Open Access

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.

Observing the ratios of the rail usage in terms of passenger travelled per km and per capita, we see that there are huge differences between countries, so some railway systems are performing better in catching passengers than others. By analysing the factors that make the railways attractive for users, and setting standard values for these factors, we can analyse how well a system is performing. This paper has investigated those factors and developed an assessment tool that will inform about the required improvements, so in a later stage specific strategies can be developed to increase the performance in order to attract more passengers. Spain will be used as case study, since the country has specially low passenger rail usage compared to other countries even though the large investments in high speed lines the country undertook in the last decades.

In recent years, numerous studies around the world have examined the environmental potential of biochar to determine whether it can help address climate challenges. Several of these studies have used the Life Cycle Assessment (LCA) method to evaluate the environmental impacts of biochar systems. However, studies focus mainly on biochar obtained from pyrolysis, while the number of studies on biochar from gasification is small. To contribute to the current state of LCA research on biochar from gasification, LCA was performed for biochar, electricity, and heat from a wood gasification plant in Vorarlberg, Austria. Woodchips from local woods are used as biomass feedstock to produce energy, i.e., electricity and heat. Thereby, biochar is obtained as a side product from gasification. The production of syngas and biochar takes place in a floating fixed-bed gasifier. Eventually, the syngas is converted to electricity in a gas engine and fed to the power grid. Throughout different stages within the gasification process, heat is obtained and fed into local heat grid to be delivered to customers. The biochar produced complies with the European Biochar Industry (EBI) guidelines and is used on a nearby farm for manure treatment and eventually for soil application. Thereby, the effect of biochar used for manure treatment is considered to reduce emissions occurring from manure, i.e., nitrogen monoxide (N2O). Further, the CO2 sequestration potential of biochar, i.e., removal of CO2 from the atmosphere and long-term storage, is considered. Several constructions, such as the construction of the gasification system and the heating grid, are included in the evaluation. As input related reference flow, 1 kg of woodchips with water content of 40 % is used. Three functionals units are eventually obtained, i.e., 0.17 kg of biochar applied to soil, 4.47 MJ of heat and 2.82 MJ of electricity, each per reference flow. The results for Global Warming Potential (GWP) for biochar is – 274.7*10 - 3 kg CO2eq per functional unit, which corresponds to – 1.6 kg CO2eq per 1 kg biochar applied to soil. The GWP for heat results in 17.1*10 - 3 CO2eq per functional unit, which corresponds to 3.6*10 - 3 kg CO2eq per 1 MJ. For electricity, a GWP of 38.1*10 - 3 kg CO2eq per functional unit is obtained, which is equivalent to 13.5*10 - 3 kg CO2eq per 1 MJ. The calculation was performed using SimaPro Version 9.1 and the ReCiPe method with hierarchist perspective.

The electricity demand due to the increasing number of EVs presents new challenges for the operation of the electricity network, especially for the distribution grids. The existing grid infrastructure may not be sufficient to meet the new demands imposed by the integration of EVs. Thus, EV charging may possibly lead to reliability and stability issues, especially during the peak demand periods. Demand side management (DSM) is a potential and promising approach for mitigation of the resulting impacts. In this work, we developed an autonomous DSM strategy for optimal charging of EVs to minimize the charging cost and we conducted a simulation study to evaluate the impacts to the grid operation. The proposed approach only requires a one way communicated incentive. Real profiles from an Austrian study on mobility behavior are used to simulate the usage of the EVs. Furthermore, real smart meter data are used to simulate the household base load profiles and a real low voltage grid topology is considered in the load flow simulation. Day-ahead electricity stock market prices are used as the incentive to drive the optimization. The results for the optimum charging strategy is determined and compared to uncontrolled EV charging. The results for the optimum charging strategy show a potential cost saving of about 30.8% compared to uncontrolled EV charging. Although autonomous DSM of EVs achieves a shift of load as pursued, distribution grid operation may be substantially affected by it. We show that in the case of real time price driven operation, voltage drops and elevated peak to average powers result from the coincident charging of vehicles during favourable time slots.

In recent years, ultrashort pulsed lasers have increased their applicability for industrial requirements, as reliable femtosecond and picosecond laser sources with high output power are available on the market. Compared to conventional laser sources, high quality processing of a large number of material classes with different mechanical and optical properties is possible. In the field of laser cutting, these properties enable the cutting of multilayer substrates with changing material properties. In this work, the femtosecond laser cutting of phosphor sheets is demonstrated. The substrate contains a 230 micrometer thick silicone layer filled with phosphor, which is embedded between two glass plates. Due to the softness and thermal sensitivity of the silicone layer in combination with the hard and brittle dielectric material, the separation of such a material combination is challenging for both mechanical separation processes and cutting with conventional laser sources. In our work, we show that the femtosecond laser is suitable to cut the substrate with a high cutting edge quality. In addition to the experimental results of the laser dicing process, we present a universal model that allows predicting the final cutting edge geometry of a multilayer substrate.

A Telecom optical fibers are still being the best transmission medium of digital data and analogue signals for long distance applications. Progress in integrated photonics enables development of photonic chips with new unique properties, circuits of the future, and overcomes current limits in information and communication technologies. The packaging of photonic chips is necessary for taking them out of research laboratories into real implementation in the information and communication technology applications. One important step of packaging is effective coupling of optical radiation between telecom optical fiber with ten microns core dimension and photonic chip optical waveguide with submicron dimensions. For complex photonic chips, it is necessary to couple not one optical fiber but several optical fibers, which are arranged in fiber arrays. In this case, it is necessary to use a 6D positioning system, which allows to optimally adjust the relative position of the photonic chip and the fiber arrays. After setting the optimal relative position of the photonic chip and the fiber array, the process of their fixation follows. One possibility of fixation is gluing with an adhesive in the optical path between the photonic chip and an array of optical fibers with a refractive index close to the refractive index of the optical fiber core. This paper is focused on the experimental test set-up for the temperature characterization of fiber array to photonics chip butt coupling at 1310 nm and 1550 nm wavelengths fixed themselves by UV adhesive in the optical path. The main aims of this works are selection of better adhesive from two types for gluing of photonic chip and fiber array in packaging process of photonics chips and validation of gluing process developing. The coupling and alignment of fiber arrays to photonics chip were done by automated active alignments system and they were fixed themselves by curable epoxy adhesive. Temperature changes of coupling insertion losses are measured and investigated for two different UV adhesives during three temperature cycles from -40 °C to 80 °C in climatic chamber according to Telcordia. Spectral dependence of insertion losses were measured and compared before and after three temperature cycles for 1530 nm to 1570 nm spectral range at room temperature. This work was supported by the Slovak Research and Development Agency under the contracts APVV-17-0662 and SK-AT-20-0017 and by the COST Action “European Network for High Performance Integrated Microwave Photonics” (EUIMWP) CA16220.

Femtosecond laser ablation on Si generates 2D ripple structures, known as laser induced periodic surface structures (LIPSS) and pinholes. We fabricated membranes with 20 to 50 μm thickness perforated by an array of tapered pinholes up to 5 μm in diameter and 10 to 20 μm spacing. Within several micrometer the pinholes transform into hollow photonic waveguides with constant diameter from 1μm to 2μm. Such structures offer a 3D photonic coupling device for polymer Y-branch- and MMI-splitter. We measured a considerable change of electrical resistivity for 500 ppm H2 in air using Si/SiO2/TiO2 substrates with 2D LIPSS. We propose to investigate 3D waveguide arrays also for photonic-chemical sensors.

We present design, simulation and optimization of polymer based 16-channel, 100-GHz AWG designed for central wavelength of 1550 nm. The input design parameters were calculated applying AWG-Parameters tool. The simulations were performed applying a commercial photonic tool PHASAR from Optiwave. The achieved transmission characteristics were evaluated by AWG-Analyzer tool and show a satisfying agreement between designed and simulated AWG optical properties. Finally, the influence of the number of phased array (PA) waveguides on the AWG performance was studied. The results show that there is a certain minimum number of PA waveguides necessary to reach sufficient AWG performance.

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.

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 leadership traits and how they can drive success within international organizations in the digital era. The basic principles of what defines a leader have undergone significant scrutiny throughout the past one hundred years, however, the digital revolution has created the most upset when considering the requirements for efficient leadership. This paper utilizes a literature review to first determine how modern leadership theory developed and the implications of current research, followed by an empirical study designed to collect real-world data which represents how current leaders active in various industries understand their role as a leader and what skills they use to promote success within their organization. Cross-examination of these sources indicates that the most effective leaders employ a combination of Transformational Leadership Theory and Emotional Intelligence-based leadership. The extent to which a leader must individualize their style is strongly contingent on the organizational culture, the individual employees, and the external environment. While traits such as communication, charisma, and trustworthiness are certainly strong indications of an efficient leader, agility and adaptability clearly stand out as the traits which are most required for highly effective leaders in the digital era.

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 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.

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.

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.

Background: Mobile health interventions are intended to support complex health care needs in chronic diseases digitally, but they are mainly targeted at general health improvement and neglect disease-specific requirements. Therefore, we designed TrackPAD, a smartphone app to support supervised exercise training in patients with peripheral arterial disease. Objective: This pilot study aimed to evaluate changes in the 6-minute walking distance (meters) as a primary outcome measure. The secondary outcome measures included changes in physical activity and assessing the patients’ peripheral arterial disease–related quality of life. Methods: This was a pilot two-arm, single-blinded, randomized controlled trial. Patients with symptomatic PAD (Fontaine stage IIa/b) and access to smartphones were eligible. Eligible participants were randomly assigned to the study, with the control group stratified by the distance covered in the 6-minute walking test using the TENALEA software. Participants randomized to the intervention 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 routine care only. TrackPAD records the frequency and duration of training sessions and pain levels using manual user input. Clinical outcome data were collected at the baseline and after 3 months via validated tools (the 6-minute walk test and self-reported quality of life). The usability and quality of the app were determined using the Mobile Application Rating Scale user version. Results: The intervention group (n=19) increased their mean 6-minute walking distance (83 meters, SD 72.2), while the control group (n=20) decreased their mean distance after 3 months of follow-up (–38.8 meters, SD 53.7; P=.01). The peripheral arterial disease–related quality of life increased significantly in terms of “symptom perception” and “limitations in physical functioning.” Users’ feedback showed increased motivation and a changed attitude toward performing supervised exercise training. Conclusions: Besides the rating providing a valuable support tool for the user group, the mobile intervention TrackPAD was linked to a change in prognosis-relevant outcome measures combined with enhanced coping with the disease. The influence of mobile interventions on long-term prognosis must be evaluated in the future.

The phenomenon of the increase of numerous widespread and common diseases, ranging from simple dental problems to obesity, high blood pressure or diabetes, is a concern which can be observed in various aspects of the entire world. Reasons for this is a combination of an unhealthy diet and insufficient physical activity. Consequently, governments across the globe are seeing the need to change consumer behaviour by introducing plain packaging regulations. From an entrepreneurial point of view, this would result in financial losses as well as various limitations in product design, branding and differentiation. Therefore, an empirical study with 232 respondents was conducted, which revealed that the use of images on packaging activates emotions in customers within a few seconds. This master thesis examines possible correlations and differences between the importance of emotionally loaded product packaging and consumer behaviour at the point of sale. The persuasive effect of images on purchase decisions is based on personal consumer experiences and validated processing in the brain which trigger specific emotions. Modern companies are able to communicate company values through emotions by using images correctly. The results of the conducted survey enable Diezano to successfully implement the communication strategy in the event of the introduction of plain packaging regulations. By using mountain graphics, Diezano conveys values such as home, regional, refreshment, tasty, memories of childhood and nostalgia, which the brand aims to convey to the market. Based on the result of this master thesis, it is concluded that the picture superiority effect is mostly underestimated, yet it is an indispensable medium for emotional differentiation and thus a company’s success.

Packaging has important functions, such as the marketing function or protecting the product from spoilage. However, the supply in the supermarket must be viewed critically, as the majority of packaging is designed for single use. The question of how producers and retailers can increase customer acceptance of sustainable packaging in supermarkets has particular relevance in terms of the environmental impact of packaging waste. Although more and more customers are interested in the topic of sustainability, a gap between their attitude and behavior is apparent. This is addressed in more detail on the basis of two product categories. Expert interviews with international producers and retailers as well as a consumer survey allow the views of these three decision-makers to be taken into account. At the end, concrete recommendations for action are presented. These show that, among other things, information and transparency are essential in order to be able to influence consumers' purchasing decisions. In addition, the responsibility of all decision-makers is seen as the key to success.

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.

In this paper, low-loss Y-branch splitters up to 128 splitting ratio are designed, simulated, and optimized by using 2D beam propagation method in OptiBPM tool by Optiwave. For an optical waveguide, a silica-on-silicon material platform is used. The splitters were designed as a planar structure for a telecommunication operating wavelength of 1.55 m. According to the minimum insertion loss and minimum non-uniformity, the optimum length for each Y-branch is determined. The influence of the pre-defined S-Bend waveguide shapes (Arc, Cosine, Sine) and of the waveguide core size reduction on the splitter performance has been also studied. The obtained simulation results of all designed splitters with different S-Bend shape waveguides together with the different waveguide core sizes are discussed and compared with each other.

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.

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.

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.

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 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.

In this work, we present a significant step toward in vivo ophthalmic optical coherence tomography and angiography on a photonic integrated chip. The diffraction gratings used in spectral-domain optical coherence tomography can be replaced by photonic integrated circuits comprising an arrayed waveguide grating. Two arrayed waveguide grating designs with 256 channels were tested, which enabled the first chip-based optical coherence tomography and angiography in vivo three-dimensional human retinal measurements. Design 1 supports a bandwidth of 22 nm, with which a sensitivity of up to 91 dB (830 µW) and an axial resolution of 10.7 µm was measured. Design 2 supports a bandwidth of 48 nm, with which a sensitivity of 90 dB (480 µW) and an axial resolution of 6.5 µm was measured. The silicon nitride-based integrated optical waveguides were fabricated with a fully CMOS-compatible process, which allows their monolithic co-integration on top of an optoelectronic silicon chip. As a benchmark for chip-based optical coherence tomography, tomograms generated by a commercially available clinical spectral-domain optical coherence tomography system were compared to those acquired with on-chip gratings. The similarities in the tomograms demonstrate the significant clinical potential for further integration of optical coherence tomography on a chip system.

With Cloud Computing and multi-core CPUs parallel computing resources are becoming more and more affordable and commonly available. Parallel programming should as well be easily accessible for everyone. Unfortunately, existing frameworks and systems are powerful but often very complex to use for anyone who lacks the knowledge about underlying concepts. This paper introduces a software framework and execution environment whose objective is to provide a system which should be easily usable for everyone who could benefit from parallel computing. Some real-world examples are presented with an explanation of all the steps that are necessary for computing in a parallel and distributed manner.