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Förderpreise 2015
(2015)
Praxisorientierte, wissenschaftliche Lehre und Forschung in enger Zusammenarbeit mit Unternehmen, Organisationen und gesellschaftlichen Gruppierungen ist das zentrale Leitbild des Fachbereichs Wirtschaftswissenschaften an der Hochschule Bonn-Rhein-Sieg.
Alles dreht sich um's Denken im gerade erschienenen Jahresbericht 2014.
Im Interview erörtern Hochschulpräsident Hartmut Ihne und 3Sat-Moderator Gert Scobel den Denkbegriff - "Dürfen wir unsere Autonomie aus freien Stücken an Algorithmen abgeben?".
James Chamberlain, Leiter des Sprachenzentrums der H-BRS, geht der Frage auf den Grund, in wieweit sich das Denken in unterschiedlichen Sprachen unterscheidet.
Professor Paul Plöger vom Fachbereich Informatik erklärt, warum Roboter große Probleme damit haben, komplexe Zusammenhänge in offenen Umgebungen zu verstehen.
Der knapp 90 Seiten starke Jahresbericht verknüpft sein großes Thema mit der enormen Vielfalt von Leben, Forschung und Lehre an der H-BRS und wirft nicht nur einen Blick in die Zukunft der Hochschule.
Lehren an Hochschulen
(2015)
Die Servicestelle Lehrbeauftragtenpool ist ein vom Bundesministerium für Bildung und Forschung (BMBF) gefördertes Verbundprojekt der Hochschulen Bonn-Rhein-Sieg, Düsseldorf, Niederrhein und Rhein-Waal. Unser Ziel ist es, die Qualität der Lehre zu verbessern, indem wir Menschen mit Berufserfahrung an die Hochschulen und in die Lehre bringen.
The central theme of the 2014 Annual Report is human thinking.
In an interview, University President Hartmut Ihne and 3Sat moderator Gert Scobel discuss the concept of thought: "Should we be allowed to give up our autonomy voluntarily?"
Our university’s Language Centre Director James Chamberlain examines to what extent thinking varies in different languages.
Professor Paul Plöger from the Department of Computer Science explains why robots have tremendous problems understanding complex relationships in open environments.
Rather than focusing solely on our university’s future, the Annual Report links the fascinating theme to the enormous variety of life, research and tuition offered by H-BRS.
Background: Falls and fall-related injuries are a serious public health issue. Exercise programs can effectively reduce fall risk in older people. The iStoppFalls project developed an Information and Communication Technology-based system to deliver an unsupervised exercise program in older people’s homes. The primary aims of the iStoppFalls randomized controlled trial were to assess the feasibility (exercise adherence, acceptability and safety) of the intervention program and its effectiveness on common fall risk factors.
Methods: A total of 153 community-dwelling people aged 65+ years took part in this international, multicentre, randomized controlled trial. Intervention group participants conducted the exercise program for 16 weeks, with a recommended duration of 120 min/week for balance exergames and 60 min/week for strength exercises. All intervention and control participants received educational material including advice on a healthy lifestyle and fall prevention. Assessments included physical and cognitive tests, and questionnaires for health, fear of falling, number of falls, quality of life and psychosocial outcomes.
Results: The median total exercise duration was 11.7 h (IQR = 22.0) over the 16-week intervention period. There were no adverse events. Physiological fall risk (Physiological Profile Assessment, PPA) reduced significantly more in the intervention group compared to the control group (F1,127 = 4.54, p = 0.035). There was a significant three-way interaction for fall risk assessed by the PPA between the high-adherence (>90 min/week; n = 18, 25.4 %), low-adherence (<90 min/week; n = 53, 74.6 %) and control group (F2,125 = 3.12, n = 75, p = 0.044). Post hoc analysis revealed a significantly larger effect in favour of the high-adherence group compared to the control group for fall risk (p = 0.031), postural sway (p = 0.046), stepping reaction time (p = 0.041), executive functioning (p = 0.044), and quality of life (p for trend = 0.052).
Conclusions: The iStoppFalls exercise program reduced physiological fall risk in the study sample. Additional subgroup analyses revealed that intervention participants with better adherence also improved in postural sway, stepping reaction, and executive function.
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.