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In this paper, we propose and simulate a new type of three-dimensional (3D) optical splitter based on multimode interference (MMI) for the wavelength of 1550 nm. The splitter was proposed on the square basis with the width of 20 x 20 µm2 using the IP-Dip polymer as a standard material for 3D laser lithography. We present the optical field distribution in the proposed MMI splitter and its integration possibility on optical fiber. The design is aimed to the possible fabrication process using the 3D laser lithography for forthcoming experiments.
Power plant operators increasingly rely on predictive models to diagnose and monitor their systems. Data-driven prediction models are generally simple and can have high precision, making them superior to physics-based or knowledge-based models, especially for complex systems like thermal power plants. However, the accuracy of data-driven predictions depends on (1) the quality of the dataset, (2) a suitable selection of sensor signals, and (3) an appropriate selection of the training period. In some instances, redundancies and irrelevant sensors may even reduce the prediction quality.
We investigate ideal configurations for predicting the live steam production of a solid fuel-burning thermal power plant in the pulp and paper industry for different modes of operation. To this end, we benchmark four machine learning algorithms on two feature sets and two training sets to predict steam production. Our results indicate that with the best possible configuration, a coefficient of determination of R^2 = 0.95 and a mean absolute error of MAE=1.2 t/h with an average steam production of 35.1 t/h is reached. On average, using a dynamic dataset for training lowers MAE by 32% compared to a static dataset for training. A feature set based on expert knowledge lowers MAE by an additional 32 %, compared to a simple feature set representing the fuel inputs. We can conclude that based on the static training set and the basic feature set, machine learning algorithms can identify long-term changes. When using a dynamic dataset the performance parameters of thermal power plants are predicted with high accuracy and allow for detecting short-term problems.
This thesis aims to support the product development process. Therefore, an approach is developed, implemented as a prototype and evaluated, for automated solution space exploration of formally predefined design automation tasks holding the product knowledge of engineers. For this reason, a classification of product development tasks related to the representation of the mathematical model is evaluated based on the parameters defined in this thesis. In a second step, the mathematical model should be solved. A Solver is identified able to handle the given problem class.
Due to the context of this work, System Modelling Language (SysML) is chosen for the product knowledge formalisation. In the next step the given SysML model has to be translated into an object-oriented model. This translation is implemented by extracting information of a ".xml"-file using the XML Metadata Interchanging (XMI) standard. The information contained in the file is structured using the Unified Modelling Language (UML) profile for SysML. Afterwards a mathematical model in MiniZinc language is generated. MiniZinc is a mathematical modelling language interpretable by many different Solvers. The generated mathematical model is classified related to the Variable Type and Linearity of the Constraints and Objective of the generated mathematical model. The output is stored in a ".txt"-file.
To evaluate the functionality of the prototype, time consumption of the different performed procedures is measured. This data shows that models containing Continuous Variables need a longer time to be classified and optimised. Another observation shows that the transformation into an object-oriented model and the translation of this model into a mathematical representation are dependent on the number of SysML model elements. Using MiniZinc resulted in the restriction that models which use non-linear functions and Boolean Expressions cannot be solved. This is because the implementation of non-linear Solvers at MiniZinc is still in the development phase. An investigation of the optimally of the results, provided by the Solvers, was left for further work.
The Digital Factory Vorarlberg is the youngest Research Center of Vorarlberg University of Applied Sciences. In the lab of the research center a research and learning factory has been established for educating students and employees of industrial partners. Showcases and best practice scenarios for various topics of digitalization in the manufacturing industry are demonstrated. In addition, novel methods and technologies for digital production, cloud-based manufacturing, data analytics, IT- and OT-security or digital twins are being developed. The factory comprises only a minimum core of logistics and fabrication processes to guarantee manageability within an academic setup. As a product, fidget spinners are being fabricated. A webshop allows customers to individually design their products and directly place orders in the factory. A centralized SCADA-System is the core data hub for the factory. Various data analytic tools and methods and a novel database for IoT-applications are connected to the SCADA-System. As an alternative to on premise manufacturing, orders can be pushed into a cloud-based manufacturing platform, which has been developed at the Digital Factory. A broker system allows fabrication in distributed facilities and offers various optimization services. Concepts, such as outsourcing product configuration to customers or new types of engineering services in cloud-based manufacturing can be explored and demonstrated. In this paper, we present the basic concept of the Digital Factory Vorarlberg, as well as some of the newly developed topics.
Flexibility estimation is the first step necessary to incorporate building energy systems into demand side management programs. We extend a known method for temporal flexibility estimation from literature to a real-world residential heat pump system, solely based on historical cloud data. The method proposed relies on robust simplifications and estimates employing process knowledge, energy balances and manufacturer's information. Resulting forced and delayed temporal flexibility, covering both domestic hot water and space heating demands as constraints, allows to derive a flexibility range for the heat pump system. The resulting temporal flexibility lay within the range of 24 minutes and 6 hours for forced and delayed flexibility, respectively. This range provides new insights into the system's behaviour and is the basis for estimating power and energy flexibility - the first step necessary to incorporate building energy systems into demand side management programs.
A novel calorimetric technique for the analysis of gas-releasing endothermic dissociation reactions
(2020)
In engineering design, optimization methods are frequently used to improve the initial design of a product. However, the selection of an appropriate method is challenging since many
methods exist, especially for the case of simulation-based optimization. This paper proposes a systematic procedure to support this selection process. Building upon quality function deployment, end-user and design use case requirements can be systematically taken into account via a decision
matrix. The design and construction of the decision matrix are explained in detail. The proposed
procedure is validated by two engineering optimization problems arising within the design of box-type boom cranes. For each problem, the problem statement and the respectively applied optimization methods are explained in detail. The results obtained by optimization validate the use
of optimization approaches within the design process. The application of the decision matrix shows the successful incorporation of customer requirements to the algorithm selection.
Purpose: The purpose of this qualitative phenomenological study is to explore the of self-initiated expatriates prior to and during acculturation to life in a smaller periphery region such as Vorarlberg, Austria. By providing insights into their lived experience this research aims to fill in the gaps of missing information on motivators, success factors to adjustment, issues, and stressors, and more that SIEs experience when adjusting. Specifically, what items promote adjustment and what items hinder adjustment.
Findings: Developed a better understanding of how and what motivational factors lead to expatriation. Furthermore, that opportunities arise by chance. During acculturation, language factors (dialect), cultural differences act as stressors. While social support, and organizational support, learning of the language act as promoters of acculturation.
Further Research could be done including ethnicities, SIEs moving from developed to developing countries, adjustment in regions with dialect vs no dialect.
Key words: self-initiated expatriates, expatriation, acculturation, adjustment, promoting acculturation, hindering acculturation.
A rapid change to remote work during the beginning of the Covid-19 pandemic allowed many organizations to roll out new collaboration platforms to rapidly digitalize their workflows and processes in order to continue operation. This sudden shift to remote work revealed to employees the potential benefits of working remotely in the form of additional flexibility and also showed the challenges and barriers organizations could face by introducing such a strategy. This thesis aims to uncover the key considerations that the organizations of the industrial sector in Vorarlberg need to consider establishing a remote work strategy. According to the results from the research, the Covid-19 pandemic was as a paradigm change for the interviewed decision makers about how they thought about remote work and how they transformed their respective organizations too continue to operate. After the initial phase of Covid-19 restrictions organizations started to experiment with a remote work strategy of their own, based on their past experiences. For now, most of the interviewed organizations use already different remote work concepts and evaluate which one suits best their needs. The main considerations as to why an organization introduced a remote work strategy are to be an attractive employer and to stay ahead in the search for new talent. Further by introducing a remote work strategy, organizations need to change their rules of collaboration, adapt their core values to fit a remote workplace and to introduce collaboration platforms which are designed to support a remote workforce.
Creating a schedule to perform certain actions in a realworld environment typically involves multiple types of uncertainties. To create a plan which is robust towards uncertainties, it must stay flexible while attempting to be reliable and as close to optimal as possible. A plan is reliable if an adjustment to accommodate for a new requirement causes only a few disruptions. The system needs to be able to adapt to the schedule if unforeseen circumstances make planned actions impossible, or if an unlikely event would enable the system to follow a better path. To handle uncertainties, the used methods need to be dynamic and adaptive. The planning algorithms must be able to re-schedule planned actions and need to adapt the previously created plan to accommodate new requirements without causing critical disruptions to other required actions.
Scrum has been a prominent project management framework for managing software development projects. The scrum team embodies values such as commitment, focus, respect, courage, and openness to develop trust, which serves as the foundation of the scrum framework. However, in recent years, scrum teams are shifting towards a work-from-home environment which is relatively new to most of them and known to present various challenges. Looking at the benefits of adhering to scrum values, this study aims to investigate the challenges scrum teams experience in adhering to scrum values while operating virtually, as well as to explore practical strategies to overcome the identified challenges, particularly during the storming stage of team development. This research employed a qualitative methodology using semi-structured interviews with scrum team members who have experience working in a virtual environment. Through qualitative content analysis of semi-structured interviews, this research identifies significant challenges within five main categories: communication, collaboration, interpersonal dynamics, the virtual work environment, and personal workspace issues. However, beyond the challenges, the study reveals practical strategies as well for successful team dynamics and higher efficiency. The strategies derived from team members' experiences are categorized into six categories: enhanced meeting management, leveraging in-person engagements, optimizing tools & technology, effective communication strategies, team-building, and nurturing a positive work culture.
Traditional power grids are mainly based on centralized power generation and subsequent distribution. The increasing penetration of distributed renewable energy sources and the growing number of electrical loads is creating difficulties in balancing supply and demand and threatens the secure and efficient operation of power grids. At the same time, households hold an increasing amount of flexibility, which can be exploited by demand-side management to decrease customer cost and support grid operation. Compared to the collection of individual flexibilities, aggregation reduces optimization complexity, protects households’ privacy, and lowers the communication effort. In mathematical terms, each flexibility is modeled by a set of power profiles, and the aggregated flexibility is modeled by the Minkowski sum of individual flexibilities. As the exact Minkowski sum calculation is generally computationally prohibitive, various approximations can be found in the literature. The main contribution of this paper is a comparative evaluation of several approximation algorithms in terms of novel quality criteria, computational complexity, and communication effort using realistic data. Furthermore, we investigate the dependence of selected comparison criteria on the time horizon length and on the number of households. Our results indicate that none of the algorithms perform satisfactorily in all categories. Hence, we provide guidelines on the application-dependent algorithm choice. Moreover, we demonstrate a major drawback of some inner approximations, namely that they may lead to situations in which not using the flexibility is impossible, which may be suboptimal in certain situations.
Alleviating the curse of dimensionality in minkowski sum approximations of storage flexibility
(2023)
Many real-world applications require the joint optimization of a large number of flexible devices over some time horizon. The flexibility of multiple batteries, thermostatically controlled loads, or electric vehicles, e.g., can be used to support grid operations and to reduce operation costs. Using piecewise constant power values, the flexibility of each device over d time periods can be described as a polytopic subset in power space. The aggregated flexibility is given by the Minkowski sum of these polytopes. As the computation of Minkowski sums is in general demanding, several approximations have been proposed in the literature. Yet, their application potential is often objective-dependent and limited by the curse of dimensionality. In this paper, we show that up to 2d vertices of each polytope can be computed efficiently and that the convex hull of their sums provides a computationally efficient inner approximation of the Minkowski sum. Via an extensive simulation study, we illustrate that our approach outperforms ten state-of-the-art inner approximations in terms of computational complexity and accuracy for different objectives. Moreover, we propose an efficient disaggregation method applicable to any vertex-based approximation. The proposed methods provide an efficient means to aggregate and to disaggregate typical battery storages in quarter-hourly periods over an entire day with reasonable accuracy for aggregated cost and for peak power optimization.
Bubble column humidifiers (BCHs) are frequently used for the humidification of air in various water treatment applications. A potential but not yet profoundly investigated application of such devices is the treatment of oily wastewater. To evaluate this application, the accumulation of an oil-water emulsion using a BCH is experimentally analyzed. The amount of evaporating water vapor can be evaluated by measuring the humidity ratio of the outlet air. However, humidity measurements are difficult in close to saturated conditions, as the formation of liquid droplets on the sensor impacts the measurement accuracy. We use a heating section after the humidifier, such that no liquid droplets are formed on the sensor. This enables us a more accurate humidity measurement. Two batch measurement runs are conducted with (1) tap water and (2) an oil-water emulsion as the respective liquid phase. The humidity measurement in high humidity conditions is highly accurate with an error margin of below 3 % and can be used to predict the oil concentration of the remaining liquid during operation. The measured humidity ratio corresponds with the removed amount of water vapor for both tap water and the accumulation of an oil-water emulsion. Our measurements show that the residual water content
in the oil-water emulsion is below 4 %.
Vast amounts of oily wastewater are byproducts of the petrochemical and the shipping industry and to this day frequently discharged into water bodies either without or after insufficient treatment. To alleviate the resulting pollution, water treatment processes are in great demand. Bubble column humidifiers (BCHs) as part of humidification–dehumidification systems are predestined for such a task, since they are insensitive to different feed liquids, simple in design and have low maintenance requirements. While humidification in a bubble column has been investigated plentiful for desalination, a systematic investigation of oily wastewater treatment is missing in literature. We filled this gap by analyzing the treatment of an oil–water emulsion experimentally to derive recommendations for future design and operation of BCHs. Our humidity measurements indicate that the air stream is always saturated after humidification for a liquid height of only 10 cm. A residual water mass fraction of 3.5 wt% is measured after a batch run of six hours. Furthermore, continuous measurements show that an increase in oil mass fraction leads to a decrease in system productivity especially for high oil mass fractions. This decrease is caused by the heterogeneity of the liquid temperature profile. A lower liquid height mitigates this heterogeneity, therefore decreasing the heat demand and improving the overall efficiency. The oil content of the produced condensate is below 15 ppm, allowing discharge into various water bodies. The results of our systematic investigation prove suitability and indicate a strong future potential for the use of BCHs in oily wastewater treatment.
An implementation approach of the gap navigation tree using the TurtleBot 3 Burger and ROS Kinetic
(2020)
The creation of a spatial model of the environment is an important task to allow the planning of routes through the environment. Depending on the number of sensor inputs different ways of creating a spatial environment model are possible. This thesis introduces an implementation approach of the Gap Navigation Tree which is aimed for usage with robots that have a limited amount of sensors. The Gap Navigation Tree is a tree structure based on depth discontinuities constructed from the data of a laser scanner. Using the simulated TurtleBot 3 Burger and ROS kinetic a framework is created that implements the theory of the Gap Navigation Tree. The framework is structured in a way that allows using different robots with different sensor types by separating the detection of depth discontinuities from the building and updating of the Gap Navigation Tree.
Skiing is one of the most popular winter sports in the world and especially in the alps. As the skiers enjoy their time on the slopes the most annoying thing that could happen is long waiting times at a lift. Unfortunately, because of climate changes, this happens more regularly because smaller skiing areas at lower altitudes have to close and the number of good skiing days decreases as well. This leads to a increase in the number of skiers in the skiing areas which inevitably leads to longer waiting times and dissatisfied skiers. To prevent this from happening, the carriers of the skiing areas have to manage the skiers flow and distribution and what better way to analyse the current situation and possible changes then by simulating the whole area. A simulation has the advantage of being flexible with regards to time as well as configuration. Be it simulating a skiing day and look into detail of the behaviour of a single skier and how it moves in the area by simulating in real time or setting the focus to the whole area and find out when and where queues are forming throughout the whole day by speeding up the time and simulate the day in only seconds, everything is possible. Even simulating a scenario where some part of the area is closed and the skiers cannot take specific lifts due to some technical error or some slopes because of to less snow. By simulating and analysing all these scenarios not only does the experts of the skiing area gain valuable statistical information about the area but can also simulate changes to the system like a crowd fl ow control or an increase or decrease in capacity of a lift. The simulation built in context with this work for the skiing area of Mellau shows all those applications but can also be used as a basis for further improvements of the skiing area or be expanded to other areas like Damüls. The simulation was implemented using the Anylogic simulation environment and the statistical evaluation was also performed in this program.
This master’s thesis provides an overview of a more efficient, future-oriented living concept in Dornbirn, Austria. The use of a combined heat and power unit (CHP), in combination with a thermal storage, as a heating system is specifically investigated. In order to make this heating system more attractive for the consumer, the sale of the generated electricity from the CHP is considered. The more efficient use of energy for heating increases the attractiveness by a minimisation of the living space. This master’s thesis aims to draw attention to the issue and to achieve a rethinking in the planning of future living space. For the research and elaboration of this thesis, statistics and trustworthy literature were used, and physical modelling was applied. This Master’s thesis can be assigned to the fields of energy technology, mechatronics, architecture and civil engineering. It contributes for students, researchers, and other interested person in these sectors.
Activation of heat pump flexibilities is a viable solution to support balancing the grid via Demand Side Management measures and fulfill the need for flexibility options. Aggregators as interface between prosumers, distribution system operators and balance responsible parties face the challenge due to data privacy and technical restrictions to transform prosumer information into aggregated available flexibility to enable trading thereof. Thereby, literature lacks a generic, applicable and widely accepted flexibility estimation method for heat pumps,which incorporates reduced sensor and system information, system- and demand-dependent behaviour. In this paper, we adapt and extend a method from literature, by incorporating domain knowledge to overcome reduced sensor and system information. We apply data of five real-world heat pump systems, distinguish operation modes, estimate power and energy flexibility of each single heat pump system, proof transferability of the method, and aggregate the flexibilities available to showcase a small HP pool as a proof of concept.
The demand for managing data across multiple domains for product creation is steadily increasing. Model-Driven Systems Engineering (MDSE) is a solution for this problem. With MDSE, domain-specific data is formalized inside a model with a custom language, for example, the Unified Modelling Language (UML). These models can be created with custom editors, and specialized domains can be integrated with extensions to UML, e.g., the Systems Modeling Language (SysML). The most dominant editor in the open-source sector is Eclipse Papyrus SysML 1.6 (Papyrus), an editor to create SysML diagrams for MDSE.
In the pursuit of creating a model and diagrams, the editor does not support the user appropriately or even hinders them. Therefore, paradigms from the diagram modelling and Human Computer Interaction (HCI) domains, as well as perceptual and design theory, are applied to create an editor prototype from scratch. The changes fall into the categories of hierarchy, aid in the diagram composition, and navigation. The prototype is compared with Papyrus in a user test to determine if the changes have the effect of improving usability.
The study involved 10 participants with different knowledge levels of UML, ranging from beginners to experts. Each participant was tested on a navigation and modelling task in both the newly created editor, named Modelling Studio, and Papyrus. The study was evaluated through a questionnaire and analysis of the diagrams produced by the tasks.
The findings are that Modelling Studio’s changes to the hierarchical elements improved their rating. Furthermore, aid for diagram composition could be reinforced by changes to the alignment helper tool and adjustments to the default arrow behaviour of a diagram. Lastly, model navigation adjustments improve a link’s visibility and rating of a specialized link (best practice). The introduction of breadcrumbs had limited success in bettering navigation usability. The prototype deployed a broad spectrum of changes that found improvement already, which can, however, be further improved and tested more thoroughly.
Zeros can cause many issues in data analysis and dealing with them requires specialized procedures. We differentiate between rounded zeros, structural zeros and missing values. Rounded zeros occur when the true value of a variable is hidden because of a detection limit in whatever mechanism was used to acquire the data. Structural zeros are values which are truly zero, often coming about due to a hidden mechanism separate from the one which generates values greater than 0. Missing values are values that are completely missing for unknown or known reasons. This thesis outlines various methods for dealing with different kinds of zeros in different contexts. Many of these methods are very specific in their ideal usecase. They are separated based on which kind of zero they are intended for and if they are better suited for compositional or for standard data.
For rounded zeros we impute the zeros with an estimated value below the detection limit. The author describes multiplicative replacement, a simple procedure that imputes values at a fixed fraction of the detection limit. As a more advanced technique, the author describes Kaplan Meier smoothing spline replacement, which interpolates a spline on a Kaplan Meier curve and uses the spline below the detection limit to impute values in a more natural distribution. Rounded zeros cannot be imputed with the same techniques that would be used for regular missing values, since there is more information available on the true value of a rounded zero than there would be for a regular missing value.
Structural zeros cannot be imputed since they are a true zero. Imputing them would falsify their values and produce a value where there should be none. Because of this, we apply modelling techniques that can work around structural zeros and incorporate them. For standard data, the zero inflated Poisson model is presented. This model utilizes a mixture of a logistic and a Poisson distribution to accurately model data with a large amount of structural zeros. While the Poisson distribution is only applicable to count data, the zero inflation concept can be applied to different kinds of distributions. For compositional data, the zero adjusted Dirichlet model is introduced. This model mixes Dirichlet distributions for every pattern of zeros found within the data. Non-algorithmic techniques to reduce the amount of structural zeros present are also shown. These techniques being amalgamation, which combines columns with structural zeros into more broad descriptors and classification, which changes columns into categorical values based on a structural zero being present or not.
Missing values are values that are completely missing for various known or unknown reasons. Different imputation techniques are introduced. For standard data, MissForest imputation is introduced, which utilizes a RandomForest regression to impute mixed type missing values. Another imputation technique shown utilizes both a genetic algorithm and a neural network to impute values based on the genetic algorithm minimizing the error of an autoencoder neural network. In the case of compositional data, knn imputation is presented, which utilizes the knn concept also found in knn clustering to impute the values based on the closest samples with a value available.
All of these methods are explained and demonstrated to give readers a guide to finding the suitable methods to use in different scenarios.
The thesis also provides a general guide on dealing with zeros in data, with decision flowcharts and more detailed descriptions for both compositional and standard data being presented. General tips on getting better results when zeros are involved are also given and explained. This general guide was then applied to a dataset to show it in action.
Nowadays, the area of customer management strives for omni-channel and state-of-the-art CRM concepts including Artificial Intelligence and the approach of Customer Experience. As a result, modern CRM solutions are essential tools for supporting customer processes in Marketing, Sales and Service. AI-driven CRM accelerates sales cycles, improves lead generation and qualification, and enables highly personalized marketing. The focus of this thesis is to present the basics of Customer Relationship Management, to show the latest Gartner insights about CRM and CX, and to demonstrate an AI Business Framework, which introduces AI use cases that are used as a basis for the expert interviews conducted in an international B2B company. AI will transform CX through a better understanding of customer behavior. The following research questions are answered in this thesis: In which AI use cases can Sales and CRM be improved? How can Customer Experience be improved with AI-driven CRM?
Companies develop and implement strategies with the aim to address the needs of their customers. Acquisition is one market expansion strategy that companies can use to acquire new market access, technologies and/or to grow organically. In recent years, Chinese companies have been active in acquiring companies all over the globe to develop their strategic position. This caused certain contra reaction in Europe and as well in the Swiss media against cross-border acquisitions of Swiss companies.
Swiss companies and particularly the Swiss-MEM (Machinery, Electrical and Mechanical) industry is highly export oriented and their value proposition builds on attributes like knowledge, technology, and differentiating products. Among them are many “hidden champions” and niche players who successfully dominate the market segment.
As observed with Chinese companies, Indian companies also started to become more active outside of their domestic markets by increasing their foreign direct investments into Europe, Asia and North America, over the last decades. The lasting and good relationship of India and Switzerland might trigger the wish for Indian companies to acquire Swiss and particularly Swiss-MEM companies for acquisitions.
This Master’s Thesis assesses how often Indian investments into public and privately owned Swiss-MEM companies by acquisition happen, how are the attempts of acquisitions perceived by the stakeholders and what measures Swiss and Swiss-MEM companies can take, to protect themselves from being acquired. To access the research topic, several sub-questions will be analysed with the aid of primary and secondary research to assess the situation.
The research topic is of particular interested to the author since he spent over 20 years working in the Swiss-MEM industry, involved in international affairs and in recent years specifically with India. The observation of Chinese acquisition activities and insight into the size and potential of India were the drivers for researching whether India might follow China’s example.
In conclusion, Indian companies are not explicitly targeting Swiss and Swiss-MEM companies, but there are reasons to believe that it would make sense for Indian companies to look into the acquisition of Swiss and Swiss-MEM companies. The perception of such acquisitions varies, but there are arguments for and against them. Companies must take strategic and organisational measures in order to prevent themselves from becoming the target of an acquisition. However, it is known that the state should not interfere in the market and a discussion at a political level, planning how to deal with cross-border acquisition, is needed.
Further areas for research based on this Master’s Thesis could be the review of how the targeting of Swiss and Swiss-MEM companies by Indian companies would look, and also the topic of the succession planning in Swiss secondary sector in conjunction with Indian targeting for acquisitions. A third area to research might be investigating the political aspects involved in the research questions.
The boom of information technology development created high demand for skilled labour force in IT occupations. IT professionals install, test, build, repair or maintain hardware and software and can do the job from any location in the world.
Demand for the workforce significantly outstrips the global supply. In a situation of staff shortage employers have to compete on local and global labour markets. The ability of a firm to attract and retain the best talent would become a source of its sustainable competitive advantage.
Aim of the study is to understand what influences perception of employment attractiveness by IT professionals the most. This study intends to expend the existing knowledge about employees´ needs and “psychological contract” concept.
The research was conducted with the participation of 4 IT and 4 HR English-speaking experts who live and work in Austria. In the study the grounded theory approach and the descriptive qualitative methods were applied.
The research findings explain which factors influence the decision of IT professionals to join, stay or leave an employer. The results are discussed in relation to talent attraction and retention practices of Austrian employers.
With the digitalisation, and the increased connectivity between manufacturing systems emerging in this context, manufacturing is shifting towards decentralised, distributed concepts. Still, for manufacturing scenarios manual input or augmentation of data is required at system boundaries. Especially in distributed manufacturing environments, like Cloud Manufacturing (CMfg) systems, constant changes to the available manufacturing resources and products pose challenges for establishing connections between them. We propose a feature-oriented representation of concepts, especially from the manufacturing domain, which serves as the basis for (semi-) automatically linking, e.g., manufacturing resources and products. This linking methodologies, as well as knowledge inferred using it, is then used to support distributed manufacturing, especially in CMfg environments, and enhance product development. The concepts and methodologies are to be evaluated in a real world learning factory.
Pooled data from published reports on infants with clinically diagnosed vitamin B12 (B12) deficiency were analyzed with the purpose of describing the presentation, diagnostic approaches, and risk factors for the condition to inform prevention strategies. An electronic (PubMed database) and manual literature search following the PRISMA approach was conducted (preregistration with the Open Science Framework, accessed on 15 February 2023). Data were described and analyzed using correlation analyses, Chi-square tests, ANOVAs, and regression analyses, and 102 publications (292 cases) were analyzed. The mean age at first symptoms (anemia, various neurological symptoms) was four months; the mean time to diagnosis was 2.6 months. Maternal B12 at diagnosis, exclusive breastfeeding, and a maternal diet low in B12 predicted infant B12, methylmalonic acid, and total homocysteine. Infant B12 deficiency is still not easily diagnosed. Methylmalonic acid and total homocysteine are useful diagnostic parameters in addition to B12 levels. Since maternal B12 status predicts infant B12 status, it would probably be advantageous to target women in early pregnancy or even preconceptionally to prevent infant B12 deficiency, rather than to rely on newborn screening that often does not reliably identify high-risk children.
With the rise of people wearing smartwatches and the ever-lasting issue of stress, there has been an interest in detecting stress with wearables in real-time. This allows for interventions that take place exactly when stress occurs. However, many situations require all of our attention, making them unsuitable for any interventions. Additionally, many approaches currently do not factor in this aspect, running the risk of offering users undesirable interventions.
This thesis examines how contextual user information can be incorporated into a stress intervention system to reduce undesirable intervention timings. The system is split into detecting stress using heart rate variability (HRV) metrics obtained from a photoplethysmography (PPG) signal, and inferring user context from available sensor data. It is evaluated with a simulation-based approach using daily schedules of created personas and randomly sampled stressors during daily life.
The results obtained indicate the benefit of adding contextual user information to a stress intervention system. Depending on the busyness of the schedule, it can greatly decrease the number of received interventions. However, as these findings are attained without performing a user testing, it is unclear how they compare to results from real-world usage.
The production of liquid-gas dispersions places high demands on the process technology, which requires knowledge of the bubble formation mechanisms, as well as the phase parameters of the media combinations used. To obtain the bubble sizes introduced to a flow not knowing the phase parameters, different process parameters are investigated. Their quality and applicability are evaluated. The results obtained make it possible to simplify long design processes of dispersion processes in manufacturing plants and to ensure the product quality of the products manufactured, by reducing waste.
In the context of this master thesis, general tensions within the relationship between headquarters and their subsidiaries are examined using the practical example of a Swiss company with its subsid-iary in Kenya. Thereby, the influence of cultural aspects and the associated different expectations on management and leadership are emphasized. In doing so, two countries are compared which have not yet been considered in the same context. The objective of this master thesis is to develop a framework that enables the headquarter in the German speaking area of Switzerland and the sub-sidiary in the Bantu speaking area of Kenya to overcome cultural barriers and to increase mutual understanding in the business context. This will facilitate the identification of potentially dysfunc-tional aspects in the working relationship and provide a basis for optimizing the existing business relationship between the Swiss headquarter and the Kenyan subsidiary.
This thesis addresses the overarching question of what the two business entities need to know about each other in terms of cultural characteristics and emerging differences in business practices (in terms of management/leadership) in order to improve the overall cooperation and working rela-tionship between the headquarter and its subsidiary. Thus, the following topics are emphasized with-in this thesis: tensions within the headquarter/subsidiary relationship, concise country profiles of Switzerland and Kenya including a cultural overview of both countries, cultural concepts including organizational culture, common leadership theories related to the situational leadership approach, and finally, an evaluation of the current status quo in the working relationship between the Swiss headquarter and the Kenyan subsidiary based on interviews.
The increasing digitalisation of daily routines confronts people with frequent privacy decisions. However, obscure data processing often leads to tedious decision-making and results in unreflective choices that unduly compromise privacy. Serious Games could be applied to encourage teenagers and young adults to make more thoughtful privacy decisions. Creating a Serious Game (SG) that promotes privacy awareness while maintaining an engaging gameplay requires, however, a carefully balanced game concept. This study explores the benefits of an online role-playing boardgame as a co-designing activity for creating SGs about privacy. In a between-subjects trial, student groups and educator/researcher groups were taking the roles of player, teacher, researcher and designer to co-design a balanced privacy SG concept. Using predefined design proposal cards or creating their own, students and educators played the online boardgame during a video conference session to generate game ideas, resolve potential conflicts and balance the different SG aspects. The comparative results of the present study indicate that students and educators alike perceive support from role-playing when ideating and balancing SG concepts and are happy with their playfully co-designed game concepts. Implications for supporting SG design with role-playing in remote collaboration scenarios are conclusively synthesised.
In today’s world, companies feel the urge to disguise from competitors and to connect emotionally with consumers in order to foster a meaningful and long-lasting relationship. Simultaneously, stakeholders demand an increase of companies’ social responsibility. Cause-related marketing (CRM) is a marketing tool that addresses the change in societal values and the rising expectations from stakeholder groups. The increasing number of companies that choose to partner with a non-profit organization highlights that linking a charitable cause to the company's brand is an effective marketing tool. Authors illustrate that CRM, as a form of showing corporate social responsibility, will become even more important in the future. This master thesis examines the relationship between CRM, emotions, and culture. The research goal is to identify if CRM programs are effective in evoking emotions in consumers and if the cultural background of a consumer influences the evocation of certain emotions. The empirical findings outline that CRM programs are effective in evoking emotions. Other-focused emotions evoked by CRM programs are stronger expe-rienced by members of collectivistic countries than by members of individualistic countries. Likewise other-focused emotions evoked by CRM programs are stronger experienced by high interdependent selves than by low interdependent selves.
In recent years, much research has been done on medical laser applications inside the human body, as they are minimally invasive and therefore have fewer side effects and are less expensive than conventional therapies. In order to bring the laser light into the human body, a glass fibre with a diffuser is needed. The goal of this master thesis is the characterization and production of fibre optic diffusers that can be used for the three therapeutic applications: photodynamic therapy, laser-induced thermotherapy and endovenous laser therapy. For this purpose the following goals have to be achieved:
- Optimization of the efficiency and homogeneity of internally structured diffusers
- Examine damage thresholds of the diffusers in the tissue using a crash test
- Achieving a better understanding of the decouple mechanism with a simulation
Using an ultra-short pulse laser, modifications could be introduced into the fibre in this way that the radiation profile is homogeneous and the decoupling efficiency is 68.3 %. It was discovered that the radiation profile depends on the wavelength. Attempts have been made to improve the decoupling efficiency by mirroring the distal end of the fibre. The mirror reflects the remaining light back into the fibre, so that it is also decoupled lateral on the modifications. Vapor-deposited aluminum with physical vapor deposition is a promising approach. However, the adhesion of the coating must be improved or the coating must be protected by a mechanical cover, otherwise it will flake off too quickly.
In a crash test, it was shown that the glass fibre diffusers can withstand 20 W laser power for 300 s without visible change. In an ex vivo test, the coagulation zone in the tissue was examined and it was showed that the diffusers radiate radially homogeneously. Using a ray trace simulation, the course of the light rays in the fibre was examined and the correlation of modification width and length with the decoupling efficiency was investigated. It was discovered that there are helical light rays in the fibre, which cannot be decoupled by modifications in the fibre centre.
Bubble columns are recently used for the humidification of air in water treatment systems and fuel cells. They are well applicable due to their excellent heat and mass transfer and their low technical complexity. To design and operate such devices with high efficiency, the humidification process and the impact of the operating parameters need to be understood to a sufficient degree. To extend this knowledge, we use a refined and novel method to determine the volumetric air–liquid heat and mass transfer coefficients and the humidifier efficiency for various parametric settings. The volumetric transfer coefficients increase with both of the superficial air velocity and the liquid temperature. It is further shown that the decrease of vapor pressure with an increase of the salinity results in a corresponding decrease in the outlet humidity ratio. In contrast to previous studies, liquid heights smaller than 0.1 m are investigated and significant changes in the humidifier efficiency are seen in this range. We present the expected humidifier efficiency with respect to the superficial air velocity and the liquid height in an efficiency chart, such that optimal operating conditions can be determined. Based on this efficiency chart, recommendations for industrial applications as well as future scientific challenges are drawn.
Gas hydrates are usually synthesized by bringing together a pressurized gas and liquid or solid water. In both cases, the transport of gas or water to the hydrate growth site is hindered once an initial film of hydrate has grown at the water–gas interface. A seemingly forgotten gas-phase technique overcomes this problem by slowly depositing water vapor on a cold surface in the presence of the pressurized guest gas. Despite being used for the synthesis of low-formation-pressure hydrates, it has not yet been tested for hydrates of CO 2 and CH 4 . Moreover, the potential of the technique for the study of hydrate decomposition has not been recognized yet. We employ two advanced implementations of the condensation technique to form hydrates of CO 2 and CH 4 and demonstrate the applicability of the process for the study of hydrate decomposition and the phenomenon of self-preservation. Our results show that CO 2 and CH 4 hydrate samples deposited on graphite at 261–265 K are almost pure hydrates with an ice fraction of less than 8%. Rapid depressurization experiments with thin deposits (approx. 330 mm thickness) of CO 2 hydrate on an aluminum surface at 265 K yield identical dissociation curves when the deposition is done at identical pressure. However, hydrates deposited at 1 MPa almost completely withstand decomposition after rapid depressurization to 0.1 MPa, while samples deposited at 2 MPa decompose 7 times faster. Therefore, this synthesis technique is not only applicable for the study of hydrate decomposition but can also be used for the controlled deposition of a super-preserved hydrate.
In times of global climate change, it is increasingly important to investigate emissions and resource consumption of all machines and, if possible, to improve them. This includes within the transport sector car ferries.
In order to reduce the environmental impacts of car ferries, the electrification has penetrated into this sector, which has led to the world's first fully electric car ferry. One of the most important components to operate this ferry is the energy storage. Not only the battery storage of the ferry itself is needed, but also an onshore battery storage system is needed to support the electrical grid.
The present study examines how storage technologies and concepts can impact the environment considering the world's first all-electric car ferry, MF Ampere, which operates in Norway.
To examine this, the current onshore battery storage system is compared to a concrete sphere storage system. For this purpose, data from the first test run of this new storage technology, which was successfully carried out by the Fraunhofer Institute in 2016, is considered. Subsequently, a life cycle assessment of the two storage systems is carried out to compare the environmental impacts.
The concrete sphere storage system performs better for 15 of 17 impact categories compared to the existing onshore battery storage system. Depending on the impact category the impact reduction is about 2% to 8%.
Nevertheless, it is difficult to estimate how long the useful life and how good the efficiency of the concrete ball storage will be, since no system of this size has been tested yet. Also, the costs of the concrete sphere storage system have not been considered.
A concept for a recommender system for the information portal swissmom is designed in this work. The challenges posed by the cold start problem and the pregnancy-related temporal interest changes need to be considered in the concept. A state-of-the-art research on recommender systems is conducted to evaluate suitable models for solving both challenges. The explorative data analysis shows that the article's month of pregnancy is an important indicator of how relevant an article is to a user. Neither collaborative filtering, content-based filtering, hybrid models, nor context-aware recommender systems are applicable because the user's pregnancy phase is unknown in the available data. Therefore, the proposed recommender system concept is a case-based model that recommends articles which belong to the same gestation phase as the currently viewed article.
This recommender system requires that the month of pregnancy, in which an article is relevant, is known for each article. However, this information is only available for 31% of all articles about pregnancy. Consequently, this work looks for an approach to predict the month of gestation based on the article text. The challenges with this are that only few training data are available, and the article texts of the various months of pregnancy often contain the same terms, considering all articles are about pregnancy. A keyword-based approach using the TF-IDF model is compared with a context-based approach using the BERT model. The results show that the context-based approach outperforms the keyword-based approach.
This master thesis investigates a Computational Intelligence-based method for solving PDEs. The proposed strategy formulates the residual of a PDE as a fitness function. The solution is approximated by a finite sum of Gauss kernels. An appropriate optimisation technique, in this case JADE, is deployed that searches for the best fitting parameters for these kernels. This field is fairly young, a comprehensive literature research reveals several past papers that investigate similar techniques.
To evaluate the performance of the solver, a comprehensive testbed is defined. It consists of 11 different Poisson equations. The solving time, the memory consumption and the approximation quality are compared to the state of the art open-source Finite Element solver NGSolve. The first experiment tests a serial JADE. The results are not as good as comparable work in the literature. Further, a strange behaviour is observed, where the fitness and the quality do not match. The second experiment implements a parallel JADE, which allows to make use of parallel hardware. This significantly speeds up the solving time. The third experiment implements a parallel JADE with adaptive kernels. It starts with one kernel and introduce more kernels along the solving process. A significant improvement is observed on one PDE, that is purposely built to be solvable. On all other testbed PDEs the quality-difference is not conclusive. The last experiment investigates the discrepancy between the fitness and the quality. Therefore, a new kernel is defined. This kernel inherits all features of the Gauss kernel and extends it with a sine function. As a result, the observed inconsistency between fitness and quality is mitigated.
The thesis closes with a proposal for further investigations. The concepts here should be reconsidered by using better performing optimisation algorithms from the literature, like CMA-ES. Beyond that, an adaptive scheme for the collocation points could be tested. Finally, the fitness function should be further examined.
Many test drives are carried out in the automotive environment. During these test drives many signals are recorded. The task of the test engineers is to find certain patterns (e.g. an emergency stop) in these long time series. Finding these interesting patterns is currently done with rule based processing. This procedure is very time consuming and requires a test engineer with expertise. In this thesis it is examined if the emerging field of machine learning can be used to support the engineers in this task. Active Learning, a subarea of machine learning, is used to train a classifier during the labeling process. Thereby it proposes similar windows to the already labeled ones. This saves the annotator time for searching or formulating rules for the problem. A data generator is worked out to replace the missing labeled data for tests. The custom performance measure “proportion of seen samples” is developed to make the success measurable. A modular software architecture is designed. With that, several combinations of Time Series Classification algorithms and query strategies are compared on artificial data. The results are verified on real datasets, which are open source available. The best performing, but computational intensive solution is an adapted RandOm Convolutional KErnel Transform (ROCKET). The custom query strategy “certainty sampling” shows the best results for highly imbalanced datasets.
The rapidly evolving nature of Industry 4.0 has confronted corporates with the challenge of being able to react rapidly and nimbly (Van Solingen, 2020). Hence, many corporates need to embark on a journey of adaptation toward becoming agile organisations (Schmitz, 2018). However, this adaptation can only be achieved if employees fully commit to changing to an agile posture, and the required commitment is simply not forthcoming without proper corporate initiatives (Neves & Caetano, 2009). As there is no holistic summary of corporate initiatives required to boost employees' commitment to change when approaching an agile transformation, this study supplements the current research. The initiatives are derived from the existing literature and from unique insights given into a European automotive supplier that is currently managing a global agile transformation. Employees’ perceptions of the transformation in Austria and China were recorded and conclusions regarding what drives employees’ commitment to change and what led to job terminations were determined.
This paper sought to identify and analyze what are the barriers towards women career’s development as business leaders in Brazil and Nicaragua when it comes to the country societal variables. In order to comprehend these barriers through women’s perception, qualitative data was chosen for this investigation, which was gathered through one-to-one interviews within businesswomen from Brazil and Nicaragua that have experience in leadership positions. The results of this research confirm that societal, economic, and political factors have great influence at gender equality and in how it affects women’s progress as business leaders. Thus, it can vary considerably between countries, even when they have similar culture backgrounds. Furthermore, it is imperative to comprehend these differences in order to close any gender gap in the field.
Recently the use of microRNAs (miRNAs) as biomarkers for a multitude of diseases has gained substantial significance for clinical as well as point-of-care diagnostics. Amongst other challenges, however, it holds the central requirement that the concentration of a given miRNA must be evaluated within the context of other factors in order to unambiguously diagnose one specific disease. In terms of the development of diagnostic methods and devices, this implies an inevitable demand for multiplexing in order to be able to gauge the abundance of several components of interest in a patient’s sample in parallel. In this study, we design and implement different multiplexed versions of our electrochemical microfluidic biosensor by dividing its channel into subsections, creating four novel chip designs for the amplification-free and simultaneous quantification of up to eight miRNAs on the CRISPR-Biosensor X (‘X’ highlighting the multiplexing aspect of the device). We then use a one-step model assay followed by amperometric readout in combination with a 2-minute-stop-flow-protocol to explore the fluidic and mechanical characteristics and limitations of the different versions of the device. The sensor showing the best performance, is subsequently used for the Cas13a-powered proof-of-concept measurement of two miRNAs (miRNA-19b and miRNA-20a) from the miRNA-17∼92 cluster, which is dysregulated in the blood of pediatric medulloblastoma patients. Quantification of the latter, alongside simultaneous negative control measurements are accomplished on the same device. We thereby confirm the applicability of our platform to the challenge of amplification-free, parallel detection of multiple nucleic acids.
Cultural Due Diligence
(2020)
Much research has been conducted in recent years to discover the reasons for the high failure rate of M&As, whereas one frequently cited reason is the incompatibility of the corporate cultures. In order to minimize this risk and to be able to react to these differences already at an early stage, Cultural Due Diligence offers itself as part of the due diligence process. Unlike existing, more general research, I emphasize the cultural challenges companies face when investing transnationally with this thesis. Using the results of a single case study with inductive character, I answer the question how to conduct Cultural Due Diligence in cross-border M&As and propose an appropriate model. The findings reveal that especially in cross-border M&As, cultural incompatibility poses a risk for failure. I was able to find out that companies that seek to grow internationally with M&As deal with similar issues in terms of corporate culture as pointed out in existing Cultural Due Diligence methods. The present study, however, shows that national culture has a great influence on corporate culture, which is why it is essential to include it in the cultural assessment in cross-border acquisitions. This provides information about why there are differences, besides the fact that they exist. Only this understanding puts a company in the appropriate starting position to recognize differences, understand them, assess whether these differ-ences are acceptable, as well as to develop appropriate strategies to address them in the integration phase.
The purpose of an energy model is to predict the energy consumption of a real system and to use this information to address challenges such as rising energy costs, emission reduction or variable energy availability. Industrial robots account for an important share of electrical energy consumption in production, which makes the creating of energy models for industrial robots desirable. Currently, energy modeling methods for industrial robots are often based on physical modeling methods. However, due to the increased availability of data and improved computing capabilities, data-driven modeling methods are also increasingly used in areas such as modeling and system identification of dynamic systems. This work investigates the use of current data-driven modeling methods for the creation of energy models focusing on the energy consumption of industrial robots.
For this purpose, a robotic system is excited with various trajectories to obtain meaningful data about the system behavior. This data is used to train different artificial neural network (ANN) structures, where the structures used can be categorized into (i) Long Short Term Memory Neural Network (LSTM) with manual feature engineering, where meaningful features are extracted using deeper insights into the system under consideration, and (ii) LSTM with Convolutional layers for automatic feature extraction. The results show that models with automatic feature extraction are competitive with those using manually extracted features. In addition to the performance comparison, the learned filter kernels were further investigated, whereby similarities between the manually and automatically extracted features could be observed. Finally, to determine the usefulness of the derived models, the best-performing model was selected for demonstrating its performance on a real use case.
In this thesis the effect of dc voltage bias on the equivalent series resistance (ESR) of capacitors and especially ferroelectric dielectric ceramic capacitors (FDCC) is analysed. Further the influence of the dc biased ESR on the losses of capacitors is investigated. Also piezoelectric resonances (PR) occurring in FDCCs with applied dc bias and their influence on the losses are analysed.
Therefore a measurement circuit to measure the impedance and thus the ESR of capacitors in combination with a vector network analyser (VNA) is developed. Using the developed circuit the ESR of capacitors of different technologies is measured and their behaviour with dc bias is evaluated. The losses of an FDCC are measured in a power electronic (PE) circuit with a developed calorimetric measurement system (CMS). The influence of the PR is investigated by tuning the switching frequency of the PE system and thus the frequency of the capacitor current exactly into the PR. The measured losses are then compared to a calculation based on the capacitor current harmonics and the respective ESR.
The measurements show an increase of the ESR with dc bias for all measured FDCCs. The loss measurements show a significant increase of the losses in an FDCC if the current frequency matches the PR frequency. Consequently a decrease of the PE system's efficiency is measured. The loss calculations do not exactly match the measurements but there is a systematic deviation of the same order for all measurements.
This paper presents a project developed at the K.S.Rangasamy College of Technology (Tamilnadu,India) aimed at designing, implementing, and testing an autonomous multipurpose vehicle with safe, efficient, and economic operation. This autonomous vehicle moves through the crop lines of a Agricultural land and performs tasks that are tedious and/or hazardous to the farmers. First, it has been equipped for spraying, but other configurations have also been designed, such as: a seeding ,plug platform to reach the top part of the plants to perform different tasks (pruning, harvesting, etc.), and a trailer to transport the fruits, plants, and crop waste.
Design and optimization of 1x2N Y-branch optical splitters for telecommunication applications
(2020)
This paper presents the design and optimization of 1x2N Y-branch optical splitters for telecom applications. A waveguide channel profile, used in the splitter design, is based on a standard silica-on-silicon material platform. Except for the lengths of the used Y-branches, design parameters such as port pitch between the waveguides and simulation parameters for all splitters were considered fixed. For every Y-branch splitter, insertion loss, non-uniformity, and background crosstalk are calculated. According to the minimum insertion loss and minimum non-uniformity, the optimum length for each Y-branch is determined. Finally, the individual Y-branches are cascade joined to design various Y-branch optical splitters, from 1x2 to 1x64.
Introducing 3D sub-micrometer technologies based on polymers opened new possibilities of design and fabrication of photonic devices and components in 3D arrangement. 3D laser lithography is direct writing process based on two photon polymerization exhibiting high accuracy and versatility, where numerous resists and even polymer ceramic mixtures can be used. We present design and simulation of polymer based photonic components with a focus on arrayed waveguide gratings (AWG) based on optical multiplexers/demultiplexers and optical splitters. All optical components were designed for 1550 nm operating wavelength, applying two commercial photonics tools. This study creates a basis for the design of optical components in 3D arrangement, which will be fabricated by 3D laser lithography.
Having autonomy in the workplace can have a positive impact on employees’ performance, which in turn can benefit the organization’s competitive advantages. While previous researches have primarily focused on the psychological effects of job autonomy on employee performance and has been limited to certain domains, the relationship between job autonomy and organizational design is an important area of study for organizations seeking to improve their competitiveness. This thesis proposes a conceptual model for designing an organization structure that promotes employee performance in manufacturing companies by removing obstacles towards obtaining job autonomy. The focus is on ambitious employees who seek growth and development opportunities within their organization. The model is based on a review of existing literature on job autonomy and organizational design. Exploratory qualitative research was conducted with selected ambitious employees from different industries by means of one-on-one semi-structured interviews. Overall, the proposed model has practical implications for manufacturing companies looking to motivate their employees, as well as for researchers seeking to advance their understanding of organizational design in our times.
Debugging errors in software applications can be a major challenge. It is not enough to know that a specific error exists, but the cause of it must be found in order to be able to fix it. Finding the source of an error can be time and cost intensive. The general approach is to analyse and debug the presumably erroneous part of the software. The analysis can be accompanied by instrumentation to gather additional information during the program execution. The analysis is made more difficult by the existence of different errors categories. Each category may need to be handled individually. Especially in embedded software applications, which commonly lack features like process or memory isolation, error detection and prevention can be even more challenging. This is the kind of problem this thesis tackles. This thesis tries to support developers during debugging and troubleshooting. The main focus is on errors related to memory management and concurrency. Specific features and properties of Arm Cortex-M processors are used to try to detect errors as well as their causes. For example, the memory protection unit is used to isolate the stack memories of different tasks running in a RTOS. The thesis tries to provide as much information as possible to the developer when reporting errors of any kind. The solution developed in this thesis also contains a custom memory allocator, which can be used to track down errors related to dynamic memory management. Furthermore, a Eclipse plugin has been developed which provides assertions for array accesses to detect and prevent out-of-bound accesses. The resulting solution has been implemented in commercial embedded software applications. This ensures that the developed solution is not only suitable for newly developed applications, but also for the integration into already existing products.
Development of a low pressure syringe pump for detecting cannabinoids through liquid chromatography
(2022)
The following thesis covers the miniaturization and characterization of a pneumatic syringe pump, which is used for applications in low-pressure liquid chromatography. For this purpose, the components of the prototype are dealt with in the first section. These include the membrane pump and the cylinder for pressure and force generation, the syringe used for sample preparation and the construction of the test column. Furthermore, the pressure preparation on the cylinder, the friction losses of the syringe and then the behavior of the syringe in various application scenarios are considered. In the second section, the focus is on the different behaviors when using water and ethanol as a solvent. Tests in normal applications, as well as with air pockets or leaking seals, show the different behavior and the resulting deviations in the test pressure of the column. In addition, the maximum forces that can be applied to the syringe are worked out in several tests and the different maximum pressures, which depend on the solvent contained, are evaluated. These different maximum pressures, which are due to the different sealing behavior in connection with the surface tension of the liquid, will be discussed in conclusion. An outlook follows, up to which test pressures the system can be used and how these can be achieved.
The detection of glucose is an essential part of diabetes management and can help to prevent secondary diseases, that can occur as a result of diabetes. For this reason, it is important to improve the current glucose monitoring by developing novel sensors with high efficiency, low cost and compact design. The use of microelectrodes with interdigitated array (IDA) structures reduces the total detector size while providing benefits such as large currents, high sensitivity, and fast response. The aim of this thesis is to develop a novel sensor based on platinum interdigitated array (IDA) electrodes and to investigate which method is most effective for the detection of glucose. This work is divided into two parts. The first part is focused on the design and the fabrication of the sensor chips. The second part is concerned with the electrochemical characterisation of the sensors. Two distinct sensor designs are created, each consisting of a four-electrode system arranged as an interdigitated array. For the fabrication of the sensors, two different manufacturing processes are used. A lift-off process is used to fabricate the 2 μm-Gap sensor chips, whereas a lift-off free process is applied to produce the nanogap sensor chips. The electrochemical characterisation of both sensor chips is achieved by the immobilisation of the enzyme glucose oxidase (GOx) on the electrode surface. This thesis investigates the immobilisation of GOx by reduction of diazonium salts and the direct immobilisation of GOx by cyclic voltammetry. As a result of this work, it has been demonstrated that glucose detection by reduction of diazonium salts is error-prone due to modification with a multi-step procedure and is not suitable for our sensors based on platinum IDA electrodes. The direct immobilisation of GOx by cyclic voltammetry, by contrast, demonstrates the successful detection of glucose. In glucose solutions ranging from 5 mM to 20 mM, a direct correlation between the glucose concentration and the measured current is obtained. The reproducibility of direct immobilization is demonstrated by repeated performance with various sensors.
In today’s world, fiber optic networks for data transmission are an essential technology. This technology provides multiple advantages compared to conventional electrical data transmission. The simultaneous transmission of multiple optical signals in a single fiber is one of the main benefits of fiber optic cable. This is accomplished by directing the different optical signals into a single fibre and splitting them up after the transmission in order to obtain the individual signals. Arrayed Waveguide Gratings (AWGs) are used for this purpose in modern optical networks. Design and evaluation process are two components of AWG development. During the evaluation of several simulated and already manufactured AWGs for telecommunication applications, it was discovered that the channel spacing parameter does not conform telecommunication standards. The correct shift of the geometric parameter ”separation of the output waveguides” leads to the standard-conform channel spacing.
According to the current state of the art, no commercial tool is available which calculates the shift of this parameter correctly. The aim of this thesis is the development of a software tool to calculate the accurate shifting of the geometric parameter ”separation of the output waveguides” of an AWG. This tool operates as an interface between the design and evaluation processes and must be able to import the data format of the evaluation process and returns the data in a suitable data format for the design process. The Vorarlberg University of Applied Sciences uses three different methods for the shifting of the geometric parameter ”separation of the output waveguides”. These methods are evaluated and optimised as part of this thesis. Additionally, it has been determined that the shift of the geometric parameter ”separation of the output waveguides” has no significant impact on the performance of the AWG.
Digitalisation poses great challenges for regional tourism management. However, many organisations are currently undergoing a transformation from a marketing to a destination management organisation (DMO), which is why only a few have managed to adopt new digital approaches and to assert themselves as DMOs within the destination and against ever growing global platforms.
The presented master thesis therefore deals with this issue and aims to pave the way for DMOs to develop and use digital business models themselves.
The objective of the thesis is to develop a systematic process for the development of own DMO business models and to evaluate whether the establishment of a multi-sided platform as the recipe for the success of global platform providers is also suitable for DMOs. For this purpose, an extensive literature research was conducted and semi-structured expert interviews were evaluated. In addition, the Anchor Point Canvas was developed as a supporting framework for the modelling of business models for companies with historically grown structures and constraints.
Today, industrial B2B manufacturers face a rapidly changing environment, exacerbated by increasing globalization and associated shifts in the competitive landscape. Digital transformation and the emergence of new innovations and technologies are forcing companies to rethink their business models and offerings to integrate digital services to strengthen competitive advantages. Suppliers are becoming more deeply involved in customer processes through digital after-sales services, with the aim of exploiting efficiencies. Following the servitization transformation, companies intend to change their purpose from focusing on the pure physical product to becoming a service provider with emphasis on value creation and the capture of the customer.
To investigate how customer and supplier perspectives agree and what requirements each side has for digital after-sales services, exploratory qualitative research was conducted with customers and suppliers by means of one-on-one interviews. The thesis aimed to assess the status, progress, and future possibilities of implementing digital after-sales services and business models based on them. Research shows that the far-reaching establishment of product-accompanying services with strong connectivity and customer-centricity is primarily relevant. Disruptive business models still require a mind-shift and organizational readiness on the part of both customers and suppliers. In principle, digitization in after-sales interaction is beneficial and should be steadily advanced to make customer processes as well as further developments at the supplier level more efficient and well-founded through the analysis of real data. Overall, this thesis outlines important aspects that need to be considered while developing digital service innovations to deal with customer demands appropriately.
Keywords: Servitization, Digital After-Sales Services, Predictive Maintenance, Remote Monitoring, Digital Interaction, Digital Service Innovation, Digital Service Innovation Process
Lack of transparency and traceability of products and their raw materials means that most products can only be thrown away or not properly recycled due to a lack of relevant data. This conflicts with the circular economy principles, which are demanded by several initiatives, including the European Union. The aim of this master thesis is to analyze this conflict and to propose a technical solution based on Distributed Ledger Technology that enables transparency and traceability of products and their materials. Therefore, the thesis addresses two central research questions: 1. How can traceability and transparency be enabled by integrating a DLT solution? 2. How would a prototype with the integration of smart contracts and DLT look like? To answer these questions, a blockchain solution is implemented using Hyperledger Fabric. The solution uses the immutability and decentralized nature of DLT to record and track the movement of products and their materials throughout their life cycle in the Circular Economy. Furthermore, with private data collections, confidentiality, and privacy are granted while ensuring transparency. The thesis contributes to the Circular Economy field by exploring the principles, models, and challenges of the Circular Economy and the circularity goals of a Digital Product Passport to develop a suitable technical solution. The chosen blockchain framework, Hyperledger Fabric, is presented, and its key components and features are highlighted. The thesis also delves into the design decisions and considerations behind the Digital Product Passport platform, explaining the architecture and transaction flow together with the prototype implementation and demonstration to showcase the functionality of the solution. Results and analysis provide insights into the challenges of the Circular Economy, sustainable resource management, and the Digital Product Passport, resulting in recommendations for future improvements and enhancements. Overall, this thesis offers a practical solution utilizing DLT to enable transparency and traceability in the Circular Economy, contributing to the realization of sustainable and efficient resource management practices to ultimately contribute to the set Circular Economy initiatives.
This master thesis investigates drivers and barriers of innovation workshops for an intercultural participant group. Actively dealing with innovation management is considered vital for companies which are acting on competing markets. An innovation workshop is a useful tool in order to foster innovation ability, develop innovative ideas and drive innovation forward. Intercultural participant groups are not only a common challenge in today's business world but also entail several benefits as they incorporate diverse knowledge bases and perspectives and hence contribute to the ideation and innovation process. Within the master thesis a broad variety of barriers and drivers are evaluated. Main barriers of innovation workshops for an intercultural participant group are high conflict potential, miscommunication, language barriers, a lack of management support, no agreement on workshop objectives as well as poor workshop preparation, organization and facilitation. Main drivers of innovation workshops for an intercultural participant group are a heterogeneous group composition, intercultural competence of the facilitator, the opening up of mindset silos, an intensive workshop preparation and empathetic facilitation. These drivers and barriers build the basis for the determination of success factors and recommendations for action for organizers and facilitators of an innovation workshop for an intercultural participant group. In the further course of the paper an exemplary workshop design will be presented as a guideline and framework for managerial practice
The research focused on the wood pellet market for private consumers in Germany and has the objective to understand the factors affecting the purchase decisions of wood pellets buy-ers. The aims of the research were achieved by applying the Engel, Kollat, Blackwell model of consumer behaviour, by conducting in-depth interviews and deriving the grounded theory. The application of EKB model revealed that the following groups of factors may influence the con-sumers: cultural (culture and social class), social (family influence), personal (age and lifecycle stage), psychological (believes, motives, attitudes) and unexpected circumstances. In-depth interviews with the buyers of wood pellets helped specify the influencing factors to finally an-swer the research question. The analysis showed that the buyers of wood pellets are influ-enced by family, personal believes and attitudes, and the unexpected circumstances. The most important factors for the buyers are the quality of the pellets and reliability of the supplier. If they are satisfied with the quality of product and service, they will be reluctant to look for an alternative. And on the opposite side, in case the quality of the product or the service is unsat-isfactory this is a limiting factor and will stop the buyer from purchasing this product. Price is an important factor for the buyers of pellets in bags. However, in the situation of volatile mar-ket and exploding prices, the price factor will play a bigger role. Thus, the strategic factors for marketing of pellets is to concentrate on quality and price communication, and to focus on the quality of pellet delivery service.
Real-time measurements of the differences in inhaled and exhaled, unlabeled and fully deuterated acetone concentration levels, at rest and during exercise, have been conducted using proton transfer reaction mass spectrometry. A novel approach to continuously differentiate between the inhaled and exhaled breath acetone concentration signals is used. This leads to unprecedented fine grained data of inhaled and exhaled concentrations. The experimental results obtained are compared with those predicted using a simple three compartment model that theoretically describes the influence of inhaled concentrations on exhaled breath concentrations for volatile organic compounds with high blood:air partition coefficients, and hence is appropriate for acetone. An agreement between the predicted and observed concentrations is obtained. Our results highlight that the influence of the upper airways cannot be neglected for volatiles with high blood:air partition coefficients, i.e. highly water soluble volatiles.
Effective lead management
(2023)
In the last few years the global interest on lead management has increased. This classic topic for marketing and sales departments is aimed at converting potential customers into sales. The following thesis identifies the challenges and solutions for marketing and sales departments in order to process effective lead management. Using data from a literature review and qualitative empirical research, conducted with representatives of marketing and sales departments, the results showed overall and task specific challenges and solutions. The research indicates that overall challenges and solutions regarding the gap between marketing and sales, new processes and data management including data quality, software and silos emerge. In addition task specific challenges and solutions concerning lead generation including purchased leads, lead qualification, lead nurturing and sales specific challenges and solutions conclusively the focus on existing customers, time famine and lead routing were identified. This thesis provides a framework for further studies regarding the challenges and solutions for marketing and sales departments processing lead management.
This master thesis investigates effective leadership behaviour of multicultural teams during change management. Multicultural teams can be highly effective in dealing with complex change processes and can represent a key player to tackle today’s VUCA-world challenges.
Effectiveness of multicultural teams during change depends critically on leadership with a range of specific behaviours. Involvement and support of the employees in a coaching role is key. Leaders need to display behaviours such as continuous development of cultural and emotional intelligence, critical self-reflection, open-mindedness, and readiness to serve as authentic role models. Furthermore, the creation of a sense of unity based on good communication and common sense is essential to build multicultural teams, and to enable them to embrace their differences as opportunity. Trust, transparency and a holistic change process are vital. Effectiveness essentially depends on the following factors: the organization’s culture, the characteristics of the employees and of their leader, and on the external environment. Leaders should take these factors into consideration at all times.
Throughout history, a variety of influences have changed the way we sell our products. Starting with the Industrial Revolution up to the first saturation phase in the 1970s. The question now arises as to whether the heating industry is currently back on an evolutionary development path with the increasing digitalisation of distribution. How the sales process in the B2B sector will change with increasing digitalisation and what effects this will have on sales personnel is only documented by a few sources which do not allow any conclusions to be drawn about the craft or even the heating industry. This results in a research gap which is to be closed in the context of this thesis. The aim of this research project is to find out the effects of a further digitalisation of the sales process on the sales force in the defined environment of the heating industry in Central Europe. For this purpose the following research questions are asked: Which steps in the sales process in the heating industry in Central Europe should be digitalised? How will the digitalisation of the sales process affect the sales force in the heating industry in Central Europe? A case study, according to Yin was chosen as the research method. The data were collected by means of in-depth interviews and analysed qualitatively, according to Mayring. The increasing digitalisation will have a large effect on the sales force, tasks will disappear, new tasks will be added and new ones will replace conventional working methods. In summary, automation will simply make tasks superfluous, software tools will improve quality and increase efficiency, and personal selling will become a premium skill. Companies will try to automate as many backoffice activities as possible and reduce the number of office staff if necessary.
The master thesis concentrates on two different cases to generate energy from MSW. In the first case, the MSW is incinerated in an incineration plant. This approach represents the present situation in the waste treatment in large parts of the UK.
In the second case, the OFMSW is separated in a treatment facility and used in a fermentation plant. The remaining waste is again used as a feedstock in an incineration plant. The difference in the net energy yield between these two cases is investigated in this thesis.
To calculate the difference in the energy yield of case 1 and case 2, a research of the existing literature about comparisons of incineration and fermentation plants and their results are reflected and data about the MSW in the UK is collected. With the input of the literature and the researched data, a model is built which compares the two different cases of waste treatment. The results of the comparisons are then examined by varying different parameters. This step is repeated by using different input parameters. Afterwards, the results are compared and analysed.
In the next part of the thesis, an economic analysis of the incineration and fermentation combined technology plant is made. In this analysis, the investment costs, the annual profits and the annual costs of an additional fermentation plant are discussed and calculated. The result of the analysis is displayed as an amortization time calculation. The results are then analysed by varying the parameters in a sensitivity analysis.
Finally, the research question is answered and a forecast for possible plant designs with an incineration and a fermentation plant in combination are discussed.
Power cables play an important role in power grids. Insulation faults in cables can have adverse effects on the operating behaviour. These effects can be assessed through an AC withstand test by using a very-low frequency high voltage generator. This generator produces a sinusoidal voltage waveform at 0.1Hz with high voltage levels up to 65kV peak. During the quality assessment, the power cable is repeatedly charged and discharged. The discharging process is done by a discharging circuit where the energy is dissipated thermally. But to reuse the dissipated energy a novel extension in form of an energy storage system is presented. This thesis, therefore, describes the design process of an energy storage system that allows the temporary storage of the discharge energy. The developed system is composed of a bidirectional DC/DC converter and an aluminium electrolytic capacitor as storage type. Based on the maximum VLF system ratings the energy storage unit is dimensioned and sized. The effective power flow control between the storage system and the available discharge energy is done by a synchronous buck-boost converter. This bidirectional converter works in continuous conduction mode over the complete charging phase. Together with a theoretical analysis of the underlying problem and the use of converter analysis methods the selected synchronous buck-boost converter is dimensioned and sized. In addition, a state space AC modeling of the converter with its electrical uncertainties is conducted. With the converters AC model, the controller is designed. A closed-loop input converter current control scheme based on a proportional-integral controller is implemented. The system assessment is done by a model-based hardware implementation in Matlab Simulink and Plecs Blockset. The system is rated to store discharge energies up to 4.3kJ in a short charging period of 2.5s. The maximum peak power during the charging phase is 2.7kW. The digital proportional-integral controller is implemented through an emulation process of the designed analog controller. Based on a C-code implementation of the digital controller the gap between the real hardware is reduced. During the design process theoretical calculations are made and reveal that designing a capacitor storage unit has a direct impact on the peak system currents and also impose also limitations on permissible DC voltage ranges on electrical components. The developed energy storage system and its power flow control strategy were investigated through simulation studies. The results show proper charging of the energy storage medium. In addition, also a statement of the final technical feasibility is made. In total, this work summarizes a detailed design process of the energy storage system. This proof of concept is intended to further advance the system integration.
Over the last years, polymers have gained great attention as substrate material, because of the possibility to produce low-cost sensors in a high-throughput manner or for rapid prototyping and the wide variety of polymeric materials available with different features (like transparency, flexibility, stretchability, etc.). For almost all biosensing applications, the interaction between biomolecules (for example, antibodies, proteins or enzymes) and the employed substrate surface is highly important. In order to realize an effective biomolecule immobilization on polymers, different surface activation techniques, including chemical and physical methods, exist. Among them, plasma treatment offers an easy, fast and effective activation of the surfaces by micro/nanotexturing and generating functional groups (including carboxylic acids, amines, esters, aldehydes or hydroxyl groups). Hence, here we present a systematic and comprehensive plasma activation study of various polymeric surfaces by optimizing different parameters, including power, time, substrate temperature and gas composition. Thereby, the highest immobilization efficiency along with a homogenous biomolecule distribution is achieved with a 5-min plasma treatment under a gas composition of 50% oxygen and nitrogen, at a power of 1000 W and a substrate temperature of 80 C. These results are also confirmed by different surface characterization methods, including SEM, XPS and contact angle measurements.
In previous studies of linear rotary systems with active magnetic bearings, parametric excitation was introduced as an open-loop control strategy. The parametric excitation was realized by a periodic, in-phase variation of the bearing stiffness. At the difference between two of the eigenfrequencies of the system, a stabilizing effect, called anti-resonance, was found numerically and validated in experiments. In this work, preliminary results of further exploration of the parametric excitation are shared. A Jeffcott rotor with two active magnetic bearings and a disk is investigated. Using Floquet theory, a deeper insight into the dynamic behavior of the system is obtained. Aiming at a further increase of stability, a phase difference between excitation terms is introduced.
The Fast Average Current Mode control methodology is a novel method for the implementation of a current compensator in a switched-mode power supply. It does not require compensation against sub-harmonic instability and is inductor independent. In this work, the digital implementation of this topology is compared against an analog implementation using simulation. Additionally, a hardware prototype is created to validate the digital simulation's results. In a Simulink environment, parameters of the digital implementation, such as the digital-to-analog converter resolutions and the delay counter frequency are varied to research their impact on system performance. The simulations show that a digital current compensator has similar performance as an analog implementation when designed tailored to the application. When evaluating the whole control loop the digital system is inferior due to added delays caused by digital to analog conversion. By operating the Buck converter hardware implementation as a current source, the functionality of the current mode control implementation in a FPGA was proven. Voltage control cannot be validated due to hardware issues. Due to the successful simulation of the source code with a mixed signal model of the converter, it can be assumed that it is functional. Apart from performance, a digital implementation shows many benefits compared to an analog solution, such as configurability of control parameters and easy compensation of component variations and aging.
In the residential construction industry, the focus on energy efficiency and cost effectiveness has been gaining importance. In order to achieve these contradicting objectives, a shift towards a reduced complexity in building practices can be observed.
Within the HVAC sector, the Tempering method for space heating has received particular attention as an alternative way to heat museums and buildings worthy of preservation.
In spite of the simplified design, this space heating system is claimed to offer significant advantages in its present field of application.
This study evaluates the implementation of Tempering in the residential context. So far, there is no scientific research on the implementation of Tempering in energy efficient-dwellings.
This master thesis provides initial results on achievable heat flux values, the impact on heat generation efficiency, the inherent installation costs as well as the particular
consequences in terms of end energy consumption of the building as a whole. The findings are compared to the individual performances of well-established heat emission approaches.
By means of a numerical analysis and a case study on a real-case single-family home, it is found that the heat flux values of Tempering systems suffice for the implementation within buildings, which comply with the low-energy building standard. Comparing radiant walls, radiant floors and radiators, the inherent installation costs are lowest for Tempering and radiant floors. The impact on the end energy consumption depends largely on the utilised heat generation system. With a gas-condensing boiler, Tempering performs equal to the radiant systems. When a ground source heat pump system is installed, however, Tempering performs poorly and accounts for a significantly increased energy consumption. Radiator systems are found to be the most energy-efficient method for space heating in both cases.
This thesis evaluates the feasibility of conducting visual inspection tests on power industry constructions using object detection techniques. The introduction provides an overview of this field’s state-of-the-art technologies and approaches. For the implementation, a case study is then conducted, which is done in collaboration with the partner company OMICRON Electronics GmbH, focusing on power transformers as an example. The objective is to develop an inspection test using photographs to identify power transformers and their subcomponents and detect existing rust spots and oil leaks within these components. Three object detection models are trained: one for power transformers and sub-components, one for rust detection, and one for oil leak detection. The training process utilizes the implementation of the YOLOv5 algorithm on a Linux-based workstation with an NVIDIA Quadro RTX 4000 GPU. The power transformer model is trained on a dataset provided by the partner company, while open-source datasets are used for rust and oil leak detection. The study highlights the need for a more powerful GPU to enhance training experiments and utilizes an Azure DevOps Pipeline to optimize the workflow. The performance of the power transformer detection model is satisfactory but influenced by image angles and an imbalance of certain sub-components in the dataset. Multi-angle video footage is a proposed solution for the inspection test to address this limitation and increase the size of the dataset, focusing on reducing the imbalance. The models trained on open-source datasets demonstrate the potential for rust and oil leak detection but lack accuracy due to their generic nature. Therefore, the datasets must be adjusted with case-specific data to achieve the desired accuracy for reliable visual inspection tests. The results of the case study have been well-received by the partner company’s management, indicating future development opportunities. This case study will likely be a foundation for implementing visual inspection tests as a product.
Moving from one country to another, from one cultural context to a different one comes with many challenges and problems. The expatriate adjustment process, in general, has been evaluated extensively in the literature. Little is known if the knowledge in the literature is also valid for the situation of expatriates in rural Vorarlberg. In this paper was examined, which are the most common problems for highly skilled immigrants that are moving to Vorarlberg. In a mixed-method approach, information was gathered with an online questionnaire whose results served as a basis for a series of semi-structured interviews. In addition, an expert talk with a local relocation consultant was conducted. It was found that by far, the most severe difficulty is based on the domestic language situation. An expatriate needs to talk and understand German, but the local language is an Alemannic subsection of the German language that is not easy to understand. Additional difficulties that cause culture shock are limited opening hours, mobility troubles, and several others. The awareness about the composing of these problems might help to find the appropriate measures to support expatriates to come in the future.
The humidification dehumidification (HDH) cycle is a process for thermal water treatment. Many studies were carried out investigating operation of an HDH cycle with water and seawater as working liquid. Currently research into other areas of application is limited. Exchanging the working liquid in the humidifier from seawater to a water oil emulsion and investigating its behavioural changes is the basis for the expansion into applications such as bilge water treatment. This master’s thesis covers analysis of the behaviour of an HDH cycle operated with a water oil emulsion. The main elements are (1) proof of concept for operation of the HDH cycle with a water oil emulsion, (2) comparison of measurements and thermodynamic calculations, (3) investigation of the impact of operating parameters and (4) optical analysis of the bubbly flow in water and oil.
Operation of the HDH cycle using water oil emulsion was shown to be feasible with a small change to the setup previously used for investigations with seawater as working liquid. To keep the emulsion from separating into its individual parts, constant movement of the working liquid needs to be ensured. For this a magnetic stirrer was introduced into the bubble column humidifier (BCH) used. In a batch process an oil concentration of >97 % was reached without visible traces of oil in the produced condensate.
Comparison of the measured and thermodynamically evaluated productivity shows that measured productivity is higher. The proposed explanation for this is supersaturation of air at the BCH exit. Further investigation into this phenomenon is needed to confirm this hypothesis.
Influential parameters investigated are (1) liquid temperature, (2) superficial air velocity and (3) sieve plate orifice diameter. Increase of liquid temperature results in an exponential increase in productivity. At superficial air velocities up to 3 cm/s productivity increases with superficial air velocity. For superficial air velocities higher than 3 cm/s productivity plateaus. At low superficial air velocity, an increase of sieve plate orifice diameter results in increasing productivity. Further increase of the sieve plate orifice diameter inverses this phenomenon.
Bubbly flow in water and oil is influenced by the different viscosities of the liquids. Water creates small bubbles of similar size at low superficial air velocities. At superficial air velocities >2 cm/s turbulences start to increase and finely dispersed bubbles are present in the water. Bubbly flow in oil creates larger bubbles at all superficial air velocities. The airflow transitions to plug flow at velocities of 3 cm/s and above.
Result from this master’s thesis can be used for as a basis to broaden the understanding of the HDH cycle and find new areas of applications.
The humidification-dehumidification process (HDH) for desalination is a promising technology to address water scarcity issues in rural regions. However, a low humidifier efficiency is a weakness of the process. Bubble column humidifiers (BCH) are promising for HDH, as they provide enhanced heat and mass transfer and have low maintenance requirements. Previous studies of HDH-systems with BCHs draw different conclusions regarding the impact of superficial air velocity and liquid height on the humidification. Furthermore, the impact of flow characteristics has never been investigated systematically at all. In this study, an optimized BCH test setup that allows for optical analysis of the humidifier is used and evaluated. Our test setup is validated, since the influence of water temperature on the humidification, which is exponential, is reproduced. Measurements with seawater show that the normalised system productivity is increased by about 56 % with an increase in superficial air velocity from 0.5 to 5 cm/s. Furthermore, the system productivity is increased by around 29 % with an increase in liquid height from 60 to 378 mm. While the impact of superficial air velocity can be traced back to temperature changes at the humidifier and dehumidifier outlets, the impact of liquid height is shown to be caused by a smaller heat loss surface in the humidifier with an increase in liquid height. For the impact of sieve plate orifice diameter, a clear influence on the humidification is not apparent, this parameter needs to be investigated further. Finally, our new test setup allows for analysing the humidification of air (1) in a systematic way, (2) in relevant measurement ranges and (3) in comparison with optical analyses of the flow characteristics.
Modern portable electronic devices have seen component heat load increasing, while the space available for heat dissipation has decreased. This requires the thermal management system to be optimized to attain the high performance heat sink. Heat sinks plays a major role for dissipating heat in electronic devices. Phase change material (PCM) is used to enhance the heat dissipation in heat sink. This paper reports the results of an experimental investigation of the performance of Pin fin heat sinks filled with phase change materials for thermal management of electronic devices. The experimental set ups are prepared with the graphical programming language with Lab VIEW (Laboratory Virtual Instruments for Engineering Workbench. Three different types of Pin fin Heat sink with and without PCM are investigated based on different operational timings and the temperature is acquired with the help of Data Acquisition Card (DAQ). The results indicated that the inclusion of the PCM could stabilize the temperature for a longer period and reduce the heating rates and peak temperatures of heat sink with increasing the number of fins can enhance the thermal performance of electronic devices.
The alarming degradation of the natural environment is leading many consumers to increasingly demand sustainable products. Since 2017, the global purchase intention of such products has increased by 63%. To respond to the increasing demand, more and more companies have started producing products from sustainable materials such as recycled products. However, purchase intention does not always result in actual behavior and can vary due to different products and in country-specific contexts. Hence, it is the purpose of this study to determine which factors influence the purchase intention of recycled products and whether these factors differ between a developed country such as Germany and a developing country such as South Africa. Furthermore, the study aims to discover whether there are differences in purchase intention with regard to different product categories, whether there is an intention-behavior gap, and whether there are country-specific differences. Finally, target groups of the corresponding countries will be derived. To answer the research questions, a quantitative study was conducted using an online questionnaire in Germany (n = 603) and South Africa (n = 692). The findings demonstrate that the purchase intention for recycled products is significantly higher in South Africa than in Germany, but no significant difference in the factors influencing the purchase intention could be found. However, the factors differ in terms of the extent of their influence. Thus, the factor “Attitude / Environmental Concern” has the strongest influence in South Africa, while the factor “Value / Accessibility” has the strongest influence in Germany. Likewise, a difference could be found concerning the products, with the purchase intention for mobile phones generally smaller than for t-shirts and toilet paper. In a country-specific comparison, however, purchase intention for t-shirts is significantly higher in South Africa than in Germany. An intention-behavior gap was identified for the sample, and it was found that the age groups 25 to 49 have the strongest purchase intentions and that the purchase intention increases significantly with increasing education level.
Fear of failure is a major factor influencing entrepreneurial actions. Since the female quota for startups and self-employment is still lower than for men, the aim is to determine the extent to which the fear of failure is incorporated into the entrepreneurial actions of women in Austria. The trailblazer and pioneer in female entrepreneurship America is used as an international benchmark for evaluation. A quantitative survey was conducted among women from Austria and America on their fears of failure related to self-employment and their aspirations to become self-employed. There were significant differences in the quantitative study between self-employed and non-self-employed women, irrespective of their country of origin. As a result, recommendations for action were created to reduce the influence of Fear of Failure on entrepreneurial actions of Austrian women.
Background: Peripheral arterial disease (PAD) is a common and severe disease with a highly increased cardiovascular morbidity and mortality. Through the circulatory disorder and the linked undersupply of oxygen carriers in the lower limbs, the ongoing decrease of the pain-free walking distance occurs with a significant reduction in patients’ quality of life. Studies including activity monitoring for patients with PAD are rare and digital support to increase activity via mobile health technologies is mainly targeted at patients with cardiovascular disease in general. The special requirement of patients with PAD is the need to reach a certain pain level to improve the pain-free walking distance. Unfortunately, both poor adherence and availability of institutional resources are major problems in patient-centered care.
Objective: The objective of this trackPAD pilot study is to evaluate the feasibility of a mobile phone–based self tracking app to promote physical activity and supervised exercise therapy (SET) in particular. We also aim for a subsequent patient centered adjustment of the app prototype based on the results of the app evaluation and process evaluation.
Methods: This study was designed as a closed user group trial, with assessors blinded, and parallel group study with face-to-face components for assessment with a follow-up of 3 months. Patients with symptomatic PAD (Fontaine stage IIa or IIb) and possession of a mobile phone were eligible. Eligible participants were randomly assigned into study and control group, stratified by their distance covered in the 6-min walk test, using the software TENALEA. Participants randomized to the study group received usual care and the mobile intervention (trackPAD) for the follow-up period of 3 months, whereas participants randomized to the control group received only usual care. TrackPAD records the frequency and duration of training sessions and pain level using manual user input. Clinical outcome data were collected at the baseline and after 3 months via validated tools (6-min walk test, ankle-brachial index, and duplex ultrasound at the lower arteries) and self-reported quality of life. Usability and quality of the app was determined using the user version of the Mobile Application Rating Scale.
Results: The study enrolled 45 participants with symptomatic PAD (44% male). Of these participants, 21 (47%) were randomized to the study group and 24 (53%) were randomized to the control group. The distance walked in the 6-min walk test was comparable in both groups at baseline (study group: mean 368.1m [SD 77.6] vs control group: mean 394.6m [SD 100.6]).
Conclusions: This is the first trial to test a mobile intervention called trackPAD that was designed especially for patients with PAD. Its results will provide important insights in terms of feasibility, effectiveness, and patient preferences of an app-based mobile intervention supporting SET for the conservative treatment of PAD.
In the regime of incentive-based autonomous demand response, time dependent prices are typically used to serve as signals from a system operator to consumers. However, this approach has been shown to be problematic from various perspectives. We clarify these shortcomings in a geometric way and thereby motivate the use of power signals instead of price signals. The main contribution of this paper consists of demonstrating in a standard setting that power tracking signals can control flexibilities more efficiently than real-time price signals. For comparison by simulation, German renewable energy production and German standard load profiles are used for daily production and demand profiles, respectively. As for flexibility, an energy storage system with realistic efficiencies is considered. Most critically, the new approach is able to induce consumptions on the demand side that real-time pricing is unable to induce. Moreover, the pricing approach is outperformed with regards to imbalance energy, peak consumption, storage variation, and storage losses without the need for additional communication or computation efforts. It is further shown that the advantages of the optimal power tracking approach compared to the pricing approach increase with the extent of the flexibility. The results indicate that autonomous flexibility control by optimal power tracking is able to integrate renewable energy production efficiently, has additional benefits, and the potential for enhancements. The latter include data uncertainties, systems of flexibilities, and economic implementation.
Increasing international competition and accelerated technological change characterize the environment in which companies must maintain and, if possible, expand their competitive advantage. In this context, the new, popular keyword innovation management is often mentioned. Many corporations propagate and use it for marketing purposes. As a result, the companies have to evaluate, develop and launch innovations increasingly faster, which poses great challenges for many and requires a high degree of adaptability.
This master thesis analyzes innovation management (IM) in the automotive industry and in other industries (material manufacturers, service providers, medicine, ...) depending on the number of employees and turnover. In addition, the maturity levels of the IMs and the innovation management systems (IMS) are examined. It also tries to determine which design or "building blocks" are necessary for a successful innovation management. Furthermore, factual and monetary guidelines by the management are evaluated. The thesis also aims to find out how the success of IM is measured. Therefore, guideline-based expert interviews were conducted with responsible people from the innovation departments and then systematically analyzed.
In the literature, expenses for innovations are often wrongly equated with the R&D rate. In this master thesis, it could be shown that this ratio is highest in the automotive industry. However, it does not correlate with the number of employees, turnover, maturity level, success or design of the IM. Furthermore, it could be shown that larger companies have a higher degree of maturity. The reason for this is that more people are usually involved in innovation and that a holistic understanding of innovation is better anchored in large corporations. When designing the IM or the roles of the innovation department, large companies use several different types. While the IM departments in small and medium-sized companies are usually incubators and accelerators, large companies also use corporate venture capital to support start-ups and develop new business models. In this thesis, the success of IM was determined by the number of innovations implemented in customer projects. It was found that, regardless of the size of the company, a higher degree of maturity of the IM and the accelerator role seem to have a positive influence.
Unfortunately, there are rarely concrete goals and targets set by the management although these, along with a holistic understanding of innovation in the company, are without doubt the most important part of a successful innovation management.
The research activity described in this master thesis focus on global leadership in team sport. Football head coaches working or who have worked in the globalised Big Five leagues of England, France, Germany, Spain and Italy are investigated. These leagues are host to players, staff, executives, fandoms and head coaches from around the globe. Sport in general is posed as a valid platform to investigate global leadership. Elite and globalised clubs in association football are further posed the archetype of global sport. Head coaches at the helm of the on-field and off-field teams are hypothesised as global leaders, due to their squad, staff and networks of global nature and the span of their influence on individuals around the globe.
It is proposed that investigations of the leadership in this setting can usefully contribute to insights on global leadership. The research activity follow an exploratory purpose resulting from a gap found in the literature review. The research design framework is a first sequential loop of Ground Theory methodology with the aim to identify useful hypotheses for future theoretical sampling. Secondary data was gathered and analysed qualitatively. The data stems from the public domain and statements from interviews, commentaries, biographies, and conferences on or by the head coaches. The theoretical framework of the presented re-search covers the personal traits and attributes of the investigated individuals.
Findings both overlap and contrast with findings from other global leadership research activities. The differences were identified in properties of the global sport business such as constant public attention. Based on the findings from the purposive sampling and acknowledging applicable limitations on the findings, hypotheses for theoretical sampling are proposed. Theoretical sampling is the next step in the workflow of the Grounded Theory methodology used for this study.
Erosion due to cavitation is a common problem for any kind of water turbine. Most of the currently used techniques to detect cavitation are using an Acoustic Emission (AE) sensor and highspeed cameras during operation. For the pelton wheel which is subject of this thesis it is impossible to take pictures during operation, because of the splashing water and the mist. Therefore this thesis aims to explore possibilities in detecting erosion on the buckets of the pelton wheel on images taken during manual inspections. Since the provided images are snapshots taken with a mobile phone camera without a tripod, a lot of effort was invested in the preprocessing of the images. For the main task, the classification of the erosion, two methods were evaluated: Local Binary Patterns (LBP) + kN-earest neighbor classification and the classification with a Convolutional Neural Network (CNN). The given 2405 images, contained 4810 buckets on which the erosion was graded from zero to four. This means the baseline for the classification accuracy is 20%. LBP + kNearest neighbor classification scored 32.03%. The chosen CNN model, a light version of the Xception architecture outperformed the LBP + kNearest classification with 58,29%. The biggest issue found during research is the variance of the erosion grading by the maintainance personnel. Reasons for this are: no objective grading critera like the area of erosion in mm2, classification by different employees, a shift in grading from overall bucket condition to erosion from cavitation and too many classes for grading. The mentioned reasons were confirmed by the manual classification experiment were an IllwerkeVKW employee had to perform the grading on images of the dataset. The contestants accuracy score was 36% for this task. The result of 58,29% classification accuracy indicates that an automated grading of erosion by cavitation is feasible.
Highly-sensitive single-step sensing of levodopa by swellable microneedle-mounted nanogap sensors
(2023)
Microneedle (MN) sensing of biomarkers in interstitial fluid (ISF) can overcome the challenges of self-diagnosis of diseases by a patient, such as blood sampling, handling, and measurement analysis. However, the MN sensing technologies still suffer from poor measurement accuracy due to the small amount of target molecules present in ISF, and require multiple steps of ISF extraction, ISF isolation from MN, and measurement with additional equipment. Here, we present a swellable MN-mounted nanogap sensor that can be inserted into the skin tissue, absorb ISF rapidly, and measure biomarkers in situ by amplifying the measurement signals by redox cycling in nanogap electrodes. We demonstrate that the MN-nanogap sensor measures levodopa (LDA), medication for Parkinson disease, down to 100 nM in an aqueous solution, and 1 μM in both the skin-mimicked gelatin phantom and porcine skin.
This paper gives an insight into how cybersecurity is built inside and outside banks in Austria. The research was conducted based on information received from bank representatives in Austria as well as on literature, participation in various kinds of online conferences, and so on. The main objective of this paper was to investigate the cybersecurity execution scheme and to consider the possible impact of the cultural factor on cybersecurity execution. Due to a force majeure situation like coronavirus, the author was able to obtain little information from participants, but even this helped to draw satisfactory conclusions and make recommendations to banks. Thanks to the vast amount of literature and research, confirmation of the factor under study was found, confirming the relevance of the work and the potential for further research.
HRM Practices and Innovative Work Behavior: Employee Involvement and Job Auton-omy as influencing factors of Innovative Work Behavior
An organization´s capacity to innovate often resides within its employee´s innovative work behavior. Previous research suggested positive effects of employee involvement and job autonomy on innovative behavior. This research aims to analyze the impact of involvement- and autonomy-focused HRM practices (participation, information-sharing, work-scheduling autonomy, decision-making autonomy, and work-methods autonomy) on innovative work behavior. It is hypothesized that all five HRM practices mentioned above positively influence employees´ innovative work behavior. Therefore, a cross-sectional quantitative research design was chosen. Online questionnaire data from 376 employees in Austria was analyzed. Although all five HRM practices correlated with innovative work behavior, only work-methods autonomy had a statistically significant influence on the innovative work behavior of all employees. Thus, practitioners should include work-methods autonomy as critical HRM practice in a “high-innovation” HRM system to facilitate employees´ innovative work behavior.
The impact of global warming and climate change has forced countries to introduce strict policies and decarbonization goals toward sustainable development. To achieve the decarbonization of the economy, a substantial increase of renewable energy sources is required to meed energy demand and to transition away from fossil fuels. However, renewables are sensitive to environmental conditions, which may lead to imbalances between energy supply and demand. Battery energy storage systems are gaining more attention for balancing energy systems in existing grid networks at various levels such as bulk power management, transmission and distribution, and for end-users. Integrating battery energy storage systems with renewables can also solve reliability issues related to transient energy production and be used as a buffer source for electrical vehicle fast charging. Despite these advantages, batteries are still expensive and typically built for a single application – either for an energy- or power-dense application – which limits economic feasibility and flexibility. This paper presents a theoretical approach of a hybrid energy storage system that utilizes both energy- and power-dense batteries serving multiple grid applications. The proposed system will employ second use electrical vehicle batteries in order to maximise the potential of battery waste. The approach is based on a survey of battery modelling techniques and control methods. It was found that equivalent circuit models as well as unified control methods are best suited for modelling hybrid energy storages for grid applications. This approach for hybrid modelling is intended to help accelerate the renewable energy transition by providing reliable energy storage.
Immersive educational spaces
(2023)
"If only we had had such opportunities to grasp history like this when I was young" – words by an almost 80-year-old woman holding an iPad on which both, the buildings in the background and a tower in the form of a virtual 3D object, appear within reach. To "grasp" history - what an apt use of this action-oriented word for an augmented reality application built on considerations of thinking and acting in history. This telling image emerged during the first test run of the app i.appear which will be the focus of this article's considerations on the use of immersive learning environments. The application i.appear has been used in the city of Dornbirn (Austria) for a year now to teach historical content through location-based augmented reality and other interactive and multimedia technologies. After a brief description of the potential of such applications, the epistemological structure of the hosting app i.appear and its functionality will be outlined. This article will focus on the “Baroque Master Builders” tour of the hosting app that was created and tested as part of the current research.
One goal of the project described in this paper is to create learning algorithms for machines and robots that lack a precise virtual controller for correct simulations. Using a digital twin approach, the developed mixed reality application aims for an overlay of a virtual robot model with the real world counterpart using Microsoft HoloLens 2 smart glasses. The application should help users to have an inside look into the results of the learning algorithm and therefore supervise and improve those results. The main focus of this paper is the visual representation of the digital twin on the smart glasses. One of the challenges is the level of abstraction and specific use of shaders (program code defining material attributes) to help the user differentiating between virtual and real objects. Therefore different presentation methods are described and evaluated. Study results with 48 persons show that the most abstract representation (wireframe) scores lowest, whereas a half-transparent model works best.
Breath analysis offers a non-invasive and rapid diagnostic method for detecting various volatile organic compounds that could be indicators for different diseases, particularly metabolic disorders including type 2 diabetes mellitus. The development of type 2 diabetes mellitus is closely linked to metabolic dysfunction of adipose tissue and adipocytes. However, the VOC profile of human adipocytes has not yet been investigated. Gas chromatography with mass spectrometric detection and head-space needle trap extraction (two-bed Carbopack X/Carboxen 1000 needle traps) were applied to profile VOCs produced and metabolised by human Simpson Golabi Behmel Syndrome adipocytes. In total, sixteen compounds were identified to be related to the metabolism of the cells. Four sulphur compounds (carbon disulphide, dimethyl sulphide, ethyl methyl sulphide and dimethyl disulphide), three heterocyclic compounds (2-ethylfuran, 2-methyl-5-(methyl-thio)-furan, and 2-pentylfuran), two ketones (acetone and 2-pentanone), two hydrocarbons (isoprene and n-heptane) and one ester (ethyl acetate) were produced, and four aldehydes (2-methyl-propanal, butanal, pentanal and hexanal) were found to be consumed by the cells of interest. This study presents the first profile of VOCs formed by human adipocytes, which may reflect the activity of the adipose tissue enzymes and provide evidence of their active role in metabolic regulation. Our data also suggest that a previously reported increase of isoprene and sulphur compounds in diabetic patients may be explained by their production by adipocytes. Moreover, the unique features of this profile, including a high emission of dimethyl sulphide and the production of furan-containing VOCs, increase our knowledge about metabolism in adipose tissue and provide diagnostic potential for future applications.
The workplaces are changing with the increase in the use of technology, digital communication, the shift towards multicultural teams, and remote work due to COVID-19. Leaders need more collaboration and acceptance of digital communication tools such as Teams, Slack. This study aims to determine the influence of culture in the acceptance of digital tools in leadership communication. In the literature review, 3 cultures (organizational, national, Individual) were assumed. And Individual culture was tested using Schwartz (openness to change) value survey along with other qualitative questions in 1-1 interviews of Austrians and multinationals living in Austria. Analysis from findings suggests that culture plays an important role in technology acceptance of digital tools in leadership communication. This was confirmed by the Schein model and Schwartz value ratings. The culture comprises of organizational, national, regional, and individual culture. Individual culture plays an important role, but other cultural factors cannot be avoided. Key factors affecting the technology acceptance in Vorarlberg (Austria) are listed along with recommendations to leaders.
Nowadays, online marketing is becoming increasingly important not only in the B2C but also in the B2B sector, as evidenced by marketing budget expenditures. Companies pursue overarching goals involving visibility and attention from prospective customers in order to raise brand awareness and as a result, outperform increasing market competition. This begs the question of whether online marketing is appropriate for increasing brand awareness.
The master´s thesis topic developed from both a personal as well as a professional perspective. Private research increased the author´s interest in the topic of online marketing. Furthermore, brands, whose level of awareness needs to be improved, are becoming a more common topic of professional debates. In this way, the research of the current master´s thesis was created.
The aim of this master's thesis was to discover how online marketing can be used to increase awareness of a brand. This will be analyzed by using the brand turn to zero, which offers consulting services for B2B customers in the sustainability industry. In this context, suitable and visible online marketing channels for increasing brand awareness are to be identified. In addition to this, suitable content for the company´s own as well as paid online marketing channels need to be collected. Furthermore, the influence that online marketing has on creating brand image awareness is to be presented.
Research questions are defined in order to achieve the described objectives. Within the scope of the master thesis, one main research question, as well as three sub-research questions, are to be answered based on the literature as well as the generated output resulting from the empirical part. Eight existing B2B customers of turn to zero, originating from com-mercial and industrial sectors, were interviewed in the empirical part. The interview findings were evaluated by using qualitative content analysis according to Mayring.
Research results showed that targeted combinations of online marketing channels are contributing to increase brand awareness. In addition, the research succeeded in determining suitable communication content for various online marketing channels. Furthermore, the in-fluence of online marketing could be investigated more closely in terms of brand image.
Integration of an industrial robot manipulator in ROS to enhance its spatial perception capabilities
(2020)
Robots without any external sensors are not capable of sensing their environment, often leading to damaging collisions. These collisions could potentially be avoided if the robot had a way to sense its environment in the first place. This thesis attempts to tackle this problem by equipping such a robot with extra sensor hardware for perceiving environmental objects. The robot used within this thesis is a KUKA LBR iiwa 7 R800. The goal is a robot capable of moving in an unseen environment without colliding with obstacles nearby.
The research covers different sensor options, robots in cramped areas as well as algorithms and simulation topics. Software platforms and libraries used for the implementation are briefly introduced.
Multiple infrared sensors are directly installed onto the robot manipulator. The extra sensors and the robot are integrated into the ROS middleware to create an application capable of sensing the robots’ environment and plan collision-free paths accordingly.
The experiments show, that the low amount of available sensor data can not map the robots’ environment with enough detail. Additional problems, such as sensor noise corrupting parts of the generated map or the robot recognizing itself as an obstacle, lead to a negative result in total. In future work, the choice of sensors shall be reconsidered and tested upfront via simulation software.
Electric cell-substrate impedance spectroscopy (ECIS) enables non-invasive and continuous read-out of electrical parameters of living tissue. The aim of the current study was to investigate the performance of interdigitated sensors with 50 μm electrode width and 50 μm inter-electrode distance made of gold, aluminium, and titanium for monitoring the barrier properties of epithelial cells in tissue culture. At first, the measurement performance of the photolithographic fabricated sensors was characterized by defined reference electrolytes. The sensors were used to monitor the electrical properties of two adherent epithelial barrier tissue models: renal proximal tubular LLC-PK1 cells, representing a normal functional transporting epithelium, and human cervical cancer-derived HeLa cells, forming non-transporting cancerous epithelial tissue. Then, the impedance spectra obtained were analysed by numerically fitting the parameters of the two different models to the measured impedance spectrum. Aluminium sensors proved to be as sensitive and consistent in repeated online-recordings for continuous cell growth and differentiation monitoring assensors made of gold, the standard electrode material. Titanium electrodes exhibited an elevated intrinsic ohmic resistance incomparison to gold reflecting its lower electric conductivity. Analysis of impedance spectra through applying models and numerical data fitting enabled the detailed investigation of the development and properties of a functional transporting epithelial tissue using either gold or aluminium sensors. The result of the data obtained, supports the consideration of aluminium and titanium sensor materials as potential alternatives to gold sensors for advanced application of ECIS spectroscopy.
Whenever foreign activities turn out to be essential to ensure the company's goals and competitiveness, companies become international. New markets, new lucrative resources promise profitable growth. The new step beyond the national borders requires careful consideration based on the political conditions of the target market (e.g. stability of the political system, social peace, legal certainty, institutional barriers to market entry, attitude to direct investment). The legal framework, such as state funding, environmental protection laws, tax legislation, state requirements or bureaucratic regulations, appear to be at least as relevant too. However, SMEs often lack the capacity and/or courage to take this step. Political authorities at the European level and below are aware of this problem. Numerous studies show that internationalisation is not only necessary to improve competitiveness, but greatly promote innovation, e.g. within international collaborations, it is important to get the authorities to treat these issues with special attention. Governmental promotion is supposed to work in terms of establishing regional balance and supporting socially relevant topics and research. Nevertheless, despite the willingness to support SMEs in their cross-border projects, billions of released Euros are lying around and have not been used. It seems reasonable to assume money is not easy to come by. Enormous bureaucratic hurdles are on everyone's lips. But is that the only reason? Are the people sufficiently informed to be able to take advantage of the numerous financing opportunities? Or is there even more behind the invisible hurdle at first glance? To ascertain this circumstance more precisely, an in-depth analysis to answer the research question ‘what can the institutions do better to make it easier for SMEs to access funding?’ is required.
In this work, the simulation possibilities of transient magnetic fields are investigated. For this purpose, an experimental setup is established to compare the simulation results with actual measurement data.
The experimental set-up consists of two coils, which are placed on two U-shaped iron cores. These cores are then brought together to form two air-gaps. These two gaps are used for measurement and the optional insertion of samples. The simulations are carried out with the finite element method (FEM) program ANSYS Maxwell 19R3.
In the first experiments, static simulations and measurements are compared to verify the validity of the available material data and the simulation techniques, especially the symmetry considerations, excitations of the coils, and boundary conditions. The static simulations show two main sources of uncertainty. The B-H curve of the core material used in the simulations and the air-gap distance uncertainty.
After validating the simulations with the static measurements, transient experiments are performed. In these experiments, the qualitative agreement of the simulation and measurement, as well as the characteristic rise times are compared. The experiments show a decisive influence of the considered loss mechanisms on the agreement of the simulation results with the measurements. Therefore, several simulations with different loss mechanisms are performed.
Finally, also the simulation capability including a material sample in the upper gap is investigated. Therefore, the conformity of the relative change of the measurement and the simulation is compared.
In the experiments a good simulation capability within a 5% error bar is seen. The main difficulty of this work represents the uncertainty due to the available material data. It is assumed, that with more accurate material data the error can be reduced significantly.
Investigation of non-uniformly emitting optical fiber diffusers on the light distribution in tissue
(2020)
The implementation of direct-to-consumer (D2C) business models has become more important for companies trying to develop a competitive edge and improve consumer engagement in today's rapidly expanding e-commerce market. This master's thesis investigates the important success elements and problems of deploying D2C models in the e-commerce business. The research question focuses on identifying the factors that contribute to the successful transition to D2C models and the obstacles businesses encounter along the way. Through qualitative research using the Eisenhardt method and in-depth case studies with industry experts, this study provides valuable insights into key success factors for direct-to-consumer (D2C) business models in e-commerce.The findings highlight that businesses that effectively implement D2C models utilize key success factors such as a clear value proposition, customer engagement and relationship build- ing, seamless online experiences, targeted marketing and digital advertising, brand identity and storytelling, and flexibility and adaptability. However, they also face challenges related to operational adjustments, marketing and branding investments, competition, and market saturation. Based on these research outcomes, this thesis provides recommendations for businesses seeking to switch to or implement D2C models in e-commerce. These recommendations emphasize embracing a customer-centric mindset, developing digital capabilities, foster- ing strong leadership commitment, leveraging data and analytics, establishing direct customer relationships, optimizing operational processes, building brand trust and credibility, and allocating resources wisely. This master's thesis provides a comprehensive analysis of the key success factors and challenges associated with the transition to or implementation of D2C business models in the e-commerce industry. It provides advice to help companies successfully transition to D2C models.
The utilization of lasers in dentistry expands greatly in recent years. For instance, fs-lasers are effective for both drilling and caries prevention, while cw-lasers are useful for adhesive hardening. A cutting-edge application of lasers in dentistry is the debonding of veneers. While there are pre-existing tools for this purpose, there is still potential for improvement. Initial efforts to investigate laser assisted debonding mechanisms with measurements of the optical and mechanical properties of teeth and prosthetic ceramics are presented. Preliminary tests conducted with a laser system used for debonding that is commercially available showed differences in the output power set at the systems console to that at specified distances from the handpiece. Furthermore, the optical properties of the samples (human teeth and ceramics) were characterised. The optical properties of the ceramics should closely resemble those of teeth in terms of look and feel, but they also influence the laser assisted debonding technique and thus must be taken into account. In addition first attempts were performed to investigate the mechanical properties of the samples by means of pump-probe-elastography under a microscope. By analyzing the sample surface up to 20 ns after a fs-laser pulse impact, pressure and shock waves could be detected, which can be utilized to determine the elastic constants of specific materials. Together such investigations are needed to shape the basis for a purely optical approach of debonding of veneers utilizing acoustic waves.