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Suffering from problematic smartphone use? Why not use grayscale setting as an intervention! – An experimental study
No full textIncreasingly, problematic smartphone use behavior (PSU) and excessive consumption are reported. In this study, an experiment was developed to investigate the influence of screen coloration using the grayscale setting on smartphone usage time in repeated measurements. We also investigated how individuals perceived suffering correlates with smartphone usage time and PSU, and whether differences exist by smartphone usage type (social, process, habitual). 240 subjects completed a questionnaire about smartphone usage time, PSU, perceived suffering, and smartphone usage types. Afterward, their smartphones were switched to grayscale setting for at least 24h, and thereafter 92 of these participants completed the second questionnaire. Analyses showed that grayscale setting decreases usage time and that there is a positive correlation between PSU, smartphone usage duration, and perceived suffering. The types of use (process and habitual) influence one’s perceived suffering. Thus, it shows that individuals are aware of their PSU and suffer from it. Using grayscale setting is effective in reducing smartphone use time
Mitteilungsblatt der Universität Koblenz-Landau, Nr. 9/2022
No full textTeilgrundordnung für das Qualitätssicherungssystem nach § 5 HochSchG an der Universität Koblenz
Ordnung zur Qualitätssicherung und -entwicklung in Studium und Lehre an der Universität Koblenz
Sechzehnte Ordnung zur Änderung der Prüfungsordnung für die Prüfung im lehramtsbezogenen Bachelorstudiengang Berufsbildende Schulen an der Universität Koblenz-Landau, der Hochschule Koblenz und der Philosophisch-Theologischen Hochschule Vallendar
Siebzehnte Ordnung zur Änderung der Prüfungsordnung für die Prüfung im lehramtsbezogenen Bachelorstudiengang Berufsbildende Schulen an der Universität Koblenz-Landau, der Hochschule Koblenz und der Philosophisch-Theologischen Hochschule Vallendar
Fünfzehnte Ordnung zur Änderung der Ordnung für die Prüfung im Masterstudiengang Lehramt an berufsbildenden Schulen an der Universität Koblenz-Landau, der Hochschule Koblenz und der Philosophisch-Theologischen Hochschule Vallendar
Sechszehnte Ordnung zur Änderung der Ordnung für die Prüfung im Masterstudiengang Lehramt an berufsbildenden Schulen an der Universität Koblenz-Landau, der Hochschule Koblenz und der Philosophisch-Theologischen Hochschule Vallendar
Sechsundzwanzigste Ordnung zur Änderung der Ordnung für die Prüfung im lehramtsbezogenen
Zertifikatsstudiengang (Erweiterungsprüfung) an der Universität Koblenz-Landau, Campus Koblenz und
der Hochschule Koblenz
Siebenundzwanzigste Ordnung zur Änderung der Ordnung für die Prüfung im lehramtsbezogenen
Zertifikatsstudiengang (Erweiterungsprüfung) an der Universität Koblenz-Landau, Campus Koblenz und
der Hochschule Koblenz
Richtlinie der Universität Koblenz zur Einrichtung, Ausschreibung und Besetzung von Professuren und
Juniorprofessuren (Berufungsrichtlinie)
Satzung und Qualitätssicherungskonzept der Universität Koblenz zur Einrichtung, Ausschreibung und Besetzung von Juniorprofessuren (W1) mit und ohne Tenure-Track sowie zur Besetzung von Professuren
unter Verzicht auf eine Ausschreibung (Tenure-Satzung)
Benutzungsordnung der Universitätsbibliothek
Bibliotheksordnung der Universität Koblen
Mitteilungsblatt der Universität Koblenz-Landau, Nr. 10/2022
No full textTeil-Grundordnung über die Vergabe von Leistungsbezügen sowie Forschungs- und Lehrzulagen der Universität Koblen
Prototyping of a Predictive Process Monitoring Dashboard
Full text linkPredictive Process Monitoring setzt sich als Hilfsmittel zur Unterstützung der betrieblichen Abläufe in Unternehmen immer mehr durch Die meisten heute verfüg-baren Softwareanwendungen erfordern jedoch ein umfangreiches technisches Know-how des Betreibers und sind daher für die meisten realen Szenarien nicht geeignet. Daher wird in dieser Arbeit eine prototypische Implementierung eines Predictive Process Monitoring Dashboards in Form einer Webanwendung vorgestellt. Das System basiert auf dem von Bartmann et al. (2021) vorgestellten PPM-Camunda-Plugin und ermöglicht es dem Benutzer, auf einfache Weise Metriken, Visualisierungen zur Darstellung dieser Metriken und Dashboards, in denen die Visualisierungen angeordnet werden können, zu erstellen. Ein Usability-Test mit Testnutzern mit unterschiedlichen Computerkenntnissen wird durchgeführt, um die Benutzerfreundlichkeit der Anwendung zu bestätigen.Predictive Process Monitoring is becoming more prevalent as an aid for organizations to support their operational processes. However, most software applications available today require extensive technical know-how by the operator and are therefore not suitable for most real-world scenarios. Therefore, this work presents a prototype implementation of a Predictive Process Monitoring dashboard in the form of a web application. The system is based on the PPM Camunda Plugin presented by Bartmann et al. (2021) and allows users to easily create metrics, visualizations to display these metrics, and dashboards in which visualizations can be arranged. A usability test is with test users of different computer skills is conducted to confirm the application’s user-friendliness
Erfolgskriterien für virtuelle Projektteams in der IT-Branche - Eine qualitative Studie relevanter Eigenschaften und Fähigkeiten von Teammitgliedern
Full text linkVirtuelle Teams verbreiten sich weltweit immer mehr. Die Covid-19 Pandemie und die damit verbundene Homeofficepflicht sorgten in nationalen Unternehmen für die Zunahme virtueller Zusammenarbeit. Diese virtuellen Teams bleiben oftmals auch nach Aufhebung der pandemiebedingten gesetzlichen Beschränkungen bestehen. Um eine erfolgreiche Zusammenarbeit in diesen Teams zu erreichen, sind Kenntnisse zu den benötigten Eigenschaften und Fähigkeiten von Teammitgliedern von großer Bedeutung.
Um diese zu untersuchen, werden in dieser Arbeit sieben Experteninterviews mit Teammitgliedern virtueller Projektteams in der IT-Branche geführt und mithilfe qualitativer Inhaltsanalyse ausgewertet. Die ExpertInnen stammen aus drei deutschen Dienstleistungsunternehmen. Die Ergebnisse werden anhand des KSAO-Modells untersucht und nach der deduktiven Zuordnung zu den vier Kategorien „Wissen“, „Fertigkeiten“, „Kompetenzen“ und „Andere Merkmale“ jeweils durch induktive Kategorienbildung in Unterkategorien aufgeteilt. Dabei ergeben sich insgesamt 34 Kategorien, die für die virtuelle Zusammenarbeit relevant sind.
Mit den gewonnenen Erkenntnissen trägt die vorliegende Arbeit einen wichtigen Teil zur Forschung im Bereich der virtuellen Teams bei. Außerdem liefert sie Unternehmen, Führungskräften und dem Personalmanagement Anhaltspunkte für die Bewertung von BewerberInnen, die Auswahl geeigneter Teammitglieder, die Entwicklung von Schulungen und die gezielte Verbesserung virtueller Zusammenarbeit
Wireless communication on the factory floor supporting agile production
No full textThe trends of industry 4.0 and the further enhancements toward an ever changing factory lead to more mobility and flexibility on the factory floor. With that higher need of mobility and flexibility the requirements on wireless communication rise. A key requirement in that setting is the demand for wireless Ultra-Reliability and Low Latency Communication (URLLC). Example use cases therefore are cooperative Automated Guided Vehicles (AGVs) and mobile robotics in general. Working along that setting this thesis provides insights regarding the whole network stack. Thereby, the focus is always on industrial applications. Starting on the physical layer, extensive measurements from 2 GHz to 6 GHz on the factory floor are performed. The raw data is published and analyzed. Based on that data an improved Saleh-Valenzuela (SV) model is provided. As ad-hoc networks are highly depended onnode mobility, the mobility of AGVs is modeled. Additionally, Nodal Encounter Patterns (NEPs) are recorded and analyzed. A method to record NEP is illustrated. The performance by means of latency and reliability are key parameters from an application perspective. Thus, measurements of those two parameters in factory environments are performed using Wireless Local Area Network (WLAN) (IEEE 802.11n), private Long Term Evolution (pLTE) and 5G. This showed auto-correlated latency values. Hence, a method to construct confidence intervals based on auto-correlated data containing rare events is developed. Subsequently, four performance improvements for wireless networks on the factory floor are proposed. Of those optimization three cover ad-hoc networks, two deal with safety relevant communication, one orchestrates the usage of two orthogonal networks and lastly one optimizes the usage of information within cellular networks.
Finally, this thesis is concluded by an outlook toward open research questions. This includes open questions remaining in the context of industry 4.0 and further the ones around 6G. Along the research topics of 6G the two most relevant topics concern the ideas of a network of networks and overcoming best-effort IP
Practices, Networks and Success in Creative Careers: Study of Inequalities using Large-scale Digital Behavioural Data
No full textIn the last decade, policy-makers around the world have turned their attention toward the creative industry as the economic engine and significant driver of employments. Yet, the literature suggests that creative workers are one of the most vulnerable work-forces of today’s economy. Because of the highly deregulated and highly individuated environment, failure or success are believed to be the byproduct of individual ability and commitment, rather than a structural or collective issue. This thesis taps into the temporal, spatial, and social resolution of digital behavioural data to show that there are indeed structural and historical issues that impact individuals’ and
groups’ careers. To this end, this thesis offers a computational social science research framework that brings together the decades-long theoretical and empirical knowledge of inequality studies, and computational methods that deal with the complexity and scale of digital data. By taking music industry and science as use cases, this thesis starts off by proposing a novel gender detection method that exploits image search and face-detection methods.
By analysing the collaboration patterns and citation networks of male and female computer scientists, it sheds lights on some of the historical biases and disadvantages that women face in their scientific career. In particular, the relation of scientific success and gender-specific collaboration patterns is assessed. To elaborate further on the temporal aspect of inequalities in scientific careers, this thesis compares the degree of vertical and horizontal inequalities among the cohorts of scientists that started their career at different point in time. Furthermore, the structural inequality in music industry is assessed by analyzing the social and cultural relations that breed from live performances and musics releases. The findings hint toward the importance of community belonging at different stages of artists’ careers. This thesis also quantifies some of the underlying mechanisms and processes of inequality, such as the Matthew Effect and the Hipster Paradox, in creative careers. Finally, this thesis argues that online platforms such as Wikipedia could reflect and amplify the existing biases.Die Aufmerksamkeit politischer Entscheidungsträger weltweit richtet sich in den letzten 10 Jahren verstärkt auf die Kreativwirtschaft als signifikanter Wachstums- und Beschäftigungsmotor in Städten. Die Literatur zeigt jedoch, dass Kreativschaffende zu den gefährdetsten Arbeitskräften in der heutigen Wirtschaft gehören. Aufgrund des enorm deregulierten und stark individualisierten Umfelds werden Misserfolg oder Erfolg eher individuellen Fähigkeiten und Engagement zugeschrieben und strukturelle oder kollektive Aspekte vernachlässigt. Diese Arbeit widmet sich zeitlichen, räumlichen und sozialen Aspekten digitaler behavioraler Daten, um zu zeigen, dass es tatsächlich strukturelle und historische Faktoren gibt, die sich auf die Karrieren von Individuen und Gruppen auswirken. Zu diesem Zweck bietet die Arbeit einen computergestützten, sozialwissenschaftlichen Forschungsrahmen, der das theoretische und empirisches Wissen aus jahrelanger Forschung zu Ungleichheit mit computergestützten Methoden zum Umgang mit komplexen und umfangreichen digitalen Daten verbindet. Die Arbeit beginnt mit der Darlegung einer neuartigen Methode zur Geschlechtererkennung, welche sich Image Search und Gesichtserkennungsmethoden bedient. Die Analyse der kollaborativen Verhaltensweisen sowie der Zitationsnetzwerke männlicher und weiblicher Computerwissenschaftler*innen verdeutlicht einige der historischen Bias und Nachteile, welchen Frauen in ihren wissenschaftlichen Karrieren begegnen. Zur weiterfuhrenden Elaboration der zeitlichen Aspekte von Ungleichheit, wird der Anteil vertikaler und horizontaler Ungleichheit in unterschiedlichen Kohorten von Wissenschaftler*innen untersucht, die ihre Karriere zu unterschiedlichen Zeitpunkten begonnen haben. Im Weiteren werden einige der zugrunde liegenden Mechanismen und Prozesse von Ungleichheit in kreativen Berufen analysiert, wie der Matthew-Effekt und das Hipster-Paradoxon. Schließlich zeigt diese Arbeit auf, dass Online-Plattformen wie Wikipedia bestehenden Bias reflektieren sowie verstärken können
Reports of deaths are an exaggeration: all-cause and NAA-test-conditional mortality in Germany during the SARS-CoV-2 era
No full textCounts of SARS-CoV-2-related deaths have been key numbers for justifying severe political, social and economical measures imposed by authorities world-wide. A particular focus thereby was the concomitant excess mortality (EM), i.e. fatalities above the expected all-cause mortality (AM). Recent studies, inter alia by the WHO, estimated the SARS-CoV-2-related EM in Germany between 2020 and 2021 as high as 200 000. In this study, we attempt to scrutinize these numbers by putting them into the context of German AM since the year 2000. We propose two straightforward, age-cohort-dependent models to estimate German AM for the ‘Corona pandemic’ years, as well as the corresponding flu seasons, out of historic data. For Germany, we find overall negative EM of about −18 500 persons for the year 2020, and a minor positive EM of about 7000 for 2021, unveiling that officially reported EM counts are an exaggeration. In 2022, the EM count is about 41 200. Further, based on NAA-test-positive related death counts, we are able to estimate how many Germans have died due to rather than with CoViD-19; an analysis not provided by the appropriate authority, the RKI. Through 2020 and 2021 combined, our due estimate is at no more than 59 500. Varying NAA test strategies heavily obscured SARS-CoV-2-related EM, particularly within the second year of the proclaimed pandemic. We compensated changes in test strategies by assuming that age-cohort-specific NAA-conditional mortality rates during the first pandemic year reflected SARS-CoV-2-characteristic constants
On the recognition of human activities and the evaluation of its imitation by robotic systems
No full textThis thesis addresses the problem of action recognition through the analysis of human motion and the benchmarking of its imitation by robotic systems.
For our action recognition related approaches, we focus on presenting approaches that generalize well across different sensor modalities. We transform multivariate signal streams from various sensors to a common image representation. The action recognition problem on sequential multivariate signal streams can then be reduced to an image classification task for which we utilize recent advances in machine learning. We demonstrate the broad applicability of our approaches formulated as a supervised classification task for action recognition, a semi-supervised classification task for one-shot action recognition, modality fusion and temporal action segmentation.
For action classification, we use an EfficientNet Convolutional Neural Network (CNN) model to classify the image representations of various data modalities. Further, we present approaches for filtering and the fusion of various modalities on a representation level. We extend the approach to be applicable for semi-supervised classification and train a metric-learning model that encodes action similarity. During training, the encoder optimizes the distances in embedding space for self-, positive- and negative-pair similarities. The resulting encoder allows estimating action similarity by calculating distances in embedding space. At training time, no action classes from the test set are used.
Graph Convolutional Network (GCN) generalized the concept of CNNs to non-Euclidean data structures and showed great success for action recognition directly operating on spatio-temporal sequences like skeleton sequences. GCNs have recently shown state-of-the-art performance for skeleton-based action recognition but are currently widely neglected as the foundation for the fusion of various sensor modalities. We propose incorporating additional modalities, like inertial measurements or RGB features, into a skeleton-graph, by proposing fusion on two different dimensionality levels. On a channel dimension, modalities are fused by introducing additional node attributes. On a spatial dimension, additional nodes are incorporated into the skeleton-graph.
Transformer models showed excellent performance in the analysis of sequential data. We formulate the temporal action segmentation task as an object detection task and use a detection transformer model on our proposed motion image representations. Experiments for our action recognition related approaches are executed on large-scale publicly available datasets. Our approaches for action recognition for various modalities, action recognition by fusion of various modalities, and one-shot action recognition demonstrate state-of-the-art results on some datasets.
Finally, we present a hybrid imitation learning benchmark. The benchmark consists of a dataset, metrics, and a simulator integration. The dataset contains RGB-D image sequences of humans performing movements and executing manipulation tasks, as well as the corresponding ground truth. The RGB-D camera is calibrated against a motion-capturing system, and the resulting sequences serve as input for imitation learning approaches. The resulting policy is then executed in the simulated environment on different robots. We propose two metrics to assess the quality of the imitation. The trajectory metric gives insights into how close the execution was to the demonstration. The effect metric describes how close the final state was reached according to the demonstration. The Simitate benchmark can improve the comparability of imitation learning approaches
Digital Transformation Maturity of Vietnam Aviation Industry: The Effect of Organizational Readiness
No full textThe paper studies the digital transformation maturity in the context of the aviation industry in Vietnam. Digital transformation can mean enhancing existing processes, finding new opportunities within existing business domains, or finding new opportunities outside existing business domains. In the era of post Covid-19, digital transformation will play a vital role in the recovery with the support from digital technology to leverage the communication and implementation of new projects or changes.
Digital transformation and digital transformation maturity sometimes are used indistinguishing, but they are two different definitions. This paper will further explain the differences and will apply digital transformation maturity as a scale for the digital transformation in the report.
Due to the lack of experiment in the relationship between digital transformation maturity and the organizational readiness, the study will explore four components of organizational readiness, including digital leadership, digital culture, digital capabilities, and digital partnering