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Trotz des dringenden Erfordernisses einer nachhaltigen und unabhängigen Energieerzeugung und bereits steigender Anteile photovoltaisch erzeugten Stroms stockt die Verbreitung der bauwerkintegrierten Photovoltaik (BIPV). Zahlreiche „Leuchtturm“-Projekte zeigen das große ästhetische Potential solaraktiver Bauteile und dennoch werden insbesondere von Architekt/innen-Seite neben vermeintlichen Einschränkungen in der planerischen Freiheit immer wieder auch gestalterische Vorbehalte angeführt.
Bisher wurde im Zusammenhang mit PV-Bauteilen schwerpunktmäßig die technische und konstruktive Einfügung thematisiert. Um einen Beitrag zur Diskussion um die Entwicklung visuell überzeugender Ergebnisse zu leisten, die verhindern, dass photovoltaische Bauteile am Gebäude als Fremdkörper wahrgenommen werden, ermittelt die vorliegende Arbeit auf der Grundlage ästhetischer Architekturtheorien allgemeingültige Kriterien für architektonische Wirkungsqualität und transferiert diese auf den Bereich der BIPV-Gestaltung.
Dabei werden zum Verständnis erforderliche Grundlagen der BIPV-Systemtechnik vermittelt sowie verfügbare Bauteile und die unterschiedlichen Akteure und Ziele bei der Gestaltung von BIPV aufzeigt. Auch die speziellen funktionalen und technischen Anforderungen, die PV-Bauteile als „aktive“ Bauteile stellen, werden berücksichtigt und hinsichtlich ihrer hemmenden oder synergetischen Wechselwirkungen differenziert.
Im Rahmen einer Projektstudie finden die oben genannten Kriterien Anwendung auf 13 „best practice“-Beispiele aktueller Wettbewerbsgewinner des vom Solarenergieförderverein Bayern e. V. (SeV) ausgelobten „Architekturpreis Gebäudeintegrierte Solartechnik“, die in Form von Steckbriefen vergleichend dargestellt werden.
Das Ergebnis ist die Synthese eines Kriterienkatalogs als Orientierungs-, Planungs- und Kommunikationswerkzeug, in dem alle Ergebnisse systematisiert zusammengestellt werden.
Ergänzend wird in einem kurzen Exkurs auf von der Hauptuntersuchung ausgenommene, für die Praxis aber relevante Schnittstellen zu wirtschaftlichen Aspekten eingegangen.
IT-Compliance in KMU
(2023)
In spite of the amount of new tools and methodologies adopted in the road infrastructure sector, the performance of road infrastructure projects is not constantly improving. Considering that the volume of projects undertaken is forecasted to increase every year, this is a substantial issue for the road infrastructure sector. Hence this work focuses on the principles of Blockchain Technology, road infrastructure sector and the information exchange with the aim to use the advantages of the Blockchain Technology in supporting to overcome the various challenges along the life cycle of road infrastructure projects.
Within the scope of this paper, two studies were conducted. First, focus groups were used to explore where society (road infrastructure sector) stands in terms of industry 4.0 and to get a better understanding if and where the principles of Blockchain Technology can be used when managing projects in the road infrastructure sector. Second, semi-structured interviews were administrated with experts of the road infrastructure sector and experts of Blockchain Technology to better understand the interrelation between these two areas. Based on the outcome of the two studies, technology barriers and enablers were explored for the purpose of improved information exchange within the road infrastructure sector.
The two studies revealed that there are significant and strong interrelations between the principles of the Blockchain Technology, project management within the road infrastructure sector and information exchange. These interrelations are complex and diverse, but overall it can be concluded that the adoption of the principles of Blockchain Technology into the field of information exchange improves the management of road infrastructure projects. Based on the two studies a theoretical framework was developed.
In summary this research showed that trust is an important factor and builds the foundation for communication and to ensure a proper information exchange. Within the scope of this thesis, it was demonstrated that the principles of the Blockchain Technology can be used to increase transparency, traceability and immutability during the life cycle of road infrastructure projects in the area of information exchange.
This thesis presents the development of two different state-feedback controllers to solve the trajectory tracking problem, where the vessel needs to reach and follow a time-varying reference trajectory. This motion problem was addressed to a real-scaled fully actuated surface vessel, whose dynamic model had unknown hydrodynamic and propulsion parameters that were identified by applying an experimental maneuver-based identification process. This dynamic model was then used to develop the controllers. The first one was the backstepping controller, which was designed with a local exponential stability proof. For the NMPC, the controller was developed to minimize the tracking error, considering the thrusters’ constraints. Moreover, both controllers considered the thruster allocation problem and counteracted environmental disturbance forces such as current, waves and wind.The effectiveness of these approaches was verified in simulation using Matlab/Simulink and GRAMPC (in the case of the NMPC), and in experimental scenarios, where they were applied to the vessel, performing docking maneuvers at the Rhine River in Constance (Germany).
Public-key cryptographic algorithms are an essential part of todays cyber security, since those are required for key exchange protocols, digital signatures, and authentication. But large scale quantum computers threaten the security of the most widely used public-key cryptosystems. Hence, the National Institute of Standards and Technology ( NIST ) is currently in a standardization process for post-quantum secure public-key cryptography. One type of such systems is based on the NP-complete problem of decoding random linear codes and therefore called code-based cryptography. The best-known code-based cryptographic system is the McEliece system proposed in 1978 by Robert McEliece. It uses a scrambled generator matrix as a public key and the original generator matrix as well as the scrambling as private key. When encrypting a message it is encoded in the public code and a random but correctable error vector is added. Only the legitimate receiver can correct the errors and decrypt the message using the knowledge of the private key generator matrix. The original proposal of the McEliece system was based on binary Goppa codes, which are also considered for standardization. While those codes seem to be a secure choice, the public keys are extremely large, limiting the practicality of those systems. Many different code families were proposed for the McEliece system, but many of them are considered insecure since attacks exist, which use the known code structure to recover the private key. The security of code-based cryptosystems mainly depends on the number of errors added by the sender, which is limited by the error correction capability of the code. Hence, in order to obtain a high security for relatively short codes one needs a high error correction capability. Therefore maximum distance separable ( MDS ) codes were proposed for those systems, since those are optimal for the Hamming distance. In order to increase the error correction capability we propose q -ary codes over different metrics. There are many code families that have a higher minimum distance in some other metric than in the Hamming metric, leading to increased error correction capability over this metric. To make use of this one needs to restrict not only the number of errors but also their value. In this work, we propose the weight-one error channel, which restricts the error values to weight one and can be applied for different metrics. In addition we propose some concatenated code constructions, which make use of this restriction of error values. For each of these constructions we discuss the usability in code-based cryptography and compare them to other state-of-the-art code-based cryptosystems. The proposed code constructions show that restricting the error values allows for significantly lower public key sizes for code-based cryptographic systems. Furthermore, the use of concatenated code constructions allows for low complexity decoding and therefore an efficient cryptosystem.
Particularly for manufactured products subject to aesthetic evaluation, the industrial manufacturing process must be monitored, and visual defects detected. For this purpose, more and more computer vision-integrated inspection systems are being used. In optical inspection based on cameras or range scanners, only a few examples are typically known before novel examples are inspected. Consequently, no large data set of non-defective and defective examples could be used to train a classifier, and methods that work with limited or weak supervision must be applied. For such scenarios, I propose new data-efficient machine learning approaches based on one-class learning that reduce the need for supervision in industrial computer vision tasks. The developed novelty detection model automatically extracts features from the input images and is trained only on available non-defective reference data. On top of the feature extractor, a one-class classifier based on recent developments in deep learning is placed. I evaluate the novelty detector in an industrial inspection scenario and state-of-the-art benchmarks from the machine learning community. In the second part of this work, the model gets improved by using a small number of novel defective examples, and hence, another source of supervision gets incorporated. The targeted real-world inspection unit is based on a camera array and a flashing light illumination, allowing inline capturing of multichannel images at a high rate. Optionally, the integration of range data, such as laser or Lidar signals, is possible by using the developed targetless data fusion method.
Nowadays, most digital modulation schemes are based on conventional signal constellations that have no algebraic group, ring, or field properties, e.g. square quadrature-amplitude modulation constellations. Signal constellations with algebraic structure can enhance the system performance. For instance, multidimensional signal constellations based on dense lattices can achieve performance gains due to the dense packing. The algebraic structure enables low-complexity decoding and detection schemes. In this work, signal constellations with algebraic properties and their application in spatial modulation transmission schemes are investigated. Several design approaches of two- and four-dimensional signal constellations based on Gaussian, Eisenstein, and Hurwitz integers are shown. Detection algorithms with reduced complexity are proposed. It is shown, that the proposed Eisenstein and Hurwitz constellations combined with the proposed suboptimal detection can outperform conventional two-dimensional constellations with ML detection.
The influence of sleep on human life, including physiological, psychological, and mental aspects, is remarkable. Therefore, it is essential to apply appropriate therapy in the case of sleep disorders. For this, however, the irregularities must first be recognised, preferably conveniently for the person concerned. This dissertation, structured as a composition of research articles, presents the development of mathematically based algorithmic principles for a sleep analysis system. The particular focus is on the classification of sleep stages with a minimal set of physiological parameters. In addition, the aspects of using the sleep analysis system as part of the more complex healthcare systems are explored. Design of hardware for non-obtrusive measurement of relevant physiological parameters and the use of such systems to detect other sleep disorders, such as sleep apnoea, are also referred to. Multinomial logistic regression was selected as the basis for development resulting from the investigations carried out. By following a methodical procedure, the number of physiological parameters necessary for the classification of sleep stages was successively reduced to two: Respiratory and Movement signals. These signals might be measured in a contactless way. A prototype implementation of the developed algorithms was performed to validate the proposed method, and the evaluation of 19324 sleep epochs was carried out. The results, with the achieved accuracy of 73% in the classification of Wake/NREM/REM stages and Cohen's kappa of 0.44, outperform the state of the art and demonstrate the appropriateness of the selected approach. In the future, this method could enable convenient, cost-effective, and accurate sleep analysis, leading to the detection of sleep disorders at an early stage so that therapy can be initiated as soon as possible, thus improving the general population's health status and quality of life.
Zur Erfassung von Veränderungen der Produkteigenschaften während der Trocknung von Lebensmitteln werden zerstörungsfreie Qualitätsmesstechniken gefordert, mit denen Veränderungen im Inneren des Produkts bestimmt werden können. Gerade im industriellen Einsatz sind schnelle, präzise, und gleichzeitig robuste Verfahren besonders wichtig, um qualitativ hochwertige Produkte zu erhalten.
In dieser Arbeit wurde zur optischen Qualitätsmessung ein neuartiges multispektrales Kamerasystem eingesetzt, um von Veränderungen der spektralen Oberflächenreflexion bei der Mango- und Ananastrocknung mit Veränderungen der Produktfeuchte, sowie mechanischen und chemischen Eigenschaften zu verknüpfen. Diese Verknüpfung wurde mit maschinellem Lernen erreicht.
In einem ersten Schritt wurde ein neues Kameraprinzip, eine multispektrale Flächenkamera mit vier Objektiven und Vorsatzfiltern, entwickelt und speziell auf den Einsatz in der Obsttrocknung angepasst. Anschließend wurden die Änderungen der Spektren und der Qualitätskriterien während der Trocknung gemessen. Dazu wurden Mango- und Ananasscheiben in einem Einzelschichttrockner bei Lufttemperaturen zwischen 40 °C und 80 °C und relativen Luftfeuchtigkeiten von 5 % bis 30 % getrocknet. Während der gesamten Trocknungsdauer wurde die Produktfeuchte der Proben gemessen, und Bilder mit der multispektralen Flächenkamera aufgenommen. Zur Analysen von nur ausgewählten Bereichen von Interesse in den Bildern wurde ein Softwarefilter entwickelt. Aus Spektraldaten und Prozessdaten konnte mit Algorithmen des maschinellen Lernens die Produktfeuchte zu jedem Zeitpunkt sehr genau vorhergesagt werden (Bestimmtheitsmaß R² von 0,98 bis 0,99). Die Kombination aus dem Prinzip der multispektralen Flächenkamera und maschinellem Lernen wurde in einem anderen Trocknungsprozess und mit weiteren Qualitätskriterien getestet. Dafür wurden Mangoscheiben in einem Schranktrockner getrocknet und deren Produkteigenschaften anhand der Spektraldaten und der Prozessdaten vorhergesagt. Bei der Vorhersage der Farbwerte Δa*, Δb* und ΔE00 sowie des Gehalts an gesamtlöslichen Feststoffen im Rehydrierungswasser wurden Bestimmtheitsmaße R² zwischen 0,56 und 0,94 erzielt).
Es konnte gezeigt werden, dass die Kombination aus dem neu entwickelten Multispektralkamerasystem und maschinellem Lernen zur Vorhersage der Produktfeuchte und anderer Qualitätskriterien der Produkte eingesetzt werden kann. Auf diese Weise können Qualitätsänderungen während des Prozesses mit nur wenigen Messgeräten inline überwacht werden.
Dieses Forschungsvorhaben zielt darauf ab, individuelle Entrepreneure hinsichtlich ihrer Veränderungstendenzen zur Nutzung der Entscheidungslogik Effectuation und Causation zu untersuchen – insbesondere während des Gründungsprozesses. Basierend auf einem qualitativen Fallstudiendesign zeigen sowohl fallinterne als auch fallübergreifende Analysen, wie Entrepreneure zunächst an der effektuativen Logik festhalten und im Gründungsverlauf zu hybriden Logikformen übergehen. Der Beitrag zur Weiterentwicklung der Forschung zielt in drei Richtungen: Erstens schließt die Arbeit Lücken in der Effectuation-Forschung, indem sie Entscheidungsfindung von Unternehmensgründern auf individueller Ebene spezifiziert. Zweitens ermöglicht die Fokussierung auf die einzelnen Gründungsphasen ein besseres Verständnis der Veränderungstendenzen einschließlich der Kausalzusammenhänge (wann, wie und warum). Insbesondere werden Erkenntnisse zur Auffälligkeit von Veränderungssprüngen von einer Phase zur anderen geliefert. Drittens kann durch die Beleuchtung der verschiedenen Subdimensionen von Effectuation und Causation ihre zunehmend hybride Verwendung im Zeitverlauf der Gründung das Verständnis für transformative Prozesse entwickeln.
InnoCrowd, a Product Classification System for Design Decision in a Crowdsourced Product Innovation
(2021)
System engineering focuses on how to design and manage complex systems. Meanwhile, in the era of Industry 4.0 and Internet of Things (IoT), systems are getting more complex. Contributors to higher complexity include the usage of modern components (e.g. mechatronics), new manufacturing technologies (e.g. 3D Print) and new engineering product development processes, e.g. open innovation. Open innovation is enabled by IoT, where people and devices are easily connected, and it supports development of more innovative products through ideas gained from predecessors and collaborators world wide. Some researchers suggest this approach is up to three times faster and five times cheaper than conventional approaches [Gassmann, 2012], [Howe, 2008], [Kusumah, 2018]. Because open innovation is relatively new, many managers do not know how to employ it effectively in some phases of product development [Schenk, 2009], [Afuah, 2017], including requirements definition, design and engineering processes (task assignment) through quality assurance. Also, they have trouble estimating and controlling development time and cost [Nevo, 2020], [Thanh, 2015]. As a consequence, the acceptance of this new approach in the industry is limited. Research activities addressing this new approach mainly address high-level and qualitive issues. Few effective methods are available to estimate project risk and to decide whether to initiate a project.
We propose InnoCrowd, a decision support system that uses an improved method to support these tasks and make decisions about crowdsourced engineering product development.
InnoCrowd uses natural language processing and machine learning to build a knowledgebase of crowdsourced product developments. InnoCrowd presents a manager with results of similar projects to show which practices led to good results. A manager of a new project can use this guidance to employ best practices for product requirements definition, project schedule, and other aspects, thereby reducing risk and increasing chances for success.
Die Entwicklung der Elektromobilität, als alternative Fortbewegungsform ist seit geraumer Zeit eine nicht nur regional, sondern weltweit und unter den verschiedensten Aspekten (Technik, Umwelt, Wirtschaft, Energiewende etc.) intensiv betrachtete und untersuchte Thematik. Hierbei spielt der mögliche positive Effekt auf die Umwelt und die Energiewende hin zu nicht fossilen Energieträgern eine zentrale Rolle für Politik und Forschung bei der Förderung dieser Technologie. Die vorliegende Arbeit untersucht die Elektromobilität im Bodenseetourismus. Ziel der Arbeit ist es, die Potenziale für die Integration der Elektromobilität im Bodenseetourismus darzustellen. Hierfür wird die Elektromobilität im Bodenseetourismus als innovative Mobilitätsform postuliert, verstanden und untersucht. Die Betrachtung der Diffusion der Innovation wird vor dem Hintergrund heterogener Akteursgruppen im Dreiländereck D-A-CH untersucht.
Algorithms and Architectures for Cryptography and Source Coding in Non-Volatile Flash Memories
(2021)
In this work, algorithms and architectures for cryptography and source coding are developed, which are suitable for many resource-constrained embedded systems such as non-volatile flash memories. A new concept for elliptic curve cryptography is presented, which uses an arithmetic over Gaussian integers. Gaussian integers are a subset of the complex numbers with integers as real and imaginary parts. Ordinary modular arithmetic over Gaussian integers is computational expensive. To reduce the complexity, a new arithmetic based on the Montgomery reduction is presented. For the elliptic curve point multiplication, this arithmetic over Gaussian integers improves the computational efficiency, the resistance against side channel attacks, and reduces the memory requirements. Furthermore, an efficient variant of the Lempel-Ziv-Welch (LZW) algorithm for universal lossless data compression is investigated. Instead of one LZW dictionary, this algorithm applies several dictionaries to speed up the encoding process. Two dictionary partitioning techniques are introduced that improve the compression rate and reduce the memory size of this parallel dictionary LZW algorithm.
Die Fähigkeit zur Erzeugung einer nur wenige Nanometer dicken Passivschicht gelingt nichtrostenden Edelstählen aufgrund deren chemischer Zusammensetzung. Die erzielte Korrosionsbeständigkeit wird allerdings darüber hinaus als Systemeigenschaft von einer Vielzahl von weiteren Faktoren beeinflusst. Die vorliegende Arbeit befasst sich fokussiert mit dem Einfluss der schleiftechnischen Oberflächenbearbeitung von zwei ausgesuchten metastabilen austenitischen Legierungen auf deren Korrosionsverhalten.
Obwohl beide Legierungen eine vergleichbare Beständigkeit gemäß der chemischen Zusammensetzung besitzen, kann gezeigt werden, dass infolge von unterschiedlicher Oberflächenbearbeitung und unterschiedlichem Umformgrad eine starke Variation des Korrosionsverhaltens möglich ist. Es kann ebenfalls nachgewiesen werden, dass die Ausprägung und Anzahl von lokalen Oberflächendefekten hierfür verantwortlich ist. Dem eingesetzten Schleifkornwerkstoff kommt hierbei eine besondere Bedeutung zu.
The main goal of this work was to experimentally characterize the hot air-drying process of agricultural products (Potato, Carrot, Tomato) and verify it with numerical solutions at single layer and industrial scale dryer using Comsol Multiphysics® 5.3.
Input parameters at single layer dryer effects on quality attributes were examined. Two strategies of drying were applied on batch dryer to examine the input effects on quality attributes. Constant input parameters strategy was designed by using central composite design formulation and optimized by Response Surface Methodology (RSM). The second strategy was applied for further optimization of the selected region by using square wave profile of the air temperature and relative humidity. Similarly, numerical method for single layer dryer, unsteady-state partial differential equations have been solved by means of the Finite Elements Method coupled to the Arbitrary Lagrangian-Eulerian (ALE). Also, for batch dryer, the mechanistic mathematical models of coupled heat and mass transfer were developed and solved as solid porous moist material.
With this work, the process of convective drying of agricultural products could be optimized. Furthermore, important knowledge about the basic mechanisms of the drying process was found and implemented in the numerical models.