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Subject of the thesis at hand is the analysis of symmetric block ciphers with a block length of 32 bit. It is meant to give a comprising overview over the topic of 32 bit block ciphers. The topic is divided in the examination of three questions. It contains a list of state of the art block ciphers with a block length of 32 bit. The block ciphers are being described, focussing on the encryption function. An SPN-based cipher with 32 bit block length is being proposed by rescaling the AES cipher.
The 32 bit block length results in certain security issues. These so called risk factors are analysed and mitigating measures are proposed. The result of the thesis is, that 32 bit block ciphers can be implemented in a secure manner. The use of 32 bit ciphers should be limited to specific use-cases and with a profound risk analysis, to determine the protection class of the data to be encrypted.
Die vorliegende Masterarbeit analysiert die Problematiken effektiver grafischer Repräsentationen in digitalen Informationssystemen, die mit besonders hoherund dynamischer Datendichte und Datenquellen einhergehen. Anschließend an die Analyse der Problematiken erarbeitet der Autor dieser Forschungsarbeit ein konzeptuelles Modell zur Bewältigung der geschilderten Problematiken, auf Basis von semantisch beschriebenen, wiederverwendbaren grafischen Visualisierungselementen und den ebenfalls semantisch beschriebenen in die Visualisierung zu überführenden Daten. Besonders hervorzuhebende Erkenntnisse dieser Masterarbeit sind die Identifikation von Qualitätskriterien zur Zielführung einer effektiven Visualisierung gemäß der visuellenWahrnehmung des menschlichen kognitiven Systems, die Notwendigkeit zur Erweiterung der Vokabularmenge der schema.org-Ontologie zur Anwendung der identifizieren Qualitätskriterien und das Auffinden geeigneter Visualisierungselemente sowie das Zuordnen der Daten zu entsprechenden Visualisierungselementen über den Aufbau und Vergleich einer Baumstruktur für sowohl die Daten als auch die der Visualisierungselemente. Diese Forschungsarbeit ist von besonderer Relevanz für Entscheider, Projektmanager und Softwareentwickler, die digitale Informationssysteme mit einer hohen Anzahl an heterogenen Datensätzen und Datenquellen entwickeln.
In this thesis, new methods for text classification are examined and compared to the current software of the DNB. Due to technical changes in the area machine learning in recent years, improvements in text classification have been achieved. The objective is to improve the subject groups allocation of the DNB and to allow a hierarchical classification based on the DDC system. The decision was made on the HDLTex tool, as the structure of the DNB data set and the DDC system, which supports a hierarchical classification, are perfectly designed for it. The use of RNN networks on both hierarchical levels improved the current software situation. Furthermore, the approach was examined, if a combination of the predictions of the two hierarchies levels leads to an additional improvement, which, however, produced a negative result. Both beginners and experts find themselves as readers of this master's thesis in the target group again.
In dieser Arbeit werden neue Verfahren zur Textklassifizierung untersucht und der aktuellen Software der DNB gegenübergestellt. Durch technische Veränderungen im Bereich Machine Learning in den letzten Jahren, konnten Verbesserungen in der Textklassifizierung erzielt werden. Dabei soll die Sachgruppenvergabe der DNB verbessert und anhand des DDC Systems eine hierarchische Klassifizierung ermöglicht werden. Die Entscheidung fiel auf das HDLTex Tool, da die Struktur des Datensatzes der DNB und das DDC System, welche eine hierarchische Klassifizierung unterstützt, perfekt darauf ausgelegt sind. Durch die Nutzung von RNN Netzen auf beiden Hierarchieebenen konnte eine Verbesserung zu der aktuellen Software erzielt werden. Weiterhin wurde der Ansatz untersucht, ob eine Kombinierung der Vorhersagen der beiden Hierarchieebenen zu einer aufbauenden Verbesserung führt, welches jedoch ein negatives Ergebnis hervorbrachte. Sowohl Anfänger als auch Experten finden sich als Leser dieser Masterarbeit in der Zielgruppe wieder.
Corporate debt volumes in emerging market economies have been increasing greatly post 2007-2008 financial crisis. Debt levels have increased across the globe however, the pace is faster in emerging markets than in advance markets. Major countries in emerging economies such as Brazil, Russian Federation, India and China (BRIC) have a large and concentrated share in growing corporate debts. Although, both company specific factors and macro level factors have impacted the corporate borrowings leading to depressed corporate earnings, financial strains and capital outflows in emerging markets the impact of company specific factors is highly pertinent and demands research. The rise in debt levels has affected the return on earnings (ROEs) of the corporate companies which in turn is adversely impacting emerging economy and its financial stability. This paper has empirically tested for the explaining effects of rising corporate debts and changing return on assets (ROAs) on ROEs of emerging market corporate by establishing a multiple regression model. A sample of 100 corporate companies from BRIC countries has been taken to test the model. The test results confirm the importance of corporate debts in predicting ROEs and possible financial strains. Finally, the regression model has been used to estimate ROEs of these corporate companies for the next 5 years with specific recommendation and policy implication to avoid financial crisis.
Die digitale Transformation stellt das Supply Chain Management vor große Herausforderungen. Es muss Antworten und Lösungen finden, um in einem global vernetzten Marktumfeld die Wettbewerbsfähigkeit der Supply Chain sicherzustellen. Das Konzept der Blockchain und der Smart Contracts versprechen großes Potenzial. Gerade im Bereich der Prozessautomatisierung und der Kostensenkung, durch das Entfallen bisher notwendiger Clearingstellen. Allerdings stellt sich auch immer die Frage nach der Datensicherheit und Schutz vor unbefugter Manipulation. Ziel dieser Arbeit ist es Anwendungsmöglichkeiten und Potenziale einer Blockchain und Smart Contracts im Supply Chain Management zu identifizieren und zu beschreiben
In der vorliegenden Masterarbeit wurden verschiedene Ansteuerungsstrategien für den Betrieb von dreiphasigen Active-Neutral-Point-Clamped- (ANPC) Mittelspannungs-Netzumrichtern mit Siliziumkarbid (SiC) Halbleiterschaltelementen untersucht. Durch die Vielzahl an aktiven Schaltelementen können bei der ANPC-Topologie zur Modellierung des gewünschten Ausgangssignals zahlreiche unterschiedliche Ansteuerungsstrategien eingesetzt werden. Je nach gewählter Ansteuerungsstrategie können so unter anderem die Faktoren Schalt- und Durchlassverluste, Wirkungsgrad, Verlustverteilung, Schalter- und Ausgangsschaltfrequenz, der Oberschwingungsanteil des Ausgangssignals, sowie die maximale Spannungsbelastung der Halbleiter beeinflusst werden.
Neben der elektrotechnischen Beschreibung der aktuell eingesetzten Umrichter-Technologien wurden in dieser Arbeit primär aus aktuellen Veröffentlichungen und Dissertationen verschiedene Möglichkeiten für die Ansteuerung von ANPC-Umrichter zusammengetragen und insgesamt sieben Sinus-Pulsweiten-Modulationsstrategien (S-PWM) im Detail untersucht. Hierbei wurde für jede vorgestellte Modulationsstrategie das Grundfunktionsprinzip aufgezeigt und analysiert, sowie die sich daraus ergebenden Vor- und Nachteile herausgearbeitet.
Anschließend wurden alle vorgestellten S-PWM-Strategien in der Schaltungssimulationssoftware PLECS implementiert und diese in verschiedenen Betriebszuständen simuliert. Die Simulation ergab, dass sich bei der ANPC-ALD-Strategie eine bestmögliche Verlustverteilung zwischen den Halbleiterelementen einstellt, bei der ANPC-OOZS-Strategie die geringsten Durchlassverluste entstehen und bei den Strategien ANPC-DF, -12, -R2:1 und -SSLD im Bereich der Nulldurchgänge des Ausgangssignals an den inneren Halbleitern kurzzeitige kritische Überspannungen auftreten. Bei den Strategien ANPC-11-Sync, -ALD und -OOZS treten dagegen keine Überspannungen an den Halbleitern auf.
Ausgehend von diesen Simulationsergebnissen wurden die Strategien ANPC-DF, -ALD und -OOZS für den potentiellen Einsatz in Mittelspannungsumrichtern ausgewählt, auf einem FPGA-Board implementiert und damit eine geeignete Niederspannungstestplattform in Betrieb genommen. Durch praktische Messungen auf dieser Testplattform konnten die Simulationsergebnisse in einem ersten Schritt verifiziert werden. Sowohl das erstellte Simulationsmodell als auch die in Betrieb genommene Testplattform können somit zukünftig für weitere Untersuchungen im Bereich der ANPC-Umrichter-Ansteuerungsstrategien eingesetzt werden.
The aim of this study consists oftwo main objectives: First,to investigatethe penetration and preferences of fintech solutions from the payments sector within the studied population, as well as the elaboration of a forecast for the upcoming years.Second, to examinethe main elements that influence the intention of young customers when deciding to adopt fintech-basedpayment solutions. Existing research has tested several factorsfrom which the variables of trust, transaction efficiency and ease of use are included onthis paper. Additionally,the value-added propositionfrom this studyis represented by the incorporation of sustainability-related purposes into thisanalysiswith the intention of reflecting the increasing presence of efforts to integrate this component within thefinancial industryin recent years.A research model is proposed and tested by including elements based on theTechnology Adoption Model (TAM). By exploring the results of primary data through asurvey with 463 responses from university studentsandexamining secondary sourcesof information, the findings of this study demonstratethat all four tested variables have a positive impact on the intention of using fintech-based payment solutions.Sustainability-related purposes do not play a major role in the decision of using these apps, however, even with a minimal influence, theeffect on intention is positiveand statistically significant. The findings of this study pose important implications for stakeholders within the fintech spectrum whose purposes are related to increasing the intention of young consumers towards using these productsandto provide enoughevidence of the importance of designing incentives that fuel sustainability stewardshipwithin the financial sector.
Population growth, urbanization and climate change are regarded as the megatrends of today's society. This goes hand in hand with a high consumption of resources and pollution. Indeed, these megatrends are mutually reinforcing. A significant part of this is due to mobility in daily life. Technological change such as digitalization, creates innovative concepts to improve mobility and to deal with these changing circumstances. A comprehensive concept in this respect is mobility as a service. This thesis focuses on the identification of the mobility ecosystem and thus on the various stakeholders. First of all, it deals with the definition of mobility as a service in order to identify the ecosystem in particular in the second step. Mobility is classified and analyzed by working on the basis of secondary literature and a quantitative as well as qualitative methodology in expert interviews. This allows conclusions about the relationships, prerequisites and obstacles within the ecosystem and stakeholders.
The results of the thesis suggest that collaboration within the ecosystem is a prerequisite for the implementation of mobility as a service. Furthermore, that mobility as a service should ensure adaptability, since local infrastructures differ between Germany, USA and China, but also within these countries. This adaption process is iterative. The obstacles are interoperability and the willingness to cooperate. Moreover, the results imply that mobility as a service will assert itself more quickly in urban areas due to factors such as the pressure to act and the availability of mobility services as well as the number of customers.
Digital twin as a service : Ressourcenmanagement mit Energiedaten aus cyber-physischen Systemen
(2019)
Die Energiewende führt zu einer Paradigmenänderung. Der Zeitpunkt der Energieabnahme wird sich zunehmend an dem der Energieerzeugung orientierten. Die Steuerung des Energiebedarfs kann durch energieorientierte Produktionsplanung gesteigert werden. Dies erfordert eine Vorhersage des Energiebedarfs. Hierfür wird ein System entwickelt, das eine Modellierung mittels maschinellen Lernens nutzt. Die Datenbasis wird durch eine Vorgehensweise zur Abstrahierung von Fertigungsmaschinen erzeugt. Das System besteht aus gruppierten Microservices, es berücksichtigt die unterschiedlichen Anforderungen der Modelle an die Infrastruktur. Die Modelle sind in digitalen Zwillingen integriert, die als Dienst genutzt werden. Hierdurch ist eine effiziente Adaption von ˜Äderungen an Fertigungsmaschine oder Modell-Methodik möglich. Eine exemplarische Anwendung der Abstraktionsmethode und der Modellierung mittels neuronalen Netzes demonstrieren die Umsetzbarkeit.
The current master thesis makes an effort to investigate relationships between perceived service quality, membership satisfaction, and membership loyalty at “Gesellschaft für technische Kommunikation – tekom Deutschland e.V.”, applying adjusted SERVQUAL model. To attain the formulated objectives in scope of the current research, the “Satisfaction – Profit Chain” model is applied, consisting of “Attribute Performance”, represented by SERVQUAL service quality dimensions supposed to serve as antecedent of the second component of the chain “Membership Satisfaction”, and “Membership Loyalty” in order to investigate relations between these three. The findings of the study are supposed to serve as a basis for altering the existing CRM Strategy in order to eliminate current issues within the association, develop strategic marketing capabilities, and create value for members’ attraction and retention.
Digital Transformation is gradually changing the ways of operating the business. With the advancements and innovations in technology and changing customer preferences, it is essential to adapt to these changes. Digital transformation has the capability to impact nearly every line of business but one of the most significant impact is on Customer Experience. Embracing new technology and processes provides opportunity to create better experience for customers by focussing on automation, self-service, value, quality, customer expectations etc. Advanced systems or solutions that fulfil these requirements can be incorporated in the technology and process landscape of an organization who is supporting customers. This thesis aims at conceptually integrating the Customer Service and Retail Store Support processes at HUGO BOSS into the new Enterprise Service Management (ESM) tool which will in turn drive the digital transformation at HUGO BOSS. Moreover, the purpose of the study is to provide a recommendation if the new ESM tool can replace the existing Retail & Customer Care ticketing tool, thus enabling the Retail & Customer Care team and their respective processes to be fully onboarded and implemented in future into the new tool. This thesis is a qualitative research. At first, qualitative data about the existing ticketing tools used to provide customer service and retail store support is gathered through secondary data collection methods. Secondly, in-depth semi structured interviews with nine respondents from Retail & Customer Care team and IT Support teams were conducted to collect their feedback and analyse the benefits and drawbacks of these tools. Next, the thesis introduces the new ESM tool followed by its evaluation using Fit-Gap Analysis method. Further, the thesis includes the concept of ideal customer service and retail store support processes to be supported by the new tool using process flowcharts. In conclusion, the results of the thesis are presented based on which a future recommendation is provided.
The object of the present master thesis is to understand the environment of the sales channel of Global Projects, its opportunities and challenges for Hansgrohe SE in order to clearly formulate a practicable, medium-term strategy for the period of 2020-2023 for the referred sales channel. A mixed method approach was used in this thesis, using both quantitative and qualitative methods. Raw data such as the channel’s net sales during 2016-2019 were observed from the internal sales system in order to understand the relevance in the past of the different business segments within the sales channel of Global Projects. Also, different external sources such as databases and reports from different consulting firms and international institutions were analyzed in order to determine the sales potential of the different business segments for the period of 2020-2023. A PEST analysis was conducted in order to identify the changes and effects of the external macroenvironment on the company’s strategic position. And finally, a competitor analysis was also conducted in order to identify the strengths and weaknesses of the company’s main competitors and the areas where the company should aim to improve. All previous research and analysis was complemented with expert interviews that were conducted with experts from ten different subsidiaries of the company who are in charge or involved in the sales channel of Global Projects in their respective regions, who helped defining the sales potential of the existing business segments and relevance of new segments that should be considered in order to develop the channel’s strategy. The result of the study suggested that the residential segment will represent the biggest sales potential for the channel followed by the hospitality segment. While there are other segments such as marine, retirement homes and bathroom pods & modular buildings which are expected to gain relevance in the future in some specific regions. As result of all research and analysis conducted throughout this thesis, the strategy and plan for the sales channel of Global Projects for the period of 2020-2023 was designed in line with the company’s strategic position.
All the companies need to plan and budget for future. For planning they need sale forecasting so that accordingly they can manage their supply chain efficiently. Companies do have historical data which can be used for forecasting sale. However, the accuracy of the predictive model depends on the quality of data which is being fed to the model. Poor data quality may result in poor forecasting. Hence, there is need to work on data quality management and to formulate some generic approach for ensuring data quality. Besides, it is also required to detect abnormal sale from the past data, get the reason for those abnormal sale records and remove them from the data. Subsequently, cleaned data can be used to work on predictive modelling which will forecast sales with the most likelihood of near to accurate results. These historical data can be analyzed as a time series data by using as simple time series analysis as ARIMA or by using complicated neural network. Evaluation of these predictive models will help in making a decision of selecting a best fitted model for future forecasting. The thesis aims to work on data quality management of raw data and then analyze time series data to determine predictive model for forecasting. Besides, thesis also aims to understand how data is collected and how organization performs sales processes. This would not only facilitate in finding and bridging the gaps in the business processes but also in preparing the organization for the state-of-the-art technologies to enhance their business for future.
Life insurance penetration rate in Malaysia has been stagnant in the past few years although a few InsurTech companies set up in Malaysia recently. Prior researches on InsurTech fail to clarify the gap of the target customers’ and the insurance experts’ opinions on how to enhance the customer experience in online life insurance with the help of Artificial Intelligence (AI). To address this, a model is recommended based on the literature review on similar articles and survey results conducted on both target customers and insurance experts. The recommended model has four main components: official website by InsurTech companies collaborated with traditional life insurers, customer support, customer service and customer engagement.
Prostate segmentation is an essential part of brachytherapy treatment planning, in order to perform the procedure with required accuracy. Nowadays, segmentation of the prostate is still carried out manually during the planning steps, therefore it is a process that can be tedious, time-consuming and prone to inter-observer error. Much effort has been made in development of an computer-based algorithm that can perform prostate segmentation automatically, but only with appearance of deep learning methods, more promising algorithms emerged. So far, convolutional neural networks demonstrated excellent results in fully automatic prostate segmentation. Development of such an algorithm and training an efficient deep learning model is a challenging task, and requires a lot of optimizations. The objective of this study is development and evaluation of an algorithm for image processing based on deep learning methods that can perform fully automatic segmentation of the prostate gland in transrectal ultrasound images. Additionally, we made an overview of the development process, along with challenges and their solutions and demonstrated an algorithm implemented using Python and Tensorflow library, consisted of preprocessing, augmentation, training and validation, postprocessing and validation steps, which is able to successfully carry out fully automatic prostate segmentation with expert level of accuracy. Finally, we presented our implementation of fully convolutional neural network model and results that are encouraging to continue with model improvements and potential clinical application.
Entrepreneurship research faces a crossroads and a new approach is needed to better understand entrepreneurial behavior. Incorporating neuroscience to comprehend the entrepreneurial mindset seems promising. Nevertheless, the potential of neuroscience for entrepreneurship research is only slowly being realized. Based on an extensive literature review, this thesis examines the emerging role of neuroscience with respect to entrepreneurship. Referring to the model of the entrepreneurial process, this thesis investigates how entrepreneurs discover, exploit, and finally capture opportunities. In this context, explanations regarding trait, expertise, adaptation, and mindset of the entrepreneur are relevant for further examination. Moreover, decision-making in uncertain situations is analyzed. In this context, the dynamic interplay between the reflective and reflexive system is considered. Ultimately, this thesis provides recommendations for organizational innovation to enhance entrepreneurial
activity.
Over the past few decades, there has been an increasing amount of academic literature recognizing the significance of innovation systems. Entrepreneurship is an important component of an innovation system, contributing to the enhancement of regional as well as national innovation. The transfer of knowledge and technology between science and the economy has become particularly important to reinforce overall innovation performance. Today, universities and other institutions of higher education play a crucial role in the system of innovation and have evolved as active and highly relevant participants in the innovation system. Therefore, various supportive measures have been developed to increase the level of innovation at universities and to drive entrepreneurial activities. However, due to the ever-growing entrepreneurial support environment and the great variety of support programs,the distinction between support measures has become unclear. Consequently, the main objective of the present research work is to contribute to the overall understanding of supportive measures at German universities and other institutions of higher education.
Eight experts were interviewed to ensure the compilation of meaningful data. The research findings highlight the importance of a solid network of external experts as well as collaboration with other entrepreneurial institutions. Moreover, the research results indicated that an organizational structure with decentralized decision-making processes and a greater scope of actions enhances operational efficiency. While considering the indistinctness of different support programs and specific terms, although some significant differences were evaluated, overall, the results present a clear tendency toward a more cautious use of specialist terms, therefore substantiating the missing preciseness.
Financial technology, popularly known as Fintech, has disrupted and revolutionized the financial service sector. Today, institutions such as banks are adapting digital transformation with the help of technological devices. There is no doubt that Fintech has transformed the way we bank. Nevertheless, there has been a growing need of understanding the future of financial institution with a holistic approach. Regulatory and governmental support towards maximizing opportunity, minimizing risk, and integrating financial inclusion is needed to accelerate the economy and attain sustainable development.
The following thesis aims to study financial inclusion and how to achieve it in the Fintech industry. It comprises of four areas of influence; market, social, technology and regulatory while emphasizing on the economic development, social progress, uplifting digital finance and robust regulatory system in the globalized financial market. The research aims to close the gap among the regulatory, economic, technological and social aspects of Fintech and then develop a pathway to attain financial inclusion. In addition, the objective of the research is to provide a comprehensive strategic plan towards a prespecified future in finance. This was achieved with the help of normative scenario planning. The result was calculated using scenario planning software INKA 4. The result consisted of four distinct scenarios supporting the pathway to implement financial inclusion in Fintech sector by the year 2030.
Zombie companies are widely discussed ever since the ‘lost decade’ in Japan. The prolonged recession was experienced for almost two decades and in great deal attributed to the zombie companies. The Eurozone is currently in recession and is experiencing a growing incidence of zombie companies. If this trend is not stopped but encouraged by the negative interest rates, there is a possibility for a prolonged recession or even secular stagnation. This study aims to examine the reasons for the emergence and existence of zombie companies in the past. It discusses the implications zombie companies had on the aggregate macroeconomic indicators. In discusses how zombie companies should be treated and whether they must inevitably be foreclosed. To determine the severity of the problem, it examines the incidence of zombie companies in selected industries in the Euro periphery countries based on their interest coverage ratio (ICR). The results show that there is no significant incidence in the selected markets. It concludes whether currently, the zombie companies are a real threat to the economy of the Eurozone. Furthermore, it suggests ways how the problem of zombie companies should be prevented and treated.
In the past decade the world saw an unprecedented economic boom followed by a similar bust. Most economies are still recovering and some experiencing sluggish growth. Various reasons have surfaced as to the cause of this economic boom. However, this paper explores the build-up of excessive debt as a result of financial development in spurring up the economy. This paper identified that the financial deepening coupled with other macro-economic factors have expanded credit in the economy. All sectors accumulated high levels of debt. As part of this study, an analysis of household debt was carried out, using a dataset of 30 European countries in order to ascertain determinants of debt. The results showed that household debt has a statistically significant positive correlation with Gross Domestic Production per capita and Life Expectancy at Birth. Additionally, Gross Savings and Gross Domestic Savings also had a positive correlation. This paper concludes by submitting that financial development should be reset to what it was best at doing in the first place, that is intermediation of finance so that efficiency of investment can be improved. Hence economic development.