Perceptual aspects of voice-source parameters

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Moral reasoning, death and the clinic: the ethics of end-of-life decisions

This thesis explores the ethics of end of life decision making by examining the experiences of family members who were involved with the care of a loved one with terminal cancer. There are two main objectives to this research. The first is to understand the nature of the encounters between clinical care and families, how the dying trajectory affects decision making and how family dynamics impact end of life care. The second objective is to understand the process of moral reasoning and to determine whether the nature of ethical engagement differs for end of life decision making. Each narrative case study provides a sequence of events from diagnosis to the end of the patient's life. It also includes both patient's and families' engagement with ethical problems which were encountered during the course of the trajectory, an analysis of their moral reasoning and what both patient and families considered to be a good death. Over thirty hours of interviews were conducted with ten participants. Narrative analysis is used to draw on pertinent contextual information along with an assessment of moral reasoning. This is done in two ways. First, it refers to the general rules of moral reasoning (Cohen, 2014) and applies the theories of three moral worlds (Zigon, 2007). Second, through a structural analysis of the narrative, other moral positions and indicators are revealed. Using a phenomenological approach to the data, important factors which proved to have a considerable impact on engagement with ethics included background and intention, the nature of the subject's life-world, and inter-subjectivity. In addition, both temporality and the emotions were given considerable focus to determine the way in which these elements also shaped end of life decision making. This research responded to the need for more qualitative data for end of life decisions and, by combining both medical and moral anthropology, presents an innovative approach toward understanding both decision making and morality. It reveals that both life-worlds of patients and families are altered by a terminal diagnosis consequently changing the embodied moral worlds of the decision makers. The social and perceptual transformations, the sense of liminality and the power of emotions over their embodied moral worlds changed the nature of their engagement with ethics. Indeed, background experience, inter-subjectivity and emotions sometimes had a greater influence on moral choice than outside powerful social and cultural influences which made up their moral assemblage. My concluding finding is that moral reasoning, when it comes to end of life decision making, should be understood as an exceptional space which alters the parameters of our usual engagement with ethics. The findings presented in this thesis have practical implications for medical professionals who engage with families and also for social workers and other counselors who assist families involved with end of life care. It also has implications for the study of moral anthropology by showing how death and the accompanying emotions shape our moral perspectives, decisions and worlds

Assessing the Impact of Electric Vehicle Charging Behavior on the Distribution Grid

The promise of the EVs is twofold. First, rejuvenating a transport sector that still heavily depends on fossil fuels and second, integrating intermittent renewable energies into the power mix. However, it is still not clear how electricity networks will cope with the predicted increase in EVs and their charging demand, especially in combination with conventional energy demand. This paper proposes a methodology which allows to predict the impact of EV charging behavior on the electricity grid. Moreover, this model simulates the driving and charging behavior of heterogeneous EV drivers which differ in their mobility pattern, decision-making heuristics and charging strategies. The simulations show that uncoordinated charging results in charging load clustering. In contrast, decentralized coordination allows to fill the valleys of the conventional load curve and to integrate EVs without the need of a costly expansion of the electricity grid

A comparative analysis of continuum plasticity, viscoplasticity and phase-field models for earthquake sequence modeling

This paper discusses continuum models for simulating earthquake sequences on faults governed by rate-and-state dependent friction. Through detailed numerical analysis of a conventional strike-slip fault, new observations regarding the use of various continuum earthquake models are presented. We update a recently proposed plasticity-based model using a consistently linearized formulation, show its agreement with discrete fault models for fault thicknesses of hundreds of meters, and demonstrate mesh objectivity for slip-related variables. To obtain a fully regularized fault width description with an internal length scale, we study the performance and mesh convergence of a plasticity-based model complemented by a Kelvin viscosity term and the phase-field approach to cohesive fracture. The Kelvin viscoplasticity-based model can introduce an internal length scale and a mesh-objective response. However, on grid sizes down to meters, this only holds for very high Kelvin viscosities that inhibit seismic slip rates, which renders this approach impractical for simulating earthquake sequences. On the other hand, our phase-field implementation for earthquake sequences provides a numerically robust framework that agrees with a discrete reference solution, is mesh objective, and reaches seismic slip rates. The model, unsurprisingly, requires highly refined grids around the fault zones to reproduce results close to a discrete model. Following this line, the effect of an internal length scale parameter on the phase-field predictions and mesh convergence are discussed

SERVICE INNOVATION WITH INFORMATION MARKETS

Assessing innovation alternatives is a difficult task especially in newly upcoming forms of organization like Business Value Networks. This paper highlights the use of Information Markets and discusses state of the art Market Maker models. We designed a Market Maker mechanism in order to enhance liquidity, and hence, efficiency in the market. Therefore, an agent-based simulation as well as a field experiment was run to evaluate the usefulness and performance of Market Maker. It can be shown that the introduction of automated trading techniques increases market efficiency and thus the quality of the forecasting results for service innovation assessment

Machine Learning in SME: An Empirical Study on Enablers and Success Factors

Machine learning (ML) techniques are rapidly evolving, both in academia and practice. However, enterprises show different maturity levels in successfully implementing ML techniques. Thus, we review the state of adoption of ML in enterprises. We find that ML technologies are being increasingly adopted in enterprises, but that small and medium-size enterprises (SME) are struggling with the introduction in comparison to larger enterprises. In order to identify enablers and success factors we conduct a qualitative empirical study with 18 companies in different industries. The results show that especially SME fail to apply ML technologies due to insufficient ML knowhow. However, partners and appropriate tools can compensate this lack of resources. We discuss approaches to bridge the gap for SME