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The study of locomotion in virtual environments is a diverse and rewarding research area. Yet, creating effective and intuitive locomotion techniques is challenging, especially when users cannot move around freely. While using handheld input devices for navigation may often be good enough, it does not match our natural experience of motion in the real world. Frequently, there are strong arguments for supporting body-centered self-motion cues as they may improve orientation and spatial judgments, and reduce motion sickness. Yet, how these cues can be introduced while the user is not moving around physically is not well understood. Actuated solutions such as motion platforms can be an option, but they are expensive and difficult to maintain. Alternatively, within this article we focus on the effect of upper-body tilt while users are seated, as previous work has indicated positive effects on self-motion perception. We report on two studies that investigated the effects of static and dynamic upper body leaning on perceived distances traveled and self-motion perception (vection). Static leaning (i.e., keeping a constant forward torso inclination) had a positive effect on self-motion, while dynamic torso leaning showed mixed results. We discuss these results and identify further steps necessary to design improved embodied locomotion control techniques that do not require actuated motion platforms.
We propose a high-performance GPU implementation of Ray Histogram Fusion (RHF), a denoising method for stochastic global illumination rendering. Based on the CPU implementation of the original algorithm, we present a naive GPU implementation and the necessary optimization steps. Eventually, we show that our optimizations increase the performance of RHF by two orders of magnitude when compared to the original CPU implementation and one order of magnitude compared to the naive GPU implementation. We show how the quality for identical rendering times relates to unfiltered path tracing and how much time is needed to achieve identical quality when compared to an unfiltered path traced result. Finally, we summarize our work and describe possible future applications and research based on this.
This presentation gives an overview of current research in the area of high quality rendering and visualization at the Institute of Visual Computing (IVC). Our research facility has some unique software and hardware installations of which we will describe a large, ultra- high resolution (72 megapixel) video wall in this presentation.
A recent trend in interactive environments are large, ultra high resolution displays (LUHRDs). Compared to other large interactive installations, like the CAVE tm , LUHRDs are usually flat or (slightly) curved and have a significantly higher resolution, offering new research and application opportunities.
This tutorial provides information for researchers and engineers who plan to install and use a large ultra-high resolution display. We will give detailed information on the hardware and software of recently created and established installations and will show the variety of possible approaches. Also, we will talk about rendering software, rendering techniques and interaction for LUHRDs, as well as applications.
With the increasing average age of the population in many developed countries, afflictions like cardiovascular diseases have also increased. Exercising has a proven therapeutic effect on the cardiovascular system and can counteract this development. To avoid overstrain, determining an optimal training dose is crucial. In previous research, heart rate has been shown to be a good measure for cardiovascular behavior. Hence, prediction of the heart rate from work load information is an essential part in models used for training control. Most heart-rate-based models are described in the context of specific scenarios, and have been evaluated on unique datasets only. In this paper, we conduct a joint evaluation of existing approaches to model the cardiovascular system under a certain strain, and compare their predictive performance. For this purpose, we investigated some analytical models as well as some machine learning approaches in two scenarios: prediction over a certain time horizon into the future, and estimation of the relation between work load and heart rate over a whole training session.
A novel approach to produce 2D designs by adapting the HyperNEAT algorithm to evolve non-uniform rational basis splines (NURBS) is presented. This representation is proposed as an alternative to previous pixel-based approaches primarily motivated by aesthetic interests, and not designed for optimization tasks. This spline representation outperforms previous pixel-based approaches on target matching tasks, performing well even in matching irregular target shapes. In addition to improved evolvability in the face of a well defined fitness metric, a NURBS representation has the added virtues of being continuous rather than discrete, as well as being intuitive and easily modified by graphic and industrial designers.
Communicating Sequential Processes (CSP) [7] is a calculus for concurrent systems that has been the basis of subject-oriented business process management (S-BPM) [4]. We use CSPm -- a machine readable dialect of CSP -- to create a sequence of models for a case study on an "Automated Teller Machine" [1]. We use the refinement checker FDR2 to prove that certain models are correct implementations of specifications.
We present GEM-NI -- a graph-based generative-design tool that supports parallel exploration of alternative designs. Producing alternatives is a key feature of creative work, yet it is not strongly supported in most extant tools. GEM-NI enables various forms of exploration with alternatives such as parallel editing, recalling history, branching, merging, comparing, and Cartesian products of and for alternatives. Further, GEM-NI provides a modal graphical user interface and a design gallery, which both allow designers to control and manage their design exploration. We conducted an exploratory user study followed by in-depth one-on-one interviews with moderately and highly skills participants and obtained positive feedback for the system features, showing that GEM-NI supports creative design work well.
An Empirical Evaluation of the Received Signal Strength Indicator for fixed outdoor 802.11 links
(2015)
For the evaluation of the received signal strength indication (RSSI) a different methodology compared to previous publications is introduced in this paper by exploiting a spectral scan feature of recent Qualcomm Atheros WiFi NICs. This method is compared to driver reports and to an industrial grade spectrum analyzer. During the conducted outdoor experiments a decreased scattering of the RSSI compared to previous publications is observed. By applying well-known mathematical tests for normality it is possible to show that the RSSI does not follow a normal distribution in a line-of-sight outdoor environment. The evaluated spectral scan features offers additional possibilities to develop interference classifiers which is an important step for frequency allocation in long-distance 802.11 networks.
Understanding the Internet of Things: A Conceptualisation of Business-to-Thing (B2T) Interactions
(2015)
[Context and motivation] Communication in distributed software development is usually supported by issue tracking systems. Within these systems, most of the communication is stored as unstructured natural language text. The natural language text, however, contains much information with respect to requirements management, e.g. discussion, clarification and prioritization of features, bugs, and refactorings. [Question] This paper investigates the information stored in the issue tracking systems of four different open-source projects. It categorizes the text and reports on the distribution of issue types and information types. [Principal ideas/results] A manual analysis of 80 issues, using a grounded approach, is conducted to derive a taxonomy of issue types and information types. Subsequently, the taxonomy is used as a codebook, to manually categorize and structure the text in another 120 issues. [Contribution] The first contribution of this paper is the taxonomy of issue and information types and the second contribution is an in-depth analysis of the natural language data and the communication. This analysis showed, for example, that information with respect to prioritization and scheduling can be found in natural language data, whether the ITS supports such tasks in a structured way or not.
Comparison of the subject-oriented and the Petri net based approach for business process automation
(2015)
The subject-oriented modelling approach [5] significally differs from the classic Petri net based approach of many business process modeling languages like EPC [9], Business Process Model and Notation (BPMN) [11], and also Yet Another Workflow Language (YAWL) [10]. In this work, we compare the two approaches by modeling a case study called "Procure to Pay"[3], a typical business process where some equipment for a construction site is rented and finally paid. The case study is not only modelled but also automated using the Metasonic Suite for the subject-oriented and YAWL for the Petri net based approach.