Offenburg University of Applied Sciences
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Die Macht von Influencern auf Instagram
No full textIn den letzten Jahren hat sich Instagram als eine der bedeutendsten Plattformen im Bereich des Social-Media-Marketings etabliert. Eine zentrale Rolle spielen hierbei sogenannte In-fluencer, die durch ihre Reichweite und Authentizität die Kaufentscheidungen ihrer Follower maßgeblich beeinflussen können. Unternehmen nutzen gezielt Influencer, um Produkte zu bewerben und eine engere Bindung zur Zielgruppe aufzubauen. Trotz der wachsenden Be-deutung von Influencer Marketing besteht weiterhin Forschungsbedarf hinsichtlich der Ef-fektivität dieser Werbeform und der zugrunde liegenden Mechanismen, die das Kaufverhal-ten der Konsumenten beeinflussen.
Die vorliegende Bachelorarbeit hat zum Ziel, die Macht von Influencern auf Instagram und deren Einfluss auf das Kaufverhalten der Konsumenten zu untersuchen. Dabei wird analy-siert, unter welchen Bedingungen Influencer Marketing als effektiv betrachtet werden kann und welche Faktoren eine Rolle spielen. Darüber hinaus werden die Chancen und Risiken des Influencer Marketings aufgezeigt, um Handlungsempfehlungen für Unternehmen zu entwickeln, die diese Werbeform in ihre Kommunikationsstrategie integrieren möchten.
Im Rahmen der Arbeit wurde zunächst eine umfassende Literaturrecherche durchgeführt, um den aktuellen Forschungsstand zu erfassen. Aufbauend auf theoretischen Modellen des Konsumverhaltens wurde eine quantitative Befragung mittels eines Online-Fragebogens durchgeführt. Ziel der Befragung war es, das Nutzungsverhalten und die Einstellungen der Befragten zum Thema Influencer Marketing zu erfassen. Die Ergebnisse zeigen, dass In-fluencer Marketing unter bestimmten Voraussetzungen effektiv das Kaufverhalten beein-flusst. Besonders die Faktoren Authentizität und emotionale Bindung der Follower spielen hierbei eine entscheidende Rolle.
Die gewählte Vorgehensweise, eine Kombination aus theoretischer Auseinandersetzung und empirischer Untersuchung, hat sich als zielführend erwiesen. Die gewonnenen Er-kenntnisse bieten Unternehmen wertvolle Einsichten, um die Potenziale des Influencer Mar-ketings optimal auszuschöpfen und fundierte Entscheidungen in diesem Bereich zu treffen.In recent years, Instagram has established itself as one of the most important platforms in the field of social media marketing. So-called influencers play a central role here, as their reach and authenticity can significantly influence the purchasing decisions of their followers. Companies specifically use influencers to advertise products and build a closer relationship with their target group. Despite the growing importance of influencer marketing, there is still a need for research into the effectiveness of this form of advertising and the underlying mechanisms that influence the purchasing behavior of consumers.
The aim of this bachelor thesis is to investigate the power of influencers on Instagram and their influence on consumer purchasing behavior. It analyses the conditions under which influencer marketing can be considered effective and which factors play a role. In addition, the opportunities and risks of influencer marketing are highlighted in order to develop rec-ommendations for companies wishing to integrate this form of advertising into their commu-nication strategy.
As part of the thesis, a comprehensive literature review was first carried out in order to record the current state of research. Based on theoretical models of consumer behavior, a quantitative survey was conducted using an online questionnaire. The aim of the survey was to record the usage behavior and attitudes of the respondents on the topic of influencer marketing. The results show that influencer marketing effectively influences purchasing be-havior under certain conditions. The factors of authenticity and emotional attachment of followers in particular play a decisive role here.
The chosen approach, a combination of theoretical analysis and empirical research, has proven to be effective. The knowledge gained offers companies valuable insights to opti-mally exploit the potential of influencer marketing and make well-founded decisions in this area
Unified Multi-Abstraction-Level Functional Testing and Performance Measurements for Industrial IoT in Spatially Distributed Narrow Band-Wireless Wide Area Networks
Get PDFNarrow Band-Wireless Wide Area Networking (NB-WWAN) technologies are becoming more popular across a wide range of application domains due to their ability to provide spatially distributed and reliable wireless connectivity in addition to offering low data rates, low bandwidth, long-range, and long battery life. For functional testing and performance assessments, the wide range of wireless technology alternatives within this category poses several difficulties. At the device level, it is necessary to address issues such as resource limitations, complex protocols, interoperability, and reliability, while at the network level, challenges include complex topologies and wireless channel/signal propagation problems. Testing the functionality and measuring the performance of spatially distributed NB-WWAN systems require a systematic approach to overcome these challenges. Furthermore, to provide a seamless test flow, it is also critical to test and compare the performance of wireless systems systematically and consistently across the different system development phases. To evaluate NB-WWAN technologies comprehensively across multiple abstraction levels—network simulators, emulated lab testbeds, and field test environments—we propose a unified multi-abstraction-level testing methodology. A detailed technical description of the prototype implementation and its evaluation is presented in this paper
Expansion of pyrolysis in the German energy system and its contribution to climate neutrality
No full textOverview
As awareness of climate change and its effects is raising more concern among the population and politicians, negative emissions technologies have gained attention for their role in mitigating global warming. The expansion of renewable energy systems together with decarbonisation technologies is a key factor in accomplishing this objective. With a primary focus on Germany, our research focuses on the introduction of pyrolysis and its implications in the energy system. This study explores the integration of pyrolysis as a producer of biochar and electricity into Germany's energy system as part of the "PyFlex" project.
Method
Using MyPyPSA-Ger, we model pyrolysis plants, considering costs and biomass potential. The model integrates pyrolysis outputs, like biochar and electricity, with energy system components. Different scenarios, including cost and CO2 limits, assess pyrolysis’s behaviour and influence on the system. The model focuses on utilizing unused biomass potentials, specifically straw and forest residue. Scenario analyses were conducted to evaluate the economic and technical parameters of pyrolysis, the use of storage technologies, and regulatory frameworks, examining the cost-optimal expansion of Germany's electricity system.
Results
Key findings indicate that wind and photovoltaic (PV) installations will dominate Germany's energy mix by 2045, with pyrolysis contributing flexibility to the system and reducing the installed capacity of wind power by 25%. Gas power plants will continue to be used in moment where no renewable energy is available, with their emissions being offset by the biochar produced through pyrolysis.
The model predicts significant expansion of pyrolysis only after 2030, with full utilization of available biomass not expected until 2035. The rate of pyrolysis deployment will be driven by the cost of implementation until 2045, after which decreasing emission limits and the need for flexible electricity generation will determine its role in the energy system. Pyrolysis is shown to contribute to achieving net negative emissions at lower costs, especially when deployed as a flexible energy provider in a system with high renewable energy shares.
Overall, the study highlights the dual role of pyrolysis in the energy system: when investment costs are low, pyrolysis is primarily used for electricity generation; when costs are high, it functions as a negative emissions technology. The findings underscore the potential of pyrolysis to support Germany's transition to a climate-neutral energy system by providing flexibility and reducing overall costs
Pyrolysis as a key technology: Flexible energy provision and reduction of hydrogen storage
No full textThe poster examines pyrolysis as a key technology for flexible energy provision and reducing hydrogen storage reliance in future energy systems. It highlights that rapid pyrolysis expansion can lower hydrogen storage requirements by 60% by 2050 compared to a baseline scenario. Solar energy capacity expands more in the pyrolysis scenario, reaching 231 GW by 2050, while wind energy grows more in the baseline scenario (254 GW vs. 188 GW). Pyrolysis provides increasingly flexible electricity generation, with installed capacities rising and full-load hours decreasing to 3,000 hours annually. It supports residual loads of up to 14.5 TWh annually, particularly during periods of low or no solar power, such as nights and winters. Pyrolysis also reduces reliance on gas power plants while offsetting emissions using biochar. The PyFlex project (2024–2027) will further investigate pyrolysis’s role in enhancing Germany’s energy system flexibility and achieving decarbonization goals
Layer Thickness Estimation with Ground Penetrating Radar by Using Convolutional Neural Networks
No full textPrior knowledge of subsurface layers is crucial in many applications, particularly infrastructural projects. Ground Penetrating Radar (GPR) is a preferred measurement technique for investigating subsurface layers due to its non-destructive nature when probing the ground. However, interpreting GPR data is not trivial and requires the experience of the user. In this paper, the possibility of using one-dimensional Convolutional Neural Networks (1D CNNs) is investigated to estimate the thickness of up to two different subsurface layers with different electromagnetic characteristics. For this purpose, the network is trained on a synthetically generated stepped-frequency GPR A-scan dataset. The predicted thickness results using the trained 1D CNN showed good accuracy with a relative error of 2.6 % and 9.2 % for the first and second layers, respectively
One Shoe to Fit Them All? Effect of Various Carbon Plate Running Shoes on Running Economy in Male and Female Amateur Triathletes and Runners at Individual Training and Race Paces
Get PDFCarbon plate running shoes (CPRSs) have gained widespread popularity among elite and amateur runners, representing one of the most substantial changes in running gear over the past decade. Compared to elite runners, however, amateurs run at lower speeds and show more diverse running styles. This is a meaningful difference as many previous studies on CPRSs focus either on highly trained male runners and higher speeds or only on a single CPRSs manufacturer. The present study aims at bridging this gap by investigating how CPRSs from four different manufacturers affect running economy in amateurs of both sexes at their individual running speeds. For this purpose, 21 trained amateur triathletes (12 men; 9 women) completed an incremental treadmill test until volitional exhaustion, yielding running speeds at ventilatory thresholds 1 (vVT1) and 2 (vVT2). In a second session, subjects ran five trials of 3 × 3 min (speeds of 90% vVT1, ½ (vVT1 + vVT2), and 100% vVT2), wearing one out of four different pairs of CPRSs or their own preferred non-CPRS shoes in each trial. Our results show that tested CPRS models resulted in a significant reduction in the mean energy cost of transport, compared to the non-CPRS control condition, with Cohen’s d amounting to −1.52 (p = 0.016), 2.31 (p < 0.001), 2.57 (p < 0.001), and 2.80 (p < 0.001), respectively, although effect sizes varied substantially between subjects and running speeds. In conclusion, this study provides evidence that amateur athletes may benefit from various manufacturers’ CPRS models at their typical running speeds to a similar degree as highly trained runners. It is recommended that amateur athletes evaluate a range of CPRSs and select the shoe that elicits the least subjective sensation of fatigue over a testing distance of at least 400–1000 m
A framework to automatically detect near-falls using a wearable inertial measurement cluster
Get PDFAbstractAccurate and automatic assessments of body segment kinematics via wearable sensors are essential to provide new insights into the complex interactions between active lifestyle and fall risk in various populations. To remotely assess near-falls due to balance disturbances in daily life, current approaches primarily rely on biased questionnaires, while contemporary data-driven research focuses on preliminary fall-related scenarios. Here, we worked on an automated framework based on accurate trunk kinematics, enabling the detection of near-fall scenarios during locomotion. Using a wearable inertial measurement cluster in conjunction with evaluation algorithms focusing on trunk angular acceleration, the proposed sensor-framework approach revealed accurate distinguishment of balance disturbances related to trips and slips, thereby minimising false detections during activities of daily living. An important factor contributing to the framework’s high sensitivity and specificity for automatic detection of near-falls was the consideration of the individual’s gait characteristics. Therefore, the sensor-framework presents an opportunity to substantially impact remote fall risk assessment in healthy and pathological conditions outside the laboratory
Verfahren zum Erzeugen und/oder Verarbeiten von Bewegungsdaten, Verfahren zum Erfassen und/oder Bewerten von Bewegungsabläufen, Verfahren zum Erkennen und/oder Bewerten von dynamischen Instabilitäten, Verfahren zum Erzeugen und/oder Optimieren von Algorithmen und/oder Modellen, Vorrichtung zum Ausführen derartiger Verfahren und Computerprogramm (DE102023120648B3)
No full textVerfahren zum Erzeugen und/oder Verarbeiten von Bewegungsdaten eines frei beweglichen Körpers (130), wobei an dem Körper (130) wenigstens zwei jeweils einen Winkelgeschwindigkeitssensor und einen Beschleunigungssensor aufweisende Sensoreinheiten (104, 106, 108, 110) voneinander fest beabstandet angeordnet werden und auf Basis von Messsignalen der wenigstens zwei Sensoreinheiten (104, 106, 108, 110) und unter Anwendung von Gesetzen der allgemeinen Bewegung starrer Körper ein Winkelbeschleunigungsvektor direkt ermittelt wird, Verfahren zum Erfassen und/oder Bewerten von Bewegungsabläufen eines frei beweglichen Körpers (130), wobei gemäß einem derartigen Verfahren erzeugte und/oder verarbeitete Bewegungsdaten des Körpers (130) verwendet werden, Verfahren zum Erkennen und/oder Bewerten von dynamischen Instabilitäten eines frei beweglichen Körpers (130), wobei gemäß einem derartigen Verfahren erzeugte und/oder verarbeitete Bewegungsdaten des Körpers (130) verwendet werden, Verfahren zum Erzeugen und/oder Optimieren von Algorithmen und/oder Modellen zur Berechnung einer Dynamik frei beweglicher Körper (130), wobei gemäß einem derartigen Verfahren erzeugte und/oder verarbeitete Bewegungsdaten des Körpers (130) verwendet werden, und Vorrichtung (100) zum Ausführen eines derartigen Verfahrens mit wenigstens zwei an einem frei beweglichen Körper (130) voneinander fest beabstandet anordenbare, jeweils einen Winkelgeschwindigkeitssensor und einen Beschleunigungssensor aufweisende Sensoreinheiten (104, 106, 108, 110)
Can Biases in ImageNet Models Explain Generalization?
No full textThe robust generalization of models to rare, in-distribution (ID) samples drawn from the long tail of the training distribution and to out-of-training-distribution (OOD) samples is one of the major challenges of current deep learning methods. For image classification, this man-ifests in the existence of adversarial attacks, the performance drops on distorted images, and a lack of generalization to concepts such as sketches. The current under-standing of generalization in neural networks is very lim-ited, but some biases that differentiate models from human vision have been identified and might be causing these lim-itations. Consequently, several attempts with varying success have been made to reduce these biases during training to improve generalization. We take a step back and sanity-check these attempts. Fixing the architecture to the well-established ResNet-50, we perform a large-scale study on 48 ImageNet models obtained via different training methods to understand how and if these biases - including shape bias, spectral biases, and critical bands - interact with generalization. Our extensive study results reveal that contrary to previous findings, these biases are insufficient to accu-rately predict the generalization of a model holistically
Generation of time-independent torque by ultrasonic guided waves
No full textThe excitation of acoustic waves by a unidirectional transducer, integrated in a piezoelectric cylindrical tube or disk, can lead to a time-independent torque. This phenomenon, demonstrated earlier in experiments and analyzed with coupling-of mode theory, is explained in detail, starting on the level of lattice dynamics of a piezoelectric crystal. Expressions are derived for the stationary torque in the form of integrals over the volume or surface of the piezoelectric, involving the electric potential and displacement field associated with the acoustic waves generated by the transducer.
Simulations have been carried out with the help of the finite element method for a tube made of PZT for two cases: A pre-defined potential on the surface of the tube and metal electrodes buried in the piezoelectric. The displacement field and electric potential of the high-frequency acoustic waves (between 200 and 300 kHz) were computed and used in the evaluation of the integrals. The attenuation due to various loss channels of the acoustic waves in the system has been analyzed in detail, as this plays a crucial role for the efficiency of torque generation. It is conjectured that time-reversal symmetry, present in the absence of attenuation, prohibits the generation of a static torque at least in the linear limit.
A qualitative comparison is made between the simulations and earlier experiments. Discrepancies are attributed to lack of knowledge of the relevant material constants of the piezoelectric and to a simplified modeling of the electrode geometry in the cylindrical tube, which was necessary for reasons of numerical accuracy