Lowest Landau level broadened by a Gaussian random potential with an arbitrary correlation length: An efficient continued-fraction approach

For an electron in the plane subjected to a perpendicular constant magnetic field and a homogeneous Gaussian random potential with a Gau{ss}ian covariance function we approximate the averaged density of states restricted to the lowest Landau level. To this end, we extrapolate the first 9 coefficients of the underlying continued fraction consistently with the coefficients' high-order asymptotics. We thus achieve the first reliable extension of Wegner's exact result [Z. Phys. B {\bf 51}, 279 (1983)] for the delta-correlated case to the physically more relevant case of a non-zero correlation length.Comment: 9 pages ReVTeX, three figure

Method for a structured identification of suitable safety and securing systems for Level Crossings

Safety and securing systems for level crossing have a long life time. Once a system reaches a life time when it is no longer conform to applicable regulations, it has to be modernized or replaced. The planner of the level crossing system alongside the road and railroad has to adapt the system to various local conditions and rules. He has to choose a suitable system by the use of his individual expert knowledge. The decisions he made are often hard to understand or to trace for the operating company. This paper presents a structured method, which was developed as a basis for the decision making. It helps to trace the decisions of the engineer and even enables the engineer to identify a suitable level crossing system

Business Model Innovation in Times of Crisis: Highway2Hybrid – A Trade Fairs Digital Transformation

The business event industry was hit particularly hard by the COVID-19 pandemic. Within a few weeks, all trade fairs, congresses and events were cancelled in the spring of 2020 and partly replaced by video-conferencing formats as fastest possible alternative in order to reach the goals of the respective industries at least digitally. After more than a year of pandemic, many marketing and business travel budgets were forced to either be cut, frozen, or shifted into online initiatives. The crisis winners of shifted budgets were, for example, the advertising business segments of social media business networks such as LinkedIn. Trade fairs were forced to leverage digital technologies and undergo a significant transformation of their business model in order to survive. This teaching case addresses various aspects of modern live communication in the business event industry and the challenge of combining these elements with digital technologies and services to create added value

Mine the right process – towards a method for selecting a suitable use case for process mining adoption

Process mining (PM) is a big data analytics technology assisting organizations in process optimization by creating insights from event log data available in existing information systems. Although research on PM utilization exists, literature on the adoption phase is scarce. Hence, organizations lack an understanding of how to determine suitable use cases. Accordingly, we followed a design science-based approach and systematically identified twenty criteria, e.g., process variants, processual weaknesses, and analytical skills, to select suitable use cases for PM adoption. The criteria were evaluated with Celonis and Munich Airport and guide PM vendors, organizations, and consultancies through the evaluation process. Hence, we contribute to the early steps of PM diffusion by assisting in determining its consequences and founding the adoption decision. Future research may consider the criteria as a research framework to investigate their effects on the adoption decision

Privacy Discrimination: What it is and why it matters

We argue that online companies are able to exploit users’ varying levels of privacy needs. We show that by employing data analytics methods on a comparatively small amount of data it is possible to predict how high information privacy concerns of specific users are. We argue that online companies might be able to introduce “privacy discrimination”, in the sense that they might apply varying levels of privacy protection to users, based on their privacy concerns. Users indifferent about privacy could be presented with limited privacy options, adjusted terms and conditions or might be driven to disclose more personal information

A Comprehensive Study of k-Portfolios of Recent SAT Solvers

Hard combinatorial problems such as propositional satisfiability are ubiquitous. The holy grail are solution methods that show good performance on all problem instances. However, new approaches emerge regularly, some of which are complementary to existing solvers in that they only run faster on some instances but not on many others. While portfolios, i.e., sets of solvers, have been touted as useful, putting together such portfolios also needs to be efficient. In particular, it remains an open question how well portfolios can exploit the complementarity of solvers. This paper features a comprehensive analysis of portfolios of recent SAT solvers, the ones from the SAT Competitions 2020 and 2021. We determine optimal portfolios with exact and approximate approaches and study the impact of portfolio size k on performance. We also investigate how effective off-the-shelf prediction models are for instance-specific solver recommendations. One result is that the portfolios found with an approximate approach are as good as the optimal solution in practice. We also observe that marginal returns decrease very quickly with larger k, and our prediction models do not give way to better performance beyond very small portfolio sizes

Business Model Innovation and Stakeholder: Exploring Mechanisms and Outcomes of Value Creation and Destruction

Given the objective of the focal firm to generate value for stakeholders, this research aims at assessing mechanisms and outcomes for value creation and destruction between business model innovation (BMI) and stakeholders. To achieve this goal, we conduct a systematic literature review and apply grounded theory as coding scheme. Taking frequent mechanisms and outcomes into account, we construct a conceptual framework and pioneer theory building. As main result, we identify BMI creating economic return for third parties and product/service access for customers. Both outcomes are based on the mechanism of altering resources and processes. In contrast, analyzing stakeholder’s main influence, we find management creating strategic orientation by providing know-how. Our research agenda emphasizes the design of BMI from an ecosystem perspective and the destructive consequences of BMI. While the ecosystem level of analysis provides new insights into the concept, investigating negative impacts contributes to a more holistic understanding of BMI

Analyzing Measures for the Construct “Energy-Conscious Driving”: A Synthesized Measurement Model to Operationalize Eco-Feedback

During the last several years, a large number of studies have dealt with eco-driving and have defined rules for driving vehicles more ecologically, eco-friendly, and energy efficiently. These rules are vague or insufficient for achieving their purpose, and the construct “energy- conscious driving” is unsatisfactorily defined. To structure available research and develop a more extensive concept of energy-conscious driving, a measurement model for energy- conscious driving is introduced. The model stems from a literature review conducted to identify six groups of measures for energy-conscious driving, and a synthesis of these groups to identify dependencies between them. This paper contributes to theory by building on existing knowledge on eco-driving through an analysis of available literature and describing dependencies between our six measures of energy-conscious driving. Based on our model, researchers can evaluate different eco-feedback designs and practitioners can implement more specific eco-feedback systems for improved user performance

Bounds on the Hausdorff dimension of random attractors

In der vorliegenden Dissertation werden zufällige dynamische Systeme in Hilberträumen und deren Langzeitverhalten diskutiert. Der Schwerpunkt der Arbeit liegt auf der Abschätzung der Hausdorff-Dimension von zufälligen Attraktoren, welche ein wichtiges Merkmal für das Langzeitverhalten darstellen. Eine Besonderheit des ersten Teils der Arbeit ist, dass die Grundmenge des zugrunde liegenden Maßraums eine fraktale Menge ist. Eine solche Menge ist typischerweise eine Teilmenge eines euklidischen Raumes, hat ein leeres Inneres und keinen glatten Rand. Aufgrund dieser Eigenschaften ist eine klassische Differentation von Funktionen auf diesen Mengen nicht möglich. Nach einer Einführung in die Analysis auf Fraktalen und dem zugehörigen Laplace-Operator wird ein zufälliges dynamisches System aus der Lösung einer stochastischen partiellen Differentialgleichung erzeugt und die Existenz eines eindeutigen zufälligen Attraktors diskutiert. Für die Hausdorff-Dimension dieses Attraktors wird im Anschluss eine obere Schranke hergeleitet, die von dem spektralen Exponent des Laplace-Operators abhängt. Insbesondere geben wir im Rahmen eines Beispiels einen numerischen Wert für die obere Schranke an. Der zweite Teil der Arbeit befasst sich mit einer stochastischen partiellen Differentialgleichung, welche von einem multiplikativen Rauschen getrieben wird. Wir beweisen die Existenz des zufälligen Attraktors der zugehörigen Dynamik und die Existenz einer invarianten instabilen Mannigfaltigkeit. Um eine untere Abschätzung für die Hausdorff-Dimension des Attraktors zu erhalten, projizieren wir eine Teilmenge der Mannigfaltigkeit, welche auch Teilmenge des Attraktors ist, auf den instablen Teilraum des Hilbertraums