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Improving the tribological properties of Stainless Steels by low-temperature surface hardening
(2022)
A novel implant system for bone elongation will be presented. With this technique, the body's own bone material, so-called callus, can be formed by gradual distraction of the tubular bones, thus achieving an extension of femur and tibia bones. The driving principle of this fully implantable bone lengthening system is based on a shape memory element. During the surgical treatment, the intramedullary nail serves to stabilize the severed bone and enables the formation of new, endogenous bone material to lengthen the limbs or to bridge bone defects. The intramedullary nail is implanted into the medullary cavity and fixed at both ends with locking bolts. A receiver coil implanted under the skin receives the necessary energy twice a day through high-frequency energy transport to activate the thermal phase transformation of the shape memory element. This gradually increases the bone gap by 0.5 mm each time and stimulates callus formation. Consequently, osteoblasts or osteocytes are formed in the area of the desired bone extension and load-bearing bone material is formed. Three nail prototypes have already been tested for their functionality in a cadaver study in a German clinic. Currently a redesign of this intelligent implant system is underway, focusing on a novel coil geometry, a monitoring sensor system and control technology and a novel connection technology for the drive components. With this intelligent implant system, it will be possible for the first time to lengthen the bones in a patient-friendly manner and to continuously monitor, document and evaluate the entire lengthening process.
Adjusting the friction response of the wheel-rail interface is a key factor in the mitigation of wear and rollingcontact fatigue (RCF) in rails. The use of top-of-rail (TOR) friction conditioners has the potential to reduce maintenance costs significantly. Unfortunately, conflicting results on the use of commercial TOR conditioners have been presented in the literature. In this work, the performance of commercial TOR conditioners and a laboratory-made formulation were tested, both on the lab scale and in field measurements. Friction results are discussed together with the structural and chemical analysis of the tested materials.
Haarstylingutensil
(2022)
Die Beständigkeit von hochlegierten korrosions- und säurebeständigen Stählen wird primär durch den Chromgehalt bestimmt. Allerdings gibt es entlang der Wertschöpfungskette von der Stahlerschmelzung bis zum fertigen Produkt eine Vielzahl weiterer Einflussfaktoren. Dem Schleifen kommt hier eine besondere Bedeutung zu, da es je nach Wahl der Prozessparameter sowohl zu einer signifikanten Verschlechterung als auch zu einer Verbesserung der Korrosionsbeständigkeit führen kann. Im vorliegenden Beitrag wird aufgezeigt, dass die erzeugte Rauheit nur eine begrenzte Aussagekraft bietet. Vielmehr erhöhen lokale Mikrodefekte die Anfälligkeit gegen Lochfraß – je nach Ausprägung und Anzahl. Die Automatisierung für die Innenbearbeitung von Behältern im pharmazeutischen Apparatebau kann dabei zu einer signifikanten Verbesserung der Oberfläche und einem homogeneren Erscheinungsbild führen.
Durch eine Aufweitung des Kristallgitters mittels Niedertemperatur-Eindiffusion von Kohlenstoff und/oder Stickstoffatomen können in der Randzone von nichtrostenden Stählen eine hohe Härte und eine hohe Verschleißbeständigkeit erzeugt werden, ohne dass zusätzliche Legierungselemente verwendet werden müssen. Die metallkundlichen Hintergründe für die Härtung, die Wirkung auf Verschleißvorgänge und mögliche Anwendungsbereiche werden geschildert. Anhand von Reibwerten wird gezeigt, in welcher Weise das Reibungsverhalten bei Schraubverbindungen durch die Behandlung verändert wird. Über Migrationsversuche wird nachgewiesen, dass die Ionenabgabe durch die Oberflächenhärtung nicht erhöht, sondern sogar abgesenkt wird. Neben dem besseren Verschleißschutz und einer höheren Dauerfestigkeit sichert diese Oberflächenbehandlung am nichtrostenden Stahl den Schutz gegen die Kontamination von Pharmaprodukten durch Metallabrieb/-ionen. Tests an oberflächengehärteten Edelstahlproben ergaben weiterhin, dass durch die Oberflächenhärtung die Biokompatibilität des nichtrostenden Edelstahls nicht beeinträchtigt wird.
Jahresbericht 2022
(2022)
Der Prozess der Optimierung ist in Bereichen wie der Mathematik, Wirtschaft sowie sämtlichen Ingenieurswissenschaften ein zentrales und nicht mehr wegzudenkendes Werkzeug. Mit der Motivation der Nachhaltigkeit, Effizienz und Kosteneinsparung wird im Bauwesen ein optimaler Einsatz der Materialien gefordert unter Einhaltung der geforderten statischen Nachweise.
Die Methode der Verformungsreduzierung durch Materialumverteilung (kurz: MVM) greift die Anforderung auf, Material möglichst effizient einzusetzen. Diese Methode basiert darauf, die Steifigkeiten innerhalb eines geometrisch festgelegten und bereits vordimensionierten Tragwerkes durch Materialumverteilung in einem iterativen Prozess neu zu positionieren, wodurch die Verformung an einem vorab definierten kritischen Punkt reduziert wird und gleichzeitig die Verteilung der Ausnutzung vergleichmäßigt wird.
Ziel dieser Bachelorarbeit ist es, das in einer vorherigen Abschlussarbeit bereits entwickelte Grasshopper-Skript für eine praxisbezogene Anwendung zu optimieren und zu erweitern. Dieses Grasshopperskript soll neu strukturiert und auf Fehler untersucht werden. Ebenso soll ein Abbruchkriterium implementiert werden, das die Optimierung automatisch abbricht, sobald keine nennenswerte Reduzierung der Verformung infolge der Materialumverteilung mehr erfolgt. Dabei soll stetig die Tragfähigkeit aller Stäbe eingehalten sein.
Das optimierte Tool soll abschließend anhand geeigneter praxisorientierter Beispiele angewandt und validiert werden.
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.
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.
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.
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.
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.
Durch neuartige Arten der Fortbewegung, eine weitreichende Vernetzung und die Notwendigkeit einer nachhaltigen Mobilität steht die Mobilitätsplanung vor neuen Herausforderungen. Die bisherige Ausrichtung auf die Optimierung von Kapazität und Geschwindigkeit des Verkehrsflusses ist mit der modernen Stadtplanung nicht mehr vereinbar.
Ziel dieser Masterarbeit ist es, ein Konzept für eine zukunftsorientierte Mobilitätsplanung mit der Eingliederung in eine klimaresiliente Stadtplanung zu schaffen. Dafür wird der Einsatz von Fernerkundungsdaten als Datengrundlage für Planung und Monitoring und die Verwendung weicher Maßnahmen untersucht. Sie erfordern keinen direkten Eingriff in die Infrastruktur, sondern bauen auf der bereits bestehenden auf und zielen auf eine Veränderung des Mobilitätsverhalten der Reisenden ab.
Auf Basis einer Literaturrecherche wurde ein Konzept erstellt, das die identifizierten Problemstellen der heutigen Mobilitätsplanung aufgreift. Zur Validierung der technischen Machbarkeit und die Praxistauglichkeit, wurden Experteninterviews durchgeführt. Mit den daraus gewonnenen Erkenntnissen wurde der neue Ansatz darauffolgend erweitert und angepasst.
Die Auswertung zeigt, dass die Herausforderungen durch das entwickelte Konzept aufgegriffen werden und die Mobilitätsplanung von der Verwendung von Fernerkundungsdaten profitieren kann. Um eine optimale Datenverwertung zu gewährleisten, ist eine Bilderkennungssoftware erforderlich. Allerdings erfordert die angestrebte Verhaltensänderung bei den Reisenden zudem ein unterstützendes zielgruppenorientiertes Marketing. Für eine weitere Verbesserung des Monitorings ist die Bildung von KPIs bereits in der Planungsphase und eine Monitoring-Plattform hilfreich.
Zur Einbindung des Konzepts in der Praxis ist die Entwicklung einer auf die Fernerkundungsdaten angepasste Bilderkennungssoftware notwendig. Danach kann das entwickelte Konzept in Pilotprojekten angewendet werden. Dadurch können auch die prozessualen Änderungen, die durch den Ansatz erfolgen, erprobt 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.
Um gegen den Klimawandel vorzugehen, ist im Gebäudebestand eine Reduktion der Treibhausemmissionen nötig. Dafür müssen politische Entscheidungsträger, Wohnungsunternehmen und Baufirmen gemeinsam arbeiten, um CO2 Neutralität zu erreichen. Die energetische Sanierung der bedürftigen Gebäude ist mit den konventionellen Methoden bis zum Jahr 2050 nicht zu erreichen. Das Energiesprong Prinzip bietet einen Lösungsansatz, welcher finanziell interessant ist und mit weniger Personalaufwand in großer Menge umgesetzt werden kann. Es wird die Erkenntnis gewonnen, dass die bisher verwendeten konstruktiven Systeme jedoch noch Optimierungsbedarf haben, um den finanziellen Rahmen des Prinzips einzuhalten und den Massenmarkt bedienen zu können. Die Untersuchungen dieser Arbeit ergeben, dass eine im Prozess eingebundene Gebäudeaufstockung in Holzbauweise eine lohnende Ergänzung sein kann. Aus nachhaltigem Baumaterial wird mit verhältnismäßigem Mehraufwand eine größere Rentabilität der Immobilie bewirkt und dem Problem der Wohnungsknappheit in Städten entgegengewirkt.
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.
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.
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.
CoKLIMAx
(2022)
Das Ziel der vorliegenden Arbeit ist die Ermittlung relevanter Parameter der Wirtschaftlichkeitsuntersuchung von Überdeckelungen von Infrastrukturflächen in hybrider Bauweise im innerstädtischen Raum in Deutschland. Die untersuchte Hybridbauweise setzt sich aus Grünbrücken in Leichtbauweise und massive, bebaubare Module zusammen. Zusätzlich soll ein Berechnungsmodell entwickelt werden, in das die Werte der Parameter potenzieller Standorte eingegeben werden können. Hierüber können Bewertungen und Vergleiche der Standorte durchgeführt werden, welche später als Entscheidungsgrundlage für eine Realisierung dienen können. Mit Hilfe einer Sensitivitäts-, Szenarien- und Immobilienmarktanalyse werden die Parameter der Wirtschaftlichkeitsuntersuchung analysiert, wonach den maßgeblichen Einfluss auf das Endergebnis die Grundflächenzahl und die Geschossflächenzahl haben. Die Länge der Überdeckelung hat dagegen weniger bis keinen Einfluss auf das Gesamtergebnis. Die regionalen Immobilienpreise stellen den Schlüssel zur Wirtschaftlichkeit dar. Sie können geringe Werte der Grundflächenzahl und Geschossflächenzahl ausgleichen. Die verschiedenen Gegebenheiten und regionalen Unterschiede der Standorte deutschlandweit machen derartige Großprojekte jeweils zu Individuallösungen und die Entwicklung eines standardisierten Modells schwierig. Das Modell sollte für jeden Standort leicht modifiziert werden, wie die Case Study des McGraw-Grabens in München zeigt. Das Ergebnis der Case Study fällt durch die entsprechende Bebauungsdichte und die hohen Immobilienpreise positiv aus. Trotzdem muss der Detaillierungsgrad berücksichtigt werden, wonach ein solches Modell lediglich erste Anhaltspunkte für eine Bewertung geben kann. Für eine ganzheitliche Beurteilung müssen entsprechende Erweiterungen des Modells vorgenommen werden.
This report summarises up-to-date social science evidence on climate communication for effective public engagement. It presents ten key principles that may inform communication activities. At the heart of them is the following insight: People do not form their attitudes or take action as a result primarily of weighing up expert information and making rational cost-benefit calculations. Instead, climate communication has to connect with people at the level of values and emotions.
Two aspects seem to be of special importance: First, climate communication needs to focus more on effectively speaking to people who have up to now not been properly addressed by climate communications, but who are vitally important to build broad public engagement. Second, climate communication has to support a shift from concern to agency, where high levels of climate risk perception turn into pro-climate individual and collective action.
Der wirtschaftliche Erfolg eines Unternehmens wird an seinen Umsätzen und Gewinnen gemessen. Im Sinne der Lean Management-Philosophie wird versucht, Prozesse und Abläufe immer weiter zu optimieren, um immer bessere Ergebnisse zu liefern. Der maßgebliche Einfluss, den dabei die Führung des Unternehmens, aber auch die Führung innerhalb des Betriebs auf die Produktion hat, wird jedoch häufig unterschätzt. Shopfloor Management bietet hier das Führungsinstrument, um durch Führung am Ort des Geschehens Produktion und Management miteinander zu verbinden. Das Bauunternehmen Ed. Züblin AG setzt Lean Construction mit Hilfe der Methode der Taktplanung und Taktsteuerung um. Zu diesem Zweck hat es mit der digitalen Taktsteuerungstafel (dTST) ein eigenes Instrument zur Steuerung der Prozesse auf der Baustelle entwickelt, mit dem der Status täglich erfasst und bewertet wird. Ziel dieser Arbeit ist es, herauszufinden wie sich mit Hilfe der dTST und ihrer Daten Shopfloor Management Ansätze für Bauprojekte entwickeln lassen. Hierzu werden Interviews mit Stakeholdern höherer Hierarchieebenen verschiedener Bauprojekte geführt, um deren Bedürfnisse und Anforderungen an einen entsprechenden Ansatz zu eruieren. Die Verbesserung der Kommunikation, das Schaffen von Transparenz und auch die Mitarbeiterentwicklung sind die maßgeblichen Ziele der Stakeholder, die mit Shopfloor Management erreicht werden sollen. Die dTST wird dabei jetzt schon als das Werkzeug zur Durchführung von Shopfloor Management angesehen. Auf Basis dieser Erkenntnisse wurde ein Konzept in Form einer Besprechungslandschaft entwickelt. In dieser dienen die dTST und ihre Daten als Grundlage der täglich stattfindenden Kommunikation zwischen den Ebenen. Um die dTST noch aktiver in die tägliche Kommunikation einzubinden und ihre Daten aktiver und besser nutzen zu können, wurden Zusatzeigenschaften entworfen. Es muss jedoch berücksichtigt werden, dass bei der Entwicklung und Gestaltung von Shopfloor Management Ansätzen in der Praxis eine Vielzahl von Hindernissen und Herausforderungen gemeistert werden müssen. Eine maßgebliche Rolle spielen hier u.a. die Entwicklung von Standards, der notwendige Kulturwandel (z.B. Fehlerkultur, Führungsstil), die Berücksichtigung des Einflusses externer Stakeholder und die Gestaltung des Change Managements.
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.
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.
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.
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.
Die vorliegende Arbeit befasst sich mit der Frage, ob aus der auditiven Wahrnehmung allgemeingültige Gestaltungsparameter abgeleitet werden können. Hierzu wurde sowohl eine Grundlagenrecherche betrieben als auch eigene Experimente durchgeführt um sich einer Antwort auf die Frage qualitativ anzunähern.
Die Ergebnisse, die im Rahmen dieser Arbeit erbracht werden konnten, legen nahe, dass die Transformation von auditiven in gestalterische Parameter möglich ist, jedoch zum Teil auf subjektiven Empfindungen beruht, die von verschiedenen Person in individuell wahrgenommen werden können. Dennoch zeigen sich klare Tendenzen, die durch Analyse der Forschungsergebnisse und Befragung der Probanden Rückschlüsse auf Gemeinsamkeiten bei der Assoziation auditiver Variablen zulassen. Durch eine schrittweise Reduzierung der audiobezogenen Faktoren, wie Tonhöhe, Schalldruck oder Balance, kann gezeigt werden, dass beim Erfassen von auditiven Reizen, bildliche Ableitungen vorgenommen werden können und diese formspezifischer werden, je qualitativer die Klänge bewertet werden können.
Klangmuster mit vielen sich verändernden Variablen hingegen, werden im überwiegenden Maße rational und stark technisiert in Zeichenform wiedergegeben, da die Probanden offenbar versuchen, die für sie wahrnehmbaren Klangparameter auf dem Papier abzubilden. Da sich diese Parameter im Laufe der Untersuchung und Befragung als trivial herausgestellt haben, war die weitere Forschung auf die intuitive Formgebung gerichtet.
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.
Sleep is an important part of our life that significantly influences our health and well-being. The monitoring of sleep can provide data based on which sleep quality could be improved. This paper presents a system for heart rate detection during sleep. The data is collected from sensors underneath the test subjects. Though the data contains noise, it needs to be filtered to remove it. Due to the low strength of the signals, they need to be amplified after filtering. At some points of the signal, particular heartbeats may not be tracked by sensors due to the failure of a sensor or other reasons, which should be considered. The heart rate is detected in intervals of 15 s. A tool is implemented that detects the heart rate and visualizes it. The preprocessing of the data is performed with several filters: a highpass filter, a band-reject filter, a lowpass filter, and a motion detector. After the preprocessing of the data, the quality of the signal is significantly increased, and detection is possible.
Lignin is a potentially high natural source of biological aromatic substances. However, decomposition of the polymer has proven to be quite challenging, as the complex bonds are fairly difficult to break down chemically. This article is intended to provide an overview of various recent methods for the catalytic chemical depolymerization of the biopolymer lignin into chemical products. For this purpose, nickel-, zeolite- and palladium-supported catalysts were examined in detail. In order to achieve this, various experiments of the last years were collected, and the efficiency of the individual catalysts was examined. This included evaluating the reaction conditions under which the catalysts work most efficiently. The influence of co-catalysts and Lewis acidity was also investigated. The results show that it is possible to control the obtained product selectivity very well by the choice of the respective catalysts combined with the proper reaction conditions.
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.
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.
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.
Bei der Auslegung des Verteilergetriebes leistungsverzweigter Hybridantriebe müssen die Übersetzungen sorgfältig hinsichtlich des Wirkungsgrades ausgewählt werden. Die ungünstige Leistungsübertragung im seriellen, elektrischen Zweig sowie die Blindleistung sind zu minimieren. Die Formelzusammenhänge werden in diesem Aufsatz, der im Rahmen eines Freistellungssemesters entstanden ist, hergeleitet.
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.
Mit Effizienz- und Konsistenzlösungen lässt sich sowohl der Energiebedarf vermindern, als auch mit einer besseren ökologischen und strukturellen Passung im
Sinne der Bioökonomie versehen. Dieser Beitrag stellt die Möglichkeiten zur Steigerung der industriellen Energieeffizienz mittels lernenden Energieeffizienz-Netzwerken vor. Thematisiert werden Konzepte zur Überwindung von Hemmnissen durch Lernerfahrungen, insbesondere mittels des Synergiekonzeptes als innovativer Lernplattform sowie die systemischen Wechselwirkungen in diesem Kontext. Darüber hinaus werden hierzu korrespondierende innovationsorientierte Organisationsvarianten für das betriebliche Energiemanagement erläutert. Abschließend beleuchtet der Beitrag Konzepte von betrieblichen und überbetrieblichen Energieverbünden, insbesondere der gekoppelten Energieerzeugung und -nutzung, z. B. im Bereich der Wärmenutzung.
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.
Reliability Assessment of an Unscented Kalman Filter by Using Ellipsoidal Enclosure Techniques
(2022)
The Unscented Kalman Filter (UKF) is widely used for the state, disturbance, and parameter estimation of nonlinear dynamic systems, for which both process and measurement uncertainties are represented in a probabilistic form. Although the UKF can often be shown to be more reliable for nonlinear processes than the linearization-based Extended Kalman Filter (EKF) due to the enhanced approximation capabilities of its underlying probability distribution, it is not a priori obvious whether its strategy for selecting sigma points is sufficiently accurate to handle nonlinearities in the system dynamics and output equations. Such inaccuracies may arise for sufficiently strong nonlinearities in combination with large state, disturbance, and parameter covariances. Then, computationally more demanding approaches such as particle filters or the representation of (multi-modal) probability densities with the help of (Gaussian) mixture representations are possible ways to resolve this issue. To detect cases in a systematic manner that are not reliably handled by a standard EKF or UKF, this paper proposes the computation of outer bounds for state domains that are compatible with a certain percentage of confidence under the assumption of normally distributed states with the help of a set-based ellipsoidal calculus. The practical applicability of this approach is demonstrated for the estimation of state variables and parameters for the nonlinear dynamics of an unmanned surface vessel (USV).
Targetless Lidar-camera registration is a repeating task in many computer vision and robotics applications and requires computing the extrinsic pose of a point cloud with respect to a camera or vice-versa. Existing methods based on learning or optimization lack either generalization capabilities or accuracy. Here, we propose a combination of pre-training and optimization using a neural network-based mutual information estimation technique (MINE [1]). This construction allows back-propagating the gradient to the calibration parameters and enables stochastic gradient descent. To ensure orthogonality constraints with respect to the rotation matrix we incorporate Lie-group techniques. Furthermore, instead of optimizing on entire images, we operate on local patches that are extracted from the temporally synchronized projected Lidar points and camera frames. Our experiments show that this technique not only improves over existing techniques in terms of accuracy, but also shows considerable generalization capabilities towards new Lidar-camera configurations.
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.
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.
Large persistent memory is crucial for many applications in embedded systems and automotive computing like AI databases, ADAS, and cutting-edge infotainment systems. Such applications require reliable NAND flash memories made for harsh automotive conditions. However, due to high memory densities and production tolerances, the error probability of NAND flash memories has risen. As the number of program/erase cycles and the data retention times increase, non-volatile NAND flash memories' performance and dependability suffer. The read reference voltages of the flash cells vary due to these aging processes. In this work, we consider the issue of reference voltage adaption. The considered estimation procedure uses shallow neural networks to estimate the read reference voltages for different life-cycle conditions with the help of histogram measurements. We demonstrate that the training data for the neural networks can be enhanced by using shifted histograms, i.e., a training of the neural networks is possible based on a few measurements of some extreme points used as training data. The trained neural networks generalize well for other life-cycle conditions.
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.
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.
Virtual measurement models (VMM) can be used to generate artificial measurements and emulate complex sensor models such as Lidar. The input of the VMM is an estimation and the output is the set of measurements this estimation would cause. A Kalman filter with extension estimation based on random matrices is used to filter mean and covariance of the real measurements. If these match the mean and covariance of the artificial measurements, then the given estimation is appropriate. The optimal input of the VMM is found using an adaptation algorithm. In this paper, the VMM approach is expanded for multi-extended object tracking where objects can be occluded and are only partially visible. The occlusion can be compensated if the extension estimation is performed for all objects together. The VMM now receives as input an estimation for the multi-object state and the output are the measurements that this multi-object state would cause.
Digitization and sustainability are the two big topics of our current time. As the usage of digital products like IoT devices continues to grow, it affects the energy consumption caused by the Internet. At the same time, more and more companies feel the need to become carbon neutral and sustainable. Determining the environmental impact of an IoT device is challenging, as the production of the hardware components should be considered and the electricity consumption of the Internet since this is the primary communication medium of an IoT device. Estimating the electricity consumption of the Internet itself is a complex task. We performed a life cycle assessment (LCA) to determine the environmental impact of an intelligent smoke detector sold in Germany, taking its whole life-cycle from cradle-to-grave into account. We applied the impact assessment method ReCiPe 2016 Midpoint and compared its results with ILCD 2011 Midpoint+ to check the robustness of our results. The LCA results showed that electricity consumption during the use phase is the main contributor to environmental impacts. The mining of coal causes this contribution, which is a part of the German electricity mix. Consequently, the smoke detector mainly contributes to the impact categories of freshwater and marine ecotoxicity, but only marginally to global warming.
Wirkung von Design verstehen
(2022)
Um das Konstrukt Corporate Design verstehen zu lernen und einen methodischen Ansatz zur Schulung des gestalterischen Gespürs im Gestaltungsprozess zu generieren, untersucht die Independent Study bestehende Marken mithilfe theoretischer Grundlagen aus der Rhetorik. In vier Case Studies werden Corporate Designs oder Aspekte dieser unter gestalterischen sowie rhetorischen Regeln betrachtet. Die Beschäftigung mit Marken auf diese Art und Weise schafft Erfahrungen mit der Thematik, während die angewendeten Methodiken systematisches Denken in der Gestaltung fördert und einen methodischen Werkzeugkasten ermöglicht.
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.
Die digitale Transformation von Geschäftsprozessen und die stärkere Einbindung von IT-Systemen erzeugen bei kleinen und mittelständischen Unternehmen (KMU) Chancen und Risiken zugleich. Risiken, die insbesondere in einer fehlenden IT-Compliance resultieren können. Wie Studien zeigen, sind KMU in Bezug auf IT-Compliance-Maßnahmen im Vergleich zu kapitalmarktorientierten Unternehmen jedoch im Rückstand [1]. Im Beitrag wird mithilfe von Experteninterviews und einer qualitativen Datenanalyse der Frage nachgegangen, welcher Status quo an Maßnahmen aktuell implementiert und wie der empfundene Compliance-Reifegrad ist. Weiterhin werden die Gründe und Motive erörtert, die zu diesem Zustand geführt haben. Letztlich sind Treiber identifiziert worden, die zu einem höheren Bewusstsein in der Zukunft führen können. Die Arbeit zeigt interessante Erkenntnisse aus der Praxis, da die Experteninterviews Einblicke in den aktuellen Status quo in Bezug auf IT-Compliance liefern.
Business Partner Compliance
(2022)
Low-Code Development Platforms (LCDPs) enable non-information technology (IT) personnel to develop applications and workflows independently of the IT department. Consequently, these digital platforms help to overcome the growing need for software development. However, science and practice warn of several barriers that slow down or hinder the usage of LCDPs. This publication scientifically identifies, analyzes, and discusses challenges during implementation and application of LCDPs from both perspectives in a holistic manner. Therefore, we conduct an exploratory study (data from scientific literature, expert interviews, and practical studies) and assign the challenges to the socio-technical system model. The results show that the scientific and practical communities recognize common challenges (especially knowledge transfer) but also perceive differences related to technological (science) and social (practice) aspects. This paper proposes future research directions for academia, such as governance, culture change, and value evaluation of LCDPs. Additionally, practitioners can prepare for possible challenges when using LCPDs.
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.
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.
In recent years, there has been a noticeable trend towards a general contractor strategy for plant engineering companies. Multiple disciplines and departments must be administered in a joint project. In the process, different work results are often managed in various systems without any associative relationship. A possible way to address this complexity is to implement a specifically tailored PLM strategy to gain a competitive advantage. Maturity models as well as methods to evaluate possible benefits constitute increasingly applied tools during this journey. Both methods have been theoretically described in previous publications. However, this paper should provide insights in the practical application within machinery industry. Therefore, a medium-sized German plant engineering company serves as an example for determining the scope and value of a multi-national overarching Product Lifecycle Management architecture as the central piece of a future digitalization strategy. The company’s current maturity levels for several digitalization capabilities are evaluated, prioritized and benchmarked against a set of similar companies. This allows to derive suitable target states in terms of maturity levels as well as the technical specification of digitalization use cases. In order to provide profound data for cost justification the resulting benefits are quantified.
The development of a new product can be accelerated by using an approach called crowdsourcing. The engineers compete and try their best to provide the related solution based on the given product requirement submitted in the online crowdsourcing platform. The one who has submitted the best solution get a financial reward. This approach is proven to be three time faster than the conventional one. However, the crowdsourcing process is usually not transparent to a new user. The risk for the execution of a new project for developing a new product is not easy to be calculated [1, 2]. We developed a method InnoCrowd to handle this problem and the new user could use during the planning of a new product development project. This system uses AI concepts to generate a knowledgebase representing histories of successful product development projects. The system uses the knowledge to determine qualitative and quantitative risks of a new project. This paper describes the new method, the InnoCrowd design, and results of a validation experiment based on data from a current crowdsourcing platform. Finally, we compare InnoCrowd to related methods and systems in terms of design and benefits.
Digitization extends to all areas of people's lives and processes, including public administration and government technology (GovTech for short). However, there are various problems here, such as the inappropriate development of new application systems, that are to be solved efficiently by combining two aspects: methodical digitization according to the process-driven approach and the idea of an app store for processes. This simultaneously fuels a process competition to advance methodical process digitization in the EU. Furthermore, this study explains the target-oriented use of this “firing” within the EU and concludes with a proposal of a new 3-schema architecture standard for successful process digitization within the EU.
As fish farming is becoming more and more important worldwide, this ongoing project aims at the simulation and test-based analysis of highly stressed wire contacts, as they are found in off-shore fish farm cages in order to make them more reliable. The quasi-static tensile test of a wire mesh provides data for the construction of a finite element model to get a better understanding of the behavior of high-strength stainless steel from which the cages are made. Fatigue tests provide new insights that are used for an adjustment of the finite element model in order to predict the probability of possible damage caused by heavy mechanical loads (waves, storms, predators (sharks)).
As interest in the investigation of possible sources and environmental sinks of technology-critical elements (TCEs) continues to grow, the demand for reliable background level information of these elements in environmental matrices increases. In this study, a time series of ten years of sediment samples from two different regions of the German North Sea were analyzed for their mass fractions of Ga, Ge, Nb, In, REEs, and Ta (grain size fraction < 20 µm). Possible regional differences were investigated in order to determine preliminary reference values for these regions. Throughout the investigated time period, only minor variations in the mass fractions were observed and both regions did not show significant differences. Calculated local enrichment factors ranging from 0.6 to 2.3 for all TCEs indicate no or little pollution in the investigated areas. Consequently, reference values were calculated using two different approaches (Median + 2 median absolute deviation (M2MAD) and Tukey inner fence (TIF)). Both approaches resulted in consistent threshold values for the respective regions ranging from 158 µg kg−1 for In to 114 mg kg−1 for Ce. As none of the threshold values exceed the observed natural variation of TCEs in marine and freshwater sediments, they may be considered baseline values of the German Bight for future studies.
Dissipation of heat can be a major challenge when applying sensor systems outdoors under varying environmental conditions. Typically, complex software and knowledge is needed to optimize thermal management. In this paper it is shown how the thermal optimization of a LiDAR (light detection and ranging) sensor can be performed efficiently. This approach uses standard CAD (computer aided design) software, which is readily available, and saves time and cost as the thermal design can be optimized before experimental realisation. A four-step process was developed and realized: (i) Measurement of the thermal energy distribution of the current sensor design; (ii) Simulation of the time-dependant thermal behaviour using standard CAD software; (iii) Simulation of a thermally optimized design. This was compared quantitatively with the original design and was also used for verification of sufficient increase in heat dissipation; (iv) Experimental realisation and verification of the optimized design. It could be shown that the optimized prototype shows significantly improved thermal behaviour in accordance with the predictions from the simulations. The new LiDAR sensor shows lower heat generation and optimized dissipation of thermal energy which proofs the applicability of the approach to complex sensors.
Dynamic Real-Time Range Queries (DRRQ) are a common means to handle mobile clients in high-density areas where both, clients requested by the query and the inquirers, are mobile. In contrast to the very well-known continuous range queries, only a few approaches, such as Adaptive Quad Streaming (AQS), address the mandatory scalability and real-time requirements of these so-called ad-hoc mobility challenges. In this paper we present the highly decentralized solution Adaptive Quad Streaming Flexible (AQSflex) as an extension of the already existing more theoretical AQS approach. Beside a highly distributed cell structure without data structures and a lightweight streaming communication, we use a multi-cell-assignment on limited pool resources instead of an idealistic unlimited cell-per-server assignment. The described experimental results show the potential of our local capacity balancing scheme for cell handover in a strongly decentralized setting. Leafs of a cell hierarchy define a kind of self-optimizing fuzzy edge for the processing resources in high-density systems without any centralized controlling or cloud component.
Per-capita greenhouse gas emissions in cities like Bangkok or Shanghai have already reached emission levels of cities like London or Toronto. Large parts of the building stock and service infrastructure in cities in rapidly developing countries will be built in the coming decades—and may lock in high emissions pathways. A survey of projects under the Clean Development Mechanism (CDM) of the Kyoto Protocol shows that only about 1% of projects have been submitted by municipalities, mostly in the waste management and more recently in the transport sector. This is probably due to a lack of technical know-how, legal barriers, methodological challenges, long project cycles and limited “visibility” of projects for the electorate. A case study of city network ICLEI’s experience with the CDM adds practical insights. We conclude that while the new market mechanisms under Article 6 may make it easier for municipalities to engage in international market mechanisms, new forms of cooperation between actors on multiple levels, potentially facilitated by ICLEI, are required to help to realize the urban potential in international market mechanisms.
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.
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.
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.
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.
This paper presents the swinging up and stabilization control of a Furuta pendulum using the recently published 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 regarding the nonlinear system dynamics and simulations. Constraints in terms of state and input are taken into account in the cost function. The presented approach sequentially computes an optimal control sequence that minimizes this optimal control problem online. The control strategy has been tested in full-scale experiments using a pendulum prototype. The investigated MPPI controller has demonstrated excellent performance in simulation for the swinging up and stabilizing task. In order to also achieve outstanding performance in a real-world experiment using a controller with limited computing power, a linear quadratic controller (LQR) is designed for the stabilization task. In this paper, the determination of the controller parameters for the MPPI algorithm is described in detail. Further, a discussion treats the advantages of the nonlinear MPPI control.
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.
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.
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.
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.
Traggerüste
(2022)
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.
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).
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.