University of Applied Sciences Ravensburg-Weingarten

About: University of Applied Sciences Ravensburg-Weingarten is a education organization based out in Weingarten, Germany. It is known for research contribution in the topics: Tourism & Mobile robot. The organization has 90 authors who have published 150 publications receiving 2553 citations.

Nonlinear control of a quadrotor micro-UAV using feedback-linearization

Abstract: Four-rotor micro aerial robots, so called quadrotor UAVs, are one of the most preferred type of unmanned aerial vehicles for near-area surveillance and exploration both in military and commercial in- and outdoor applications. The reason is the very easy construction and steering principle using four rotors in a cross configuration. However, stabilizing control and guidance of these vehicles is a difficult task because of the nonlinear dynamic behavior. In addition, the small payload and the reduced processing power of the onboard electronics are further limitations for any control system implementation. This paper describes the development of a nonlinear vehicle control system based on a decomposition into a nested structure and feedback linearization which can be implemented on an embedded microcontroller. Some first simulation results underline the performance of this new control approach for the current realization.

Big data analytics for knowledge generation in tourism destinations – A case from Sweden

Abstract: This paper presents a knowledge infrastructure which has recently been implemented as a genuine novelty at the leading Swedish mountain tourism destination, Are. By applying a Business Intelligence approach, the Destination Management Information System Are (DMIS-Are) drives knowledge creation and application as a precondition for organizational learning at tourism destinations. Schianetz, Kavanagh, and Lockington’s (2007) concept of the ‘ Learning Tourism Destination ’ and the ‘ Knowledge Destination Framework ’ introduced by Hopken, Fuchs, Keil, and Lexhagen (2011) build the theoretical fundament for the technical architecture of the presented Business Intelligence application. After having introduced the development process of indicators measuring destination performance as well as customer behaviour and experience, the paper highlights how DMIS-Are can be used by tourism managers to gain new knowledge about customer-based destination processes focused on pre- and post-travel phases, like “ Web-Navigation ”, “ Booking ” and “ Feedback ”. After a concluding discussion about the various components building the prototypically implemented BI-based DMIS infrastructure with data from destination stakeholders, the agenda of future research is sketched. The agenda considers, for instance, the application of real-time Business Intelligence to gain real-time knowledge on tourists’ on-site behaviour at tourism destinations.

Reinforcement learning to adjust parametrized motor primitives to new situations

Abstract: Humans manage to adapt learned movements very quickly to new situations by generalizing learned behaviors from similar situations. In contrast, robots currently often need to re-learn the complete movement. In this chapter, we propose a method that learns to generalize parametrized motor plans by adapting a small set of global parameters, called meta-parameters. We employ reinforcement learning to learn the required meta-parameters to deal with the current situation, described by states. We introduce an appropriate reinforcement learning algorithm based on a kernelized version of the reward-weighted regression. To show its feasibility, we evaluate this algorithm on a toy example and compare it to several previous approaches. Subsequently, we apply the approach to three robot tasks, i.e., the generalization of throwing movements in darts, of hitting movements in table tennis, and of throwing balls where the tasks are learned on several different real physical robots, i.e., a Barrett WAM, a BioRob, the JST-ICORP/SARCOS CBi and a Kuka KR 6.

Impaired sleep quality and sleep duration in smokers-results from the German Multicenter Study on Nicotine Dependence

Abstract: Cigarette smoking is a severe health burden being related to a number of chronic diseases. Frequently, smokers report about sleep problems. Sleep disturbance, in turn, has been demonstrated to be involved in the pathophysiology of several disorders related to smoking and may be relevant for the pathophysiology of nicotine dependence. Therefore, determining the frequency of sleep disturbance in otherwise healthy smokers and its association with degree of nicotine dependence is highly relevant. In a population-based case-control study, 1071 smokers and 1243 non- smokers without lifetime Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Axis I disorder were investigated. Sleep quality (SQ) of participants was determined by the Pittsburgh Sleep Quality Index. As possible confounders, age, sex and level of education and income, as well as depressiveness, anxiety, attention deficit hyperac- tivity, alcohol drinking behaviour and perceived stress, were included into multiple regression analyses. Significantly more smokers than non-smokers (28.1% versus 19.1%; P < 0.0001) demonstrated a disturbed global SQ. After con- trolling for the confounders, impaired scores in the component scores of sleep latency, sleep duration and global SQ were found significantly more often in smokers than non-smokers. Consistently, higher degrees of nicotine dependence and intensity of smoking were associated with shorter sleep duration. This study demonstrates for the first time an elevated prevalence of sleep disturbance in smokers compared with non-smokers in a population without lifetime history of psychiatric disorders even after controlling for potentially relevant risk factors. It appears likely that smoking is a behaviourally modifiable risk factor for the occurrence of impaired SQ and short sleep duration.

E-Business Readiness, Intensity, and Impact: An Austrian Destination Management Organization Study

Abstract: The majority of today’s information and communication technology (ICT) impact studies disregard infrastructural, organizational, and environmental factors typically responsible for successful e-business adoption and use. This article proposes an empirical approach that shows how the mentioned factors determine both e-business adoption and the impact of information and communication technologies. The research framework is based on E. Rogers’ Innovation Diffusion Theory and is tested with survey data gathered in the Austrian destination management organization sector. By referring to K. Zhu and K. L. Kraemer’s (2005) e-business impact model, the proposed approach explicates how the use of e-business applications may positively affect the performance of tourism organizations. Online survey data are analyzed through a linear structural equation modeling approach.