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Multi-object tracking filters require a birth density to detect new objects from measurement data. If the initial positions of new objects are unknown, it may be useful to choose an adaptive birth density. In this paper, a circular birth density is proposed, which is placed like a band around the surveillance area. This allows for 360° coverage. The birth density is described in polar coordinates and considers all point-symmetric quantities such as radius, radial velocity and tangential velocity of objects entering the surveillance area. Since it is assumed that these quantities are unknown and may vary between different targets, detected trajectories, and in particular their initial states, are used to estimate the distribution of initial states. The adapted birth density is approximated as a Gaussian mixture, so that it can be used for filters operating on Cartesian coordinates.
In many industrial applications a workpiece is continuously fed through a heating zone in order to reach a desired temperature to obtain specific material properties. Many examples of such distributed parameter systems exist in heavy industry and also in furniture production such processes can be found. In this paper, a real-time capable model for a heating process with application to industrial furniture production is modeled. As the model is intended to be used in a Model Predictive Control (MPC) application, the main focus is to achieve minimum computational runtime while maintaining a sufficient amount of accuracy. Thus, the governing Partial Differential Equation (PDE) is discretized using finite differences on a grid, specifically tailored to this application. The grid is optimized to yield acceptable accuracy with a minimum number of grid nodes such that a relatively low order model is obtained. Subsequently, an explicit Runge-Kutta ODE (Ordinary Differential Equation) solver of fourth order is compared to the Crank-Nicolson integration scheme presented in Weiss et al. (2022) in terms of runtime and accuracy. Finally, the unknown thermal parameters of the process are estimated using real-world measurement data that was obtained from an experimental setup. The final model yields acceptable accuracy while at the same time shows promising computation time, which enables its use in an MPC controller.
The digital transformation of business processes and the integration of IT systems leads to opportunities and risks for small and medium-sized enterprises (SMEs). Risks that can result in a lack of IT Governance, Risk and Compliance (IT-GRC). The purpose of this paper is to present the current state of the research project. With this, the Design Science Research approach based on Hevner is using. Based on the phase of Problem Identification and Objectives, this paper will deal with the development of an artefact and thus present the draft of the Design phase. The artefact will be developed by selecting relevant existing frameworks and standards and the identification of SME-specific conditions.
This paper presents a modeling approach of an industrial heating process where a stripe-shaped workpiece is heated up to a specific temperature by applying hot air through a nozzle. The workpiece is moving through the heating zone and is considered to be of infinite length. The speed of the substrate is varying over time. The derived model is supposed to be computationally cheap to enable its use in a model-based control setting. We start by formulating the governing PDE and the corresponding boundary conditions. The PDE is then discretized on a spatial grid using finite differences and two different integration schemes, explicit and implicit, are derived. The two models are evaluated in terms of computational effort and accuracy. It turns out that the implicit approach is favorable for the regarded process. We optimize the grid of the model to achieve a low number of grid nodes while maintaining a sufficient amount of accuracy. Finally, the thermodynamical parameters are optimized in order to fit the model's output to real-world data that was obtained by experiments.
The present contribution proposes a novel method for the indirect measurement of the ground reaction forces (GRF) induced by a pedestrian during walking on a vibrating structure. Its main idea is to formulate and solve an inverse problem in the time domain with the aim of finding the optimal time dependent moving point force describing the GRF of a pedestrian (input data), which minimizes the difference between a set of computed and a set of measured structural responses (output data). The solution of the inverse problem is addressed by means of the gradient-based trust region optimization strategy. The moving force identification process uses output data from a set of acceleration and displacement time histories recorded at different locations on the structure. The practicability and the accuracy of the proposed GRF identification method is firstly evaluated using simulated measurements, which revealed a high accuracy, robustness and stability of the results in relation to high noise levels. Subsequently, a comprehensive experimental validation process using real measurement data recorded on the HUMVIB experimental footbridge on the campus of the Technical University of Darmstadt (Germany) was carried out. Besides the conventional sensors for the acquisition of structural responses, an array of biomechanical force plates as well as classical load cells at the supports were used for measurement reference GRFs needed in the experimental validation process. The results show that the proposed method delivers a very accurate estimation of the GRF induced by a subject during walking on the experimental structure.
Uzbekistan is an emerging tourism destination that has experienced a strong increase in tourists since 2017. However, little research on tourism development in Uzbekistan exists to date. This study therefore analyzes possible research topics and proposes a tourism research agenda for Uzbekistan. A mix of methods was used consisting of participant observation, semi-structured qualitative expert interviews and qualitative content anal- ysis. The results revealed a variety of research deficits in different areas, which could be synthesized into a total of ten research fields, which were clustered into three overarching areas, namely market research, management, and culture & environment. The subordi- nate research fields identified are Demand, Statistics, Potentials, Governance, Products, Infrastructure & Development, Marketing, Heritage & Nation-building, Sustainability as well as Peace & Conflict Prevention. A strategic research plan based on this tourism research agenda could help to foster a purposeful scientific debate. Tourism research in these fields has both the potential to investigate and compare theoretical issues in an unique context and to produce applied research results that can make a relevant contri- bution to tourism development in Uzbekistan.
This research project has been awarded as part of the research competition organized by Connect2Recover, which is a global initiative by the International Telecommunication Union (ITU) with the priority of reinforcing and strengthening the digital infrastructure and ecosystems of developing countries. Carried out by an international and transdisciplinary research consortium, the project sets out to analyze the prospects of digital federation and data sharing within the context of Botswana. Considering the country’s stage of economic and digital development, the project team identified Botswana’s smallholder agricultural sector as the most important area of digital transformation given the development need of the country’s primary sector.
Derived from semi-structured interviews, a focus group, as well as secondary research, the project team developed a digital transformation roadmap based on three development stages: (a) crowdfarming pilot, (b) crowdfarming marketplace, and (c) digital ecosystem for smallholder agriculture. Based on a detailed review of Botswana’s smallholder agriculture and the government’s digitalization strategy, the report envisions each phase, especially the pilot project, in terms of a minimal viable product. This is to consider the low level of digital penetration of Botswana’s primary sector, while providing an incentive to connect smallholders with consumers, traders, and retailers.
The project team has been successful in receiving commitment from actual smallholder farmers, the farmer association and government, as well as support for the idea of developing a crowdfarming marketplace as a novel production model and, eventually, a digital agriculture ecosystem for smallholder farmers, livestock producers, and agricultural technology companies and start-ups. The report is a proposal for a phase-one pilot project with the objective to advance smallholder agribusiness in Botswana.
Because process and product innovations are usually no longer sufficient to establish a company in the market or to generate a competitive advantage, Business Model Innovation is considered a powerful tool, especially for start-ups for which innovation is at the core of their business. Due to the complexity of this process, frameworks should help entrepreneurs with executing Business Model Innovation. However, theory and practice diverge. The aim of this paper is to identify the needs of a start-up regarding Business Model Innovation frameworks, underlining the importance of Business Model Innovation for start-ups as well as the relevance of a supporting framework. The research results aim to contribute to an ideal process for Business Model Innovation when applied to start-ups.
An IT-GRC approach in SME
(2022)
The digital transformation of business processes and the integration of IT systems leads to opportunities and risks for small and medium-sized enterprises (SMEs). Risks that can result in a lack of IT compliance. The purpose of this research-in-progress paper is to present the current state of a IT-Governance-Risk-Compliance (IT-GRC) research-project. First, the results of an already conducted literature research will be discussed, combined with qualitative interviews (expert survey) of persons close to IT compliance. In the context of this paper, a first design approach will be developed by selecting relevant existing frameworks and standards and the identification of SME-specific conditions. The first design is intended to contribute a further artefact conception of tailoring approaches and standards and the creation of a guidance.
Analyse der Nachhaltigkeit verschiedener Redevelopmentszenarien einer Unternehmensbestandsimmobilie
(2022)
Ziel dieser Arbeit ist es einen Beitrag dazu zu leisten, dass auch Argumente der Nachhaltigkeit in Investitions- und Projektentscheidungen der Immobilienbranche leichter einfließen können, indem sie besser messbar gemacht werden, und somit an Einfluss gewinnen. Betrachtet werden sollen hierbei Entscheidungen zwischen verschiedenen Redevelopmentszenarien. Wann ergibt es mehr Sinn, eine bestehende Immobilie zu modernisieren? Wann lohnt sich ein Neubau eher? Zur Beantwortung dieser Fragen soll im Rahmen dieser Arbeit eine Entscheidungshilfe entwickelt werden. Konkret soll sich diese Entscheidungshilfe auf verschiedene Redevelopmentszenarien von speziell denjenigen Bürogebäuden beziehen, welche Teil von Unternehmensimmobilien sind. Entwickelt wird die Entscheidungshilfe aus einem bestehenden „Nachhaltigkeitsrating zur Bewertung der Zukunftsfähigkeit von Immobilien“, welches von Sarah Ok Kyu Strunk im Rahmen ihrer Dissertation an der Universität Stuttgart erstellt wurde. Die Besonderheit dieses Ratings liegt darin, dass es verschiedene nachhaltigkeitsrelevante Standortund Gebäudeeigenschaften im Hinblick auf ihr Wertentwicklungsrisiko betrachtet. Dies bedeutet, dass es eine Übersicht über diejenigen Nachhaltigkeitsmerkmale einer Immobilie gibt, welche nicht nur nachhaltigkeitsrelevant sind, sondern gleichzeitig maßgeblichen Einfluss auf das wirtschaftliche Risiko und somit die Wirtschaftlichkeit der Projektentwicklung haben. Ausgelegt ist das Rating auf die Betrachtung einzelner deutscher Büroimmobilien jeglichen Alters. Im Rahmen dieser Arbeit soll hieraus eine Entscheidungshilfe für Büroimmobilien als Teil von Unternehmensimmobilien entwickelt werden, bei welcher mehrere Redevelopmentszenarien verglichen werden können, um schließlich festzustellen, welches Szenario das geringere Wertentwicklungsrisiko mit sich bringt. Das Ergebnis hieraus soll nicht die abschließende Entscheidung zwischen den beiden Redevelopmentszenarien darstellen. Es soll vielmehr neben anderen Vergleichen, beispielsweise dem Vergleich der Wirtschaftlichkeit oder der Nachhaltigkeit der Bausubstanz der beiden Szenarien, eine stichhaltige Grundlage für eine wirtschaftlich und nachhaltig sinnvolle Entscheidung bieten.
Das erfolgreiche Gestalten von Organisationen setzt die systematische Analyse ihrer Prozesse voraus. Das gilt auch und insbesondere für kleine und mittelgroße Unternehmen (KMU). Die praktische Durchführung solcher in KMU ist jedoch mit besonderen Herausforderungen verbunden, die in der vorhandenen Literatur bislang kaum reflektiert werden. In diesem Beitrag werden Erfahrungen aus 20 in KMU durchgeführten Prozessanalysen geteilt. Entlang der Prozessphasen werden unterschiedliche Gestaltungsmöglichkeiten vorgestellt und ihre spezifischen Vor- und Nachteile bei der praktischen Anwendung in KMU identifiziert. Der Beitrag unterstreicht die Relevanz von Prozessanalysen in KMU und befähigt zugleich zu ihrer Durchführung.
Wie gehen mittelständische Unternehmen mit internationaler Geschäftstätigkeit mit Compliance-Risiken um? Wie gelingt das Risikomanagement spezifischer Herausforderungen der Regelkonformität in Wachstumsländern, die aus Compliance-Gesichtspunkten als Hochrisikoländer eingestuft werden? Und was beschäftigt dabei Compliance-Officer im Mittelstand?
Diesen Fragen widmete sich ein anwendungsorientiertes Forschungsprojekt am Konstanz Institut für Corporate Governance.
Die nachfolgende Publikation stellt die zentralen Studienergebnisse vor und fokussiert dabei auf Herausforderungen und Lösungen für das Compliance- und Integrity Management.
oday many scientific works are using deep learning algorithms and time series, which can detect physiological events of interest. In sleep medicine, this is particularly relevant in detecting sleep apnea, specifically in detecting obstructive sleep apnea events. Deep learning algorithms with different architectures are used to achieve decent results in accuracy, sensitivity, etc. Although there are models that can reliably determine apnea and hypopnea events, another essential aspect to consider is the explainability of these models, i.e., why a model makes a particular decision. Another critical factor is how these deep learning models determine how severe obstructive sleep apnea is in patients based on the apnea-hypopnea index (AHI). Deep learning models trained by two approaches for AHI determination are exposed in this work. Approaches vary depending on the data format the models are fed: full-time series and window-based time series.
Home health applications have evolved over the last few decades. Assistive systems such as a data platform in connection with health devices can allow for health-related data to be automatically transmitted to a database. However, there remain significant challenges concerning intermodular communication. Central among them is the challenge of achieving interoperability, the ability of devices to communicate and share data with each other. A major goal of this project was to extend an existing data platform (COMES®) and establish working interoperability by connecting assistive devices with differing approaches. We describe this process for a sleep monitoring and a physical exercise device. Furthermore, we aimed to test this setup and the implementation with a data platform in both a laboratory and an in-home setting with 11 elderly participants. The platform modification was realized, and the relevant changes were made so that the incoming data could be processed by the data platform, as well as visually displayed in real-time. Data was recorded by the respective device and transmitted into the data server with minor disruptions. Our observations affirmed that difficulties and data loss are far more likely to occur with increasing technical complexity, in the event of instable internet connection, or when the device setup requires (elderly) subjects to take specific steps for proper functioning. We emphasize the importance for tests and evaluations of home health technologies in real-life circumstances.
In dieser Arbeit wird die Ausgangssituation der klimabezogenen Stadtplanung in Konstanz in den Bereichen Wasser, Wärme und Vegetation im Hinblick auf die Anpassung an den Klimawandel untersucht. Diese dient als eine Grundlage für das Projekt CoKLIMAx.
Ziel dieses Projektes ist es, eine einfache Toolbox zu entwickeln, die Kommunen befähigt, mit Hilfe von Satelliten- und in-situ-Daten Klimaanalysen, erforderliche Gewichtungen und späteres Monitoring selbst durchführen zu können, um Entscheidungen für auf die langfristige Stadtentwicklung treffen zu können.
Für die Feststellung der Ausgangssituation in Konstanz wurden Mitarbeiter der Stadtverwaltung Konstanz befragt, ein Planungsprozess für die Klimaanpassung künftiger Bauprojekte entwickelt und eine Stakeholderidentifikation erstellt.
Zu Beginn der Arbeit werden die Ursachen für den Klimawandel und seine Auswirkungen erörtert, Anpassungsbeispiele anderer Städte betrachtet und die Funktionsprinzipien der verwendeten Satelliten und die Dienste des Copernicus-Programms erklärt.
Der Gegenstand dieser Bachelorarbeit ist die automatisierte Extraktion von Polygonzügen anhand eines Grundrissbildes. Diese Polygonzüge sollen die Räumlichkeiten wiedergeben. In dieser Bachelorarbeit wurde daher ein Algorithmus für die Grundrissbildverarbeitung mittels Python entwickelt und implementiert. Zuerst wird ein Grundrissbild bereinigt, d. h. es werden unerwünschte Bildstrukturen verwaschen. Mithilfe des Canny-Kantendetektors werden anschließend die Kanten detektiert. Danach werden die Ecken im Grundrissbild via Harris-Eckendetektor lokalisiert. Um die Ecken sinnvoll zu verbinden, wird eine abgewandelte Form des Dijkstra Algorithmus herangezogen. Die daraus gewonnen Daten dienen zur Erstellung der Polygonzüge, welche für die Simulation von pFlow benötigt werden. Der entwickelte Algorithmus eignet sich insbesondere für klare und simple Grundrissbilder.
In diesem Aufsatz, der im Rahmen eines Freistellungssemesters entstanden ist, werden technische, umwelttechnische, ethische und rechtliche Themen zum Autonomen Fahren im Hinblick auf die Umsetzung in der Lehre betrachtet. Curricula zum Autonomen Fahren der Kettering University und Udacity werden vorgestellt.
The trajectory tracking problem for a fully-actuated real-scaled surface vessel is addressed in this paper by designing a backstepping controller with a multivariable integral action, considering the thruster allocation problem. The performance and robustness of this controller are evaluated in simulation, taking into account environmental disturbance forces and modeling mismatch, using a docking maneuver as a reference trajectory. Furthermore, a comparison between the backstepping controller and a nonlinear position PID-Control with flatness based-feedforward is also analyzed.
Die vorliegende Studie analysiert die Barrierefreiheit der
Stadt Konstanz im Hinblick auf Angebote für und Nachfrage von Touristinnen und Touristen. Die Datenerhebung basierte auf einem Methodenmix aus Interviews und Umfragen von Probanden und Probandinnen mit Behinderungen und zuständigen Akteurinnen und Akteuren in der Stadtplanung sowie Begehungen vor Ort. Als theoretische Grundlage wird das Modell der Unabhängigkeit nach
Nosek and Fuhrer (1992) verwendet. Die Untersuchung zeigt, dass der Bedarf an barrierefreien Angeboten sehr divers ist und die Umsetzung im Sinne eines Universal Design durch die zunehmende Nachfrage zentral. Die Analyse des Tourismusraum Konstanz zeigt Schwachpunkte und Stärken, mit denen sich Implikationen für andere Tourismusregionen ableiten lassen.
Im Sommersemester 2022 habe ich laufende und neue Forschungsprojekte sowohl national wie auch international vorangetrieben. Schwerpunktmäßig wurde die international etablierte Global Sanctions Data Base (GSDB) in Kooperation mit Forschern aus den USA und Österreich aktualisiert und in Form einer Forschungsarbeit der Forschungsgemeinschaft bekannt gemacht. Aufgrund der erarbeiteten Expertise habe ich zahlreiche Vorträge und Interviews in Medien zu Sanktionen und deren ökonomische Wirkung gegeben. Darüber hinaus wurde ein Buchkapitel zu Sanktionen in Kooperation mit internationalen Wissenschaftlern verfasst. Ferner wurde ein neues Forschungsprojekt in Kooperation mit einem regionalen Unternehmen zur Entwicklung eines Prozesses für die THG-Bilanzierung initiiert. Zwei wissenschaftliche Publikationen (peer-reviewed) wurden finalisiert. Ferner wurden 2 neue wissenschaftliche Forschungsprojekte mit internationalen Wissenschaftlern initiiert und die Ergebnisse in Arbeitspapieren veröffentlicht. Die zugrundeliegenden Manuskripte wurden in peer-reviewed Zeitschriften eingereicht. In Kooperation mit der Universität Konstanz wurde ein Schülertag für Gymnasiasten organisiert, um die Bedeutung von Wirtschaftspolitik den Schülern näher zu bringen.
Um im Angesicht der Klimakrise eine lebenswerte Zukunft zu sichern, brauchen wir einen grundlegenden und raschen gesellschaftlichen Wandel. Wirksame Klimakommunikation kann eine wichtige Rolle spielen, um das für diesen Wandel erforderliche gesamtgesellschaftliche Engagement zu fördern.
Im Forschungssemester wurden drei Ziele verfolgt: Erstens der Auf- und Ausbau des eigenen Kenntnisstands zur Klimakommunikation, zweitens das Kennenlernen der Arbeitsmethoden und -kultur des gastgebenden Think-Tanks Climate Outreach sowie drittens die Erstellung eines oder mehrerer für die Nachhaltigkeitstransformation nützlicher ‚Produkte‘ als Ergebnis des Forschungsaufenthalts. Alle drei Ziele konnten erreicht werden. Dabei bilden ein Working Paper, ein 4-Seiter für Praktiker sowie mehrere Artikel und ein Buchkapitel die Arbeitsergebnisse für andere nachvollziehbar und anwendbar ab (siehe Liste entstandener Veröffentlichungen in diesem Bericht).
Inhaltlich war die Kernerkenntnis, dass Menschen sich ihre Meinung zum Klima und der eigenen Rolle in der Transformation nicht in erster Linie durch mehr und bessere Informationen bilden, sondern durch Geschichten, die ihre Werte ansprechen, die von Menschen erzählt werden, denen sie vertrauen, und die durch die Überzeugungen und das Verhalten der Menschen in ihrem Umfeld bestätigt werden. Klimakommunikation sollte also neben der rationalen Vermittlung von Fakten auch unsere emotionale Seite bedienen und beispielsweise zeigen, wie sich soziale Normen verändern und Klimaschutzhandeln zum neuen Normal wird.
This policy brief presents the possibilities of using big data analytics for safe, decarbonised and climate-resilient infrastructure. The policy brief focuses on current constraints and limitations to applying big data analytics to the infrastructure ecosystem and presents several examples and best practices for different infrastructure sectors and at different policy levels (national, municipal) to highlight recommendations and policy requirements needed for deep digital transformation and sustainable solutions in infrastructure planning and delivery.
Die Frage „Wozu braucht man das?“ vonseiten der Studierenden oder Aussagen wie „Das habe ich im Beruf später nie mehr benötigt.“ von ehemaligen Studierenden ist den meisten Mathematikdozierenden sehr vertraut. Im Projekt BiLeSA wird dem Wunsch nach Integration von Praxisnähe im Mathematikunterricht mithilfe einer Smartphone-App, welche ausgewählte Themen in der Mathematik anhand von digitalen Bildern sichtbar macht, umgesetzt. Bei den ausgewählten Themen handelt es sich um (affin) lineare Abbildungen, Ableitungen in höheren Raumdimensionen und Potenzen von Komplexen Zahlen. Die Konzeptionierung des Lernobjekts erfolgte mit dem Design Based Research (DBR) Ansatz, welches im Basisprojekt des IBH-Labs „Seamless Learning“ konzipiert und entwickelt wurde.
Zur Bewertung von Strategien und Handlungsoptionen im Themenfeld Bioökonomie
ist es naheliegend, eine naturinspirierte Bewertungsmethodik zu verwenden.
Dieser Beitrag stellt daher den biokybernetischen Ansatz nach Frederic Vester als
Methodik in den Mittelpunkt, um nachhaltigkeitskonforme Passungskriterien für
bioökonomische Innovationen und Konzepte zu beschreiben sowie insbesondere
die systemischen Wechselwirkungen und damit die Komplexität dieses Themenfeldes
zu erfassen. So wird auch die Ambivalenz von Innovationen im Themen- und
Handlungsfeld Bioökonomie thematisiert. Letztlich können mit diesem Ansatz
die prinzipiellen Voraussetzungen für nachhaltigkeitsorientierte bioökonomische
Innovationen in Richtung Erneuerbarkeit, Zirkularität, Effizienz, ökologische Verträglichkeit und Klimaneutralität geklärt werden.
Botenstoffe für Innovationen
(2022)
Business Partner Compliance
(2022)
Bürgerliches Recht
(2022)
Die nun vorliegende vollständig überarbeitete und aktualisierte zehnte Auflage des bewährten Lehrbuches deckt die wesentlichen Inhalte des zivilrechtlichen Lehrstoffes ab. Es werden in kompakter Form der Allgemeine Teil des BGB, das (Allgemeine und Besondere) Schuldrecht sowie das Sachenrecht dargestellt. Vervollständigt wird dieses Buch mit einem abschließenden Kapitel zum Zivilprozessrecht. Geschult werden das Verständnis für die Strukturen und Zusammenhänge im Bürgerlichen Recht und das Verständnis für die Verbindungen mit dem Zivilprozessrecht. Eine Vielzahl von Beispielen aus der Praxis, einprägsame Illustrationen, zahlreiche Schemata und Fälle mit Lösungsvorschlägen ermöglichen damit gleichzeitig auch ein anwendungsorientiertes bzw. fallorientiertes Lernen. Seine inhaltliche Kompaktheit macht es so zu einem idealen studienbegleitenden Lehrbuch für Studierende an Universitäten, Hochschulen, Berufsakademien und anderen Bildungseinrichtungen.
A key objective of this research is to take a more detailed look at a central aspect of resilience in small and medium-sized enterprises (SMEs). A literature review and expert interviews were used to investigate which factors have an impact on the innovative capacity of start-ups and whether these can also be adapted by SMEs. First of all, it must be stated that there are considerable structural and process-related differences between start-ups and SMEs. These can considerably inhibit cooperation between the two forms of enterprise. However, in the same context, success factors and issues in the start-up sector could also be identified that can improve cooperation with SMEs. These and other findings are then discussed in both an economic and an academic context. This article was written as part of the research activities of the Smart Services Competence Centre (proper name: Kompetenzzentrum Smart Services), a central contact point for all questions in the area of smart service digitalization in Baden-Wuerttemberg. Here, companies can obtain information about various digital technologies and take advantage of various measures for the development of new ideas and innovative services (Kompetenzzentrum Smart Services BW: Über das Kompetenzzentrum, 2021).
Automotive computing applications like AI databases, ADAS, and advanced infotainment systems have a huge need for persistent memory. This trend requires NAND flash memories designed for extreme automotive environments. However, the error probability of NAND flash memories has increased in recent years due to higher memory density and production tolerances. Hence, strong error correction coding is needed to meet automotive storage requirements. Many errors can be corrected by soft decoding algorithms. However, soft decoding is very resource-intensive and should be avoided when possible. NAND flash memories are organized in pages, and the error correction codes are usually encoded page-wise to reduce the latency of random reads. This page-wise encoding does not reach the maximum achievable capacity. Reading soft information increases the channel capacity but at the cost of higher latency and power consumption. In this work, we consider cell-wise encoding, which also increases the capacity compared to page-wise encoding. We analyze the cell-wise processing of data in triple-level cell (TLC) NAND flash and show the performance gain when using Low-Density Parity-Check (LDPC) codes. In addition, we investigate a coding approach with page-wise encoding and cell-wise reading.
Chinesische Studierende in der wissenschaftlichen Auseinandersetzungskultur an deutschen Hochschulen
(2022)
Die zunehmende internationale Vernetzung der akademischen Welt, die sich in den
aktuellen Internationalisierungsbemühungen deutscher Hochschulen widerspiegelt, erfordert eine Auseinandersetzung mit interkulturellen Aspekten der Hochschuldidaktik. Unterschiedliche Lernstile und Rollenerwartungen an Lehrende und Studierende beeinflussen die gegenseitige Wahrnehmung und den Studienerfolg. Der Beitrag reflektiert Erfahrungen deutscher/westlicher Lehrender und chinesischer Studierender: Aus verschiedenen Perspektiven und auf unterschiedlichen Ebenen werden Diskrepanzen zwischen Erwartungen und tatsächlichen Gegebenheiten aufgezeigt und im Kontext unterschiedlicher Lerntraditionen erklärt. Dabei stehen die Anforderungen an die Lehrenden als den zentralen Akteur*innen einer erfolgreichen Wissensvermittlung im Vordergrund. Im internationalen Kontext sind ihre interkulturellen Kompetenzen ähnlich wichtig wie ihre Fachkompetenzen. Die chinesische Lerntradition erschwert chinesischen Studierenden einen direkten Anschluss an die Studienkultur im deutschen Hochschulsystem. Zu dem Hemmnis, in einer Fremdsprache zu studieren, kommt die Schwierigkeit, Debattenkultur und Wissenschaftsstreit als angemessene Auseinandersetzungsformen zu verstehen. Der direkte, offene und häufig nur aus westlicher Sicht als objektiv empfundene Umgang mit Themen kann aufgrund unterschiedlicher kultureller Prägung dazu beitragen, dass das Studium in Deutschland als anstrengend und befremdlich empfunden wird. In diesem Beitrag werden erfahrungsbasierte Überlegungen geteilt, wie chinesische Studierende an die Debattenkultur an deutschen Hochschulen herangeführt werden können. Der Beitrag endet mit Hinweisen und guidelines für deutsche Lehrende im Umgang mit chinesischen Studierenden.
The citizen-centered health platform project is intended to provide a platform that can be used in EU cross-border regions, where social and economic exchange occurs across national borders. The overriding challenges are: (a) social: improving citizen-centered health and care provision; (b) technical: providing a digital platform for networking citizens, service providers, and municipal actors; (c) economic: developing long-term successful (sustainable) business models/value chains. The platform should strengthen and expand existing networks and establish new regional networks. Each network addresses particular challenges and apply them in a region-specific manner. Here, the national boundary conditions and the interregional needs play an essential role. These objectives require sufficient participation of civil society representatives. Furthermore, the platform will establish an overarching, sustainable, and knowledge-based network of health experts. The platform is to be jointly developed and implemented in the regions and follow an open-access approach. Therefore, synergies will be shared more quickly, strengthening competencies and competitiveness. In addition to practice partners, scientific and municipal institutions and SMEs are involved. The actors thus contribute to scientific performance, innovative strength, and resilience.
Code-based cryptosystems are promising candidates for post-quantum cryptography. Recently, generalized concatenated codes over Gaussian and Eisenstein integers were proposed for those systems. For a channel model with errors of restricted weight, those q-ary codes lead to high error correction capabilities. Hence, these codes achieve high work factors for information set decoding attacks. In this work, we adapt this concept to codes for the weight-one error channel, i.e., a binary channel model where at most one bit-error occurs in each block of m bits. We also propose a low complexity decoding algorithm for the proposed codes. Compared to codes over Gaussian and Eisenstein integers, these codes achieve higher minimum Hamming distances for the dual codes of the inner component codes. This property increases the work factor for a structural attack on concatenated codes leading to higher overall security. For comparable security, the key size for the proposed code construction is significantly smaller than for the classic McEliece scheme based on Goppa codes.
Large-scale quantum computers threaten today's public-key cryptosystems. The code-based McEliece and Niederreiter cryptosystems are among the most promising candidates for post-quantum cryptography. Recently, a new class of q-ary product codes over Gaussian integers together with an efficient decoding algorithm were proposed for the McEliece cryptosystems. It was shown that these codes achieve a higher work factor for information-set decoding attacks than maximum distance separable (MDS) codes with comparable length and dimension. In this work, we adapt this q-ary product code construction to codes over Eisenstein integers. We propose a new syndrome decoding method which is applicable for Niederreiter cryptosystems. The code parameters and work factors for information-set decoding are comparable to codes over Gaussian integers. Hence, the new construction is not favorable for the McEliece system. Nevertheless, it is beneficial for the Niederreiter system, where it achieves larger message lengths. While the Niederreiter and McEliece systems have the same level of security, the Niederreiter system can be advantageous for some applications, e.g., it enables digital signatures. The proposed coding scheme is interesting for lightweight Niederreiter cryptosystems and embedded security due to the short code lengths and low decoding complexity.
CoKLIMAx
(2022)
This paper presents a systematic comparison of different advanced approaches for motion prediction of vessels for docking scenarios. Therefore, a conventional nonlinear gray-box-model, its extension to a hybrid model using an additional regression neural network (RNN) and a black-box-model only based on a RNN are compared. The optimal hyperparameters are found by grid search. The training and validation data for the different models is collected in full-scale experiments using the solar research vessel Solgenia. The performances of the different prediction models are compared in full-scale scenarios. %To use the investigated approaches for controller design, a general optimal control problem containing the advanced models is described. These can improve advanced control strategies e.g., nonlinear model predictive control (NMPC) or reinforcement learning (RL). This paper explores the question of what the advantages and disadvantages of the different presented prediction approaches are and how they can be used to improve the docking behavior of a vessel.
Welche Kompetenzen brauchen Führungskräfte, damit der Ansatz Compliance und Integrity als Führungsaufgabe in Organisationen verfängt? Und wie lassen sich diese systematisch nutzen und trainieren? Der Beitrag stellt den ersten Baustein eines am Konstanz Institut für Corporate Governance angesiedelten Forschungsprojekts vor, das darauf abzielt, bestehende Compliance-Systeme in Unternehmen praxistauglicher zu machen und die Wirksamkeit der Maßnahmen eines Compliance-Management-Systems (CMS) zu steigern.
Reed-Muller (RM) codes have recently regained some interest in the context of low latency communications and due to their relation to polar codes. RM codes can be constructed based on the Plotkin construction. In this work, we consider concatenated codes based on the Plotkin construction, where extended Bose-Chaudhuri-Hocquenghem (BCH) codes are used as component codes. This leads to improved code parameters compared to RM codes. Moreover, this construction is more flexible concerning the attainable code rates. Additionally, new soft-input decoding algorithms are proposed that exploit the recursive structure of the concatenation and the cyclic structure of the component codes. First, we consider the decoding of the cyclic component codes and propose a low complexity hybrid ordered statistics decoding algorithm. Next, this algorithm is applied to list decoding of the Plotkin construction. The proposed list decoding approach achieves near-maximum-likelihood performance for codes with medium lengths. The performance is comparable to state-of-the-art decoders, whereas the complexity is reduced.
Global agriculture will face major challenges in the future. In addition to the increasing demand for food due to constant population growth, the consequences of climate change will make it even more difficult to operate agriculture and supply people with food. In addition to further productivity increases in traditional agriculture, new concepts for sustainable and scalable food production are needed. Vertical farming offers a promising approach.
The aim of this project is to demonstrate how vertical farming can be used to ensure sustainable food production and how this concept can be applied in the pioneering Maun Science Park project in Botswana. In doing so, the Maun Science Park will address future challenges such as demographics, governance and climate change and become a best practice model for Botswana, the whole of Africa and the world. The country of Botswana grew to become one of the most prosperous countries in Africa in recent decades due to strong economic growth from mining. However, the population faces great challenges in the future; in addition to great social inequality, climate change threatens the country's overall supply.
With the help of a literature review and qualitative and quantitative interviews with stakeholders from Maun (Botswana), the potentials and challenges for vertical farming in Botswana could be identified and future measures for a possible realization could be derived. Basically, some challenges in Botswana are addressed by the technology, for example, Vertical Farming offers high food security through year-round production of food through the closed ecosystem and creates independence from current and future climatic conditions, poor conditions for traditional agriculture (e.g. infertile soils) and foreign imports. However, the main structural problems of agriculture in Botswana, such as the lack of infrastructure, know-how and policy support, are not addressed.
Botswana serves as a role model for other African countries due to its rapid development in recent decades. Since the country is sparsely populated and a large part of the rural population depends on agriculture, especially livestock, this sector forms the backbone of the national economy. The digitization of this sector offers promising opportunities for economic growth and driving Botswana's evolution to a digital economy, while real value is being created for smallholder farmers. To support this process, an ITU research project made the key recommendation for the development of a digital crowdfarming tool and marketplace to create a digital ecosystem for smallholder agriculture. Within the research project, infrastructural challenges such as the creation of rural electricity supply and internet access, as well as the smallholders' need for remote monitoring, management, and better connectivity, were identified.
Based on the findings of the ITU research report, this bachelor's thesis aims to identify potential innovations for the digital development of smallholder agriculture in Botswana and to conceptualize proposals to address the identified challenges and needs of smallholder farmers. To achieve this, solutions were developed through literature research, technology analysis and expert involvement. These included the design of a decentralized mini-grid for power supply, proposals to create internet access, and the graphic visualization of a conceptual app. The latter addresses smallholder farmers' needs for remote monitoring, market access, knowledge enhancement, and connection to colleagues, buyers, and investors.
The proposed solutions and developed concepts provide impulses for further research and can serve as a basis for an extended evaluation through further involvement of experts and stakeholders.
Unternehmen stehen heute vor der Herausforderung, dass eine klare Trennung von verpflichtenden Anforderungen und freiwilliger Verantwortungsübernahme nur noch schwer möglich ist. Haftungsvermeidung, Reputationsschutz sowie der Aufbau und die Sicherung von Vertrauenskapital in Kooperationsbeziehungen gehen Hand in Hand. Der Beitrag beleuchtet Corporate Compliance und Integrity Management als Gestaltungsansätze eines gezielten und integrierten Managements der Unternehmensverantwortung. Compliance ist dabei das Rückgrat, Integrity ihr Herz.
Wer schon einmal dicht gedrängt vor der Konzertbühne stand kann sich die aussichtslose Lage, wenn die Stimmung kippt und Panik aufkommt, gut vorstellen. Es ist sehr wichtig, Räume und Events, die zeitweise von sehr vielen Menschen aufgesucht werden, so zu gestalten und zu planen, dass maximale Sicherheit gewährleistet ist. Damit eine öffentliche Veranstaltung reibungslos verläuft ist eine gründliche Planung, also ein qualitativ hochwertiges Crowd Management unabdingbar.
The code-based McEliece cryptosystem is a promising candidate for post-quantum cryptography. The sender encodes a message, using a public scrambled generator matrix, and adds a random error vector. In this work, we consider q-ary codes and restrict the Lee weight of the added error symbols. This leads to an increased error correction capability and a larger work factor for information-set decoding attacks. In particular, we consider codes over an extension field and use the one-Lee error channel, which restricts the error values to Lee weight one. For this channel model, generalized concatenated codes can achieve high error correction capabilities. We discuss the decoding of those codes and the possible gain for decoding beyond the guaranteed error correction capability.
Outcomes with a natural order commonly occur in prediction problems and often the available input data are a mixture of complex data like images and tabular predictors. Deep Learning (DL) models are state-of-the-art for image classification tasks but frequently treat ordinal outcomes as unordered and lack interpretability. In contrast, classical ordinal regression models consider the outcome’s order and yield interpretable predictor effects but are limited to tabular data. We present ordinal neural network transformation models (ontrams), which unite DL with classical ordinal regression approaches. ontrams are a special case of transformation models and trade off flexibility and interpretability by additively decomposing the transformation function into terms for image and tabular data using jointly trained neural networks. The performance of the most flexible ontram is by definition equivalent to a standard multi-class DL model trained with cross-entropy while being faster in training when facing ordinal outcomes. Lastly, we discuss how to interpret model components for both tabular and image data on two publicly available datasets.
Deep Learning-based EEG Detection of Mental Alertness States from Drivers under Ethical Aspects
(2022)
One of the most critical factors for a successful road trip is a high degree of alertness while driving. Even a split second of inattention or sleepiness in a crucial moment, will make the difference between life and death. Several prestigious car manufacturers are currently pursuing the aim of automated drowsiness identification to resolve this problem. The path between neuro-scientific research in connection with artificial intelligence and the preservation of the dignity of human individual’s and its inviolability, is very narrow. The key contribution of this work is a system of data analysis for EEGs during a driving session, which draws on previous studies analyzing heart rate (ECG), brain waves (EEG), and eye function (EOG). The gathered data is hereby treated as sensitive as possible, taking ethical regulations into consideration. Obtaining evaluable signs of evolving exhaustion includes techniques that obtain sleeping stage frequencies, problematic are hereby the correlated interference’s in the signal. This research focuses on a processing chain for EEG band splitting that involves band-pass filtering, principal component analysis (PCA), independent component analysis (ICA) with automatic artefact severance, and fast fourier transformation (FFT). The classification is based on a step-by-step adaptive deep learning analysis that detects theta rhythms as a drowsiness predictor in the pre-processed data. It was possible to obtain an offline detection rate of 89% and an online detection rate of 73%. The method is linked to the simulated driving scenario for which it was developed. This leaves space for more optimization on laboratory methods and data collection during wakefulness-dependent operations.
There have been substantial research efforts for algorithms to improve continuous and automated assessment of various health-related questions in recent years. This paper addresses the deployment gap between those improving algorithms and their usability in care and mobile health applications. In practice, most algorithms require significant and founded technical knowledge to be deployed at home or support healthcare professionals. Therefore, the digital participation of persons in need of health care professionals lacks a usable interface to use the current technological advances. In this paper, we propose applying algorithms taken from research as web-based microservices following the common approach of a RESTful service to bridge the gap and make algorithms accessible to caregivers and patients without technical knowledge and extended hardware capabilities. We address implementation details, interpretation and realization of guidelines, and privacy concerns using our self-implemented example. Also, we address further usability guidelines and our approach to those.
Dieses Arbeitspapier behandelt den aktuellen Markt von Legal-Tech-Diensten in Deutschland und die rechtlichen Entwicklungen bezüglich der dort bestehenden Law-Tech-Branche. Ziel ist es dabei, anhand einer systematischen Analyse der beteiligten Marktkräfte, die Attraktivität der Legal-Tech-Branche einzuschätzen, um dem Leser dadurch eine Hilfestellung für die Strategiebildung innerhalb Law-Tech bezogener Unternehmen sowie Kanzleien zu bieten, denn die strategische Planung eines Unternehmens ist als Basis für den nachhaltigen Erfolg desselben unabdinglich.
Darüber hinaus zielt die Arbeit darauf ab, dem Leser einen Überblick über die rechtlichen Entwicklungen im Bereich von Legal-Tech sowie damit einhergehend ein Basiswissen über die Hintergründe der Gesetzgebung in Bezug auf die Law-Tech-Branche zu verschaffen.
Lidar sensors are widely used for environmental perception on autonomous robot vehicles (ARV). The field of view (FOV) of Lidar sensors can be reshaped by positioning plane mirrors in their vicinity. Mirror setups can especially improve the FOV for ground detection of ARVs with 2D-Lidar sensors. This paper presents an overview of several geometric designs and their strengths for certain vehicle types. Additionally, a new and easy-to-implement calibration procedure for setups of 2D-Lidar sensors with mirrors is presented to determine precise mirror orientations and positions, using a single flat calibration object with a pre-aligned simple fiducial marker. Measurement data from a prototype vehicle with a 2D-Lidar with a 2 m range using this new calibration procedure are presented. We show that the calibrated mirror orientations are accurate to less than 0.6° in this short range, which is a significant improvement over the orientation angles taken directly from the CAD. The accuracy of the point cloud data improved, and no significant decrease in distance noise was introduced. We deduced general guidelines for successful calibration setups using our method. In conclusion, a 2D-Lidar sensor and two plane mirrors calibrated with this method are a cost-effective and accurate way for robot engineers to improve the environmental perception of ARVs.
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.
Sleep is essential to existence, much like air, water, and food, as we spend nearly one-third of our time sleeping. Poor sleep quality or disturbed sleep causes daytime solemnity, which worsens daytime activities' mental and physical qualities and raises the risk of accidents. With advancements in sensor and communication technology, sleep monitoring is moving out of specialized clinics and into our everyday homes. It is possible to extract data from traditional overnight polysomnographic recordings using more basic tools and straightforward techniques. Ballistocardiogram is an unobtrusive, non-invasive, simple, and low-cost technique for measuring cardiorespiratory parameters. In this work, we present a sensor board interface to facilitate the communication between force sensitive resistor sensor and an embedded system to provide a high-performing prototype with an efficient signal-to-noise ratio. We have utilized a multi-physical-layer approach to locate each layer on top of another, yet supporting a low-cost, compact design with easy deployment under the bed frame.
Determination of accelerometer sensor position for respiration rate detection: Initial research
(2022)
Continuous monitoring of a patient's vital signs is essential in many chronic illnesses. The respiratory rate (RR) is one of the vital signs indicating breathing diseases. This article proposes the initial investigation for determining the accelerometric sensor position of a non-invasive and unobtrusive respiratory rate monitoring system. This research aims to determine the sensor position in relation to the patient, which can provide the most accurate values of the mentioned physiological parameter. In order to achieve the result, the particular system setup, including a mechanical sensor holder construction was used. The breathing signals from 5 participants were analyzed corresponding to the relaxed state. The main criterion for selecting a suitable sensor position was each patient's average acceleration amplitude excursion, which corresponds to the respiratory signal. As a result, we provided one more defined important parameter for the considered system, which was not determined before.
Die GIGA-Adaptionsmethode
(2022)
Der Aufsatz stellt eine schreibdidaktische Lehrmethode vor, die auf einem Cicero-Zitat über das Aptum, die Angemessenheit des Stils, basiert. Nach einigen psychologischen Vorüberlegungen zur Differenz von Sprech- und Schreibsituation wird das Zitat im Hochschulschreibunterricht in Hinblick auf die darin genannten Stilfaktoren analysiert. Die Ergebnisliste dient als Grundlage einer Methode, mit der sich die stilistische Passgenauigkeit von Texten aller Art stark verbessern lässt. Ziel ist es, eine möglicherweise schreibferne Klientel dazu zu motivieren, zu einem musterhaften, zweckdienlichen, sachgerechten und zielgruppenorientierten Schreiben zu finden.
Thema der Masterarbeit ist die Zukunft des Generalunternehmers. Auf Grund verschiedener Entwicklungen in den letzten Monaten und Jahren, wie zum Beispiel dem Auflösen der Generalunternehmungssparte des Schweizer Pioniers Steiner AG, stellt sich in der Baubranche die Frage, ob das Modell des GU zukunftsfähig ist oder ob in nächster Zeit ein disruptiver Prozess Einzug erhalten könnte.
Das primäre Ziel der Arbeit ist es, herauszufinden, ob für das Geschäftsmodell des Generalunternehmers bereits oder zukünftig eine Bedrohung besteht. Dabei wird die vergangene, derzeitige und zu-künftige Lage der Baubranche analysiert. Eine Rolle spielen dabei die betrieblichen Triebkräfte, Marktanalysen und Trends. Weiterhin sollen verschiedene Trends und Innovationen in der Baubranche er-mittelt, sowie den hieraus entstehenden Einfluss für den Generalunternehmer abgeschätzt werden. Zusätzlich soll ein Analysetool entworfen werden, mit Hilfe dessen man in Zukunft schnell, einheitlich und verlässlich Trends und Innovationen analysieren und bewerten kann.
Zuerst wird das Geschäftsmodell des Generalunternehmers erläutert. Hierbei wird unter anderem die Wertschöpfung des Generalunternehmers behandelt. Danach werden die Five Forces nach Porter betrachtet. Weiterhin wird die Rolle der Unternehmenskultur hinsichtlich ihres Einflusses auf den Betriebserfolg untersucht. Im darauffolgenden Kapitel geht es um die vergangene, derzeitige und kurzfristige Entwicklung der Baubranche in Europa. Im abschließenden Kapitel werden verschiedene Trends, die das Generalunternehmer Modell betreffen, ermittelt. Zu guter Letzt wird aufgezeigt, wie wichtig Trendanalysen für die langfristige Zukunft von Generalunternehmern sind. Außerdem wird ein Analysetool erstellt und an den Trends BIM und Nachhaltigkeit angewendet.
Das Ergebnis der Masterarbeit zeigt, dass das Modell des Generalunternehmers im Vergleich zur über-geordneten Branche derzeit nicht wesentlicher bedroht ist. Der stetige Zuwachs der Inanspruchnahme von Dienstleistungen und der steigende Fachkräftemangel in der ganzen Baubranche sind Indikatoren, die die Attraktivität des GU Modells auf dem Markt anheben. Termin- Kosten- und Qualitätsrisiken liegen beim GU aufgrund des Fachkräftemangels und steigender Materialpreise in der Baubranche. Die Digitalisierungstrends bieten für die Baubranche und somit auch für den GU neue Möglichkeiten für produktivere Projektabwicklungen. Sie dienen damit mehr als Werkzeug denn als Ersatz für das GU Modell. Die Lieferengpässe und die Bauteuerungen beeinträchtigen derzeitige und zukünftige Projekte branchenübergreifend. Abhilfe könnte hier die Mietung von Hallen bzw. Lagerflächen leisten, um das Material frühzeitig zu bestellen und zu lagern. Einzig neue Vertragsgestaltungen, wie sie zum Teil schon in England, Australien und den USA angewendet werden, können eine Bedrohung für das GU-Modell darstellen. Da in diesen Verträgen eine Kernkompetenz des GU, die Koordination zwischen den Ge-werken, durch die Kooperation zwischen den Gewerken, bedroht wird. Jedoch sträuben sich bislang die Planer und die Bauherren dagegen. Der Baubranche werden allgemein stabile Prognosen mit leichtem Umsatzplus zugesagt. Aus Sicht des Marktes besteht somit vorerst keine Gefahr für das GU Modell. Um den Einfluss von Trends und Entwicklungen auf das GU Modell anhand verschiedener Indikatoren einschätzen zu können, wurde ein Analysetool entwickelt, damit auch zukünftig der Einfluss von Neuerungen auf den GU Markt abgeleitet werden kann. Bei der Analyse der Trends spielt vor allem die Beschaffung von verlässlichen Informationen eine tragende Rolle. Die Einsatzgebiete von Trendanalysen sind in einem Unternehmen sehr vielfältig. Das Ergebnis der untersuchten Trends BIM und Nachhaltigkeit hat ergeben, dass diese eher Chancen anstatt Risiken für die Baubranche und somit auch für das GU Modell darstellen. Die allgemeine Umfrage zur Bedrohung des Geschäftsmodells GU hat ergeben, dass aus Sicht der Probanden eine mittlere Bedrohung vorliegt. Umfragewerte sind hinsichtlich ihrer Subjektivität und der aktuellen durch Krisen bestimmten Lage jedoch immer hinsichtlich Ihrer Aussagekraft in Kontext zu setzen.
Docking Control of a Fully-Actuated Autonomous Vessel using Model Predictive Path Integral Control
(2022)
This paper presents the docking control of an autonomous vessel using the nonlinear Model Predictive Path Integral (MPPI) approach. This algorithm is based on a path integral over stochastic trajectories and can be parallelized easily. The controller parameters are tuned offline using knowledge of the system and simulations, including nonlinear state and disturbance observer. The cost function implicitly contains information regarding the surrounding of the docking position. This approach allows continuous optimization of the trajectory with respect to the system state, disturbance state and actuator dynamics. The control strategy has been tested in full-scale experiments using the solar research vessel Solgenia. The investigated MPPI controller has demonstrated excellent performance in both, simulation and real-world experiments. This paper addresses the question of how the MPPI algorithm can be applied to dock a fully-actuated vessel and what benefits its application achieves.
In the last decade, both sustainability (Green &
Blue Economies) and business models for sustainability
(BMfS) have increased in importance. Social life cycle
sustainability assessment has not fully achieved goal,
mainly because sustainability‐oriented business is very
complex and dynamic. System Dynamics (SD) is a powerful
methodology and computer simulation modeling technique
for framing, understanding and discussing complex issues
and problems. This paper responds to the urgent need for
a new business model by presenting a concept for dynamic
business modeling for sustainability using system dynamics.
The paper illustrates the key operating principles through
an application from the smartphone industry with help
from STELLA® software for simulation. Simulations
suggest that dynamic business modeling for sustainability
may contribute to sustainable business model research and
practice by introducing a systemic design tool that frames
environmental, social, and economic drivers of value
generation into a dynamic business model causal feedback
structure, therefore overcoming shortcomings of current
business models when applied to complex systems.
In tomato drying, degradation in final quality may occur based on the drying method used and predrying preparation. Hence, this research was conducted to evaluate the effect of different predrying treatments on physicochemical quality and drying kinetics of twin-layer-solar-tunnel-dried tomato slices. During the experimental work, tomato slices of var. Galilea were used. As predrying treatments, 0.5% calcium chloride (CaCl2), 0.5% ascorbic acid (C6H8O6), 0.5% citric acid (C6H8O7), and 0.5% sodium chloride (NaCl) were used. The tomato samples were sliced to 5 mm thickness, socked in the pretreatments for ten minutes, and dried in a twin layer solar tunnel dryer under the weather conditions of Jimma, Ethiopia. Untreated samples were used as control. The moisture losses from the samples were monitored by weighing samples at 2 h interval from each treatment. SAS statistical software version 9.2 was used for analyzing data on the physicochemical quality of tomato slices in CRD with three replications. From the experimental result, it was observed that dried tomato slices pretreated with 0.5% ascorbic acid gave the best retention of vitamin C and total phenolic content with a high sugar/acid ratio. Better retention of lycopene and fast drying were observed in dried tomato slices pretreated with 0.5% sodium chloride, and pretreating tomatoes with 0.5% citric acid resulted in better color values than the other treatments. Compared to the control, pretreating significantly preserved the overall quality of dried tomato slices and increased the moisture removal rate in the twin layer solar tunnel dryer.
For some years, universities in countries where the first language is not English choose English as the medium of instruction. In German universities, instruction in German is still the dominant form, which makes university study in Germany less accessible to international students. To attract international students and to improve career prospects for home students, many German universities offer programmes taught in English or in a combination of German and English. It is widely expected that the implementation of EMI-programmes leads to improvements in English language proficiency (ELP). However, it has emerged that substantial gains in ELP in EMI programmes will only occur as the result of content and language integrated learning.
Purpose
The goal of this research survey was to propose an entrepreneurship education model for students in higher education institutions.
Methodology
A questionnaire was distributed to 246 randomly sampled students at the Universitas Negeri Jakarta. The data was analyzed through Structural Equation Modeling to study the variables of entrepreneurship education for higher education students and examine whether it can be predicted by the university leadership as a facilitator of entrepreneurial culture, university departments as promoters of entrepreneurial skills, and university research as an incubator of local business
development.
Findings
The results show that university leadership as a facilitator of entrepreneurial culture is supported by the university leadership’s fostering a culture of entrepreneurial thinking. It was also evident that the university placed sufficient emphasis on entrepreneurial education, and it successfully motivated lecturers to embrace entrepreneurship education, and students to embrace entrepreneurship education. The results also indicated that university departments acted as promoters of entrepreneurial skills and stimulated students to attain sufficient entrepreneurial skills during their university education. Lastly, the university research also proved as an incubator of local business development and was found influenced by the university conducting research projects with local
private sector businesses and supporting graduates planning to launch start-ups.
Implications to Research and Practice
The survey results will provide valuable policy insights to improve entrepreneurship education. The university faculty and students would have opportunities to gain practical experience in local private sector businesses. The model of entrepreneurship education proposed herein can be applied for higher education students.
Der Urban-Heat-Island-Effekt in Städten wird sich, angetrieben durch den globalen Klimawandel, weiter verstärken. Dem können städtebauliche Maßnahmen mildernd entgegenwirken.
Aus diesem Grund soll in dieser Bachelorarbeit im Rahmen des CoKLIMAx-Projekts eine Maßnahmentoolbox für resiliente Stadtplanung erstellt werden. Im Fokusbereich Wärme werden Maßnahmen näher betrachtet, die dazu beitragen können, Städte bezüglich zu erwartender vermehrter Hitzeereignisse zukünftig klimaresilienter zu gestalten.
Ziel dieser Arbeit ist die Zusammenstellung ausgewählter, konkreter Hitze-Resilienz-Maßnahmen für den städtischen Raum in einer Maßnahmentoolbox. Mithilfe dieser Toolbox sollen Möglichkeiten aufgezeigt werden, die Auswirkungen von Hitzeextremereignissen auf den städtischen Raum durch städtebauliche Maßnahmen zu minimieren beziehungsweise zu vermeiden.
Adressaten sollen in erster Linie Behörden auf kommunaler Ebene sein. Diese sollen bezüglich zunehmender Hitzeextremereignisse und ihrer negativen Auswirkungen auf Mensch, Wirtschaft sowie Gebäude und Infrastruktur, besser vorbereitet bzw. handlungsfähiger gemacht werden.
Es wird über die Erfahrungen an der Universtität Limerick und zum Klimaschutz in Irland im Zuge des Freistellungs- und Forschungssemester im WS 2021/22 berichtet. Der Aufenthalt konnte trotz Pandemie erfolgreich durchgeführt werden. Neben den Erfahrungen zu Organisation und Lehre an der UL wird über die Möglichkeiten zu weiteren Kooperation der HTWG mit UL berichtet. In einem zweiten Teil wird der Weg und Beitrag Irlands zu mehr Klimaschutz beschrieben. Hier fließen zahlreiche persönliche Recherchen, Besuche und Erfahrungen des Forschungsaufenthaltes ein.
The growing error rates of triple-level cell (TLC) and quadruple-level cell (QLC) NAND flash memories have led to the application of error correction coding with soft-input decoding techniques in flash-based storage systems. Typically, flash memory is organized in pages where the individual bits per cell are assigned to different pages and different codewords of the error-correcting code. This page-wise encoding minimizes the read latency with hard-input decoding. To increase the decoding capability, soft-input decoding is used eventually due to the aging of the cells. This soft-decoding requires multiple read operations. Hence, the soft-read operations reduce the achievable throughput, and increase the read latency and power consumption. In this work, we investigate a different encoding and decoding approach that improves the error correction performance without increasing the number of reference voltages. We consider TLC and QLC flashes where all bits are jointly encoded using a Gray labeling. This cell-wise encoding improves the achievable channel capacity compared with independent page-wise encoding. Errors with cell-wise read operations typically result in a single erroneous bit per cell. We present a coding approach based on generalized concatenated codes that utilizes this property.
The scoring of sleep stages is an essential part of sleep studies. The main objective of this research is to provide an algorithm for the automatic classification of sleep stages using signals that may be obtained in a non-obtrusive way. After reviewing the relevant research, the authors selected a multinomial logistic regression as the basis for their approach. Several parameters were derived from movement and breathing signals, and their combinations were investigated to develop an accurate and stable algorithm. The algorithm was implemented to produce successful results: the accuracy of the recognition of Wake/NREM/REM stages is equal to 73%, with Cohen's kappa of 0.44 for the analyzed 19324 sleep epochs of 30 seconds each. This approach has the advantage of using the only movement and breathing signals, which can be recorded with less effort than heart or brainwave signals, and requiring only four derived parameters for the calculations. Therefore, the new system is a significant improvement for non-obtrusive sleep stage identification compared to existing approaches.
The purpose of this paper is to examine the effects of perceived stress on traffic and road safety. One of the leading causes of stress among drivers is the feeling of having a lack of control during the driving process. Stress can result in more traffic accidents, an increase in driver errors, and an increase in traffic violations. To study this phenomenon, the Stress Perceived Questionnaire (PSQ) was used to evaluate the perceived stress while driving in a simulation. The study was conducted with participants from Germany, and they were grouped into different categories based on their emotional stability. Each participant was monitored using wearable devices that measured their instantaneous heart rate (HR). The preference for wearable devices was due to their non-intrusive and portable nature. The results of this study provide an overview of how stress can affect traffic and road safety, which can be used for future research or to implement strategies to reduce road accidents and promote traffic safety.
Recognition of sleep and wake states is one of the relevant parts of sleep analysis. Performing this measurement in a contactless way increases comfort for the users. We present an approach evaluating only movement and respiratory signals to achieve recognition, which can be measured non-obtrusively. The algorithm is based on multinomial logistic regression and analyses features extracted out of mentioned above signals. These features were identified and developed after performing fundamental research on characteristics of vital signals during sleep. The achieved accuracy of 87% with the Cohen’s kappa of 0.40 demonstrates the appropriateness of a chosen method and encourages continuing research on this topic.
Nowadays, the importance of early active patient mobilization in the recovery and rehabilitation phase has increased significantly. One way to involve patients in the treatment is a gamification-like approach, which is one of the methods of motivation in various life processes. This article shows a system prototype for patients who require physical activity because of active early mobilization after medical interventions or during illness. Bedridden patients and people with a sedentary lifestyle (predominantly lying in bed) are also potential users. The main idea for the concept was non-contact system implementation for the patients making them feel effortless during its usage. The system consists of three related parts: hardware, software, and game application. To test the relevance and coherence of the system, it was used by 35 people. The participants were asked to play a video game requiring them to make body movements while lying down. Then they were asked to take part in a small survey to evaluate the system's usability. As a result, we offer a prototype consisting of hardware and software parts that can increase and diversify physical activity during active early mobilization of patients and prevent the occurrence of possible health problems due to predominantly low activity. The proposed design can be possibly implemented in hospitals, rehabilitation centers, and even at home.
The importance of sleep for human life is enormous. It affects physical, mental, and psychological health. Therefore, it is vital to recognise sleep disorders in a timely manner in order to be able to initiate therapy. There are two methods for measuring sleep-related parameters - objective and subjective. Whether the substitution of a subjective method for an objective one is possible is investigated in this paper. Such replacement may bring several advantages, including increased comfort for the user. To answer this research question, a study was conducted in which 75 overnight recordings were evaluated. The primary purpose of this study was to compare both ways of measurement for total sleep time and sleep efficiency, which are essential parameters for, e.g., insomnia diagnosis and treatment. The evaluation results demonstrated that, on average, there are 32 minutes of difference between the two measurement methods when total sleep time is analysed. In contrast, on average, both measurement methods differ by 7.5% for sleep efficiency measurement. It should also be noted that people typically overestimate total sleep time and efficiency with the subjective method, where the perceived values are measured.
Evaluation of tech ventures’ evolving business models: rules for performance-related classification
(2022)
At the early stage of a successful tech venture's life cycle, it is assumed that the business model will evolve to higher quality over time. However, there are few empirical insights into business model evolution patterns for the performance-related classification of early-stage tech ventures. We created relevant variables evaluating the evolution of the venture-centric network and the technological proposition of both digital and non-digital ventures' business models using the text of submissions to the official business plan award in the German State of Baden-Württemberg between 2006 and 2012. Applying a principal component analysis/rough set theory mixed methodology, we explore performance-related business model classification rules in the heterogeneous sample of business plans. We find that ventures need to demonstrate real interactions with their customers' needs to survive. The distinguishing success rules are related to patent applications, risk capital, and scaling of the organisation. The rules help practitioners to classify business models in a way that allows them to prioritise action for performance.
Technologiebasierte Startups leisten einen wesentlichen Beitrag zur wirtschaftlichen sowie gesellschaftlichen Entwicklung. Im Zuge ihrer Gründung benötigen sie Unterstützung in Form von Risikokapital, das in der Seed- und Early-Stage primär durch Business Angels (BAs) bereitgestellt wird. Die Abläufe und Bewertungskriterien des BA Investmentprozesses sind bisher jedoch unzureichend erforscht. Der vorliegende Beitrag nutzt Experteninterviews im Rahmen einer Fallstudie des baden-württembergischen entrepreneurialen Ökosystems zur Identifikation des Vorgehens von BAs bei der Bewertung und Auswahl technologiebasierter Startups. Zudem werden die Kriterien, nach denen BAs vielversprechende von scheiternden Startups unterscheiden abgeleitet. Somit trägt der Beitrag zur Öffnung der „Black Box” von Investmentaktivitäten in den frühsten Gründungsphasen bei.
Ökonomische Aktivitäten sind auf den Input hochwertiger Energieträger angewiesen; diese sind knapp und werden in der fossil-nuklearen Energiewirtschaft aufgrund einer qualitativen Fehlanpassung zwischen Primärenergieeinsatz und Nutzenergiebedarf verschwenderisch genutzt. Daraus resultieren ökologische Probleme, insbesondere der Klimawandel, mit entsprechenden externen Kosten. Ein Umstieg auf erneuerbare Energien und effizientere Nutzungsstrukturen unterliegt diversen Pfadabhängigkeiten und ist aufgrund der multiplen Lernkosten mit hohen Pfadwechselkosten verbunden, die ebenfalls von der Gesellschaft getragen werden müssen. Unterschiedliche politökonomische Interessen der maßgeblichen Staaten verhindern derzeit harmonische weltweite Lösungen. Für eine evolutorische Energieökonomik ergeben sich einige Herausforderungen, insbesondere hinsichtlich der Klärung von sekundären und tertiären Pfadabhängigkeiten, der Erfassung systemischer Wechselwirkungen sowie der Problematik von Interventionsspiralen und der Formulierung von evolutorischen Designregeln für Energie- und Zertifikatemärkte.
Experimental Validation of Ellipsoidal Techniques for State Estimation in Marine Applications
(2022)
A reliable quantification of the worst-case influence of model uncertainty and external disturbances is crucial for the localization of vessels in marine applications. This is especially true if uncertain GPS-based position measurements are used to update predicted vessel locations that are obtained from the evaluation of a ship’s state equation. To reflect real-life working conditions, these state equations need to account for uncertainty in the system model, such as imperfect actuation and external disturbances due to effects such as wind and currents. As an application scenario, the GPS-based localization of autonomous DDboat robots is considered in this paper. Using experimental data, the efficiency of an ellipsoidal approach, which exploits a bounded-error representation of disturbances and uncertainties, is demonstrated.
Extended Target Tracking With a Lidar Sensor Using Random Matrices and a Virtual Measurement Model
(2022)
Random matrices are widely used to estimate the extent of an elliptically contoured object. Usually, it is assumed that the measurements follow a normal distribution, with its standard deviation being proportional to the object’s extent. However, the random matrix approach can filter the center of gravity and the covariance matrix of measurements independently of the measurement model. This work considers the whole chain from data acquisition to the linear Kalman Filter with extension estimation as a reference plant. The input is the (unknown) ground truth (position and extent). The output is the filtered center of gravity and the filtered covariance matrix of the measurement distribution. A virtual measurement model emulates the behavior of the reference plant. The input of the virtual measurement model is adapted using the proposed algorithm until the output parameters of the virtual measurement model match the result of the reference plant. After the adaptation, the input to the virtual measurement model is considered an estimation for position and extent. The main contribution of this paper is the reference model concept and an adaptation algorithm to optimize the input of the virtual measurement model.
In this paper, approximating the shape of a sailing boat using elliptic cones is investigated. Measurements are assumed to be gathered from the target's surface recorded by 3D scanning devices such as multilayer LiDAR sensors. Therefore, different models for estimating the sailing boat's extent are presented and evaluated in simulated and real-world scenarios. In particular, the measurement source association problem is addressed in the models. Simulated investigations are conducted with a static and a moving elliptic cone. The real-world scenario was recorded with a Velodyne Alpha Prime (VLP-128) mounted on a ferry of Lake Constance. Final results of this paper constitute the extent estimation of a single sailing boat using LiDAR data applying various measurement models.
Image novelty detection is a repeating task in computer vision and describes the detection of anomalous images based on a training dataset consisting solely of normal reference data. It has been found that, in particular, neural networks are well-suited for the task. Our approach first transforms the training and test images into ensembles of patches, which enables the assessment of mean-shifts between normal data and outliers. As mean-shifts are only detectable when the outlier ensemble and inlier distribution are spatially separate from each other, a rich feature space, such as a pre-trained neural network, needs to be chosen to represent the extracted patches. For mean-shift estimation, the Hotelling T2 test is used. The size of the patches turned out to be a crucial hyperparameter that needs additional domain knowledge about the spatial size of the expected anomalies (local vs. global). This also affects model selection and the chosen feature space, as commonly used Convolutional Neural Networks or Vision Image Transformers have very different receptive field sizes. To showcase the state-of-the-art capabilities of our approach, we compare results with classical and deep learning methods on the popular dataset CIFAR-10, and demonstrate its real-world applicability in a large-scale industrial inspection scenario using the MVTec dataset. Because of the inexpensive design, our method can be implemented by a single additional 2D-convolution and pooling layer and allows particularly fast prediction times while being very data-efficient.
In this paper, a novel feature-based sampling strategy for nonlinear Model Predictive Path Integral (MPPI) control is presented. Using the MPPI approach, the optimal feedback control is calculated by solving a stochastic optimal control (OCP) problem online by evaluating the weighted inference of sampled stochastic trajectories. While the MPPI algorithm can be excellently parallelized, the closed-loop performance strongly depends on the information quality of the sampled trajectories. To draw samples, a proposal density is used. The solver’s and thus, the controller’s performance is of high quality if the sampled trajectories drawn from this proposal density are located in low-cost regions of state-space. In classical MPPI control, the explored state-space is strongly constrained by assumptions that refer to the control value’s covariance matrix, which are necessary for transforming the stochastic Hamilton–Jacobi–Bellman (HJB) equation into a linear second-order partial differential equation. To achieve excellent performance even with discontinuous cost functions, in this novel approach, knowledge-based features are introduced to constitute the proposal density and thus the low-cost region of state-space for exploration. This paper addresses the question of how the performance of the MPPI algorithm can be improved using a feature-based mixture of base densities. Furthermore, the developed algorithm is applied to an autonomous vessel that follows a track and concurrently avoids collisions using an emergency braking feature. Therefore, the presented feature-based MPPI algorithm is applied and analyzed in both simulation and full-scale experiments.
Feature-Based Proposal Density Optimization for Nonlinear Model Predictive Path Integral Control
(2022)
This paper presents a novel feature-based sampling strategy for nonlinear Model Predictive Path Integral (MPPI) control. In MPPI control, the optimal control is calculated by solving a stochastic optimal control problem online using the weighted inference of stochastic trajectories. While the algorithm can be excellently parallelized the closed- loop performance is dependent on the information quality of the drawn samples. Because these samples are drawn using a proposal density, its quality is crucial for the solver and thus the controller performance. In classical MPPI control, the explored state-space is strongly constrained by assumptions that refer to the control value variance, which are necessary for transforming the Hamilton-Jacobi-Bellman (HJB) equation into a linear second-order partial differential equation. To achieve excellent performance even with discontinuous cost-functions, in this novel approach, knowledge-based features are used to determine the proposal density and thus, the region of state- space for exploration. This paper addresses the question of how the performance of the MPPI algorithm can be improved using a feature-based mixture of base densities. Further, the developed algorithm is applied on an autonomous vessel that follows a track and concurrently avoids collisions using an emergency braking feature.
In diesem Beitrag wird der finnische Tangotanztourismus
unter Berücksichtigung des Konzeptes des verkörperten Raumes (Low 2003) und des Raumverständnisses von Lefebvre (1991) auf den vielschichtig miteinander verbundenen Ebenen von Körper, Kultur und Raum analysiert. Die finnische „Kultur der Schweigsamkeit“ wird in diesem Zusammenhang im Besonderen
betrachtet. Methodisch werden hierbei sowohl Interviews mit Expertinnen und Experten, teilnehmende Beobachtung als auch die Auswertung von Filmmaterial herangezogen. Im Ergebnis zeigen sich vielfältige Wechselwirkungen von Körper, Kultur und Raum, die zusätzlich Potenziale für den finnischen Tangotanztourismus
aufzeigen.
Gamification is one of the recognized methods of motivating people in various life processes, and it has spread to many spheres of life, including healthcare. This article proposes a system design for long-term care patients using the method mentioned. The proposed system aims to increase patient engagement in the treatment and rehabilitation process via gamification. Literature research on available and earlier proposed systems was conducted to develop a suited system design. The primary target group includes bedridden patients and a sedentary lifestyle (predominantly lying in bed). One of the main criteria for selecting a suitable option was its contactless realization for the mentioned target groups in long-term care cases. As a result, we developed the system design for hardware and software that could prevent bedsores and other health problems from occurring because of low activity. The proposed design can be tested in hospitals, nursing homes, and rehabilitation centers.
In der vorliegenden Arbeit wird eine Vorlage für ein generalisiertes Betonfertigteil-Tracking für die Bauindustrie geschaffen. In dem ersten der vier Kapitel wird zuerst der Prozess des Fertigteil-Trackings dargestellt. Dieser wird anhand von Experteninterviews modifiziert und es wird ein Standardprozess als Vorlage präsentiert. Dieser Standardprozess soll für projektspezifische Wünsche modular erweiterbar sein. Hierfür werden Vorteile, Probleme und Verbesserungswünsche der Anwender eingearbeitet. Um den Prozess auf die gesamte Baubranche erweitern zu können, werden die softwaretechnischen Voraussetzungen für eine Standardschnittstelle der Fertigteil-Werke analysiert. Um Probleme bei der Implementierung und Durchführung des Trackings zu verhindern, werden die Partikularinteressen aller Beteiligten analysiert. Die Ergebnisse werden aus Experteninterviews generiert sowie durch Literaturrecherche und die eigenen Erfahrungen bei der Implementierung des Fertigteil-Trackings auf der Baustelle Telekom Areal der Ed. Züblin AG ergänzt.
Code-based cryptography is a promising candidate for post-quantum public-key encryption. The classic McEliece system uses binary Goppa codes, which are known for their good error correction capability. However, the key generation and decoding procedures of the classic McEliece system have a high computation complexity. Recently, q-ary concatenated codes over Gaussian integers were proposed for the McEliece cryptosystem together with the one-Mannheim error channel, where the error values are limited to Mannheim weight one. For this channel, concatenated codes over Gaussian integers achieve a higher error correction capability than maximum distance separable (MDS) codes with bounded minimum distance decoding. This improves the work factor regarding decoding attacks based on information-set decoding. This work proposes an improved construction for codes over Gaussian integers. These generalized concatenated codes extent the rate region where the work factor is beneficial compared to MDS codes. They allow for shorter public keys for the same level of security as the classic Goppa codes. Such codes are beneficial for lightweight code-based cryptosystems.
In this letter, we present an approach to building a new generalized multistream spatial modulation system (GMSM), where the information is conveyed by the two active antennas with signal indices and using all possible active antenna combinations. The signal constellations associated with these antennas may have different sizes. In addition, four-dimensional hybrid frequency-phase modulated signals are utilized in GMSM. Examples of GMSM systems are given and computer simulation results are presented for transmission over Rayleigh and deep Nakagami- m flat-fading channels when maximum-likelihood detection is used. The presented results indicate a significant improvement of characteristics compared to the best-known similar systems.
Generating synthetic data is a relevant point in the machine learning community. As accessible data is limited, the generation of synthetic data is a significant point in protecting patients' privacy and having more possibilities to train a model for classification or other machine learning tasks. In this work, some generative adversarial networks (GAN) variants are discussed, and an overview is given of how generative adversarial networks can be used for data generation in different fields. In addition, some common problems of the GANs and possibilities to avoid them are shown. Different evaluation methods of the generated data are also described.
Die durch den Klimawandel verursachten Auswirkungen und die daraus resultierende Betroffenheit nehmen stetig zu, dennoch ist das Bewusstsein für den Klimaschutz noch immer stärker verankert als das für die Klimaanpassung. Letztere sollte jedoch zum Schutz der Gesundheit der Bevölkerung und bestehender Infrastruktur mehr in das Bewusstsein rücken.
Die vorliegende Arbeit befasst sich mit der Frage, wie Städte widerstandsfähiger gegenüber den Folgen des Klimawandels werden können. Dazu werden die Prozesse der Stadtplanung auf diesen Kontext bezogen untersucht.
Um die Prozesse abzubilden, wird zunächst eine Übersicht über allgemeine Handlungsmöglichkeiten gegeben, bevor die Stadt Konstanz genauer betrachtet wird und die Ergebnisse, der dort geführten Experteninterviews ausgewertet werden. Mitarbeiter der Stadtverwaltung wurden in diesem Rahmen nach ihren Erfahrungen, bestehenden Prozessen und notwendigen Veränderungen befragt. Im letzten Schritt wurde der Untersuchungsraum erweitert, um Erfahrungen aus Städten, die bereits aktiv Klimaanpassung umsetzen, einzubringen. Aus diesen Ergebnissen werden Handlungsempfehlungen für die Klimaanpassung abgeleitet und beschrieben.
Ziel des Forschungsprojekts "Ekont" ist es, ein handgeführtes Gerät zum Betonabtrag an Innenkanten und Störstellen in Kernkraftwerken (KKW) zu entwickeln. Um die Reaktionskräfte zu reduzieren wird hierbei der neuartige Ansatz eines gegenläufigen Fräsprozesses untersucht. Ergebnis ist eine Getriebelösung, bei der eine mittlere Frässcheibe mit annähernd derselben Umfangsgeschwindigkeit in die entgegengesetzte Richtung von weiteren Frässcheiben rotiert.