sicherzustellen (sog. Business Conduct Compliance).
Organizational leadership
(2015)
To assess the quality of a person’s sleep, it is essential to examine the sleep behaviour by identifying the several sleep stages, their durations and sleep cycles. The established and gold standard procedure for sleep stage scoring is overnight polysomnography (PSG) with the Rechtschaffen and Kales (R-K) method. Unfortunately, the conduct of PSG is timeconsuming and unfamiliar for the subjects and might have an impact of the recorded data. To avoid the disadvantages with PSG, it is important to make further investigations in low-cost home diagnostic systems. For this intention it is necessary to find suitable bio vital parameters for classifying sleep stages without any physical impairments at the same time.
Due to the promising results in several publications we want to analyse existing methods for sleep stage classification based on the parameters body movement,
heartbeat and respiration. Our aim was to find different behaviour patterns in the several sleep stages. Therefore, the average values of 15 wholenight PSG recordings -obtained from the ‘DREAMS Subjects Database’- where analysed in the light of heartbeat, body movement and respiration with 10 different methods.
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.
Purpose The purpose of this paper is to find out tourism movement patterns via the tracking of tourists with the help of positioning systems like GPS in the rural area of the Lake Constance destination in Germany. In doing so past, present and future of tourist tracking is illustrated. Design/methodology/approach The tracking is realized via common smartphones extended by an app, with dedicated sensors like position loggers and a survey. The three different approaches are applied in order to compare and cross-check results (triangulation of data and methods). Findings Movement patterns turned out to be diverse and individualistic within the rural destination of Lake Constance and following an ants trail in sub-destinations like the city of Constance. Repeat visitors and first-time visitors alike always visit the bigger cities and main day-trip destinations of the Lake. A possible prediction tool enables new avenues of governing tourism movement patterns. Research limitations/implications The tracking techniques can be developed further into the direction of “quantified self” using gamification in order to make the tracking app even more attractive. Practical implications An algorithm-based prediction tool would offer new perspectives to the management of tourism movements. Social implications Further research is needed to overcome the feeling of invasiveness of the app to allow tracking with that approach. Originality/value This study is original and innovative because of the first-time use of a smartphone app in tourist tracking, the application on a rural destination and the conceptual description of a prediction tool.
Path planning and collision avoidance for safe autonomous vessel navigation in dynamic environments
(2017)
Stress and physical activities are important aspects of life of people. Body reactions on stress and on physical activities can be very similar but long-term stress leads to diseases and damages the body. Currently there is no method to differentiate easily and clearly between these two aspects in a time slot. We have confronted this problem while developing a mobile system for detection and analysis of stress. This paper presents an approach, which uses a long-term monitor with ECG/EKG capabilities and analysis of the heart rate data that is extracted from the device. The focus of the work is to find characteristics that are useful for differentiation between physical activity and stress.
Monitoring heart rate and breathing is essential in understanding the physiological processes for sleep analysis. Polysomnography (PSG) system have traditionally been used for sleep monitoring, but alternative methods can help to make sleep monitoring more portable in someone's home. This study conducted a series of experiments to investigate the use of pressure sensors placed under the bed as an alternative to PSG for monitoring heart rate and breathing during sleep. The following sets of experiments involved the addition of small rubber domes - transparent and black - that were glued to the pressure sensor. The resulting data were compared with the PSG system to determine the accuracy of the pressure sensor readings. The study found that the pressure sensor provided reliable data for extracting heart rate and respiration rate, with mean absolute errors (MAE) of 2.32 and 3.24 for respiration and heart rate, respectively. However, the addition of small rubber hemispheres did not significantly improve the accuracy of the readings, with MAEs of 2.3 bpm and 7.56 breaths per minute for respiration rate and heart rate, respectively. The findings of this study suggest that pressure sensors placed under the bed may serve as a viable alternative to traditional PSG systems for monitoring heart rate and breathing during sleep. These sensors provide a more comfortable and non-invasive method of sleep monitoring. However, the addition of small rubber domes did not significantly enhance the accuracy of the readings, indicating that it may not be a worthwhile addition to the pressure sensor system.
Sleep is an important aspect in life of every human being. The average sleep duration for an adult is approximately 7 h per day. Sleep is necessary to regenerate physical and psychological state of a human. A bad sleep quality has a major impact on the health status and can lead to different diseases. In this paper an approach will be presented, which uses a long-term monitoring of vital data gathered by a body sensor during the day and the night supported by mobile application connected to an analyzing system, to estimate sleep quality of its user as well as give recommendations to improve it in real-time. Actimetry and historical data will be used to improve the individual recommendations, based on common techniques used in the area of machine learning and big data analysis.
Assistive environments are entering our homes faster than ever. However, there are still various barriers to be broken. One of the crucial points is a personalization of offered services and integration of assistive technologies in common objects and therefore in a regular daily routine. Recognition of sleep patterns for the preliminary sleep study is one of the health services that could be performed in an undisturbing way. This article proposes the hardware system for the measurement of bio-vital signals necessary for initial sleep study in a non-obtrusive way. The first results confirm the potential of measurement of breathing and movement signals with the proposed system.
Personalmarketing
(2011)
Aufgrund der Corona-Pandemie kam es 2020 zu einer verstärkten Nutzung von Homeoffice und Teleworking. Sowohl bzgl. der Wahl des Arbeitsortes als auch der genutzen Kommunikationstechnologien existieren Pfadabhängigkeiten. Der Beitrag thematisiert diese Pfadabhängigkeiten systematisch, insbesondere ihre Ursachen und Folgen sowie die Möglichkeiten zur Pfadbrechung.
Die jüngeren Entscheidungen des EuGH sowie des BAG zur Arbeitszeiterfassung haben trotz ihrer eigentlich klaren Aussagen in der betrieblichen Praxis zu teils erheblichen Verunsicherungen geführt: Müssen nun wirklich die Arbeitszeiten der Beschäftigten erfasst werden und wie wirkt sich das auf die in vielen Unternehmen gelebte „Vertrauensarbeitszeit“ aus?
The multichannel Wiener filter (MWF) is a well-established noise reduction technique for speech processing. Most commonly, the speech component in a selected reference microphone is estimated. The choice of this reference microphone influences the broadband output signal-to-noise ratio (SNR) as well as the speech distortion. Recently, a generalized formulation for the MWF (G-MWF) was proposed that uses a weighted sum of the individual transfer functions from the speaker to the microphones to form a better speech reference resulting in an improved broadband output SNR. For the MWF, the influence of the phase reference is often neglected, because it has no impact on the narrow-band output SNR. The G-MWF allows an arbitrary choice of the phase reference especially in the context of spatially distributed microphones.
In this work, we demonstrate that the phase reference determines the overall transfer function and hence has an impact on both the speech distortion and the broadband output SNR. We propose two speech references that achieve a better signal-to-reverberation ratio (SRR) and an improvement in the broadband output SNR. Both proposed references are based on the phase of a delay-and-sum beamformer. Hence, the time-difference-of-arrival (TDOA) of the speech source is required to align the signals. The different techniques are compared in terms of SRR and SNR performance.
Philosophie & Rhetorik
(2020)
Photovoltaik
(2010)
Physik Methoden
(2023)
The Burrows–Wheeler transformation (BWT) is a reversible block sorting transform that is an integral part of many data compression algorithms. This work proposes a memory-efficient pipelined decoder for the BWT. In particular, the authors consider the limited context order BWT that has low memory requirements and enable fast encoding. However, the decoding of the limited context order BWT is typically much slower than the encoding. The proposed decoder pipeline provides a fast inverse BWT by splitting the decoding into several processing stages which are executed in parallel.
Pitting susceptibility of metastable austenitic stainless steels as a function of surface conditions
(2019)
The influence of surface roughness and local defects on pitting susceptibility of type 304 (UNS S30400) and type 301 (UNS S30100) in chloride solution were investigated. Because the mechanical properties can be regarded as decisive for the achieved surface quality, different properties of the base material were obtained by cold rolling the metastable austenites. This was done before the surfaces were finished. Therefor the surfaces were treated by different grinding parameters to generate different surface conditions and different defects. As a reference, different standardised surface finishes were used.
By using and comparing different methods for the characterization of surface roughness and surface texture, it is possible to find a relationship between the quantity and characteristics of local defects on the one hand and pitting susceptibility on the other hand. For the machining parameters used, a ranking of the influencing factors on the corrosion resistance achieved could be determined.
The automated application of software-based solutions for estimating the pitting susceptibility of machined surfaces and components will be discussed using concrete examples.
Pitting susceptibility of metastable austenitic stainless steels as a function of surface conditions
(2019)
Fachvortrag auf der 10th International European Stainless Steel Conference and 6th European Duplex Stainless Steel Conference (ESSC & DUPLEX 2019), 30.09. – 02.10.2019, Vienna, Austria
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.
Der Einsatz von Plagiatssoftware sollte auf die Zielgruppe abgestimmt sein. Da die Beurteilung des digitalen Prüfberichts Expertenwissen voraussetzt, erscheint ein unbegleiteter Zugriff nicht sinnvoll. Da meist nicht mit Betrugsabsicht, sondern aus Regelunkenntnis plagiiert wird, ist eine Beschränkung auf eine flächendeckende Detektion keine Lösung. Umfassendes Regelwissen, ein Verständnis für die grundlegende Bedeutung intertextueller Bezüge sowie selbstverantwortliches Handeln sind Vermittlungsziele der HTWG-Schreibberatung. Zu diesem Zweck macht das HTWG-Modell den Schreibkursbesuch zur Zulassungsvoraussetzung für die freiwillige Plagiatskontrolle und behält sich die Deutungshoheit über den Prüfbericht vor.
Planspiel KLIMA 10.X
(1992)
Pop-up Workshopreihe
(2020)
A lot of procedures for estimating the spool position in linear electromagnetic actuators using voltage and current measurements only, can be found in the literature. Subject to the accuracy of the estimated spool position some achieve better, some worse results. However, in almost every approach hysteresis has a huge impact on the estimation accuracy that can be achieved. Regardless whether these effects are caused by magnetic or mechanical hysteresis, they will limit the accuracy of the position estimate, if not taken into account. In this paper, a model is introduced which covers the hysteresis effects as well as other nonlinear ities occurring in estimated position-dependent parameters. A classical Preisach model is deployed first, which is then adjusted by using novel elementary preceding Relay-Operators. The resulting model for the estimated position-dependent parameters including the adjusted Preisach model can be easily applied to position estimation tasks. It is shown that the considered model distinctly improves the accuracy for the spool position estimate, while it is kept as simple as possible for real-time implementation reasons.
The method of signal injection is investigated for position estimation of proportional solenoid valves. A simple observer is proposed to estimate a position-dependent parameter, i.e. the eddy current resistance, from which the position is calculated analytically. Therefore, the relationship of position and impedance in the case of sinusoidal excitation is accurately described by consideration of classical electrodynamics. The observer approach is compared with a standard identification method, and evaluated by practical experiments on an off-the-shelf proportional solenoid valve.
The overall goal of this work is to detect and analyze a person's movement, breathing and heart rate during sleep in a common bed overnight without any additional physical contact. The measurement is performed with the help of
sensors placed between the mattress and the frame. A two-stage pattern classification algorithm based has been implemented that applies statistics analysis to recognize the position of patients. The system is implemented in a sensors-network, hosting several nodes and communication end-points to support quick and efficient classification. The overall tests show convincing results for the position recognition and a reasonable overlap in matching.
Post harvest technology
(2015)
The number of home office workers sitting for many hours is increasing. The sensor chair is tracking users’ sitting behavior which the help of pressure sensors and tries to avoid wrong postures which may cause diseases. The system provides live monitoring of the pressure distribution via web interface, as well as sitting posture prediction in real time. Posture analysis is realized through machine learning algorithm using a decision tree classifier that is compared to a random forest. Data acquisition and aggregation for the learning process happens with a mobile app adding users biometrical data and the taken sitting posture as label. The sensor chair is able to differentiate between an arched back, a neutral posture or a laid back position taken on the chair. The classifier achieves an accuracy of 97.4% on our test set and is comparable to the performance of the random forest with 98.9%.
In the automotive industry a strong effort has been undertaken to reduce the weight of modern vehicles. In order to reduce the energy consumption and to improve the environmental sustainability, the importance of weight reduction activities is even growing faster. As lightweight designing is becoming more and more expensive and show less potential savings, new approaches are needed. One promising technology could be the use of shape memory elements. In the last years a lot of potential application possibilities were presented, demonstrating the benefit of these functional elements in automotive design solutions: they often reduce complexity, weight and design space of an actuation device and enable new functions. In addition they work silently and are therefore ideally suitable for comfort applications in the passenger cabin. Because of the current trend to electric vehicle the hitherto existing drawback of a high electrical energy consumption of shape memory actuators in some design proposals is not given any more.
As one of the most important branches of the industry in Germany and
the European Union, the mechanical and plant engineering sector is confronted with fundamental changes due to ever shorter innovation cycles and increased competitive pressure. This makes it even more important to increase the level of service components in business models with a low service level, which are still frequently found in SMEs. This paper is dedicated to the changes that the individual components of a business model have experienced and will experience. Special attention is paid to economic sustainability, since service business models can also positively influence the long-term nature of a business. Seven interviews conducted with relevant companies serve as the empirical basis of this paper. The analysed effects of smart services and active customer integration are structured and summarized within the three pillars of every business model (value proposition, the value creation architecture and the revenue mechanic).
Die durch KMU geprägte Investitionsgüterindustrie steht aufgrund der zunehmenden Internationalisierung im Servicegeschäft, Mitarbeiterengpässen, hohen Prozesskosten sowie fehlendem Wissensmanagment vor großen Herausforderungen. Durch die Digitalisierung entstehen große Nutzenpotenziale im Servicegeschäft. Vor diesem Hintergrund wurde ein auf den Methoden Intelligent Swarming und Knowledge Centered Service basierender, integrierter Ansatz entwickelt, der KMU aus der Investitionsgüterindustrie befähigt, Servicewissen effizient zu generieren, zu strukturieren und international zu vermarkten.
PowerPoint-Rhetorik
(2017)
Praktische Rhetorik
(2023)
Die Überwindung des Bruchs (Seam) beim Lernen im Studium zwischen dem Hochschulkontext und der beruflichen Praxis ist durch die zeitlich, räumlich und organisatorisch bedingte Trennung der relevanten Akteure (u. a. Lehrende, Lernende, Unternehmensvertreter) eine sehr große Herausforderung (Milrad et al., 2013). Eine seamless-learning-basierte Konzeption einer Lehrveranstaltung auf Basis agiler Werte und Methoden (u. a. inkrementelles Vorgehen, Fokus auf lernendenzentrierte Veranstaltungen, individualisiertes Lernenden-Feedback) kann bei der Überwindung dieses bedeutenden Bruchs helfen. In dem Poster wird das grundsätzliche Design eines derartigen agilen SL-Konzepts auf Basis eines iterativ, inkrementellen Vorgehens innerhalb eines Semesterzyklus von 15 Wochen in drei Lernsprints erörtert. Darüber hinaus wird über erste Lehrerfahrungen der Dozierenden sowohl aus der Hochschule als auch aus dem industriellen Umfeld und Lernerfahrungen der Studierenden aus den vergangenen zwei Jahren berichtet.
Interpretability and uncertainty modeling are important key factors for medical applications. Moreover, data in medicine are often available as a combination of unstructured data like images and structured predictors like patient’s metadata. While deep learning models are state-of-the-art for image classification, the models are often referred to as ’black-box’, caused by the lack of interpretability. Moreover, DL models are often yielding point predictions and are too confident about the parameter estimation and outcome predictions.
On the other side with statistical regression models, it is possible to obtain interpretable predictor effects and capture parameter and model uncertainty based on the Bayesian approach. In this thesis, a publicly available melanoma dataset, consisting of skin lesions and patient’s age, is used to predict the melanoma types by using a semi-structured model, while interpretable components and model uncertainty is quantified. For Bayesian models, transformation model-based variational inference (TM-VI) method is used to determine the posterior distribution of the parameter. Several model constellations consisting of patient’s age and/or skin lesion were implemented and evaluated. Predictive performance was shown to be best by using a combined model of image and patient’s age, while providing the interpretable posterior distribution of the regression coefficient is possible. In addition, integrating uncertainty in image and tabular parts results in larger variability of the outputs corresponding to high uncertainty of the single model components.
Preliminary results of homomorphic deconvolution application to surface EMG signals during walking
(2021)
Homomorphic deconvolution is applied to sEMG signals recorded during walking. Gastrocnemius lateralis and tibialis anterior signals were acquired according to SENIAM recommendation. MUAP parameters like amplitude and scale were estimated, whilst the MUAP shape parameter was fixed. This features a useful time-frequency representation of sEMG signal. Estimation of scale MUAP parameter was verified extracting the mean frequency of filtered EMG signal, extracted from the scale parameter estimated with two different MUAP shape values.
Several possibilities of tests under load on a chassis dynamometer are presented. Consumption measurements according standard driving cycles as the New European Drive Cycle (NEDC) and Worldwide harmonized light duty test procedure/cycle (WLTP/WLTC) make special attention to the observance of the regulations necessary. The rotational masses of inertia and the load depending on velocity have to match the required values. Load tests as well allow the determination of the maximum acceleration in the current gear and the slippage of the driven wheels.
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.
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.
Probabilistic Deep Learning
(2020)
Probabilistic Deep Learning is a hands-on guide to the principles that support neural networks. Learn to improve network performance with the right distribution for different data types, and discover Bayesian variants that can state their own uncertainty to increase accuracy. This book provides easy-to-apply code and uses popular frameworks to keep you focused on practical applications.
In this paper, we propose a novel method for real-time control of electric distribution grids with a limited number of measurements. The method copes with the changing grid behaviour caused by the increasing number of renewable energies and electric vehicles. Three AI based models are used. Firstly, a probabilistic forecasting estimates possible scenarios at unobserved grid nodes. Secondly, a state estimation is used to detect grid congestion. Finally, a grid control suggests multiple possible solutions for the detected problem. The best countermeasures are then detected by evaluating the systems stability for the next time-step.
Forecasting is crucial for both system planning and operations in the energy sector. With increasing penetration of renewable energy sources, increasing fluctuations in the power generation need to be taken into account. Probabilistic load forecasting is a young, but emerging research topic focusing on the prediction of future uncertainties. However, the majority of publications so far focus on techniques like quantile regression, ensemble, or scenario-based methods, which generate discrete quantiles or sets of possible load curves. The conditioned probability distribution remains unknown and can only be estimated when the output is post-processed using a statistical method like kernel density estimation.
Instead, the proposed probabilistic deep learning model uses a cascade of transformation functions, known as normalizing flow, to model the conditioned density function from a smart meter dataset containing electricity demand information for over 4,000 buildings in Ireland. Since the whole probability density function is tractable, the parameters of the model can be obtained by minimizing the negative loglikelihood through the state of the art gradient descent. This leads to the model with the best representation of the data distribution.
Two different deep learning models have been compared, a simple three-layer fully connected neural network and a more advanced convolutional neural network for sequential data processing inspired by the WaveNet architecture. These models have been used to parametrize three different probabilistic models, a simple normal distribution, a Gaussian mixture model, and the normalizing flow model. The prediction horizon is set to one day with a resolution of 30 minutes, hence the models predict 48 conditioned probability distributions.
The normalizing flow model outperforms the two other variants for both architectures and proves its ability to capture the complex structures and dependencies causing the variations in the data. Understanding the stochastic nature of the task in such detail makes the methodology applicable for other use cases apart from forecasting. It is shown how it can be used to detect anomalies in the power grid or generate synthetic scenarios for grid planning.
Probabilistic Short-Term Low-Voltage Load Forecasting using Bernstein-Polynomial Normalizing Flows
(2021)
The transition to a fully renewable energy grid requires better forecasting of demand at the low-voltage level. However, high fluctuations and increasing electrification cause huge forecast errors with traditional point estimates. Probabilistic load forecasts take future uncertainties into account and thus enables various applications in low-carbon energy systems. We propose an approach for flexible conditional density forecasting of short-term load based on Bernstein-Polynomial Normalizing Flows where a neural network controls the parameters of the flow. In an empirical study with 363 smart meter customers, our density predictions compare favorably against Gaussian and Gaussian mixture densities and also outperform a non-parametric approach based on the pinball loss for 24h-ahead load forecasting for two different neural network architectures.
Some 165 global experts and specialists from industry and academic institutes met at the 8th Metallization & Interconnection Workshop (MIW2019) that took place from 13 to 14 May 2019 in Konstanz, Germany. Participants from 19 countries debated results of 28 oral and 11 poster presentations.
All presentations are available on www.metallizationworkshop.info as pdf documents. As in previous editions, lots of room was available for discussions and networking during the two-days program which included panel and market-place discussions as well as social events (reception, workshop dinner).
These proceedings contain: a summary of the oral and poster presentations, the results of the survey conducted during the workshop, and peer-reviewed papers based on workshop contributions.
Since its first edition in 2008, the Workshop on Metallization and Interconnection for Crystalline Silicon SolarCells has been a key event where knowledge in the critical fields of crystalline silicon solar cell metallization andinterconnection is shared between experts from academia and industry. It has become a highly recognized event forthe quality of the contributions, the lively Q&A sessions, and the exceptional networking opportunity.The situation with the Covid-19 pandemic made organizing the 9th edition as an in-person event impossible andforced us to reconsider the event format. The event took place virtually on October 5th and 6th 2020. We used aninnovative online platform that enabled not only presentations followed by Q&A but also more informal interactions,where participants could see and talk directly to other participants. 120 experts from 22 countries took part andattended 21 contributions presented live. In spite of a few technical glitches, the workshop was successful and thegoals of exchanging on the state-of-the-art in research/industry and connecting experts in the field were achieved.All presentations are available on www.miworkshop.info as .pdf documents. These proceedings contain asummary of the 9th edition (MIW2020) and peer-reviewed papers based on the workshop contributions. The organizerswish to thank the members of the Scientific Committee for the time spent reviewing the MIW2020 abstracts andproceedings. The organizers also wish to thank again the sponsors and supporters for their financial contributionswhich made the 9th Workshop on Metallization and Interconnection for Crystalline Silicon Solar Cells possible.
The target of this thesis is the introduction of a client management system (CMS) at Haaland Internet Productions (HiP), a web design and hosting company in Burbank, California, USA. The company needs a system to track orders and improve workflow. HiP needs a system which not only tracks orders, but also stores all client information in a database. This client information can be used for a variety of marketing and contact reasons. It is an important and integral part of HiP's client relationship management (CRM). The lack of a cohesive CMS at HiP caused many fundamental business problems, such as lost orders, missed billing statements, and over/under billing. The research done during the investigation and analysis of the company and their needs should lead to a global system which totally fulfils the needs of HiP. This global system could be in the form of an off-the-shelf product with some customizations, or a completely new, in-house system. Either solution will have respective pros and cons; the goal is to reach a decision that best fits HiP's needs and situation. The following is a concise version of the project. Particular emphasis is placed upon the single steps which made up the decision process, as well as the practiced techniques, methods, and their applications.
We have introduced in this paper new variants of two methods for projecting Supply and Use Tables that are based on a distance minimisation approach (SUT-RAS) and the Leontief model (SUT-EURO). We have also compared them under similar and comparable exogenous information, i.e.: with and without exogenous industry output, and with explicit consideration of taxes less subsidies on products. We have conducted an empirical assessment of all of these methods against a set of annual tables between 2000 and 2005 for Austria, Belgium, Spain and Italy. From the empirical assessment, we obtained three main conclusions: (a) the use of extra information (i.e. industry output) generally improves projected estimates in both methods; (b) whenever industry output is available, the SUT-RAS method should be used and otherwise the SUT-EURO should be used instead; and (c) the total industry output is best estimated by the SUT-EURO method when this is not available.