Refine
Year of publication
- 2015 (41) (remove)
Document Type
- Conference Proceeding (29)
- Article (3)
- Part of a Book (3)
- Part of Periodical (3)
- Contribution to a Periodical (2)
- Working Paper (1)
Is part of the Bibliography
- no (41)
Keywords
- Fachhochschule (2)
- Hochschule Ruhr West (2)
- Mülheim an der Ruhr (2)
- Zeitschrift (2)
- Data visualization (1)
- Framework (1)
- Image color analysis (1)
- Intercultural sharing (1)
- Knowledge sharing (1)
- Layout (1)
In this demo paper we present a new visualization technique for dynamic networks. It displays the time slices of the dynamic network using two dimensional graph layouting algorithms and stacks these in the third dimension to show the development over time. The visualization ensures that the same node always has the same position in each time slice so that it is easy to follow its development. It also allows filtering data and influencing node appearance based on properties. Additionally we offer a two dimensional comparison view for two time slices which highlights changes in graph structure and (if available) in measures of nodes. The presented visualization technique is implemented using Web technology and is available in a Web-based analytics workbench. We demonstrate the benefits of these techniques by an analysis of a data set from a learning community.
Mensch-Maschine-Interaktion in sicherheitskritischen Systemen ist ein für die Informatik und die jeweiligen Anwendungsdomänen in der Bedeutung weiter zunehmendes Thema. Dieser Workshop der GI-Fachgruppe „Mensch-Maschine-Interaktion in sicherheitskritischen Systemen" innerhalb des Fachbereichs Mensch-Computer-Interaktion soll aktuelle Entwicklungen und Fragestellungen offenlegen und neue Impulse für das Forschungsgebiet geben.
Human computer interaction in security and time-critical systems is an interdisciplinary challenge at the seams of human factors, engineering, information systems and computer science. Application fields include control systems, critical infrastructures, vehicle and traffic management, production technology, business continuity management, medical technology, crisis management and civil protection. Nowadays in many areas mobile and ubiquitous computing as well as social media and collaborative technologies also plays an important role. The specific challenges require the discussion and development of new methods and approaches in order to design information systems. These are going to be addressed in this special issue with a particular focus on technologies for citizen and volunteers in emergencies.
Recently, rescue worker resources have not been sufficient to meet the regular response time during large-scale catastrophic events in every case. However, many volunteers supported official forces in different disaster situations, often self-organized through social media. In this paper, a system will be introduced which allows the coordination of trained volunteers by a professional control center with the objective of a more efficient distribution of human resources and technical equipment. Volunteers are contacted via app on their private smartphone. The design of this app is based on user requirements gathered in focus group discussions. The feedback of the potential users includes privacy aspects, low energy consumption, and mechanisms for long-term motivation and training. The authors present the results of the focus group analyses as well as the transfer to their app design concept.
4. Workshop Automotive HMI
(2015)
Benutzerschnittstellen im Fahrzeug stellen eine besondere Herausforderung in Konzeption und Entwicklung dar, steht doch eine sichere Bedienung in allen Fahrsituationen sowohl von Fahrerassistenzsystemen als auch von Komfort-und Unterhaltungsfunktionen im Vordergrund. Zugleich treffen durch zunehmende Vernetzung die langen Entwicklungszyklen von Kraftfahrzeugen auf die hochdynamische Welt von Mobiltelefonen und Internet. Ein-und Ausgabetechnologien gehören des Weiteren zu den zentralen Mitteln der Hersteller, die Wertigkeit der im Fahrzeug eingebauten Systeme hervorzuheben und sich gegenüber der Konkurrenz abzuheben. Dafür werden in diesem Workshop Konzepte und technische Lösungen von Designern, Entwicklern und Human Factors Experten aus Hochschulen, Forschungsinstituten und der Automobilindustrie vorgestellt und diskutiert.
Bei Großschadensereignissen kann es durch die Vielzahl der Alarme dazu kommen, dass die verfügbaren Rettungskräfte nicht mehr ausreichen, um die anfallenden Aufgaben zu bewältigen oder Hilfsfristen einzuhalten. Die vorliegende Arbeit beschreibt einen Ansatz, sich zusätzlicher Hilfe aus der Bevölkerung zu bedienen, die über einen Disponenten aus der vorhandenen Leitstelle koordiniert wird. Dabei stehen nicht spontan organisierte Helfer im Vordergrund, sondern Personen, die sich vorab mit einem klaren Fertigkeitsprofil und ggf. auch Ausstattung im System registriert haben. Besondere Anforderungen entstehen bei den Disponenten der Leitstelle, deren Mehrbelastung durch das neue System gering zu halten ist, als auch bei den freiwilligen Helfern, die über eine App auf dem Mobiltelefon alarmiert werden und auch darüber die Kommunikation führen sollen. Die Anforderungen beeinflussen sowohl die System-Infrastruktur als auch die Benutzerschnittstelle.
We present a novel approach of distributing matrix multiplications among GPU-equipped nodes in a cluster system. In this context we discuss the induced challenges and possible solutions. Additionally we state an algorithm which outperforms optimized GPU BLAS libraries for small matrices. Furthermore we provide a novel theoretical model for distributing algorithms within homogeneous computation systems with multiple hierarchies. In the context of this model we develop an algorithm which can find the optimal distribution parameters for each involved subalgorithm. We provide a detailed analysis of the algorithms space and time complexities and justify its use with a structured evaluation within a small GPU-equipped Beowulf cluster.
We present a novel method to perform multi-class pattern classification with neural networks and test it on a challenging 3D hand gesture recognition problem. Our method consists of a standard one-against-all (OAA) classification, followed by another network layer classifying the resulting class scores, possibly augmented by the original raw input vector. This allows the network to disambiguate hard-to-separate classes as the distribution of class scores carries considerable information as well, and is in fact often used for assessing the confidence of a decision. We show that by this approach we are able to significantly boost our results, overall as well as for particular difficult cases, on the hard 10-class gesture classification task.
A light-weight real-time ap- plicable hand gesture recognition system for automotive applications
(2015)
We present a novel approach for improved hand-gesture recognition by a single time-of-flight(ToF) sensor in an automotive environment. As the sensor's lateral resolution is comparatively low, we employ a learning approach comprising multiple processing steps, including PCA-based cropping, the computation of robust point cloud descriptors and training of a Multilayer perceptron (MLP) on a large database of samples. A sophisticated temporal fusion technique boosts the overall robustness of recognition by taking into account data coming from previous classification steps. Overall results are very satisfactory when evaluated on a large benchmark set of ten different hand poses, especially when it comes to generalization on previously unknown persons.
We present a system for efficient dynamic hand gesture recognition based on a single time-of-flight sensor. As opposed to other approaches, we simply rely on depth data to interpret user movement with the hand in mid-air. We set up a large database to train multilayer perceptrons (MLPs) which are subsequently used for classification of static hand poses that define the targeted dynamic gestures. In order to remain robust against noise and to balance the low sensor resolution, PCA is used for data cropping and highly descriptive features, obtainable in real-time, are presented. Our simple yet efficient definition of a dynamic hand gesture shows how strong results are achievable in an automotive environment allowing for interesting and sophisticated applications to be realized.
We present a novel hierarchical approach to multi-class classification which is generic in that it can be applied to different classification models (e.g., support vector machines, perceptrons), and makes no explicit assumptions about the probabilistic structure of the problem as it is usually done in multi-class classification. By adding a cascade of additional classifiers, each of which receives the previous classifier's output in addition to regular input data, the approach harnesses unused information that manifests itself in the form of, e.g., correlations between predicted classes. Using multilayer perceptrons as a classification model, we demonstrate the validity of this approach by testing it on a complex ten-class 3D gesture recognition task.
Utilizing biometrie traits for privacy- and security-applications is receiving an increasing attention. Applications such as personal identification, access control, forensics appli-cations, e-banking, e-government, e-health and recently person-alized human-smart-home and human-robot interaction present some examples. In order to offer person-specific services for/of specific person a pre-identifying step should be done in the run-up. Using biometric in such application is encountered by diverse challenges. First, using one trait and excluding the others depends on the application aimed to. Some applications demand directly touch to biometric sensors, while others don't. Second challenge is the reliability of used biometric arrangement. Civilized application demands lower reliability comparing to the forensics ones. And third, for biometric system could only one trait be used (uni-modal systems) or multiple traits (Bi- or Multi-modal systems). The latter is applied, when systems with a relative high reliability are expected. The main aim of this paper is providing a comprehensive view about biometric and its application. The above mentioned challenges will be analyzed deeply. The suitability of each biometric sensor according to the aimed application will be deeply discussed. Detailed com-parison between uni-modal and Multi-modal biometric system will present which system where to be utilized. Privacy and security issues of biometric systems will be discussed too. Three scenarios of biometric application in home-environment, human-robot-interaction and e-health will be presented.
As smart homes are being more and more popular, the needs of finding assisting systems which interface between users and home environments are growing. Furthermore, for people living in such homes, elderly and disabled people in particular and others in general, it is totally important to develop devices, which can support and aid them in their ordinary daily life. We focused in this work on sustaining privacy issues of the user during a real interaction with the surrounding home environment. A smart person-specific assistant system for services in home environment is proposed. The role of this system is the assisting of persons by controlling home activities and guiding the adaption of Smart-Home-Human interface towards the needs of the considered person. At the same time the system sustains privacy issues of it’s interaction partner. As a special case of medical assisting the system is so implemented, that it provides for elderly or disabled people person-specific medical assistance . The system has the ability of identifying its interaction partner using some biometric features. According to the recognized ID the system, first, adopts towards the needs of recognized person. Second the system represents person-specific list of medicines either visually or auditive. And third the system gives an alarm in the case of taking medicament either later or earlier as normal taking time.
Forschung an Hochschulen
(2015)
In diesem Aufsatz soll die Forschung an Fachhochschulen beispielhaft aus dem Blickwinkel des Instituts Informatik der in 2009 gegründeten Hochschule Ruhr West betrachtet werden. Am Institut Informatik ist es das Ziel Lehre und Forschung geeignet zu verknüpfen, um Studierenden, wissenschaftlichen Mitarbeiterinnen und Mitarbeitern und auch Lehrenden ein attraktives Angebot in Forschung und Lehre im Bereich der Informatik zu liefern. Dabei bilden neben der Durchführung interessanter Lehrveranstaltungen, welche durch aktuelle Forschungsfragestellungen angereichert werden, das kooperative Bearbeiten von gesellschaftlich relevanten und zukunftsweisenden Forschungsaufgaben, die Teilnahme an Forschungsverbünden, bilaterale Forschungsaktivitäten mit Partnern aus der Wirtschaft und das Einwerben von externen Mitteln, die Basis der Arbeit am Institut.
We present a novel approach of distributing small-to mid-scale neural networks onto modern parallel architectures. In this context we discuss the induced challenges and possible solutions. We provide a detailed theoretical analysis with respect to space and time complexities and reinforce our computation model with evaluations which show a performance gain over state of the art approaches.
Object detection systems which operate on large data streams require an efficient scaling with available computation power. We analyze how the use of tile-images can increase the efficiency (i.e. execution speed) of distributed HOG-based object detectors. Furthermore we discuss the challenges of using our developed algorithms in practical large scale scenarios. We show with a structured evaluation that our approach can provide a speed-up of 30-180 % for existing architectures. Due to the its generic formulation it can be applied to a wide range of HOG-based (or similar) algorithms. In this context we also study the effects of applying our method to an existing detector and discuss a scalable strategy for distributing the computation among nodes in a cluster system.
Die Entwicklung von vollautomatisierten Fahrzeugen wird in der gesellschaftlichen Diskussion immer präsenter. Wichtig für die Durchsetzung und verbreitete Nutzung dieser technischer Neuerungen ist jedoch vor allem die Akzeptanz der Bevölkerung – in diesem Fall nicht nur die der potenziellen KäuferInnen sondern auch die der übrigen Verkehrs-teilnehmenden. Vorgestellt wird eine explorative Online-Studie zur Akzeptanz von auto-nomen Fahren basierend auf quantitativen und qualitativen Daten einer Stichprobe von N = 89. Die Ergebnisse zeigen unter anderem eine geringe Vertrautheit mit dem Thema, ein vergleichsweise ausgeprägtes Vertrauen aber eine geringe Nutzungsabsicht.
E-Learning and openness in education are receiving ever increasing attention in businesses as well as in academia. However, these practices have only to small extent been introduced in public administrations. The study addresses this gap by presenting a literature review on Open Educational Resources [OER] and E-Learning in the public sector. The main goal of the article is to identify challenges to open E-Learning in public administrations. Experiences will be conceptualized as barriers which need to be considered when introducing open E-Learning systems and programs in administrations. The main outcome is a systematic review of lessons learned, presented as a contextualized Barrier Framework which is suitable to analyze requirements when introducing E-Learning and OER in public administrations.
Why do barriers to the exchange of open knowledge resources change in public administrations? Experts in the public sector have been interviewed and outlined antecedents of change to certain barriers. The results are an initial step towards theorizing on barrier change and stepping beyond the current trend of categorizing difficulties to e-Learning and use of open knowledge resources. Categorizing only shows the range of potential challenges. Whether and how the barriers change, however, is seldom addressed in previous literature. The results presented in this study thus provide a new perspective on the phenomenon. Results are part of a longitudinal study about open e-Learning in the public sector across four European countries. They will provide fresh empirical input for discussions at the World Conference on E-Learning how to advance future research and practices in the domain
In this paper we present an approach for People-to-People recommendations based on a Rich Context Model (RCM). We consider personal user information as contextual information used for our recommendations. The evaluation of our recommendation approach was performed on a social network of students. The obtained results do show a significant increase in performance while, at the same time, a slight increase in quality in comparison to a manual matching process. The proposed approach is flexible enough to handle different data types of contextual information and easy adaptable to other recommendation domains.