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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.
International Entrepreneurship explains the opportunities and challenges facing internationalizing entrepreneurial ventures. The book inlcudes a thorough discussion of fundamentals as well as contemporary research findings. Numerous cases, featuring diverse contexts, illustrate theory and help classroom use.
We have investigated the ablation behaviour of single crystal SrTiO3 <100> with focus on the influence of the pulse duration at a wavelength of 248 nm. The experiments were performed with KrF-excimer lasers with pulse durations of 34 ns and 500 fs, respectively. Femtosecond-ablation turns out to be more efficient by one order of magnitude and to eliminate the known problem of cracking of SrTiO3 during laser machining with longer pulses. In addition, the cavities ablated with femtosecond pulses display a smoother surface with no indication of melting and well-defined, sharp edges. These effects can be explained by the reduced thermal shock effect on the material by using ultrashort pulses.
The properties of diamond make it an attractive material for MEMS and sensor devices. We present the feasibility to fabricate membranes and cantilevers made of nano-(micro-) crystalline diamond films grown on Si/SiO2 substrates using microwave chemical vapour deposition (MWCVD). The patterning of micromechanical structures was performed by a combined process of femtosecond laser ablation and wet etching. We designed cantilever structures with varying lengths and widths (25, 50, 100, 200 and 300 μm). The cantilevers were made in a symmetric left- and right-hand configuration. An additional laser treatment was used to modify the mechanical properties of the left-hand cantilever. The deflection of the laser-treated, and non-treated sections was measured. The global mechanical system properties were simulated and corresponded with high accuracy to the measured results of deflection.
The properties of SiC and diamond make them attractive materials for MEMS and sensor devices. We innovated specific laser ablation techniques to fabricate membranes and cantilevers made of SiC or nano-(micro-) crystalline diamond films grown on Si/SiO2 substrates by microwave chemical vapour deposition (MWCVD). We started research to generate surface moulds to grow corrugated diamond films for membranes and cantilevers. A software tool was developed to support the design of micromechanical cantilevers. We can measure deformation and resonant frequency of diamond cantilevers and identify the global mechanical properties. A benchmark against finite element simulations enables an inverse identification of the specific system parameters and simplifies the characterization procedure.
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.
By a simple femtosecond laser process, we fabricated metal-oxide/gold composite films for electrical and optical gas sensors. We designed a dripple wavelength AWG-spectrometer, matched to the plasma absorption wavelength region of the composite films. H2/CO absorptions fit well with the AWG design for multi gas detection sensor arrays
Black titanium dioxide in situ generated on femtosecond laser induced periodic surface structures
(2018)
Semiconducting metal oxides are widely used for solar cells, poto-catalysis, bio-active materials and gas sensors. Besides the material properties of the used semiconductor,the specific surface topology of the sensor determines the device performance. We investigate the preparation and transfer suitable metals onto LIPPS structures on glass for gas sensing applications.
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.
Adult muscle carnitine palmitoyltransferase (CPT) II deficiency is a rare autosomal recessive disorder of long-chain fatty acid metabolism. It is typically associated with recurrent episodes of exercise-induced rhabdomyolysis and myoglobinuria, in most cases caused by a c.338C > T mutation in the CPT2 gene. Here we present the pedigree of one of the largest family studies of CPT II deficiency caused by the c.338C > T mutation, documented so far. The pedigree comprises 24 blood relatives
of the index patient, a 32 year old female with genetically proven CPT II deficiency. In total, the mutation was detected in 20 family members, among them five homozygotes and 15 heterozygotes. Among all homozygotes, first symptoms of CPT II deficiency occurred during childhood. Additionally, two already deceased relatives of the index patient were carriers of at least one copy of the genetic variant, revealing a remarkably high prevalence of the c.338C > T mutation within the tested family. Beside the index patient, only one individual had been diagnosed with CPT II deficiency prior to this study and three cases of CPT II deficiency were newly detected by this family study, pointing
to a general underdiagnosis of the disease. Therefore, this study emphasizes the need to raise awareness of CPT II deficiency for correct diagnosis and accurate management of the disease.
Oral applications of ultra-short laser pulses - a new approach for gentle and painless treatment?
(2006)
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.
The fact that services have emerged a driving force and the fastest growing sector in international trade attracts researchers to follow the changes taking place in the service industry. This study extends the scientific discussion on internationalization of service firms. Unlike previous research that examined factors that influence a single firm’s decision to internationalize, I acknowledge the heterogeneity of services, and based on the results obtained from secondary analysis of primary qualitative data sets, answer the main research question how internationalization motives differ between people-processing services, possession-processing services, and information-based services. This research goes beyond identification of variation in internationalization motives and analyses the service characteristics that might be responsible for the differences. In addition, I assess the key trends in the service sector and predict the possible future internationalization motives that are likely to emerge from the current trends.
Findings of this study reveal two major issues. First, it is evident that reasons for internationalization differ among hotel, retail firms and Higher education institutions representing people-processing services, possession-processing services, and information-based services respectively. Second, a few motives are common across sub-sectors, however the significance of the motives vary from sub-sector to sub-sector. I conclude that the differences in underlying structures of the respective service sub-sectors is the fundamental cause for the variation in internationalization motives among service sub-sectors. Other factors such as distinctive characteristics of service, firm’s competitive strategies, income elasticity of demand, and life-cycle stage of the service sub-sector also contribute to the differences in internationalization motives.
This paper also presents three different factors, which are likely to emerge as significant factors that influence service firm internationalization decision in future. (1) Company’s urge to be socially responsible and the need to contribute towards the environmental well-being (2) The need to sell regional products and services to neighbouring nations and respond to consumers’ demand for sustainable consumerism (3) Decision to penetrate foreign markets facilitated by the low risks and low cost of internationalization.
Industrial demand side management has shown significant potential to increase the efficiency of industrial energy systems via flexibility management by model-driven optimization methods. We propose a grey-box model of an industrial food processing plant. The model relies on physical and process knowledge and mass and energy balances. The model parameters are estimated using a predictive error method. Optimization methods are applied to separately reduce the total energy consumption, total energy costs and the peak electricity demand of the plant. A viable potential for demand side management in the plant is identified by increasing the energy efficiency, shifting cooling power to low price periods or by peak load reduction.
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.
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.
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.
Offline speech to text engine for delimited context in combination with an offline speech assistant
(2022)
The inatura museum in Dornbirn had planned an interactive speech assistant-like exhibit. The concept was that visitors could ask the exhibit several questions that they would like to ask a flower. Solution requirements regarding the functionalities were formulated, such as the capacity to run offline because of privacy reasons. Due to the similarity of the exhibit, open-source offline Speech To Text (STT) engines and speech assistants were examined. Proprietary cloud-based STT engines associated with the corresponding speech assistants were also researched. The aim behind this was to evaluate the hypothesis of whether an open-source offline STT engine can compete with a proprietary cloud-based STT engine. Additionally, a suitable STT engine or speech assistant would need to be evaluated. Furthermore, analysis regarding the adaption possibilities of the STT models took place. After the technical analysis, the decision in favour of the STT engines called "Vosk" was made. This analysis was followed by attempts to adapt the model of Vosk. Vosk was compared to proprietary cloud-based Google Cloud Speech to Text to evaluate the hypothesis. The comparison resulted in not much of a significant difference between Vosk and Google Cloud Speech to Text. Due to this result, a recommendation to use Vosk for the exhibit was given. Due to the lack of intent parsing functionality, two algorithms called "text matching algorithm" and "text and keyword matching algorithm" were implemented and tested. This test proved that the text and keyword matching algorithm performed better, with an average success rate of 83.93 %. Consequently, this algorithm was recommended for the intent parsing of the exhibit. In the end, potential adaption possibilities for the algorithms were given, such as using a different string matching library. Some improvements regarding the exhibit were also presented.
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.
Varying mindsets in Design Thinking. Why they change during the process and how to nudge them
(2019)
Production and tribological characterization of tailored laser-induced surface 3D microtextures
(2019)
Purpose: In this thesis the viable system model (VSM) is used as a framework to develop a model for the management of a business alliance that contains the necessary and sufficient conditions for maintaining synergy of its constituent organisations and for adapting to a changing environment so that it can remain a long-term viable alliance. In addition, a model is developed that makes explicit the inherent link between the VSM and the core elements of knowledge management theory. Based then on the alliance management model and the link established between the VSM and knowledge management, an application framework is developed to guide practitioners in defining necessary alliance management functions and relationships, the knowledge required by that management to fulfill those functions, and the processes that need to be in place to manage that knowledge. Design/strategy: The research has been divided into four phases: theoretical construction, refinement with practitioners, real-world application, and evaluation of test case and toolset. The researcher has worked closely with practitioners actively involved in the formation of a new international alliance to develop a VSM model and application framework for the alliance management. Formally, the research strategy has been defined as an action research and the research philosophy as one of pragmatism. Findings/limitations: The developed application framework, has been successfully used to identify absent and incomplete roles, actions, and interactions within the management of the specific alliance test case. This has helped to demonstrate how the application framework and VSM model can be used to diagnose and, most importantly, to articulate and visualise management deficiencies to facilitate clear and unambiguous discussions. The timing of this cross-sectional research did not allow the application framework to be utilised from the outset of the alliance formation as an organisational planning tool and also not to its full extent to support the development of knowledge processes for the alliance management. However, the step-by-step approach used in developing the toolset and then explaining its application will allow the reader to judge its credability and generalisability for other practical applications. Practical implications: The developed toolset consists of a VSM for an alliance management, job descriptions for that management (responsibilities, interfaces, and core competencies), a visual model illustrating the link between the VSM and knowledge management, and an application framework to guide the filling of the alliance management job descriptions in phases of recruitment, onboarding, and development (of interfaces and activities processes). Overall, one could say that the conditions prescribed by the VSM are rather obvious and yet, as seen by the specific alliance test case, many of these conditions have been completely overlooked by a management that was more than capable, willing, and empowered to enact those conditions. This gives a good indication that the toolset which has been compiled in a visual and tabular systematic fashion may well be useful to practitioners for the organisational planning of an alliance management. The visual representation of a management role in the VSM as a set of knowledge episodes put forward by this research is significant. It forces the express recognition that knowledge management is an integral part of every interaction that takes place and every action performed that, according to the VSM, are necessary and altogether are sufficient for viability. It means that knowledge management cannot be considered as some abstract topic or unnecessary overhead or afterthought – it is entirely necessary, practical and forms a natural course of events during design of action/interaction processes. In other words, if an organisation is viable then, by definition, it does knowledge management whether or not it is formally recognised as such. The VSM, by defining necessary and sufficient actions and interactions for its roles, therefore provides a focus for relevant knowledge and serves as a tool for structured knowledge management. Originality/value: This research addresses a general academic call for hands-on insights of VSM applications by sharing real-world insights, artifacts and reflections generated by a practical and relevant organisational management application. It also addresses the potential, recognised by academics, for VSM as a framework for knowledge management by developing an intuitive model linking those theories and then using that model as part of a framework to guide its application. The introduction to aspects of knowledge management theory relevant to the model developed as well as the meticulousness and comprehensive explanation of the VSM provides a solid theoretical foundation for practitioners. The developed toolset is based on existing theories from multiple fields of research that have been logically linked and extended in an original and novel manner with a strong focus on practical application. This researcher’s hope is that this will stimulate interest for future research and practical application from academics and practitioners alike.
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.
Digital twin as enabler of business model innovation for infrastructure construction projects
(2023)
Emerging technologies and methods are becoming an important element of the construction industry. Digital Twins are used as a base to store data in BIM models and make use out of the data respectively make the data visible. The transparency in all phases of the lifecycle of building and infrastructure assets is crucial in order to get a more efficient lifecycle of planning, construction and maintenance. Whereas other industries increased performance in these phases by making use out of the data, construction industry is stuck in traditional methods and business models. In this paper we propose a concept that focuses on the digital production twin. The comparison of planning data with As-Is production data can empower a data driven continuous improvement process and support the decision making process of future innovations and suitable business models. This paper outlines the possibility to use the data stored in a digital twin with regards to the evaluation of possible business models.
Through mandatory ESG (environmental, social, governance) reporting large companies must disclose their ESG activities showing how sustainability risks are incorporated in their decision-making and production processes. This disclosure obligation, however, does not apply to small and medium-sized enterprises (SME), creating a gap in the ESG dataset. Banks are therefore required to collect sustainability data of their SME customers independently to ensure complete ESG integration in the risk analysis process for loans. In this paper, we examine ESG risk analysis through a smart science approach laying the focus on possible value outcomes of sustainable smart services for banks as well as for their (SME) customers. The paper describes ESG factors, how services can be derived from them, targeted metrics of ESG and an ESG Service Creation Framework (business ecosystem building, process model, and value creation). The description of an exemplary use case highlighting the necessary ecosystem for service creation as well as the created value concludes the paper.
Modeling the dynamic of breath methane concentration profiles during exercise on an ergometer
(2015)
The number of electric vehicles will increase rapidly in the coming years. Studies suggest that most owners prefer to charge their electric vehicle at home, which will fuel the need for charging stations in residential complexes where vehicles can be charged overnight. Currently, there already are over 100 such residential complexes, with another 70 added every year in Vorarlberg alone. In most existing residential complexes, however, the grid connections are not sufficient to charge all vehicles at the same time with maximum power. In addition, it is also desirable for grid operators and electricity producers that the power demand be as smooth and predictable as possible. To achieve this, ways to manage flexible loads need to be found, which can operate within the technical constraints. Therefore, the most common scenarios how the load can be made grid-friendly with the help of optional battery storage and/or photovoltaics using optimization methods of linear and stochastic programming were examined. At the same time, the needs of the vehicle owners for charging comfort - namely to find their vehicles reliably charged at the time of their respective departure - were addressed by combining both objectives using suitable weights. The algorithms determined were verified in practice on an existing Vlotte prototype installation. For this purpose, the necessary programs were implemented in Python, so that the data obtained during the test operation, which lasted one month, could be subjected to a well-founded analysis. In addition, simulation studies helped to further reveal the influence of PV and BESS sizing on the achievable optimums and confirm that advanced optimization algorithms such as the ones discussed are a vital contribution in reducing the charging stations’ peak load while at the same time maintaining high satisfaction levels.
Background: Cardiovascular disease is the major cause of death worldwide. Although knowledge regarding diagnosing and treating cardiovascular disease has increased dramatically, secondary prevention remains insufficiently implemented due to failure among affected individuals to adhere to guideline recommendations. This has continued to lead to high morbidity and mortality rates. Involving patients in their healthcare and facilitating their active roles in their chronic disease management is an opportunity to meet the needs of the increasing number of cardio-vascular patients. However, simple recall of advice regarding a more preventive lifestyle does not affect sustainable behavioral lifestyle changes. We investigate the effect of plaque visualization combined with low-threshold daily lifestyle tasks using the smartphone app PreventiPlaque to evaluate change in cardiovascular risk profile. Methods: and study design: This randomized, controlled clinical trial includes 240 participants with ultrasound evidence of atherosclerotic plaque in one or both carotid arteries, defined as focal thickening of the vessel wall measuring 50% more than the regular vessel wall. A criterion for participation is access to a smartphone suitable for app usage. The participants are randomly assigned to an intervention or a control group. While both groups receive the standard of care, the intervention group has additional access to the PreventiPlaque app during the 12-month follow-up. The app includes daily tasks that promote a healthier lifestyle in the areas of smoking cessation, medication adherence, physical activity, and diet. The impact of plaque visualization and app use on the change in cardiovascular risk profile is assessed by SCORE2. Feasibility and effectiveness of the PreventiPlaque app are evaluated using standardized and validated measures for patient feedback.
Silicon nanophotonics
(2013)
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.
During two studies the influence of technologies on sleep were analyzed. The first one is about the effect of light on the circadian rhythm and as a consequence on sleep quality of persons in a vegetative state. The second one, which is still running, surveys the influence of several technologies on the sleep of elderly people living in a nursing home.
Projects, in which software products, services, systems and solutions are developed, all rely on the right requirements to be established. Software requirements are the expression of user wants or needs that have to be addressed, business objectives that have to be met, as well as capabilities and functionality that has to be developed. Meanwhile, practice shows that very often incorrect, unclear or incomplete requirements are established, which causes major problems for such projects. It could lead to budget overruns, missed deadlines and overall failure in worst-case scenarios.
The field of requirements engineering emerged as an answer to these shortcomings, aiming to systematize and streamline the process that
establishes requirements. Requirements elicitation is a key component of this process, and one of its starting points. The current thesis attempts to outline best practices in requirements elicitation, as well as what issues, obstacles and challenges are currently faced, and then present this through the lens of national culture. In this way its effects on the practice, if any, could be highlighted and studied further. The way this was achieved was by interviewing practitioners from two nations, which are shown to be
culturally different, and then comparing and contrasting the findings.
Meanwhile, the validity of those findings was enhanced by comparisons with existing literature.
Even though the findings were not compelling enough to form generalizations or concrete conclusions about the effects of national culture on requirements elicitation, these findings revealed patterns that could be worth exploring further. When it comes to requirements elicitation itself, it was observed to benefit from a structured and systematic approach, and be
most effective with one-on-one, instead of group interactions. The main pain points of the process stem from the complexity of communication, but are not always obvious. Practitioners are also advised to carefully plan the gathering of requirements, as the source may not have them readily available, and could even be unclear about what exactly is needed. Overall, this thesis research could be considered successful in its goal to shed a modicum of light on the issue at hand from a different, underexplored angle. By following a systematic and methodical approach, this research has also been made easier to expand or replicate.
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.
Smart services disrupt business models and have the potential to stimulate the circular economy transition of regions, enabling an environmentally friendly atmosphere for sustainable and innovation-driven growth of regions. Although smart services are powerful means for deploying circular economy goals in industrial practices, there is little systematic guidance on how the adoption of smart services could improve resource efficiency and stimulate smart regional innovation-driven growth, enabled through circular design. Implemented in the scope of Vorarlberg’s smart specialization strategy, this paper contributes to the literature on the circular economy and regional innovation-driven growth by assessing critical factors of the value creation and value capture implemented within the scope of the quadruple helix system. By identifying the main challenges and opportunities of collaborative value creation and value capture in setting-up smart circular economy strategies and by assessing the role of innovation actors within the quadruple helix innovation system, the study provides recommendations and set of guidelines for managers and public authorities in managing circular transition. Finally, based on the analysis of the role of actors in creating shared value and scaling-up smart circular economy practices in the quadruple helix innovation systems, the paper investigates the role of banks as enablers of circular economy innovation-driven regional growth and smart value creation.
Complementarities and synergies of quadruple helix innovation design in smart city development
(2020)
Increased urbanization trends are stimulating regional needs to support transitions from urban environments to smart cities, using its holistic perspective as a source to innovation. Strong relations between smart cities, urban and regional development, are getting increased attention both at policy and implementation level, providing fertile ground for execution of the new European policy frameworks that supports quadruple helix approaches to innovation. Smart specialization strategies (RIS3) encompass such initiatives, placing ICT and collaboration between academia, industry, government, and citizen at the center of urban innovation. However, there is still lack of research on effects of such approaches to innovation, involving both quadruple helix clusters and ICT in utilizing innovation potentials for developing smart cities. This study aims to increase the understanding on how quadruple helix urban innovation strengthens competitiveness of regions by improving its local smart areas – RIS3. We identified smart specialization patterns and applied comparative benchmark between nine smallmedium sized urban regions in Central Europe. Building on these results, the study provides an overview of the effects of RIS3 strategies implemented through quadruple helix innovation clusters on competitiveness of regions and Smart City development.
Investigations on mechanical stability of laser machined optical fibre tips for medical application
(2019)
Light delivery is a challenging task, when it comes to medical applications. The light is guided through optical fibers from the light source towards the treatment region. In case of interstitial light application, the light has to be decoupled from the fibre and spread to the surrounding tissue. To reach larger tissue volumes, this can be either obtained by adding a scattering volume to the tip of the fibre, or by directly modifying the optical fibre itself in order to break the total reflection within the fibre core. Such modifications can be either on the fibre surface itself or internally in the fibre core. One approach to obtain the fibre structuring could be laser induced surface roughening using an ultrafast laser source. While using volume scattering as diffusor at the fibre tip is currently the gold standard for non-thermal applications (< 0.3W/cm), the decoupling of high power laser intensities for thermal treatment options is still challenging. Structuring the fibre core itself usually is related with a loss of mechanical stability. As fibre breakage and potential loss within the human body can have serious consequences, the mechanical stability is one of the quality criterion in diffuser manufacturing. Therefore, investigations about the mechanical stability of laser manufactured optical fibre diffusers are needed.
In order to evaluate the mechanical stability, a 4-point as well as a 2-point breaking test were developed. Different fibre diffusers, based on volume or surface scattering, were manufactured using fs-laser ablation techniques and its breaking strengths were investigated.
It could be shown that for surface fibre modifications, the mechanical stability reduces with increasing defect depth. The stability significantly drops when the laser ablation was performed in the thermal energy range. Volume scattering modified fibres only showed a slight reduction in stability compared to un-machined fibres.
In conclusion, internal fibre modification seems to be the most promising method to establish optical fibre diffusers, which are capable of several watts of emission power, while preserving its mechanical strength.
Ultrafast-laser manufacture of radially emitting optical fiber diffusers for medical applications
(2018)
Interstitial photodynamic therapy (iPDT) treats malignant brain cancer cells by irradiation with low power laser light. The light is guided into the human body by diffuse emitting fibers. This study targets the light distribution of optical diffusers within the brain tissue. It was shown, that by submerging an optical diffuser into human brain phantom, its radiation profile measured in air converges towards a Gaussian distribution with increasing phantom depth. A camera method using digital averaging filters as well as an integrating sphere setup, both, smoothing the diffuser radiation profile were applied onto the evaluated diffuser.
Investigation of non-uniformly emitting optical fiber diffusers on the light distribution in tissue
(2020)
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.
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.