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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.
Was ist dran am Hype um die Cloud? Während Gartner Research bereits von einem Abwärts trend spricht, sehen Prof. Alda und Prof. Bonne von der Hochschule Bonn-Rhein-Sieg viele gewinnbringende Anwendungsszenarien in der Praxis. Insbesondere auf den Finance- und Accounting-Bereich lassen sich die positiven Vorteile einer Cloud- Lösung übertragen.
Binary relations with certain properties such as biorders, equivalences or difunctional relations can be represented as particular matrices. In order for these properties to be identified usually a rearrangement of rows and columns is required in order to reshape it into a recognisable normal form. Most algorithms performing these transformations are working on binary matrix representations of the underlying relations. This paper presents an approach to use the RLE-compressed matrix representation as a data structure for storing relations to test whether they are biorders in a hopefully more efficient way.
Digitalisierung eines Pen-&-Paper-Rollenspiels mit Übertragung von Interaktionen in die reale Welt
(2015)
Das hier vorliegende Werk ist eine Zusammenführung des Masterprojekts und der darauf aufbauenden Masterarbeit von Antony Konstantinidis und Nicolas Kopp. Diese Arbeiten sind in den Jahren 2013 und 2014 entstanden und ergeben zusammen ein umfassendes Bild der Software- und Spielenentwicklung, der Konzeption von Echtzeitanwendungen und vermitteln Hintergründe aus den verschiedensten Bereichen der Mixed Reality, des Storytelling, der Netzwerkkonzeption und der künstlichen Intelligenz.
Advanced driver assistance systems (ADAS) are technology systems and devices designed as an aid to the driver of a vehicle. One of the critical components of any ADAS is the traffic sign recognition module. For this module to achieve real-time performance, some preprocessing of input images must be done, which consists of a traffic sign detection (TSD) algorithm to reduce the possible hypothesis space. Performance of TSD algorithm is critical.
One of the best algorithms used for TSD is the Radial Symmetry Detector (RSD), which can detect both Circular [7] and Polygonal traffic signs [5]. This algorithm runs in real-time on high end personal computers, but computational performance of must be improved in order to be able to run in real-time in embedded computer platforms.
To improve the computational performance of the RSD, we propose a multiscale approach and the removal of a gaussian smoothing filter used in this algorithm. We evaluate the performance on both computation times, detection and false positive rates on a synthetic image dataset and on the german traffic sign detection benchmark [29].
We observed significant speedups compared to the original algorithm. Our Improved Radial Symmetry Detector is up to 5.8 times faster than the original on detecting Circles, up to 3.8 times faster on Triangle detection, 2.9 times faster on Square detection and 2.4 times faster on Octagon detection. All of this measurements were observed with better detection and false positive rates than the original RSD.
When evaluated on the GTSDB, we observed smaller speedups, in the range of 1.6 to 2.3 times faster for Circle and Regular Polygon detection, but for Circle detection we observed a decreased detection rate than the original algorithm, while for Regular Polygon detection we always observed better detection rates. False positive rates were high, in the range of 80% to 90%.
We conclude that our Improved Radial Symmetry Detector is a significant improvement of the Radial Symmetry Detector, both for Circle and Regular polygon detection. We expect that our improved algorithm will lead the way to obtain real-time traffic sign detection and recognition in embedded computer platforms.
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.
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.