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Open Access
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Diese Bachelorarbeit analysiert das Medienkonsumverhalten der deutschen Bevölkerung und die vielfältigen Nutzungen von YouTube. Mit dieser Abhandlung sollte es möglich sein, wichtige Punkte für die Erstellung eines eigenen YouTube-Kanals zu sammeln. Dies gilt sowohl für Ersteller von Inhalten als auch für Unternehmen.
Zu Beginn wird analysiert, welche Funktionen YouTube für Content Creator, Unternehmen und Konsumenten bietet. Des Weiteren werden die verschiedenen Finanzierungsmöglichkeiten aufgezeigt, welche die Videoplattform anbietet.
Die für die Analyse erforderlichen Daten stammen aus verschiedenen Studien zum Verhalten des Medienkonsums. Darüber hinaus werden auf sozialen Plattformen eigene Umfragen durchgeführt, um einen spezifischen Überblick über die Nutzung von YouTube und seinen Alternativen zu erhalten.
Mit dem Ergebnis der Analyse wird ein Prozess entwickelt, der dazu beitragen soll, Fehler beim Erstellen eines YouTube-Kanals zu vermeiden und einen positiven Effekt für den Kanal zu erzielen. Dieser Prozess enthält wichtige Punkte, die beim Ausführen eines Kanals zu beachten sind.
With economic weight shifting toward net zero, now is the time for ECAs, Exim-Banks, and PRIs to lead. Despite previous success, aligning global economic governance to climate goals requires additional activities across export finance and investment insurance institutions. The new research project initiated by Oxford University, ClimateWorks Foundation, and Mission 2020 including other practitioners and academics from institutions such as Atradius DSB, Columbia University, EDC, FMO and Offenburg University focuses on reshaping future trade and investment governance in light of climate action. The idea of a ‘Berne Union Net Zero Club’ is an important item in a potential package of reforms. This can include realigning mandates and corporate strategies, principles of intervention, as well as ECA, Exim-Bank and PRI operating models in order to accelerate net zero transformation. Full transparency regarding Berne Union members’ activities would be an excellent starting point. We invite all interested parties in the sector to come together to chart our own path to net zero
Künstliche Intelligenz gilt immer noch als eine der zukunftsweisenden Technologien, die viele Bereiche wie etwa Medizin, Handel, Verkehr und öffentliche Verwaltung revolutioniert. So scheint es nicht verwunderlich, dass bereits knapp jedes fünfte Unternehmen in Deutschland zurzeit KI-Systeme implementiert oder zumindest ihren Einsatz plant. Besonders hoch im Kurs stehen KI-Projekte, um Daten zu analysieren. Ganze 70 Prozent der Unternehmen sehen hier das größte Potenzial, so die Ergebnisse einer Umfrage von PWC [1]. Dennoch lauern einige Stolpersteine, wollen Unternehmen intelligente Datenprojekte umsetzen. Welche Hürden auftauchen können und wie sich diese meistern lassen, erläutert dieser Artikel anhand eines KI-Projektes zur Analyse von Geschäftspartnerdaten [2].
Generative convolutional deep neural networks, e.g. popular GAN architectures, are relying on convolution based up-sampling methods to produce non-scalar outputs like images or video sequences. In this paper, we show that common up-sampling methods, i.e. known as up-convolution or transposed convolution, are causing the inability of such models to reproduce spectral distributions of natural training data correctly. This effect is independent of the underlying architecture and we show that it can be used to easily detect generated data like deepfakes with up to 100% accuracy on public benchmarks. To overcome this drawback of current generative models, we propose to add a novel spectral regularization term to the training optimization objective. We show that this approach not only allows to train spectral consistent GANs that are avoiding high frequency errors. Also, we show that a correct approximation of the frequency spectrum has positive effects on the training stability and output quality of generative networks.
Vulnerabilitätsanalyse "Hitzestress und menschliche Gesundheit" am Beispiel der Stadt Reutlingen
(2020)
In diesem Modellprojekt wird das Schutzgut "Menschliche Gesundheit" insbesondere unter dem Gesichtspunkt der im Rahmen des globalen Klimawandels zu erwartenden Überhitzung der Städte ("städtische Hitzeinseln") betrachtet.
In der Großstadt Reutlingen ("Tor zur Schwäbischen Alb/112.500 EW) mit ihrer Pfortenlage am Rande der Schwäbischen Alb und der Höhenlage (400-800 m) sowie der Bebauungsdichte werden bis 2050 bzw. 2100 (Strategie zur Anpassung an den Klimawandel Baden-Württemberg - Vulnerabilitäten und Klimaanpassungsmaßnahmen, 2015) die massivsten Auswirkungen bezüglich Aufenthaltsbehaglichkeit und Gesundheitsfolgen in Reutlingen erwartet.
Der Untersuchungsschwerpunkt liegt im Wirkungsbereich Mensch-Siedlung, d.h. in der Betrachtung von empfindlichen Bevölkerungspopulationen (z.B. ältere Menschen) und hitzeempfindlichen Nutzungsstrukturen (z.B. verdichteten städtischen Siedlungsflächen). Insbesondere die bereits in der abgeschlossenen Gesamtstädtischen Klimaanalyse ermittelten überwärmten Areale ("hot spots") und die im Rahmen des Klimawandels für 2020-2050 zukünftig zu erwartende Hitzestressbelastung bei empfindlichen Bevölkerungsgruppen in Stadtquartieren und Funktionsbauten, stehen im Zenit der Untersuchung.
Dabei wird über das Kriterium Empfindlichkeit (Basis sind z.B. quartierbezogene Datenstrukturen von Älteren, Einrichtungen wie Krankenhäuser, Kinderpflegeeinrichtungen, Alten- Behinderten- und Pflegeheime) die zukünftige Hitzestress-Belastung für Reutlingen erarbeitet. Weiteres wichtiges Kriterium ist die Betroffenheit nach Standortsituation (Höhenlage, Durchlüftungsverhältnisse, Bioklima/PMV = Maß für die bioklimatische Behaglichkeit) und die Anzahl hitzestressgeplagter Menschen (Kinder, Kranke, Ältere). Insbesondere für das Szenarium 2020 bis 2050 (s. Strategie zur Anpassung an den Klimawandel Baden-Württemberg - Vulnerabilitäten und Klimaanpassungsmaßnahmen, 2015) werden objekt- bzw. einrichtungsbezogen (z.B. Altenpflegeeinrichtungen) sowie quartiersspezifisch (Stadtstrukturtypen) die Auswirkungen bzw. Verwundbarkeiten erarbeitet. Dieser objektspezifische (bauklimatische) Ansatz, die innovative Indikatorenbildung zur situativen kommunalen Anwendbarkeit auch über Reutlingen hinaus sowie der partizipative Ansatz mit Nichtregierungsorganisationen (NGO´s) begründet den Modellcharakter ("Reutlinger Modell") dieser Untersuchung. Das Modellprojekt bildet das zweite Modul in einem dreiteiligen Klimaanpassungskonzept für die Stadt Reutlingen.
Mit der Implementierung sowie einer anschließenden aussagekräftigen Evaluierung, soll das, visuelle-inertiale Kartierungs- und Lokalisierungssystem maplab analysiert werden. Hierbei basiert die Kartierung bzw. Lokalisierung auf der Detektion von Umgebungsmerkmalen. Neben der Möglichkeit der Kartenerstellung besteht ferner die Option, mehrere Karten zu fusionieren und somit weitreichende Gebiete zu kartieren sowie für weitere Datenauswertungen zu nutzen. Aufgrund der Durchführung und Bewertung der Ergebnisse in unterschiedlichen Anwendungsszenarien zeigt sich, dass maplab besonders zur Kartierung von Räumen bzw. kleinen Gebäudekomplexen geeignet ist. Die Möglichkeit der Kartenfusionierung bietet weiterhin die Option, den Informationsgehalt von Karten zu erhöhen, welches die Effektivität für eine anschließende Lokalisierung steigert. Bei wachsender Kartierungsgröße hingegen zeigt sich jedoch eine Vergrößerung geometrischer Inkonsistenzen.
Multiple Object Tracking (MOT) is a long-standing task in computer vision. Current approaches based on the tracking by detection paradigm either require some sort of domain knowledge or supervision to associate data correctly into tracks. In this work, we present an unsupervised multiple object tracking approach based on visual features and minimum cost lifted multicuts. Our method is based on straight-forward spatio-temporal cues that can be extracted from neighboring frames in an image sequences without superivison. Clustering based on these cues enables us to learn the required appearance invariances for the tracking task at hand and train an autoencoder to generate suitable latent representation. Thus, the resulting latent representations can serve as robust appearance cues for tracking even over large temporal distances where no reliable spatio-temporal features could be extracted. We show that, despite being trained without using the provided annotations, our model provides competitive results on the challenging MOT Benchmark for pedestrian tracking.
Africa was the last region to witness significant spread of the COVID-19. Nonetheless, it was expected that the continent would be hardest hit due to the fragility of its health and social infrastructure as well as the vulnerability of its economies. While the rates of infection and death were initially relatively low and contained economically, the continent was hard hit early on. Cuts in credit and trade services by international banks, along with a decline in export earnings, tourism receipts, and inward remittances, have severely constrained the ability of African countries to finance imports of essential goods and to service maturing debt obligations.
However, Africa has over time created mechanisms and institutions to help cushion its economies from the adverse consequences of global shocks. Among these institutions is Afreximbank, which emerged out of the debt crisis of the 1980s. This paper presents an overview of the Bank’s support to African countries in dealing with two major derivatives of the COVID-19 pandemic: the trade finance challenges resulting from cuts in international financial flows to the continent, and the health consequences of the pandemic.
Bei vielen Marketingthemen geht es nicht nur um die Vermittlung eines konkreten Kundennutzens, mit dem aufgezeigt wird, welches Problem mit dem beworbenen Produkt – seien es nun Sachgüter oder Dienstleistungen – gelöst werden kann, sondern um die emotionale Ansprache der Zielgruppen. Dabei ist es keineswegs nur eine Kommunikationsaufgabe, sondern die Produktkonzeption und die Gesamtausrichtung des Marketings verändern sich so, dass eine Teilhabe am Produkt, der Produktentwicklung und der Produktidee möglich wird.
Silicon (Si) has turned out to be a promising active material for next‐generation lithium‐ion battery anodes. Nevertheless, the issues known from Si as electrode material (pulverization effects, volume change etc.) are impeding the development of Si anodes to reach market maturity. In this study, we are investigating a possible application of Si anodes in low‐power printed electronic applications. Tailored Si inks are produced and the impact of carbon coating on the printability and their electrochemical behavior as printed Si anodes is investigated. The printed Si anodes contain active material loadings that are practical for powering printed electronic devices, like electrolyte gated transistors, and are able to show high capacity retentions. A capacity of 1754 mAh/gSi is achieved for a printed Si anode after 100 cycles. Additionally, the direct applicability of the printed Si anodes is shown by successfully powering an ink‐jet printed transistor.
The coronavirus affects the strongly export-oriented Swiss economy in a situation where political and economic developments are already making the cross-border exchange of goods and services difficult. For this reason, the question arises of how Switzerland can maintain or strengthen its position in global competition in the export business during an unprecedented period of crisis such as the current one.
In order to find an answer to this question, this paper critically examines the existing government support measures for Swiss exporters in times of COVID-19. The fact that Switzerland has so far not taken any specific support measures for exporters raises the actual research question of whether there is a specific necessity and demand for a special export promotion. To answer this research question, various expert opinions are compared and overall conclusions are drawn. By rapidly introducing and adapting the already existing instruments – liquidity assistance and an expansion of short-time work benefits – the federal government was able to ensure the survival of many companies. According to the authors of this paper, this focus of government support in times of crisis is just right for a small national economy in the short term and therefore preferable to a specific support of exporters. Nevertheless, given the high relative importance of foreign trade for Switzerland’s overall economic performance, there can be no recovery of national economy without a recovery of foreign trade.
Supporting the COVID-19 response in Asia and the Pacific—The role of the Asian Development Bank.
(2020)
The COVID-19 pandemic has affected all countries of the Asia Pacific region over the last few months with far reaching economic, health and social consequences. To counter the impact, governments have accelerated their health spending and announced large macroeconomic stabilization and stimulus policy packages. As with past disasters and crises in the region, the Asian Development Bank has reacted with a number of targeted support interventions since the very early stages of the outbreak. In mid- April 2020, the Bank then put forward a comprehensive COVID-19 Response Package totalling $20 billion to support its member countries which rests on four pillars.
The last few months have proven that multilateral development banks like the Asian Development Bank have the ability to respond quickly and to mobilize significant resources for a global emergency like COVID-19. Whilst this financial supported is urgently needed at this point, attention will need to be paid on how debt sustainability for low- and middle-income countries can be ensured in the coming years. Given the unprecedented scale of and uncertainty around the COVID-19 pandemic, it may offer a window of opportunity to redesign the way developmental finance is coordinated and the way it is delivered. This also includes a chance to “build back better” and to focus on a sustainable, resilient and green recovery.
Strings
(2020)
This article presents the currently ongoing development of an audiovisual performance work with the title Strings. This work provides an improvisation setting for a violinist, two laptop performers, and two generative systems. At the core of Strings lies an approach that establishes a strong correlation among all participants by means of a shared physical principle. The physical principle is that of a vibrating string. The article discusses how this principle is used in both natural and simulated forms as main interaction layer between all performers and as natural or generative principle for creating audio and video.
Alle drei Anträge argumentieren technikdeterministisch, als sei (Digital)Technik mehr als ein mögliches, nicht notwendiges Hilfsmittel im Unterricht. Seit über 30 Jahren wird jede neue Geräte-Generation (PC, Laptops, heute Tablets) mit identischen Argumenten (innovativ, modern, motivationsfördernd) für den Einsatz im Unterricht reklamiert. Doch entscheidend für Lernerfolge und Bildungsprozesse sind die Lehrer-Schülerbeziehung, die direkte Interaktion zwischen Lehrenden und Lernenden und die Sozial- und Klassengemeinschaft, nicht die technische Ausstattung von Schulen. Lernprozesse in Bildungseinrichtungen beruhen auf dem sozialen Miteinander und wechselseitigem Vertrauen. Lernen ist ein individueller und sozialer Prozess, kein technischer Vorgang. Kein Mensch lernt digital.
Keiner der Anträge unterscheidet nach dem Alter der Schülerinnen und Schüler als dem entscheidenden Kriterium für den Einsatz von Medientechnik im Unterricht. Stattdessen wird technikeuphorisch einer zunehmenden Automatisierung des Beschulens und Testens das Wort geredet (Lernsoftware, Lernmanagementsysteme, Lernprofile u.a.). Stand der Wissenschaft (einschließlich der Erfahrungen mit Covid-19 und erzwungenen Schulschließungen) ist aber, dass Präsenzunterricht das oberstes Primat der Schulen sein muss. Schulen sind die Orte des sozialen Miteinander und Schutzraum gerade für sozial Benachteiligte. Das Ziel sind Lern- und Verstehensprozesse der Schülerinnen und Schüler, die Entwicklung ihrer Persönlichkeit und ihre Bildungschancen, nicht quantitative Vergleiche über die technische Ausstattung von Schulen in anderen Bundesländern oder dem Ausland. Pädagogisch argumentierend würde nicht auf digitale Medien(technik) verkürzt; es würden analoge wie technische Medien gleichwertig einbezogen. Ob und ggf. für was man Digitaltechniken altersangemessen und ohne Rückkanal (!) für Nutzerdaten einsetzen kann, ist hingegen erst durch ergebnisoffene Studien zu belegen. Was in allen Anträgen fehlt, ist daher ein klares Verbot der Profilierung Minderjähriger.
Wer darüber hinaus das Ziel der digitalen Transformation der gesamten Gesellschaft mit dem Ziel der digitalen Organisation aller Lebensbereiche kennt, weiß, dass wir IT erst neu denken und alternative Infrastrukturen aufbauen müssen, bevor Digitaltechnik in Schulen einsetzbar wird. Datensparsamkeit und Dezentralisierung, Hoheit über die eigenen Daten und DSGVO-konforme Systeme sind zukunftsweisende Stichworte für IT in Schulen, nicht EdTech als Big Business der Global Education Industries (GEI).
This essay deals with the Spanish economy and especially with the Spanish governmental measures for SME exporters in times of COVID-19. The focus was set on SMEs, as they are an essential part of trade for the government and are particularly affected by the pandemic. Since the financial crisis, the Spanish economy has become highly diversified, with a greater focus on exports. Competitiveness, productivity and efficiency have increased significantly. The Spanish government measures largely affect the areas liquidity and financing, taxes and protection of the employment. One of the most important measures is the 100-billion-euro credit line and the policies on unemployment. The Spanish government is dependent on further aid packages and is criticized for the measures.
Sollen soziale Roboter Teil unserer Gesellschaft werden?
Eingebettet in eine spannende Kriminalgeschichte vermittelt der Wissenschaftscomic von Oliver Korn und Jonas Grund den aktuellen Stand und Ausblick der Wissenschaft auf Social Robots.
Die Geschichte spielt in der nahen Zukunft: In einem internationalen Projekt erforschen Wissenschaftler die Anforderungen an soziale Roboter für den Gesundheitsbereich. Kurz bevor der Prototyp eines Pflegeroboters in einer Feldstudie zum Einsatz kommt, verschwindet er spurlos. In ihrem ersten großen Fall begibt sich die junge Kommissarin Kira auf eine Reise in die Welt der Wissenschaft. Dabei lernt sie viel über soziale Roboter, KI und die Welt internationaler wissenschaftlicher Kooperationen. Immer wieder kommen kritische Stimmen zu Wort: Anti-Roboter-Aktivisten protestieren gegen Automatisierung und ein Schwinden von Menschlichkeit und Empathie. Selbst in der Familie der Kommissarin wird die mögliche Pflege älterer Menschen durch Roboter kontrovers diskutiert.
Übergreifendes Ziel ist es, über alle Altersstufen hinweg Wissen aufzubauen, damit die Vor- und Nachteile dieser neuen Technologien kontrovers, aber kenntnisreich diskutiert werden können. „Soziale Roboter – ein Science Comic“ ist ein Beitrag zu einer informierten Diskussion in den Feldern Robotik, künstliche Intelligenz, Ethik und Politik und damit auch als Lehr- und Lernmittel geeignet.
Der Comic wurde für Jugendliche und Erwachsene konzipiert und gestaltet. Insbesondere aber für jene, die bisher kaum in Berührung mit sozialen Robotern und künstlicher Intelligenz gekommen sind. Eine weitere Zielgruppe sind im Gesundheitswesen tätige Personen, denn die Betreuung und Pflege älterer Menschen gelten als einer der zukünftig wichtigsten Anwendungsbereiche für soziale Roboter.
DINA4 Hochformat, Hardcover Fadenheftung, erschienen in Deutsch und Englisch. Herausgegeben im Selbstverlag Affective & Cognitive Institute (ACI), Hochschule Offenburg
Should social robots become part of our society?
Embedded in an exciting crime story, the science comic by Oliver Korn and Jonas Grund conveys the current state and outlook of science on social robots.
The story takes place in the near future: In an international project, scientists are researching the requirements for social robots for the health sector. Shortly before the prototype of a nursing robot is used in a field study, it disappears without a trace. In her first major case, the young inspector Kira embarks on a journey into the world of science. In the process, she learns a lot about social robots, AI and the world of international scientific cooperation. Again and again, critical voices are heard: anti-robot activists protest against automation and a dwindling of humanity and empathy. Even in the Commissioner's family, the possible care of elderly people by robots is controversially discussed.
The overarching goal is to build knowledge across all age groups so that the advantages and disadvantages of these new technologies can be discussed controversially but knowledgeably. "Social Robots - a Science Comic" is a contribution to an informed discussion in the fields of robotics, artificial intelligence, ethics and politics and is thus also suitable as a teaching and learning tool.
The comic was conceived and designed for young people and adults. In particular, however, for those who have hardly come into contact with social robots and artificial intelligence so far. Another target group are people working in the health care sector, because the care and nursing of elderly people are considered to be one of the most important areas of application for social robots in the future.
DINA4 portrait format, hardcover thread stitching, published in German and English. Self-published by the Affective & Cognitive Institute (ACI), Offenburg University.
The COVID-19 pandemic has led to an economic downturn in the Slovak Republic. To bridge corporate liquidity problems the Slovakian Government has introduced several support measures. The investigation discusses the effectiveness of the measures imposed. Based on theoretical foundations, the research question is empirically examined by using a qualitative expert survey. As the automotive industry plays a leading role in Slovakia, the research conducted is oriented towards the financing phases, a typical automotive exporter is undergoing. As a result of the research, bridging loans and government grants were identified as the most important measures. Additionally, tendencies towards political recommendations for action were identified. The research explored, that the Slovakian Government should focus on meeting the short-term liquidity needs, boosting exports and promoting innovation as well as considering a support package for the automotive industry.
Die transösophageale Neurostimulation ist eine neue Therapieform und könnte unter anderem zur Schmerzlinderung während einer transösophagealen Linksherzstimulation angewendet werden. Sie ist in die Kategorie der Rückenmarksstimulation (SCS) einzuordnen, die die meist verwendete Technik der Neurostimulation ist. Die derzeit auf dem Markt vorhandenen Ösophaguskatheter werden bei einer elektrophysiologischen Untersuchung mit Ablation und transösophagealer Echokardiographie zur Temperaturüberwachung eingesetzt. Das Ziel dieser Arbeit war, das vorhandene Offenburger Herzrhythmusmodell, um die Wirbelsäule zu erweitern, einen neuen Ösophagus-Elektroden- Katheter für die transösophageale elektrische Stimulation des Rückenmarks zu modellieren und mittels 3D-Computer-Simulationen auf Ihre Wirksamkeit zu untersuchen.
Schlussbericht IntelliKOMP
(2020)
Im Rahmen des Verbundprojektes IntelliKOMP sollten smarte Werkzeughalter und Spannfutter für Werkzeugmaschinen im Hinblick auf Industrie 4.0 entwickelt werden. Durch eine hochintegrierte Elektronik in den peripheren Maschinenkomponenten soll mittels Sensoren eine Datenerfassung, -verarbeitung und drahtlose -übertragung erfolgen. Durch diese Daten soll bspw. eine prädiktive Wartung ermöglicht werden.
Die Erfindung betrifft eine Schaltungsanordnung (10) für ein Kraftfahrzeug, mit einer Hochvolt-Batterie (12) zum Speichern von elektrischer Energie, mit wenigstens einer elektrischen Maschine (14) zum Antreiben des Kraftfahrzeugs, mit einem Stromrichter (16), mittels welchem von der Hochvolt-Batterie (12) bereitstellbare Hochvolt-Gleichspannung in Hochvolt-Wechselspannung zum Betreiben der elektrischen Maschine (14) umwandelbar ist, und mit einem Ladeanschluss (20) zum Bereitstellen von elektrischer Energie zum Laden der Hochvolt-Batterie (12), wobei der Stromrichter (16) als ein Drei-Stufen-Stromrichter ausgebildet ist und wenigstens eine einer Phase (u) der elektrischen Maschine (14) zugeordnete Schaltereinheit (46) aufweist, welche zwei in Reihe geschaltete Schaltergruppen (52, 54) umfasst, die jeweils zwei in Reihe geschaltete IGBTs (T11, T12, T13, T14) aufweisen, wobei zwischen den IGBTs (T11, T12) einer der Schaltergruppen (52, 54) ein Anschluss (64) angeordnet ist, welcher direkt mit einer Leitung (34) des Ladeanschlusses (20) elektrisch verbunden ist.
Rudolf E. Kaiser
(2020)
Ecological concerns on the climatic effects of the emissions from electricity production stipulate the remuneration of electricity grids to accept growing amounts of intermittent regenerative electricity feed-in from wind and solar power. Germany’s eager political target to double regenerative electricity production by 2030 puts pressure on grid operators to adapt and restructure their transmission and distribution grids. The ability of local distribution grids to operate autonomous of transmission grid supply is essential to stabilize electricity supply at the level of German federal states. Although congestion management and collaboration at the distribution system operator (DSO) level are promising approaches, relatively few studies address this issue. This study presents a methodology to assess the electric energy balance for the low-voltage grids in the German federal state of Baden-Württemberg, assuming the typical load curves and the interchange potential among local distribution grids by means of linear programming of the supply function and for typical seasonal electricity demands. The model can make a statement about the performance and development requirements for grid architecture for scenarios in 2035 and 2050 when regenerative energies will—according to present legislation—account for more than half of Germany’s electricity supply. The study details the amendment to Baden-Württemberg’s electricity grid required to fit the system to the requirements of regenerative electricity production. The suggested model for grid analysis can be used in further German regions and internationally to systematically remunerate electricity grids for the acceptance of larger amounts of regenerative electricity inflows. This empirical study closes the research gap of assessing the interchange potential among DSO and considers usual power loads and simultaneously usual electricity inflows.
Sustainable design of equipment for process intensification requires a comprehensive and correct identification of relevant stakeholder requirements, design problems and tasks crucial for innovation success. Combining the principles of the Quality Function Deployment with the Importance-Satisfaction Analysis and Contradiction Analysis of requirements gives an opportunity to define a proper process innovation strategy more reliably and to develop an optimal process intensification technology with less secondary engineering and ecological problems.
In den vergangenen Jahren wurden im Rahmen journalistischer Recherchen immer wieder große Datenmengen zu komplexen Firmenkonstruktionen und globalen Finanztransaktionen veröffentlicht, die dem Waschen illegaler Gelder und dem Verschleiern von Vermögenswerten dienten. Als Beispiele seien hierzu die „Panama Papers“ oder „Paradise Papers“ von 2016 genannt, mit denen zahlreiche Briefkastenfirmen und Finanzgeschäfte in Steueroasen gegenüber der Öffentlichkeit aufgedeckt wurden. Die Recherche der Journalisten ordnete den offenbar illegal erworbenen Vermögenswerten auch prominente Namen zu. Als Folge wurden unter anderem Strafverfahren wegen Steuerhinterziehung eingeleitet. Selbst Minister und Regierungschefs mussten zurücktreten. Auch die Europäische Union wurde in den letzten Jahren immer wieder von Geldwäsche-Skandalen erschüttert. Der mit Abstand umfangreichste Fall ereignete sich in der estnischen Filiale der Danske Bank, welche über Jahre massiv die Sorgfaltspflichten missachtet hatte und so in den Jahren 2007 bis 2015 rund 200 Milliarden Euro aus dubiosen russischen Quellen über die Konten der Bank geflossen sein sollen. Es handelt sich derzeit um den weltgrößten Geldwäscheskandal, der bisher aufgedeckt werden konnte. Auch die Deutsche Bank, die als Korrespondenzbank für das dänische Geldhaus tätig war, soll jahrelang verdächtige Transaktionen im Zusammenhang mit der Dankse Bank nicht offengelegt haben. Ferner hatte im Juli 2018 die Berliner Polizei und Staatsanwaltschaft 77 Immobilien einer kurdisch-libanesischen Großfamilie im Wert von zehn Millionen Euro beschlagnahmt. Durch den Kauf der Gebäude sollen illegale Gelder aus Raub und Drogenhandel gewaschen worden sein. Darüber hinaus hat erst im November 2019 das sog. Hawala-Banking in Deutschland Schlagzeilen gemacht. Mehr als 850 Polizeibeamte aus fünf Bundesländern gingen gegen eine vermutlich international agierende kriminelle Vereinigung vor. Die Behörden ermittelten 27 Beschuldigte, die im großen Stil Bargeld ins Ausland transferiert und so über das Hawala-Bankensystem mehr als 200 Millionen Euro aus illegalen Quellen gewaschen haben sollen.
Short-term load forecasting (STLF) has been playing a key role in the electricity sector for several decades, due to the need for aligning energy generation with the demand and the financial risk connected with forecasting errors. Following the top-down approach, forecasts are calculated for aggregated load profiles, meaning the sum of singular loads from consumers belonging to a balancing group. Due to the emerging flexible loads, there is an increasing relevance for STLF of individual factories. These load profiles are typically more stochastic compared to aggregated ones, which imposes new requirements to forecasting methods and tools with a bottom-up approach. The increasing digitalization in industry with enhanced data availability as well as smart metering are enablers for improved load forecasts. There is a need for STLF tools processing live data with a high temporal resolution in the minute range. Furthermore, behin-the-meter (BTM) data from various sources like submetering and production planning data should be integrated in the models. In this case, STLF is becoming a big data problem so that machine learning (ML) methods are required. The research project “GaIN” investigates the improvement of the STLF quality of an energy utility using BTM data and innovative ML models. This paper describes the project scope, proposes a detailed definition for a benchmark and evaluates the readiness of existing STLF methods to fulfil the described requirements as a reviewing paper.
The review highlights that recent STLF investigations focus on ML methods. Especially hybrid models gain more and more importance. ML can outperform classical methods in terms of automation degree and forecasting accuracy. Nevertheless, the potential for improving forecasting accuracy by the use of ML models depends on the underlying data and the types of input variables. The described methods in the analyzed publications only partially fulfil the tool requirements for STLF on company level. There is still a need to develop suitable ML methods to integrate the expanded data base in order to improve load forecasts on company level.
Communication protocols enable information exchange between different information systems. If protocol descriptions for these systems are not available, they can be reverse-engineered for interoperability or security reasons. This master thesis describes the analysis of such a proprietary binary protocol, named the DVRIP or Dahua private protocol from Dahua Technology. The analysis contains the identification of the DVRIP protocol header format, security mechanisms and vulnerabilities inside the protocol implementation. With the revealing insights of the protocol, an increase of the overall security is achieved. This thesis builds the foundation for further targeted security analyses.
OVVL (the Open Weakness and Vulnerability Modeller) is a tool and methodology to support threat modeling in the early stages of the secure software development lifecycle. We provide an overview of OVVL (https://ovvl.org), its data model and browser-based UI. We equally provide a discussion of initial experiments on how identified threats in the design phase can be aligned with later activities in the software lifecycle (issue management and security testing).
In the work at hand, we state that privacy and malleability of data are two aspects highly desired but not easy to associate. On the one hand, we are trying to shape data to make them usable and editable in an intelligible way, namely without losing their initial information. On the other hand, we are looking for effective privacy on data such that no external or non-authorized party could learn about their content. In such a way, we get overlapping requirements by pursuing different goals; it is trivial to be malleable without being secure, and vice versa. We propose four “real-world” use cases identified as scenarios where these two contradictory features are required and taking place in distinct environments. These considered backgrounds consist of firstly, cloud security auditing, then privacy of mobile network users and industry 4.0 and finally, privacy of COVID-19 tracing app users. After presenting useful background material, we propose to employ multiple approaches to design solutions to solve the use cases. We combine homomorphic encryption with searchable encryption and private information retrieval protocol to build an effective construction for the could auditing use case. As a second step, we develop an algorithm to generate the appropriate parameters to use the somewhat homomorphic encryption scheme by considering correctness, performance and security of the respective application. Finally, we propose an alternative use of Bloom filter data structure by adding an HMAC function to allow an outsourced third party to perform set relations in a private manner. By analyzing the overlapping bits occurring on Bloom filters while testing the inclusiveness or disjointness of the sets, we show how these functions maintain privacy and allow operations directly computed on the data structure. Then, we show how these constructions could be applied to the four selected use cases. Our obtained solutions have been implemented and we provide promising results that validate their efficiency and thus relevancy.
Modern society is more than ever striving for digital connectivity -- everywhere and at any time, giving rise to megatrends such as the Internet of Things (IoT). Already today, 'things' communicate and interact autonomously with each other and are managed in networks. In the future, people, data, and things will be interlinked, which is also referred to as the Internet of Everything (IoE). Billions of devices will be ubiquitously present in our everyday environment and are being connected over the Internet.
As an emerging technology, printed electronics (PE) is a key enabler for the IoE offering novel device types with free form factors, new materials, and a wide range of substrates that can be flexible, transparent, as well as biodegradable. Furthermore, PE enables new degrees of freedom in circuit customizability, cost-efficiency as well as large-area fabrication at the point of use.
These unique features of PE complement conventional silicon-based technologies. Additive manufacturing processes enable the realization of many envisioned applications such as smart objects, flexible displays, wearables in health care, green electronics, to name but a few.
From the perspective of the IoE, interconnecting billions of heterogeneous devices and systems is one of the major challenges to be solved. Complex high-performance devices interact with highly specialized lightweight electronic devices, such as e.g. smartphones and smart sensors. Data is often measured, stored, and shared continuously with neighboring devices or in the cloud. Thereby, the abundance of data being collected and processed raises privacy and security concerns.
Conventional cryptographic operations are typically based on deterministic algorithms requiring high circuit and system complexity, which makes them unsuitable for lightweight devices.
Many applications do exist, where strong cryptographic operations are not required, such as e.g. in device identification and authentication. Thereby, the security level mainly depends on the quality of the entropy source and the trustworthiness of the derived keys. Statistical properties such as the uniqueness of the keys are of great importance to precisely distinguish between single entities.
In the past decades, hardware-intrinsic security, particularly physically unclonable functions (PUFs), gained a lot of attraction to provide security features for IoT devices. PUFs use their inherent variations to derive device-specific unique identifiers, comparable to fingerprints in biometry.
The potentials of this technology include the use of a true source of randomness, on demand key derivation, as well as inherent key storage.
Combining these potentials with the unique features of PE technology opens up new opportunities to bring security to lightweight electronic devices and systems. Although PE is still far from being matured and from being as reliable as silicon technology, in this thesis we show that PE-based PUFs are promising candidates to provide key derivation suitable for device identification in the IoE.
Thereby, this thesis is primarily concerned with the development, investigation, and assessment of PE-based PUFs to provide security functionalities to resource constrained printed devices and systems.
As a first contribution of this thesis, we introduce the scalable PE-based Differential Circuit PUF (DiffC-PUF) design to provide secure keys to be used in security applications for resource constrained printed devices. The DiffC-PUF is designed as a hybrid system architecture incorporating silicon-based and inkjet-printed components. We develop an embedded PUF platform to enable large-scale characterization of silicon and printed PUF cores.
In the second contribution of this thesis, we fabricate silicon PUF cores based on discrete components and perform statistical tests under realistic operating conditions. A comprehensive experimental analysis on the PUF security metrics is carried out. The results show that the silicon-based DiffC-PUF exhibits nearly ideal values for the uniqueness and reliability metrics. Furthermore, the identification capabilities of the DiffC-PUF are investigated and it is shown that additional post-processing can further improve the quality of the identification system.
In the third contribution of this thesis, we firstly introduce an evaluation workflow to simulate PE-based DiffC-PUFs, also called hybrid PUFs. Hereof, we introduce a Python-based simulation environment to investigate the characteristics and variations of printed PUF cores based on Monte Carlo (MC) simulations. The simulation results show, that the security metrics to be expected from the fabricated devices are close to ideal at the best operating point.
Secondly, we employ fabricated printed PUF cores for statistical tests under varying operating conditions including variations in ambient temperature, relative humidity, and supply voltage. The evaluations of the uniqueness, bit aliasing, and uniformity metrics are in good agreement with the simulation results. The experimentally determined mean reliability value is relatively low, which can be explained by the missing passivation and encapsulation of the printed transistors. The investigation of the identification capabilities based on the raw PUF responses shows that the pure hybrid PUF is not suitable for cryptographic applications, but qualifies for device identification tasks.
The final contribution is to switch to the perspective of an attacker. To judge on the security capabilities of the hybrid PUF, a comprehensive security analysis in the manner of a cryptanalysis is performed. The analysis of the entropy of the hybrid PUF shows that its vulnerability against model-based attacks mainly depends on the selected challenge building method. Furthermore, an attack methodology is introduced to assess the performances of different mathematical cloning attacks on the basis of eavesdropped challenge-response pairs (CRPs). To clone the hybrid PUF, a sorting algorithm is introduced and compared with commonly used supervised machine learning (ML) classifiers including logistic regression (LR), random forest (RF), as well as multi-layer perceptron (MLP).
The results show that the hybrid PUF is vulnerable against model-based attacks. The sorting algorithm benefits from shorter training times compared to the ML algorithms. If the eavesdropped CRPs are erroneous, the ML algorithms outperform the sorting algorithm.
Fast charging of lithium-ion batteries remains one of the most delicate challenges for the automotive industry, being seriously affected by the formation of lithium metal in the negative electrode. Here we present a physicochemical pseudo-3D model that explicitly includes the plating reaction as side reaction running in parallel to the main intercalation reaction. The thermodynamics of the plating reaction are modeled depending on temperature and ion concentration, which differs from the often-used assumption of a constant plating condition of 0 V anode potential. The reaction kinetics are described with an Arrhenius-type rate law parameterized from an extensive literature research. Re-intercalation of plated lithium was modeled to take place either via reverse plating (solution-mediated) or via an explicit interfacial reaction (surface-mediated). At low temperatures not only the main processes (intercalation and solid-state diffusion) become slow, but also the plating reaction itself becomes slower. Using this model, we are able to predict typical macroscopic experimental observables that are indicative of plating, that is, a voltage plateau during discharge and a voltage drop upon temperature increase. A spatiotemporal analysis of the internal cell states allows a quantitative insight into the competition between intercalation and plating. Finally, we calculate operation maps over a wide range of C-rates and temperatures that allow to assess plating propensity as function of operating condition.
Prediction of Claims in Export Credit Finance: A Comparison of Four Machine Learning Techniques
(2020)
This study evaluates four machine learning (ML) techniques (Decision Trees (DT), Random Forests (RF), Neural Networks (NN) and Probabilistic Neural Networks (PNN)) on their ability to accurately predict export credit insurance claims. Additionally, we compare the performance of the ML techniques against a simple benchmark (BM) heuristic. The analysis is based on the utilisation of a dataset provided by the Berne Union, which is the most comprehensive collection of export credit insurance data and has been used in only two scientific studies so far. All ML techniques performed relatively well in predicting whether or not claims would be incurred, and, with limitations, in predicting the order of magnitude of the claims. No satisfactory results were achieved predicting actual claim ratios. RF performed significantly better than DT, NN and PNN against all prediction tasks, and most reliably carried their validation performance forward to test performance.
Zur Herstellung von Spritzgussformeinsätzen kommen in der Regel spanende Verfahren zum Einsatz. In den letzten Jahren hat sich allerdings auch die additive Herstellung dieser Werkzeuge als zweckmäßig erwiesen. In der Produktentwicklung spielt die Agilität heute eine immer wichtigere Rolle. Um mögliche Potentiale des Additive Tooling im Rahmen des Agile Prototyping und um Unterschiede zu den konventionellen Herstellverfahren aufzuzeigen, werden Angebote für die Fertigung mehrerer Formeinsätze durch eine CNC- und HSC-Fertigung, sowie durch additive Herstellung angefragt und hinsichtlich Beschaffungskosten und -zeiten miteinander verglichen. Zudem erfolgt eine Bewertung der technischen Unterschiede. Aus diesen beiden Betrachtungen kann schließlich ein Profil über die drei Herstellverfahren abgeleitet werden, welches bei der anwendungsfallspezifischen Verfahrensauswahl unterstützen soll.
We introduce an open source python framework named PHS-Parallel Hyperparameter Search to enable hyperparameter optimization on numerous compute instances of any arbitrary python function. This is achieved with minimal modifications inside the target function. Possible applications appear in expensive to evaluate numerical computations which strongly depend on hyperparameters such as machine learning. Bayesian optimization is chosen as a sample efficient method to propose the next query set of parameters.
PHOTOPUR hat die Entwicklung eines photokatalytischen Prozesses zur Beseitigung von Pflanzenschutzmitteln (PSM) aus dem Reinigungswasser von Spritzgeräten zum Ziel. Am INES wurde eine Energieversorgung für die photokatalytische Reinigung in zwei Bachelorarbeiten entwickelt und als Demosystem aufgebaut. Das Gesamtsystem ist nun als mobile Einheit verfügbar und wurde zuletzt um das Reaktormodul für den photokatalytischen Prozeß erweitert und den Partnern für intensive Tests übergeben.
In this paper, we describe the PALM model system 6.0. PALM (formerly an abbreviation for Parallelized Large-eddy Simulation Model and now an independent name) is a Fortran-based code and has been applied for studying a variety of atmospheric and oceanic boundary layers for about 20 years. The model is optimized for use on massively parallel computer architectures. This is a follow-up paper to the PALM 4.0 model description in Maronga et al. (2015). During the last years, PALM has been significantly improved and now offers a variety of new components. In particular, much effort was made to enhance the model with components needed for applications in urban environments, like fully interactive land surface and radiation schemes, chemistry, and an indoor model. This paper serves as an overview paper of the PALM 6.0 model system and we describe its current model core. The individual components for urban applications, case studies, validation runs, and issues with suitable input data are presented and discussed in a series of companion papers in this special issue.
In this contribution, we propose an system setup for the detection andclassification of objects in autonomous driving applications. The recognition algo-rithm is based upon deep neural networks, operating in the 2D image domain. Theresults are combined with data of a stereo camera system to finally incorporatethe 3D object information into our mapping framework. The detection systemis locally running upon the onboard CPU of the vehicle. Several network archi-tectures are implemented and evaluated with respect to accuracy and run-timedemands for the given camera and hardware setup.
A new concept for robust non-invasive optical activation of motorized hand prostheses by simple and non-contactcommands is presented. In addition, a novel approach for aiding hand amputees is shown, outlining significantprogress in thinking worth testing. In this, personalized 3D-printed artificial flexible hands are combined withcommercially available motorized exoskeletons, as they are used e.g. in tetraplegics.
Modern Franciscan Leadership
(2020)
This article combines two important areas of practical theology: Monastic rules and leadership in a cloistral organisation, using the Rule of Saint Francis as a prominent example. The aim of this research is to examine how living Christian tradition in a monastic order affects leadership today, discovering how the Rule and Franciscan spirituality impact managing a convent. The research question is answered within this inductive research applying the methodology of the ‘theology in four voices.’ Based on the results, it is possible to build a coherent leadership system based on Biblical and Franciscan sources.
In the past decades, developments in the fields of medicine, new media, and biotechnologies challenged many representations and practices, questioning the understanding of our corporeal limits. Using concrete examples from literary fiction, media studies, philosophy, performance arts, and social sciences, this collection underlines how bodily models and transformations, thought until recently to be only fictional products, have become a part of our reality. The essays provide a spectrum of perspectives on how the body emerges as a transitional environment between fictional and factual elements, a process understood as faction.
The term attribute transfer refers to the tasks of altering images in such a way, that the semantic interpretation of a given input image is shifted towards an intended direction, which is quantified by semantic attributes. Prominent example applications are photo realistic changes of facial features and expressions, like changing the hair color, adding a smile, enlarging the nose or altering the entire context of a scene, like transforming a summer landscape into a winter panorama. Recent advances in attribute transfer are mostly based on generative deep neural networks, using various techniques to manipulate images in the latent space of the generator.
In this paper, we present a novel method for the common sub-task of local attribute transfers, where only parts of a face have to be altered in order to achieve semantic changes (e.g. removing a mustache). In contrast to previous methods, where such local changes have been implemented by generating new (global) images, we propose to formulate local attribute transfers as an inpainting problem. Removing and regenerating only parts of images, our Attribute Transfer Inpainting Generative Adversarial Network (ATI-GAN) is able to utilize local context information to focus on the attributes while keeping the background unmodified resulting in visually sound results.
Learning to Walk With Toes
(2020)
This paper explains how a model-free (with respect to the robot model and the behavior to learn) approach can facilitate learning to walk from scratch. It is applied to a simulated Nao robot with toes. Results show an improvement of 30% in speed compared to a model without toes and also compared to our model-based approach, but with less stability.