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Die im Rahmen dieser Masterarbeit durchgeführte Analyse von Ernährungsumstellungen auf die vegane Ernährung in Form von vier Portraits lotet mit ihrer interdisziplinären Perspektive aus Gastrosophie, Ethnologie und Leibphilosophie die soziokulturellen Aspekte dieser Transmissionsprozesse aus. Dazu gehören der zivilisatorisch erlernte Umgang mit Nahrung, das Umsetzen und Reflektieren sinnlicher Wahrnehmungen im Ernährungsprozess und die Prägung von Relationen zwischen Essendem und Zu-Essendem. Geleitet wird die Analyse dabei von der Forschungsfrage: „Welche leiblich sinnlichen Wahrnehmungen geben den Anstoß zu einer Ernährungsumstellung und wie begleiten diese den Prozess der Umstellung?“. Damit gibt die Frage den Fokus auf das (leibliche) Wahrnehmungsvermögen des Menschen vor und begrenzt Ernährung bewusst nicht auf ihre physiologische Funktion der Energiegewinnung. Dadurch flicht sie sich in den Diskurs um den cultural turn in der Ernährungswissenschaft ein und zielt weg von der metabolischen Durchmessung des Essens, hin auf das Verständnis von Ernährung als Praxis des Sich-Einverleibens-von-Anderem – Essen als Vollzug von Beziehungen. Das Sich-Ernähren wird damit als sozial geprägter und leiblich vermittelter Erfahrungsvorgang sichtbar, der über das Geschmackserlebnis hinaus durch Betroffenheitserfahrung konstituiert wird. Durch das Zusammenbringen philosophischer Perspektiven, wie die der Gastrosophie Harald Lemkes, die Essen u. a. auch als Selbstbestimmung denkt, und soziologischen Theorien, wie die des Habitus-Konzepts nach Pierre Bourdieu, wird deutlich, wie die Wahrnehmungspraxis und -fähigkeit des Menschen, in ihrem leiblichsinnlichen Aspekt, die Verhaltensbestimmung im Umgang mit Nahrung und deren Quellen beeinflusst. Die vier Portraits entstanden während einer sechsmonatigen ethnographischen Feldforschung und stellen anonymisiert die Motivation, den Verlauf und das Konfliktthema der jeweiligen Ernährungsumstellung dar. Die Portraits sind sehr individuell und zeigen auf, wie und warum beispielsweise die gesundheitliche Selbstsorge oder das empathische Mitleiden mit Nutztieren Veränderungen oder Tabuisierungen im Ernährungshandeln anstoßen.
Commonsense reasoning can be seen as a process of identifying dependencies amongst events and actions. Understanding the circumstances surrounding these events requires background knowledge with sufficient breadth to cover a wide variety of domains. In the recent decades, there has been a lot of work in extracting commonsense knowledge, a number of these projects provide their collected data as semantic networks such as ConceptNet and CausalNet. In this thesis, we attempt to undertake the Choice Of Plausible Alternatives (COPA) challenge, a problem set with 1000 questions written in multiple-choice format with a premise and two alternative choices for each question. Our approach differs from previous work by using shortest paths between concepts in a causal graph with the edge weight as causality metric. We use CausalNet as primary network and implement a few design choices to explore the strengths and drawbacks of this approach, and propose an extension using ConceptNet by leveraging its commonsense knowledge base.
A gonioreflectometer is a device to measure the reflection properties of arbitrary materials. In this work, such an apparatus is being built from easily obtainable parts. Therefore three stepper-motors and 809 light-emitting diodes are controlled by an Arduino microcontroller. RGB-images are captured with an industrial camera which serve as refelction data. Furthermore, a control software with several capture programs and a renderer for displaying the measured materials are implemented. These allow capturing and rendering entire bidirectional reflection distribution functions (BRDFs) by which also complex anisotropic material properties can be represented. Although the quality of the results has some artifacts due to shadows of the camera, these artifacts can be largely removed by using special algorithms like inpainting. In addition, the goniorefelctometer is applied to other use cases. One can perform 3D scans, light field capturing and light staging without altering the construction. The quality of these processes also meet the expectations in a positive way. Thus, the gonioreflectometer built in this work can be seen as a widely applicable and economical alternative to other publications.
With the appearance of modern virtual reality (VR) headsets on the consumer market, there has been the biggest boom in the history of VR technology. Naturally, this was accompanied by an increasing focus on the problems of current VR hardware. Especially the control in VR has always been a complex topic.
One possible solution is the Leap Motion, a hand tracking device that was initially developed for desktop use, but with the last major software update it can be attached to standard VR headsets. This device allows very precise tracking of the user’s hands and fingers and their replication in the virtual world.
The aim of this work is to design virtual user interfaces that can be operated with the Leap Motion to provide a natural method of interaction between the user and the VR environment. After that, subject tests are performed to evaluate their performance and compare them to traditional VR controllers.
The status of Business Process Management (BPM) recommender systems is not quite clear as research states. The use of recommenders familiarized itself with the world during the rise of technological evolution in the past decade.Ever since then, several BPM recommender systems came about. However, not a lot of research is conducted in this field. It is not well known to what broad are the technologies used and how are they used. Moreover, this master’s thesis aims at surveying the BPM recommender systems existing. Building on this, the recommendations come in different shapes. They can be positionbased where an element is to be placed at an element’s front, back or to autocomplete a missing link. On the other hand, Recommendations can be textual, to fill the labels of the elements. Furthermore, the literature review for BPM recommender systems took place under the guides of a literature review framework. The framework suggests 5stages of consecutive stages for this sake. The first stage is defining a scope for the research. Secondly, conceptualizing the topic by choosing key terms for literature research. After that in the third stage, comes the research stage.As for the fourth stage, it suggests choosing analysis features over which the literature is to be synthesized and compared. Finally, it recommends defining the research agenda to describe the reason for the literature review. By invoking the mentioned methodology, this master’s thesis surveyed 18 BPM recommender systems. It was found as a result of the survey that there
are not many different technologies for implementing the recommenders. It was also found that the majority of the recommenders suggest nodes that are yet to come in the model, which is called forward recommending. Also, one of the results of the survey indicated the scarce use of textual recommendations to BPM labels. Finally, 18 recommenders are considered less than excepted for a developing field therefore as a result, the survey found a shortage in the number of BPM recommender systems. The results indicate several shortages in several aspects in the field of BPM recommender systems. On this basis, this master’s thesis recommends the future work on it the results.
Current political issues are often reflected in social media discussions, gathering politicians and voters on common platforms. As these can affect the public perception of politics, the inner dynamics and backgrounds of such debates are of great scientific interest. This thesis takes user generated messages from an up-to-date dataset of considerable relevance as Time Series, and applies a topic-based analysis of inspiration and agenda setting to it. The Institute for Web Science and Technologies of the University Koblenz-Landau has collected Twitter data generated beforehand by candidates of the European Parliament Election 2019. This work processes and analyzes the dataset for various properties, while focusing on the influence of politicians and media on online debates. An algorithm to cluster tweets into topical threads is introduced. Subsequently, Sequential Association Rules are mined, yielding wide array of potential influence relations between both actors and topics. The elaborated methodology can be configured with different parameters and is extensible in functionality and scope of application.
Recently the workflow control as well as compliance analysis of the Enterprise Resource Planning systems are of a high demand. In this direction, this thesis presents the potential of developing a Workflow Management System upon a large Enterprise Resource Planning system by involving business rule extraction, business process discovery, design of the process, integration and compliance analysis of the system. Towards this, usability, limitations and challenges of every applied approach are deeply explained in the case of an existing system named SHD ECORO.
Unterschiedliche Quellen (Print-Medien, Fernsehberichte u. Ä.) berichten immer wieder davon, dass es mit der Datenschutzkompetenz bei Kindern und Jugendlichen schlecht bestellt ist. Daher ist dem Thema Datenschutz im Informatikunterricht eine besondere Bedeutung zuzuschreiben.
Im Rahmen der Dissertation von Herrn Hug wird ein Datenschutzkompetenzmodell [Quelle INFOS17] entwickelt, anhand dessen die Datenschutzkompetenz von Schülerinnen und Schülern im Altern von 10 bis 13 Jahren gemessen werden kann.
Im Rahmen dieser Masterarbeit werden existierende Unterrichtsmaterialien zum Thema Datenschutz gesammelt und dazu eine Unterrichtsreihe entwickelt. Hierbei werden auch eigene Zugänge aufzeigt, um ein kohärentes und abgeschlossenes Projekt zu entwerfen, bei dem aktuelle Gefahren für Schülerinnen und Schüler aufgezeigt werden. Ziel ist es, dass die Schülerinnen und Schüler dazu befähigt werden, ihr Verhalten bezüglich Datenschutz besser einzuschätzen und verantwortungsvoller mit ihren persönlichen Daten umzugehen. Im Rahmen eines Feldversuches in einer 6. Klasse eines Gymnasiums wurde die Unterrichtsreihe erprobt.
In this master's thesis the principle of hybrid ray tracing, consisting of a rasterization pipeline which includes ray tracing techniques for certain effects, is explained and the implementation of an application which uses a hybrid approach in which ray tracing is used to calculate shadows, ambient occlusion, and reflections and combines those with direct lighting is documented and explained. Hybrid ray tracing is based on the idea of combining the performance and flexibility of rasterization-based approaches with ray tracing to overcome the limitation of not being able to access the complete surrounding geometry at any point in the scene.
While describing the implementation of said application, the RTX API which is being used for ray tracing is explained as well Vulkan, the graphics API used.
Based on the results and the insights gained while using the RTX API, it is assessed in regards of its usage scenarios and technical sophistication.
Our work finds the fine grained edits in context of neighbouring tokens in Wikipedia articles. We cluster those edits according to similar neighbouring context. We encode neighbouring context into vector space using word vectors. We evaluate clusters returned by our algorithm on extrinsic and intrinsic metric and compare it with previous work. We analyse the relation between extrinsic and intrinsic measurements of fine grained edit tokens.
Most social media platforms allow users to freely express their opinions, feelings, and beliefs. However, in recent years the growing propagation of hate speech, offensive language, racism and sexism on the social media outlets have drawn attention from individuals, companies, and researchers. Today, sexism both online and offline with different forms, including blatant, covert, and subtle lan- guage, is a common phenomenon in society. A notable amount of work has been done over identifying sexist content and computationally detecting sexism which exists online. Although previous efforts have mostly used peoples’ activities on social media platforms such as Twitter as a public and helpful source for collecting data, they neglect the fact that the method of gathering sexist tweets could be biased towards the initial search terms. Moreover, some forms of sexism could be missed since some tweets which contain offensive language could be misclassified as hate speech. Further, in existing hate speech corpora, sexist tweets mostly express hostile sexism, and to some degree, the other forms of sexism which also appear online was disregarded. Besides, the creation of labeled datasets with manual exertion, relying on users to report offensive comments with a tremendous effort by human annotators is not only a costly and time-consuming process, but it also raises the risk of involving discrimination under biased judgment.
This thesis generates a novel sexist and non-sexist dataset which is constructed via "UnSexistifyIt", an online web-based game that incentivizes the players to make minimal modifications to a sexist statement with the goal of turning it into a non-sexist statement and convincing other players that the modified statement is non-sexist. The game applies the methodology of "Game With A Purpose" to generate data as a side-effect of playing the game and also employs the gamification and crowdsourcing techniques to enhance non-game contexts. When voluntary participants play the game, they help to produce non-sexist statements which can reduce the cost of generating new corpus. This work explores how diverse individual beliefs concerning sexism are. Further, the result of this work highlights the impact of various linguistic features and content attributes regarding sexist language detection. Finally, this thesis could help to expand our understanding regarding the syntactic and semantic structure of sexist and non-sexist content and also provides insights to build a probabilistic classifier for single sentences into sexist or non-sexist classes and lastly find a potential ground truth for such a classifier.
This scientific paper deals with the question to which extend the increasing digitization has an impact on work-life balance. Answering this question is the main goal of this study.
To reach this goal a literature review is made, in which it is possible to create a direct correlation between the subjective feel of work-life balance and the perceived stress level. With the help of Antonovsky’s salutogenesis model (1997) from the stress research field, factors are ascertained which determine the perceived stress level and linked with that the perceived work-life balance. These stress-influencing factors are examined through a qualitative content analysis by Mayring (2014) on a base of a problem-centered interview.
The results suggest that the digitization has impact on all these ascertained factors and linked to them on the work-life balance. This shows, that the digitization influences us in almost every aspect of work or private life. Whether this impact is positive or negative towards the work life balance depends on the individual, that assesses this factor. Clear distinctions can be made between people working in an IT-based job and those that do not. In comparison, people with IT-based jobs perceive a substantial better impact of digitization on work-life balance.
Business rules have become an important tool to warrant compliance at their business processes. But the collection of these business rules can have various conflicting elements. This can lead to a violation of the compliance to be achieved. This conflicting elements are therefore a kind of inconsistencies, or quasi incon- sistencies in the business rule base. The target for this thesis is to investigate how those quasi inconsistencies in business rules can be detected and analyzed. To this aim, we develop a comprehensive library which allows to apply results from the scientific field of inconsistency measurement to business rule formalisms that are actually used in practice.
In dieser Arbeit wird eine Unterrichtsreihe beschrieben, welche aus den drei Bereichen „mathematische Relationen“, „Datenbanken in Sozialen Netzwerken“ und „Datenschutz“ zusammengesetzt ist. Zu jedem Bereich wird ein eigener Unterrichtsentwurf präsentiert.
Außerdem wurde im Rahmen der vorliegenden Arbeit ein Programm zur Visualisierung der Relationen des Sozialen Netzwerks Instahub entworfen, welches im Anschluss an die Beschreibung der Unterrichtsreihe aufgeführt wird.
Data visualization is an effective way to explore data. It helps people to get a valuable insight of the data by placing it in a visual context. However, choosing a good chart without prior knowledge in the area is not a trivial job. Users have to manually explore all possible visualizations and decide upon ones that reflect relevant and desired trend in the data, are insightful and easy to decode, have a clear focus and appealing appearance. To address these challenges we developed a Tool for Automatic Generation of Good viSualizations using Scoring (TAG²S²). The approach tackles the problem of identifying an appropriate metric for judging visualizations as good or bad. It consists of two modules: visualization detection: given a data-set it creates a list of combination of data attributes for scoring and visualization ranking: scores each chart and decides which ones are good or bad. For the later, an utility metric of ten criteria was developed and each visualization detected in the first module is evaluated on these criteria. Only those visualizations that received enough scores are then presented to the user. Additionally to these data parameters, the tool considers user perception regarding the choice of visual encoding when selecting a visualization. To evaluate the utility of the metric and the importance of each criteria, test cases were developed, executed and the results presented.
As a result of the technical progress, processes have to be adjusted. On the one hand, the digital transformation is absolutely necessary for every organization to operate efficient and sustainable, on the other hand whose accomplishment is a tremendous challenge. The huge amount of personal data, which accrue in this context, is an additional difficulty.
Against the background of the General Data Protection Regulation (GDPR), this thesis focuses on process management and ways of optimizing processes in a Human Resources Department. Beside the analysis of already existing structures and workflows, data management and especially the handling of personal data in an application process are examined. Both topics, the process management and the data protection are vitally important by itself, but it is necessary to implement the requirements of data protection within the appropriate position of a corresponding process. Relating to this, the thesis deals with the research question of what barriers may occur by a sustainable process integration and to which extend the GDPR prevent an unobstructed workflow within the Human Resources Department of the Handwerkskammer Koblenz. Additionally, answering the question of which subprocesses are convenient for a process automation is highly significant.
In scope of these questions Business Process Management is the solution. By means of the graphical representation standard, Business Process Model and Notation, a process model with the relevant activities, documents and responsibilities of the recruitment process is designed. Based on a target-actual comparison it becomes apparent, that standardized process steps with less exceptions and a large amount of information are basically convenient for automation respectively partial automation. After the different phases of the recruitment process are documented in detail, a Workflow-Management-System can ex-port the transformed models, so the involved employees just have to carry out a task list with assigned exercises. Against the background of the data protection regulations, access rights and maturities can be determined. Subsequently only authorized employees have admission to the personal data of applicants. Because of impending sanctions by violation against the GDPR, the implementation of the relevant legal foundations within the recruitment process is necessary and appropriate. Relating to the defined research questions, it appears that in principle not every activity is appropriate for a process automation. Especially unpredictable and on a wide range of factors depending subprocesses are unsuitable. Additionally, media discontinuities and redundant data input are obstacles to an enduring process integration. Nevertheless, a coherent consideration of the topics of business process management and the data protection regulations is required.