Hochschule Konstanz University of Applied Sciences
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Advanced Stress Management: Integration of Physiological Signals and Personal Characteristics to Prevent and Manage Stress
No full textStress management is becoming increasingly important in our society. It is evident that stress, whether measured subjectively or physiologically, has a detrimental effect on decision-making abilities and significantly impacts an individual's health and well-being, as well as the private and public economy. While technological advances simplify our daily lives, managing stress is more challenging than ever due to individual perceptions, cultural nuances, and personality traits. The need to respond quickly to workplace challenges, traffic, and the drive to achieve more is making chronic stress more prevalent, underscoring the importance of understanding, measuring, and predicting stress. In this work, stress is defined as the body's response to a stressor. Stressors can be either short-term or long-term, causing the body to function differently than it should, but also helping it respond to and cope with situations. Common ways of measuring stress include two main approaches: the classic method using questionnaires or direct conversations, and the use of physiological signals. In this research, we used questionnaires and heart rate characteristics to determine baseline stress levels, compared stress with physical activity, and studied the relationship between stress, personality traits, and demographics of the participants. It is important to remember that stress cannot be entirely avoided in our lives. Stress optimizes bodily functions and assists in coping with dangerous or challenging situations. However, it is possible to develop a system that helps us understand and detect stress more efficiently, thereby avoiding dangerous or hazardous situations. This could lead to significant improvements in sectors where errors are costly or can influence health. By doing so, a better understanding, better management, and a reduction of the negative long-term effects of stress can be achieved
Tracing Career Trajectories of Corporate Entrepreneurs: Identifying Patterns & Future Research
No full textCorporate Entrepreneurs have become an important resource for established companies to drive entrepreneurial behavior for new types of innovation and cultural change. Identifying and hiring employees with tailored competences and behaviors of a Corporate Entrepreneur is critical given that most corporates struggle to find the knowledge and capabilities needed to develop new types of ventures. The knowledge of CVs is described as relevant for hiring and developing employees but has not yet been sufficiently considered in the context of CE. Therefore, this study investigates past career experiences by leveraging optimal matching analysis, we examine a dataset comprising 50 sequences extracted from LinkedIn profiles, representing various career transitions over a 10-year period. Our findings reveal a dominant trajectory within the corporate sector, with limited transitions to other categories such as startups or consulting roles. With this, our research contributes to a deeper understanding of the career experiences of corporate entrepreneurs and underscores the need for future studies to explore the holistic factors shaping their professional trajectories
Integriertes Klimaschutzkonzept
Full text linkDie Hochschule Konstanz hat ein umfassendes Klimaschutzkonzept entwickelt, um ihre Treibhausgasemissionen zu reduzieren und nachhaltiges Handeln auf dem Campus zu fördern. Ausgangspunkt ist eine detaillierte Ist-Analyse, die sowohl qualitativ als auch quantitativ den Ist-Zustand hinsichtlich Klimawirkung an der Hochschule erfasst. Ein großer Teil dieser Analyse ist die Erhebung des Energieverbrauchs und der Treibhausgasemissionen. Zusätzlich zur Analyse der durch den Hochschulbetrieb erzeugten Emissionen wurden mögliche Maßnahmen zu deren Reduktion erörtert. Dies geschah auf Grundlage bisheriger Pläne der Hochschule zum Klimaschutz, dem Austausch mit dem Amt für Vermögen und Bau sowie der Hochschulgemeinschaft und externer Beratung.
Die Maßnahmen wurden Handlungsfeldern zugeordnet und innerhalb von Maßnahmensteckbriefen detailliert beschrieben. Mittels Treibhausgas- und Energiebilanz und der möglichen Minderungspotenziale von Maßnahmen konnten Szenarien zur Reduktion der Emissionen, sogenannte Absenkpfade, aufgestellt werden.
Durch den Vergleich zwischen einem Referenzszenario ohne zusätzliche Klimaschutzbemühungen und einem Klimaschutzszenario wird aufgezeigt, wohin die Hochschule sich mit ihren Klimaschutzaktivitäten entwickeln möchte und welche Emissionsreduktionen als Ziele realistisch sind. Zur Sicherstellung der Zielerreichung werden die Maßnahmen kontinuierlich überwacht und angepasst. Die Hochschule betont die Bedeutung der Einbindung verschiedener Stakeholder und hat entsprechende Kommunikationsstrategien und Beteiligungsformate entwickelt, um das Engagement für den Klimaschutz zu fördern.The Konstanz University of Applied Sciences has developed a comprehensive climate protection concept to reduce its greenhouse gas emissions and promote sustainable actions on campus. The basis is a detailed current-state analysis that captures the status quo of climate protection at the university, both qualitatively and quantitatively. This analysis includes one main part, the survey of current energy consumption and greenhouse gas emissions.
In addition to analyzing the emissions generated by university operations, potential measures for their reduction were discussed. This was based on previous climate protection plans of the university, consultations with the asset and construction management office, the university com-munity, and external advisors.
The measures were assigned to specific action areas and detailed within action briefs. By as-sessing the greenhouse gas and energy balance and the potential reduction capabilities of the measures, scenarios for emission reduction, known as reduction pathways, were established.
By comparing a reference scenario without additional climate protection efforts to a climate pro-tection scenario, the university outlines its desired direction for climate protection activities and identifies realistic emission reduction targets. To ensure the achievement of these goals, the measures are continuously monitored and adjusted. The university emphasizes the importance of involving various stakeholders and has developed corresponding communication strategies to promote participation and engagement in climate protection
Definition of Emotional States Interval for Application of Artificial Intelligence and Stress Estimation
No full textThe perception of the amount of stress is subjective to every person, and the perception of it changes depending on many factors. One of the factors that has an impact on perceived stress is the emotional state. In this work, we compare the emotional state of 40 German driving students and present different partitions that can be advantageous for using artificial intelligence and classification. Like this, we evaluate the data quality and prepare for the specific use. The Stress Perceived Questionnaire (PSQ20) was employed to assess the level of stress experienced by individuals while participating in a driving simulation for 5 and 25 min. As a result of our analysis, we present a categorisation of various emotional states into intervals, comparing different classifications and facilitating a more straightforward implementation of artificial intelligence for classification purposes
Grundlagen des Wirtschaftsprivatrechts
No full textDie vorliegende Veröffentlichung gibt einen einführenden Überblick über wesentliche Regelungen des Wirtschaftsprivatrechts, insbesondere der handels- und gesellschaftsrechtlichen Regelungen
Empirical model for the effect of air humidity during manufacturing on the glass transition temperature of carbon fiber reinforced hot curing epoxy – a case study
Full text linkCarbon fiber-epoxy laminates are used in aerospace manufacturing, e.g. as substrates for solar cells of satellites. Commonly, fibers or fibermats are impregnated with epoxy resin and placed in the required orientation. During subsequent curing, the resin molecules are crosslinked. Cured parts are characterized by their glass transition temperature (Tg). It has been observed that Tg of epoxy matrix resin vary with recorded absolute air humidity during wet fiber placement manufacturing. Based on the production data of a series production of 203 carbon fiber laminates for space application, an empirical linear relationship between the absolute air humidity at the beginning of each production day and the observed glass transition temperature of the fully cured laminate is formulated and validated. The empirical equation describes a linear decrease of achievable glass transition temperature with increasing absolute air humidity. The quantitative nature of the results encourages straightforward practical application to determine the maximum achievable Tg for given production conditions
Learning Physics Methods
No full textFor many years, a team of physicists at the HTWG Konstanz has been shifting the focus of physics education from teaching “content” to teaching “methods”. An overview is given on the derived state. Several questions are addressed, such as: What are the advantages? Are there constraints and limits? How can a shift be achieved? What are student reactions and how does other teaching staff deal with the new situatio
Classification of the sleep-wake state through the development of a deep learning model
No full textThe classification of sleep and wake states is of paramount importance in the context of sleep disorders. In order to detect and monitor disorders such as obstructive sleep apnea (OSA), it is essential to obtain the total sleep time (TST) so as to assess the severity of the patient’s sleep apnea. With the advent of new technologies for detecting events associated with sleep disorders, it is not always straightforward to calculate the sleep/wakefulness state. Consequently, this work presents the development of a deep learning model (a variant of U-Net) for the detection of sleep/wakefulness states. For this purpose, an engineering approach using Keras Tuner and the use of three signals with minimal processing was employed. The three signals, oxygen saturation (SpO2), heart rate (HR) and abdominal respiratory effort (AbdRes), were selected to ensure both patient comfort during signal collection and the possibility of using portable monitors. The models were trained and tested on data from polysomnography studies, namely the Sleep Heart Health Study (SHHS) and the Multiethnic Study of Atherosclerosis (MESA). The best performing model achieved results with 88% binary precision, 88% recall, 89% precision, 89% f1-score and Cohen’s Kappa of 0.74 for the SHHS test set. The model obtained 82% binary accuracy, 82% recall, 84% precision, 82% f1-score and 0.62 Cohen’s kappa for the MESA data set