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Relevance & Research Question: Smartphones have become an integrated part in everyday life facilitating communication, information access, entertainment and organization anytime and anywhere. However, the omnipresence of such devices can evoke psychological dependencies and the need of being always connected resulting in discomfort when the smartphone is not accessible. While few studies have found heightened anxiety during smartphone absence (e.g. Cheever, Rosen, Carrier, & Chavez, 2014), such research is scarce. Therefore, we aimed at expanding existing research asking whether the mere imagination of smartphone absence suffices to trigger anxiety and affect user’s context evaluations.
Rolling mills are continually improved and opti-mized by implementing innovative technology to decrease costs and scrap. Despite of the progressive automation and experience, some important process parameters can still not be determined with sufficient accuracy. As part of the research project PIREF, the velocity of the hot rolled rod shall be measured by using im-pedance analysis to estimate the volumetric flow rate of the mate-rial. For a high accuracy measurement of the impedance, a pow-erful VNA is used. To minimize errors in the measurement, caused by e.g. temperature drift, a correction of the measurement fre-quency is needed. This must be achieved without recalibration of the VNA to avoid faulty behavior of the online control. To solve this problem, an approach based on a polynomial regression is presented in this work.
Quality and dimensional accuracy of hot rolled steel rods depend on several process parameters. In fact many of these crucial parameters are not be sufficiently determined yet. By improving automation and process control costs and scrap of production can be decreased. As part of the research project PIREF, one of these parameters – the roll gap – is under investigation beside other topics. Before starting rolling, the roll gap is typically set to a fixed value according to the planed dimensions of the product, but the forces during the rolling of the rod cause an enlargement of the roll gap. In which way the rolls change their position and form shall be examined in our research project. Therefore a first experimental setup has been built up to determine the change in position of the rolls under applied force. This is realized by a pot core coil as sensor using impedance analysis. The first results are presented in this work as a proof-of-principle.
System design for well-being needs an appropriate tool to help designers to determine relevant requirements that can help human well-being to flourish. Personas come as a simple yet powerful tool in the early development stage of the user interface design. Considering well-being determinants in the early design process provide benefits for both the user and the development team. Therefore, in this short paper, we performed a literature study to provide a conceptual model of well-being in personas and propose positive design interventions in personas’ creation process.
The adoption of Open Educational Resources (OER) can support collaboration and knowledge sharing. One of the main areas of the usage OER is the internationalization, i.e., the use in a global context. However, the globally distributed co-creation of digital materials is still low. Therefore, we identify essential barriers, in particular for co-authoring of OER in global environments. We use a design science research method to introduce a barrier framework for co-authoring OER in global settings and propose a wellbeing-based system design constructed from the barrier framework for OER co-authoring tool. We describe how positive computing concepts can be used to overcome barriers, emphasizing design that promotes the author's sense of competence, relatedness, and autonomy.
In this review, we describe current Machine Learning approaches to hand gesture recognition with depth data from time-of-flight sensors. In particular, we summarise the achievements on a line of research at the Computational Neuroscience laboratory at the Ruhr West University of Applied Sciences. Relating our results to the work of others in this field, we confirm that Convolutional Neural Networks and Long Short-Term Memory yield most reliable results. We investigated several sensor data fusion techniques in a deep learning framework and performed user studies to evaluate our system in practice. During our course of research, we gathered and published our data in a novel benchmark dataset (REHAP), containing over a million unique three-dimensional hand posture samples.
Enabling decentral collaborative innovation processes -a web based real time collaboration platform
(2018)
The main goal of this paper is to define a collaborative innovation process as well as a supporting tool. It is motivated through the increasing competition on global markets and the resultant propagation of decentralized projects with a high demand of innovative collaboration in global contexts. It bases on a project accomplished by the author group. A detailed literature review and the action design research methodology of the project led to an enhanced process model for decentral collaborative innovation processes and a basic realization of a browser based real time tool to enable these processes.The initial evaluation in a practical distributed setting has shown that the created tool is a useful way to support collaborative innovation processes.