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Institute
Towards a Business Process Complexity Analysis Framework Based on Textual Data and Event Logs
(2022)
Die vorliegende Arbeit beschäftigt sich mit der Frage, wie ein E-Learning-Angebot an der Technischen Hochschule Brandenburg das Interesse am Thema der Informationskompetenz steigern sowie diese Kompetenzen entsprechend vermitteln kann. Der Fokus liegt dabei auf zwei quantitativen Umfragen, der Erstellung eines Kurses in Moodle sowie eine Handlungsempfehlung, um die Digitale Lehre an der THB und der Hochschulbibliothek weiter zu etablieren.
Forecasting ist eine wichtige Methode zur Entscheidungsfindung für Unternehmen, Organisationen und Regierungen, da so der Ressourcenverbrauch reduziert werden kann. Der Forecast des prozentualen Marktanteils der neuen BEV-PKW-Zulassungen in Deutschland kann helfen, um strategische und zukunftsorientierte Entscheidungen, z.B. die vom Bund gesetzten Klimaziele, besser steuern zu können. Zur Durchführung des Forecastings wurde der Einsatz unterschiedlicher Machine-Learning-Methoden ausgenutzt.
Es wurden zwei Machine-Learning-Modelle für das Forecasting des prozentualen Marktanteils der BEV-PKW-Neuzulassungen in Deutschland verwendet: Die SARIMA(X)- und DeepAR-Modelle. Aufgrund der Unterschiede in den Eingabedatensätzen wurden vier Modelle der Univariate- und Multivariate- Zeitreihenanalyse trainiert. Mit Hilfe der RMSE-Fehlermetrik wurden die vier trainierten Modelle miteinander verglichen. Die letzten sechs Monate der Eingabedatensätze wurden zur Evaluierung der Modellqualität genutzt.
Die Ergebnisse dieser Masterarbeit zeigen, dass das SARIMAX-Modell zur Erstellung einer Prognose der multivariaten Datensätze die exogenen Variablen benötigt. Allerdings braucht das DeepAR-Modell keine exogenen Variablen, um eine Prognose generieren zu können. Wenn der Eingabedatensatz mindestens 300 Zeitreihen beträgt, eignet sich das DeepAR-Modell besser als das SARIMA(X)-Modell. Das DeepAR-Modell unterstützt nicht nur die univariaten- und multivariaten Datensätze, sondern generiert auch ein globales Modell, wodurch eine Prognose je Variable erstellt wird. Das ist ein großer Vorteil gegenüber dem SARIMA(X)-Modell, welches dazu nicht in der Lage ist.
Diese Arbeit gibt einen Einblick sowie eine Einschätzung eines Code-basierten
Werkzeuges zur Datenvisualierung, der d3js bibliothek für JavaScript. Es
werden nicht nur das Potential, sondern auch die Vor- und Nachteile evaluiert.
Weiterhin wird eine Einschätzung gegeben, wann der Einsatz dieses Werkzeuges
sinnvoll ist. Um diese Einschätzungen treffen zu können, werden einige Di-
agramme, bezüglich der aktuellen Flüchtlichgssituation, die aufgrund des
bewaffneten Ukrainekonfilktes besteht, erstellt. Dafür werden zunächst die
nötigen Grundlagen erklärt. Dies umfasst sowohl Daten und Datentypen,
als auch Diagramme und deren Aufbau. Abschließend werden die erstellten
Diagramme, sowie d3js im Diskussionsteil ausgewertet.
Da d3js in reinem JavaScript implementiert ist, lässt es sich problem-
los mit anderen Frameworks kombinieren. Der Fokus von d3js liegt auf der
schnellen und einfachen Manipulation von Elementen im Document Object
Model. d3js ist jedoch kein Werkzeug, mit dem in wenigen Zeilen Quell-
code ganze Diagramme erstellt werden können. Vielmehr müssen sowohl die
einzelnen Elemente eines Diagrammes, wie auch deren Position und Ausse-
hen händisch definiert werden. Das ermöglicht ein Höchstmaß an Kontrolle
über das Aussehen und Verhalten der Diagramme. Es ist jedoch auch zeitin-
tensiv und führt eventuell zur Implementation unübersichtlicher Diagramme.
Gepaart mit der hohen initialen Lernkurve kann die Nutzung von d3js nur
in speziellen Fällen, welche die volle Kontrolle über Aussehen und Verhalten
von Diagrammen benötigen, empfohlen werden.
In der heutigen Zeit finden Single-Page-Webanwendung immer mehr Verwendung.
Entsprechend dieser Entwicklung wurden Technologien, zur Erstellung von Single-Page-Webanwendungen, angefertigt. Um ihre Unterschiede und individuellen
Anwendungsmöglichkeiten zu ermitteln, wurde mit den drei populärsten
Technologien eine Webanwendung gebaut und eine Evaluation anhand einer Reihe
von Kriterien durchgeführt.
In recent years, the messaging application has been Indonesia’s most widely used mobile app. The number of users of these instant messaging (IM) applications has also been increasing constantly. Unfortunately, research has mentioned that older users often face challenges in using them. Although some papers have created guidelines for designing interfaces for the elderly, these applications are still focused on developing according to the need of young people. In addition, the aging of adults increases their chances of facing some difficulties. Therefore, this thesis aims to give a better understanding of the interface of the mobile instant messaging (MIM) application preferred by its users, specifically Indonesian users. By distributing an online-based survey to 150 Indonesian users of the MIM application, the preferences of several features in the message list and messaging interface of this application are collected. Then, the statistical analysis of the results found that the preferences of both users’ age groups differ. Among them are the button or icon each age group finds more suitable, the bottom bar in the messaging interface, and the placement of action options to be performed to the message they prefer most. Thus, this research also presents design recommendations that both younger and older users prefer.
How do we interact with the digital world in the future by only using our thoughts to interact? To interact with the digital world, we use gestures (most common: swipe gestures), voice, facial expressions and mental commands. The latter has become more important by recent press releases about scientific achievements, for example, from Neuralink [1] using invasive technology to control a computer game by thoughts only [2]. Another study says an application can display text on a screen by just thinking about a word [3]. Currently, BCIs are mainly developed for neurotechnology and healthcare. However, it is a question of time when these services will be available for commercial products for everyday life. (Until then, manufacturers have to minimize health risks and face privacy and safety regulations.) The thesis is that in the future, you will be able to interact with your digital devices just by using your thoughts and you’ll do much faster. This makes sense in many situations where you f. e. do not have a free hand (manufacturing, sports) or cannot speak (underwater). But for such services, you cannot rely on conventional visual design guidelines or interaction patterns, frameworks or libraries. Navigation interacting with a digital service by mental command has a lot of advantages, the human brain comes naturally with some specific features that force us to find a radically new way to interact with digital interfaces. The following study introduces you first into working conditions with mental commands, comparing invasive and non-invasive technologies, and later on comparing several possibilities of interaction patterns for a BCI of everyday usage. [1] Neuralink is a US neurotechnology company founded in July 2016 by Elon Musk and eight other persons. Neuralink’s goal is to develop a device for communication between human brain and computers, a so-called brain-computer-interface(BCI). [2] The Guardian, Fr. 9th April 2021 “Elon Musk startup shows monkey with brain chip implants playing video game”. https://www.theguardian.com/technology/2021/apr/09/elon-musk- neuralink-monkey-video-game . [3] Scientific American, 15th July 2021, Neuroscience, author Emily Willingham: “New Brain Implant Transmits Full Words from Neural Signals”.
Companies are increasingly facing the challenges of a persistent cyber threat landscape. By means of AI, cyber attacks can be efficiently conducted more successful through offensive AI. As for cyber defense, AI can be also utilized against cyber threats (defensive AI). Due to limited resources, especially in small and medium-sized companies (SMEs), there is a need to deploy more effective defensive cyber security solutions. Precisely, the adaptation of AI-based resilient defenses must be driven forward. Therefore, the aim of this paper is to identify and evaluate AI-related use cases with a high impact potential on the cyber security level, while being applicable to SMEs at the same time. In order to reach the research goal, an extensive literature review of several online catalogs, surveys and online platforms was conducted. In conclusion, seven crucial AI-based security features were outlined that are providing a high impact potential to the security level for SMEs. Afterwards, the results are discussed and set into a broader context. Even though AI-based security solutions are providing a large range of advantages, certain challenges and barriers using AI-related security applications are addressed in the paper as well. A high need for usable state of the art AI based cyber security solution for SMEs was identified.
Biomass gasification is recognized as a viable avenue to accelerate the sustainable production of hydrogen. In this work, a numerical simulation model of air gasification of rice husks is developed using the Aspen Plus to investigate the feasibility of producing hydrogen-rich syngas. The model is experimentally validated with rice husk gasification results and other published studies. The influence of temperature and equivalence ratio on the syngas composition, H2 yield, LHVSyngas, H2/CO ratio, CGE, and PCG was studied. Furthermore, the synchronized effects of temperature and ER are studied using RSM to determine the operational point of maximizing H2 yield and PCG. The RSM analysis results show optimum performance at temperatures between 820 °C and 1090 °C and ER in the range of 0.06–0.10. The findings show that optimal operating conditions of the gasification system can be achieved at a more refined precision through simulations coupled with advanced optimization techniques.
Single dielectric microspheres can manipulate light focusing and collection to enhance optical interaction with surfaces. To demonstrate this principle, we experimentally investigate the enhancement of the Raman signal collected by a single dielectric microsphere, with a radius much larger than the exciting laser spot size, residing on the sample surface. The absolute microsphere-assisted Raman signal from a single graphene layer measured in air is more than a factor of two higher than that obtained with a high numerical aperture objective. Results from Mie’s theory are used to benchmark numerical simulations and an analytical model to describe the isolated microsphere focusing properties. The analytical model and the numerical simulations justify the Raman signal enhancement measured in the microsphere-assisted Raman spectroscopy experiments.
4.1.: Grundlagen
(2022)
Due to the increasing number of complaints alleging privacy violations against companies to data protection authorities, the translation of business goals to system design goals and the subsequent consequences for customers’ privacy poses a challenge for many companies. For this reason, there is a need to bridge the economics of privacy and threats to privacy. To this end, our work relies on the concept of privacy as contextual integrity. This framework defines privacy as appropriate information flows subjected to social norms within particular social contexts or spheres. In this paper, we introduce a preliminary version of a semantic model which aims to relate and provide understanding on how well-established business goals may affect their customers’ privacy by designing IoT devices with permission access, data acquired by sensors, among other factors. Finally, we provide a use case application showing how to use the semantic model. The model aims to be an educational tool for professionals in business informatics during the modeling and designing process of a product which may gather sensitive data or may infer sensitive information, giving an understanding of the interaction of the product and its footprint with diverse actors (humans or machines). In the future, a further complete model of the presented may also target other groups, such as law enforcement bodies, as part of their educational training in such systems.