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Background: The development of mobile interventions for noncommunicable diseases has increased in recent years. However, there is a dearth of apps for patients with peripheral arterial disease (PAD), who frequently have an impaired ability to walk.
Objective: Using a patient-centered approach for the development of mobile interventions, we aim to describe the needs and requirements of patients with PAD regarding the overall care situation and the use of mobile interventions to perform supervised exercise therapy (SET).
Methods: A questionnaire survey was conducted in addition to a clinical examination at the vascular outpatient clinic of the West-German Heart and Vascular Center of the University Clinic Essen in Germany. Patients with diagnosed PAD were asked to answer questions on sociodemographic characteristics, PAD-related need for support, satisfaction with their health care situation, smartphone and app use, and requirements for the design of mobile interventions to support SET.
Results: Overall, a need for better support of patients with diagnosed PAD was identified. In total, 59.2% (n=180) expressed their desire for more support for their disease. Patients (n=304) had a mean age of 67 years and half of them (n=157, 51.6%) were smartphone users. We noted an interest in smartphone-supported SET, even for people who did not currently use a smartphone. “Information,” “feedback,” “choosing goals,” and “interaction with physicians and therapists” were rated the most relevant components of a potential app.
Conclusions: A need for the support of patients with PAD was determined. This was particularly evident with regard to disease literacy and the performance of SET. Based on a detailed description of patient characteristics, proposals for the design of mobile interventions adapted to the needs and requirements of patients can be derived.
The classification of waste with neural networks is already a topic in some scientific papers. An application in the embedded systems area with current AI processors to accelerate the inference has not yet been discussed. In this master work a prototype is created which classifies waste objects and automatically opens the appropriate container for the object. The area of application is in the public space.
For the classification a dataset with 25,681 images and 11 classes is created to re-train the Convolution Neuronal Networks EfficientNet-B0, MobileNet-v2 and NASNet-mobile. These Convolution Neuronal Networks run on the current Edge \acrshort{ai} processors from Google, Intel and Nvidia and are compared for performance, consumption and accuracy.
The master thesis evaluates the result of these comparisons and shows the advantages and disadvantages of the respective processors and the CNNs. For the prototype, the most suitable combination of hardware and AI architecture is used and exhibited at the university fair KasetFair2020. An opinion survey on the application of the machine is conducted.
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.
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.
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.
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.
Although pilot projects are an accepted means of entry into prospects, research on the object of startups selling SaaS and use pilots to enter and to further scale within their prospect’s organization is limited. The reader can expect a collection of key practices of SaaS startups in the field of Decision Support Software. These combine the main sales-oriented elements within pilot projects that are reflected on by Customer Success Management, Change Management as well as cultural dimensions. Explorative interviews, mainly with stakeholders in Decision Support Software startups, were conducted to further gain an understanding of the research object. Results indicate that pilots are strategically used in the sales of such startups to simultaneously deal with their customer’s uncertainties and as a means for the startups to get commitment and increase their value proposition through the additional service that they offer in order to acquire an internal support basis. Customer Success Management as well as Change Management are furthermore advantageous in quickly achieving measurable results that leverage buyers and seller’s justification for further sales.
The purpose of this work is to explore implicit schemes underlying the market segmentation analysis process. Boosting transparency for and in the new discipline of healthcare marketing, the work offers a toolbox of both primary and secondary methods to identify the accurate target market. This is crucial, since resource allocation in B2C segmentation and targeting is still often misleading. An Austrian, internationally present niche player serves as a research object to turn theoretical insights into practical verification. Data for the thesis are collected through company-internal data analysis and desk research, grounded in a multi-method approach with primary and secondary research. On the one hand, the work assesses the most effective segmentation and attractiveness/knock-out criteria according to scientific sources. Delving into the topic of a priori and a posteriori segmentation, an overview of suitable techniques is going to be offered. On the other hand, the thesis illustrates how the accurate target segment in the healthcare industry can be evaluated and determined through companyinternal consumer and market data.
Primary research on demographics (age, gender), psychographics (preferred channels), behavioral criteria (new/existing, CLC) and product categories is found to be particularly meaningful for the healthcare player. Results vary between countries, which is why an international-marketing strategy instead of a domestic-marketing approach is advisable.
Secondary research shows that socio-demographic and behavioral criteria are most used as a priori criteria, whereas a posteriori segmentation is promising to reveal psychographic clusters. One of the author’s recommendations is to niche down accurate market segments such as LOHAS or “best agers” by refining psychographics/socio-demographics with behavioral segmentation through “occasions” (e.g. back pain, depression, injuries). Novel approaches such as outcome-based segmentation or emphasizing “promoters” are discussed too.
The findings pave marketing managers the way for identifying the accurate target segments in the B2C health industry, selecting accurate methods grounded in profound scientific research and with concepts suitable for SMEs. The thesis proves that marketing segmentation is no longer a “nice-to-have” but a “must” in the health(care) industry.
The Convention on the Rights of the Child (CRC) is a human rights framework in the context of multi-level governance child protection policies central to social work education and practice (United Nations, 1989). In line with this statement, children’s rights-based education introduces undergraduate social work students to the principles of the CRC, namely participation, protection, harm prevention and provision, to facilitate knowledge acquisition by building core competencies for critical practice (IFSW, 2002). It equips social workers with analytical and advocacy skills that foster critical thinking and creativity in the juxtaposition between child protection, autonomy and self-determination.
This chapter provides insights for social work education to locate and analyse the underlying casualties of social problems using a problem and resource framework, the w-questions (Geiser, 2015). The framework is used to develop theory driven social work interventions as illustrated against the backdrop the anonymised case study, Amira, an accompanied child asylum seeker in Austria (Fritsche, Glawischnig, & Wolfsegg, 2019). Correspondingly, CRC is addressed along a continuum between human needs fulfilment and human right entitlements (Obrecht, 2009; IFSW, 2002; Ife, 2012). The concept of need is understood as tension in our concrete biological and psychological bio-values and states (Obrecht, 2009, p. 27). The assertion is that when children lack support or are obstructed from achieving their equal right to education due to social, cultural or economic barriers, this exacerbates social marginalisation because it deprives them of membership in the school social system. Social marginalisation thwarts the fulfilment of needs and weakens social cohesion by causing alienation and anomie (Mayrhofer, 2015). The tentative conclusion is that knowledge and practice models that link human needs and children’s rights equip social workers with the expertise to reduce children’s vulnerability whilst strengthening their protection, autonomy and self-determination.
For a given set of banks, how big can losses in bad economic or financial scenarios possibly get, and what are these bad scenarios? These are the two central questions of stress tests for banks and the banking system. Current stress tests select stress scenarios in a way which might leave aside many dangerous scenarios and thus create an illusion of safety; and which might consider highly implausible scenarios and thus trigger a false alarm. We show how to select scenarios systematically for a banking system in a context of multiple credit exposures. We demonstrate the application of our method in an example on the Spanish and Italian residential real estate exposures of European banks. Compared to the EBA 2016 stress test our method produces scenarios which are equally plausible as the EBA stress scenario but yield considerably worse system wide losses.
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.
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.
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.
Graphite substrates underwent two methods of creating doped silicon carbide films via carbothermal reduction; the first method being liquid-phase processing, or dip-coating, and the second gas-phase processing, otherwise referred to as the solid-vapour reaction. The dip-coating procedure resulted in flaky coatings, while the solid-vapour reaction resulted in polycrystalline films with columnar growth that displayed promising morphological and electrical properties. The films were tested on their performance as semiconductor diodes, and proved that carbothermal reduction in the gas phase is a promising technique for creating polycrystalline silicon carbide films for the application of light-emitting diodes.
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.
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.
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.
Clathrate hydrates, or hydrates for short, are inclusion compounds in which water molecules form a hydrogen-bonded host lattice that accommodates the guest molecules. While vast amounts of hydrates are known to exist in seafloor sediments and in the permafrost on Earth, these occurrences might be dwarfed by the amounts of hydrates occurring in space and on celestial bodies. Since methane is the primary guest molecule in most of the natural occurrences on Earth, hydrates are considered a promising source of energy. Moreover, the ability of one volume of hydrate to store about 170 volumes of gas, make hydrates a promising functional material for various industrial applications. While the static properties of hydrates are reasonably well known, the dynamics of hydrate formation and decomposition are insufficiently understood. For instance, the stochastic period of hydrate nucleation, the memory effect, and the self-preservation phenomenon complicate the development of predictive models of hydrate dynamics. Additionally, the influence of meso- and macroscopic defects as well as the roles of mass and heat transport on different length scales remain to be clarified.
Due to its non-invasive and non-destructive nature and the high spatial resolution of approx. 1µm or even less, micro-computed X-ray attenuation tomography ( µCT ) seems to be the perfect method for the study of the evolving structures of forming or decomposing hydrates on the meso- and macroscopic length scale. However, for the naturally occurring hydrates of low atomic number guests the contrast between hydrate, ice, and liquid water is typically very weak because of similar X-ray attenuation coefficients. So far, good contrast was only restricted to synchrotron beamline experiments which utilize the phase information of monochromatic X-rays.
In this thesis it is shown that with the help of a newly developed sample cell, a contrast between the hydrate and the ice phase sufficiently good for the reliable segmentation of the materials can also be achieved in conventional tube-based µCT. An accurate pressure and temperature management, i.e., the added functionality of the cell, further allows for cross-correlation of structural and thermodynamic data. The capability of this µCT setup is demonstrated in a series of studies on the formation and decomposition of hydrates which yield new insights for the development of a novel route to hydrate synthesis. At last, this thesis points towards possibilities how better models of hydrate formation and decomposition can be developed with the aid of µCT and computer simulations.
Post-operative isoflurane has been observed to be present in the end-tidal breath of patients who have undergone major surgery, for several weeks after the surgical procedures. A major new noncontrolled, non-randomized, and open-label approved study will recruit patients undergoing various surgeries under different inhalation anaesthetics, with two key objectives, namely to record the washout characteristics following surgery, and to investigate the influence of a patient’s health and the duration and type of surgery on elimination. In preparation for this breath study using proton transfer reaction time-of-flight mass spectrometry (PTR-TOF-MS), it is important to identify first the analytical product ions that need to be monitored and under what operating conditions. In this first paper of this new research programme, we present extensive PTR-TOF-MS studies of three major
anaesthetics used worldwide, desflurane (CF3CHFOCHF2), sevoflurane ((CF3)2CHOCH2F), and isoflurane (CF3CHClOCHF2) and a fourth one, which is used less extensively, enflurane (CHF2OCF2CHFCl), but is of interest because it is an isomer of isoflurane. Product ions are identified as a function of reduced electric field (E/N) over the range of approximately 80 Td to 210 Td, and the effects of operating the drift tube under ‘normal’ or ‘humid’ conditions on the intensities of the product ions are presented. To aid in the analyses, density functional theory (DFT) calculations of the proton affinities and the gas-phase basicities of the anaesthetics have been determined. Calculated energies for the ion-molecule reaction pathways leading to key product ions, identified as ideal for monitoring the inhalation anaesthetics in breath with a high sensitivity and selectivity, are also presented.
The importance of Agent-Based Simulation (ABS) as scientific method to generate data for scientific models in general and for informed policy decisions in particular has been widely recognised. However, the important technique of code testing of implementations like unit testing has not generated much research interested so far. As a possible solution, in previous work we have explored the conceptual use of property-based testing. In this code testing method, model specifications and invariants are expressed directly in code and tested through automated and randomised test data generation. This paper expands on our previous work and explores how to use property-based testing on a technical level to encode and test specifications of ABS. As use case the simple agent-based SIR model is used, where it is shown how to test agent behaviour, transition probabilities and model invariants. The outcome are specifications expressed directly in code, which relate whole classes of random input to expected classes of output. During test execution, random test data is generated automatically, potentially covering the equivalent of thousands of unit tests, run within seconds on modern hardware. This makes property-based testing in the context of ABS strictly more powerful than unit testing, as it is a much more natural fit due to its stochastic nature.