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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.
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.
We present a light-weight real-time applicable 3D-gesture recognition system on mobile devices for improved Human-Machine Interaction. We utilize time-of-flight data coming from a single sensor and implement the whole gesture recognition pipeline on two different devices outlining the potential of integrating these sensors onto mobile devices. The main components are responsible for cropping the data to the essentials, calculation of meaningful features, training and classifying via neural networks and realizing a GUI on the device. With our system we achieve recognition rates of up to 98% on a 10-gesture set with frame rates reaching 20Hz, more than sufficient for any real-time applications.
We present a publicly available benchmark database for the problem of hand posture recognition from noisy depth data and fused RGB-D data obtained from low-cost time-of-flight (ToF) sensors. The database is the most extensive database of this kind containing over a million data samples (point clouds) recorded from 35 different individuals for ten different static hand postures. This captures a great amount of variance, due to person-related factors, but also scaling, translation and rotation are explicitly represented. Benchmark results achieved with a standard classification algorithm are computed by cross-validation both over samples and persons, the latter implying training on all persons but one and testing on the remaining one. An important result using this database is that cross-validation performance over samples (which is the standard procedure in machine learning) is systematically higher than cross-validation performance over persons, which is to our mind the true application-relevant measure of generalization performance.
Touch versus mid-air gesture interfaces in road scenarios-measuring driver performance degradation
(2016)
We present a study aimed at comparing the degradation of the driver's performance during touch gesture vs mid-air gesture use for infotainment system control. To this end, 17 participants were asked to perform the Lane Change Test. This requires each participant to steer a vehicle in a simulated driving environment while interacting with an infotainment system via touch and mid-air gestures. The decrease in performance is measured as the deviation from an optimal baseline. This study concludes comparable deviations from the baseline for the secondary task of infotainment interaction for both interaction variants. This is significant as all participants are experienced in touch interaction, however have had no experience at all with mid-air gesture interaction, favoring mid-air gestures for the long-term scenario.
Given the success of convolutional neural networks (CNNs) during recent years in numerous object recognition tasks, it seems logical to further extend their applicability to the treatment of three-dimensional data such as point clouds provided by depth sensors. To this end, we present an approach exploiting the CNN’s ability of automated feature generation and combine it with a novel 3D feature computation technique, preserving local information contained in the data. Experiments are conducted on a large data set of 600.000 samples of hand postures obtained via ToF (time-of-flight) sensors from 20 different persons, after an extensive parameter search in order to optimize network structure. Generalization performance, measured by a leave-one-person-out scheme, exceeds that of any other method presented for this specific task, bringing the error for some persons down to 1.5 %.
Checking wind turbines for damage is a common problem for operators of wind parks, as regular inspections are legally required in many countries and prevention is economically viable. While some of the common forms of damage are easily visible on the surface, structural problems can remain invisible for years before they eventually result in catastrophic failure of a rotor blade. Common forms of testing fibre composite parts like ultrasonic testing or X-ray tests are impractical due to the large dimensions of wind turbine components and their limited accessibility for any short-range methods. Active thermographic inspection of wind turbines is a promising approach to testing for structural flaws beneath the surface of rotor blades. As part of an ongoing research project, a setup for testing the general viability of this method was built and used to compare different thermographic cameras. A sample cut from a discarded rotor blade was modified to emulate structural damage. The results are promising for the development of a cost effective on-site testing system.
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.
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
We present a system for 3D hand gesture recognition based on low-cost time-of-flight(ToF) sensors intended for outdoor use in automotive human-machine interaction. As signal quality is impaired compared to Kinect-type sensors, we study several ways to improve performance when a large number of gesture classes is involved. Our system fuses data coming from two ToF sensors which is used to build up a large database and subsequently train a multilayer perceptron (MLP). We demonstrate that we are able to reliably classify a set of ten hand gestures in real-time and describe the setup of the system, the utilised methods as well as possible application scenarios.
PROPRE is a generic and modular neural learning paradigm that autonomously extracts meaningful concepts of multimodal data flows driven by predictability across modalities in an unsupervised, incremental and online way. For that purpose, PROPRE consists of the combination of projection and prediction. Firstly, each data flow is topologically projected with a self-organizing map, largely inspired from the Kohonen model. Secondly, each projection is predicted by each other map activities, by mean of linear regressions. The main originality of PROPRE is the use of a simple and generic predictability measure that compares predicted and real activities for each modal stream. This measure drives the corresponding projection learning to favor the mapping of predictable stimuli across modalities at the system level (i.e. that their predictability measure overcomes some threshold). This predictability measure acts as a self-evaluation module that tends to bias the representations extracted by the system so that to improve their correlations across modalities. We already showed that this modulation mechanism is able to bootstrap representation extraction from previously learned representations with artificial multimodal data related to basic robotic behaviors [1] and improves performance of the system for classification of visual data within a supervised learning context [2]. In this article, we improve the self-evaluation module of PROPRE, by introducing a sliding threshold, and apply it to the unsupervised classification of gestures caught from two time-of-flight (ToF) cameras. In this context, we illustrate that the modulation mechanism is still useful although less efficient than purely supervised learning.
Mobile devices are nowadays used almost ubiquitously by a large number of users. 2013 was the first year in which the number of sold mobile devices (tablet computers and mobile phones) outperformed the number of PCs’ sold. And this trend seems to be continuing in the coming years. Additionally, the scenarios in which these kinds of devices are used, grow almost day by day. Another trend in modern landscapes is the idea of Cloud Computing, that basically allows for a very flexible provision of computational services to customers. Yet, these two trends are not well connected. Of course there exists already quite a large amount of mobile applications (apps) that utilize Cloud Computing based services. The other way round, that mobile devices provide one of the building blocks for the provision of Cloud Computing based services is not well established yet. Therefore, this paper concentrates on an extension of a technology that allows to provide standardized Web Services, as one of the building blocks for Cloud Computing, on mobile devices. The extension hereby consists of a new approach that now also allows to provide asynchronous Web Services on mobile devices, in contrast to synchronous ones. Additionally, this paper also illustrates how the described technology was already used in an app provided by a business partner.
This paper describes the design and development stages of a web-based framework, aiming to support the creation of mobile applications within the context of mobile learning. The suggested approach offers the opportunity to deploy and execute these applications on mobile devices. This web-based solution additionally offers the possibility to visualize the data collected by the mobile applications in a web-browser. Despite previous research efforts carried out in this domain, few of the projects have addressed these processes from a purely web-based perspective. Currently, a prototype of an authoring tool for creating mobile data collection applications is already implemented. In order to integrate and validate this solution in everyday educational settings, we are collaborating with a network of high schools. On the basis of workshops with teachers we will carry out, refinements and requirements for further enhancements will be collected and will be used to guide our coming efforts.
Recommender systems have become an important application domain related to the development of personalized mobile services. Thus, various recommender mechanisms have been developed for filtering and delivering relevant information to mobile users. This paper presents a rich context model to provide the relevant content of news to the current context of mobile users. The proposed rich context model allows not only providing relevant news with respect to the user’s current context but, at the same time, also determines a convenient representation format of news suitable for mobile devices.
In recent years, teachers have started to conduct pedagogical activities to promote different kinds of learning interactions supported by rich media. The deployment of such activities is rapidly increasing, as teachers and students own technological means that allow supporting them along such interactions. These activities can be carried out in traditional classroom settings while using regular computers. Additionally, they can also be conducted from anywhere at any time while using smartphones and tablets. In this paper, we describe a pedagogical activity requiring students to author and later peer- assess learning interactions
incorporated to videos in YouTube. We describe EDU.Tube, an environment that enables them to create, share and consume such rich media learning activities across a variety of devices. We then detail a plan for the implementation of an activity that took place in 3 different classes dealing with diverse materials addressing computer science related topics. Finally, we also
provide an evaluation presenting students' insights and feedbacks resulting from the experienced activity. We discuss and analyze these outcomes in order to elaborate on them as concerns that could be applied for the further deployment of the EDU.Tube environment.
This paper presents a web-based framework that allows the creation and deployment of mobile learning activities. We present an authoring tool that allows not-technically skilled persons to design mobile learning tasks and deploy them as a web-based mobile application. Since the presented approach is based exclusively on web-technologies, the deployed mobile application can be executed via a mobile browser and therefore is platform independent. Despite previous research efforts carried out in this domain, few of the projects have addressed this course of actions from a purely web-based perspective. Through the latest development of web technologies, mobile applications have access to internal sensors like camera, microphone and GPS and therefore allow data collection within web-applications. In order to validate whether the proposed framework can be applied in educational settings, we conducted a pilot study with experienced teachers and present the results of these efforts in this paper.
With the introduction of Apple’s iPhone, gesture control became pop-
ular and was perceived as an intuitive means of interaction. Contact-
less gestures received broad attention with the X-Box Kinect.
Current technology is limited to a small number of uses, mainly
in entertainment systems. The target of this project is to increase the
range of possible applications, e.g. to the field of automotive,
industrial applications (manufacturing plants), assisted living in con-
texts ranging from private households to hospitals (interaction for
people with disabilities) and many more.
With a rapidly ageing population, it is increasingly important to de-
velop devices for elderly and disabled people that can support and aid
them in their daily lives, helping them to live at home as long as pos-
sible. The goal of this project is to implement a human-machine inter-
action and assistance system that can offer personalised health sup-
port for elderly people, or for those who have special needs in the
home environment.
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 elderly and disabled people living in such homes it is totally important to develop devices, which can support and aid them in their ordinary daily life. This demands means and tools that extend independent living and promote improved health. In this work we reviewed the state of the art in the assistant systems in home environments. A case study of medical assisting system for elderly and people with disabilities is discussed deeply. A smart nfc-based person-specific assistant system for services in home environment is proposed. The role of this system is the assisting by controlling of home activities and adaption of home-human interface towards the needs of the considered person. For the special case of medical assisting the system has the ability of providing 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 medicaments either visually, on screen, or acoustic, speaker. And third the system gives an alarm in the case of taking medicament either later or earlier as normal taking time.
In the context of existing approaches to cluster computing we present a newly developed modular framework `SimpleHydra' for rapid deployment and management of Beowulf clusters. Instead of focusing only the pure computation tasks on homogeneous clusters (i.e. clusters with identically set up nodes), this framework aims to ease the configuration of heterogeneous clusters and to provide a low-level / high-level object-oriented API for low-latency distributed computing. Our framework does not make any restrictions regarding the hardware and minimizes the use of external libraries to the case of special modules. In addition to that our framework enables the user to develop highly dynamic cluster topologies. We describe the framework's general structure as well as time critical elements, give application examples in the `Big-Data' context during a research project and briefly discuss additional features. Furthermore we give a thorough theoretical time/space complexity analysis of our implemented methods and general approaches.
In this paper, we describe an efficient method for a fast people re-identification based on models of human clothes. An initial model is estimated during people detection and tracking, which will be refined during the re-identification. This stepwise extraction, combination and comparing of features speeds up the whole re-identification. For the refining, several saliency maps are used to extract individual features. These individual features are located separately for any human body part. The body parts are located with an optimized GPU-based HOG detector. Furthermore, we introduce a meanshift-based fusion concept which utilizes multiple detectors in order to increase the detection reliability.
Currently in home environments, robot assisting systems with emotion understanding ability are generally achieved in two several manners. The first is the implementing of such systems in such a way that they offer general services for all considered persons without considering privacy, special needs of their interaction partners. The second way is the targetting of such systems for merely one person. In this work we present a robot assisting system, which has both the abilities of assisting several persons at the same time and sustaining their privacy and security issues. The robot can interact with it's interaction partner emotionally by analyzing the emotions of her expressed either visually, facial expression, or auditive, speech prosody. The role of this system is the providing of person-specific support in home environment. In order to identify its interaction partner the system uses diverse biometric traits. According to the recognized ID the system, first, adopts towards the needs of recognized person. Second the system loads the corresponding emotional profile of the detected interaction partner in order to practice a person-specific emotional human-robot interaction, which has an advantage over the person independent interaction.
One of the technical building blocks of Cloud Computing infrastructures are Web Services. With respect to mobile devices their role as Web Service consumers is widely accepted and today a large number of mobile applications already consume Web Services in order to fulfill their task. Still, not much research is conducted, as yet, to allow deploying Web Services on mobile devices and thus uses these kinds of devices as Web Service providers. This paper presents an analysis of one already implemented approach for provisioning mobile Web Services with respect to energy/battery consumption. Here, after shortly presenting the implementation for the provisioning of mobile Web Services an evaluation of the battery consumption that results in using the approach is presented. Last but not least, an improvement with respect to the battery consumption is presented. The performance test shows that the improved approach provides a reasonable way to introduce Web Service provisioning for mobile devices.
The development of web based applications gained enormous interests in recent years. Most of formerly desktop based applications nowadays provide at least a web based version or are completely re-implemented as web based applications. Nevertheless, from the development point of view, there are still a lot of strategies for the development of web based applications borrowed from the development strategies for desktop applications. Therefore, this paper concentrates on the description of an approach that allows to re-use a from the development of desktop applications well-known Design Pattern with a distinct enhancement for web based applications.
Mobile devices, in the form of smartphones, are endowed with rich capabilities in terms of multimedia, sensors and connectivity. The wide adoption of these devices allows using them across different settings and situations. One area in which mobile devices become more and more prominent is within the field of mobile learning. Here, mobile devices provide rich possibilities for the contextualization of the learner, by using the set of sensors available in the device. On the one hand, the usage of mobile devices enables participation in learning activities independent of time and space. Nevertheless, developing mobile learning applications for the heterogeneity of mobile devices available in the market becomes a challenge. Not only this is a problem related to form factor aspects, but also the large number of different operating systems, platforms and app infrastructures (app stores) are aspects to be considered. In this paper we present our initial efforts with regard to the development of cross-platform mobile applications to support the contextualization of learning content.
The mathematical competence of first year students is an important success factor at least for technical studies. As a significant percentage of students do not have sufficient mathematical skills, universities often utilise blended learning courses to increase these skills prior to the start of studies. Due to the diversity of students and their educational backgrounds, individual strategies are needed to achieve the necessary competence for successfully managing their studies. This paper describes our approach at the University of Applied Sciences Ruhr West, where we are using personalized blended learning concepts based on the measurement of individual mathematical competences at the beginning of a coaching process. This is used to gain a better matching between the individual learner level and the adapted learning concepts. We combine individual presence learning groups and a personalized e-learning environment. This environment is adapted based on mathematical skills of each stud ent. It uses individual learning advices, short-term optical feedback and up to date e-learning material in a Moodle-based LMS (learning management system). The coaching concept is approved by the results of summative and formative evaluations.
Durch Anpassung der Mathematik-Qualifizierungsmaßnahmen in der Studieneingangsphase an die einzelnen Kompetenzen der Studienanfängerinnen und Studienanfänger wird die individuelle Passgenauigkeit der Maßnahmen erhöht und ein hoher Lernfortschritt erzielt. Dies führt zu einer wesentlichen Verbesserung der
Eingangsqualifikation im Bereich der Mathematik und zu einer Homogenisierung der Leistungsfähigkeit von
Studierenden
The term “Cloud Computing” does not primarily specify new types of core technologies but rather addresses features to do with integration, inter-operability and accessibility. Although not new, virtualization and automation are cor features that characterize Cloud Computing. In this paper, we intend to explore the possibility of integrating cloud services with educational scenarios without re-defining neither the technology nor the usage scenarios from scratch. Our suggestion is based on certain solutions that have already been implemented and tested for specific cases.
Design and Evaluation of a Platform Independent Application for Mobile Access of Moodle Quizzes
(2013)
The use of Web Services in modern software development is widely accepted and provides (integrated in an according architecture) a fast, flexible and scalable way for the implementation of modern software products. On the other hand, the development of mobile applications, so called apps, becomes more and more important. While using Web Services also from mobile devices is an already accepted scheme in the development of mobile apps, there is not much work done yet for providing Web Services on mobile devices. Therefore, this paper presents a new perspective to Web Services that could be run on mobile devices and, by this, become mobile Web Services.
One of the most stressing challenges in our culture is the demographic change. On the one hand, people become older and older, at the same time less young people are available in order to support the elderly. Currently, this fact already provides a number of social impacts that need to be solved in the near future. This paper concentrates on the integration of mobile devices in scenarios that allow elderly people to age successfully. Here, the term "aging successfully" refers to broad range of aspects from health to social life of elderly people. A special focus of this paper lies in the question whether services deployed to a mobile device provide advantages in the area of aging successfully. In order to answer this question, both technical challenges are explained and solved by example architectures, and scenarios that benefit from services deployed to mobile devices are explained.
In jedem Unternehmen gibt es Stellen, an denen es nicht rund läuft. In manchen Organisationseinheiten ist Sand im Getriebe, es knirscht und knackt – schon bereits bei der Zusammenarbeit mit anderen Abteilungen. Was kann man tun?
Eine Möglichkeit besteht darin, ein großes Veränderungsprojekt aufzusetzen und alle Mitarbeiter und Führungskräfte ins kalte Wasser zu werfen.
Doch viele dieser großen Veränderungsprojekte scheitern. Hauptgrund ist, dass Führungskräfte von der Notwendigkeit der Änderungen nicht überzeugt sind.
Die Autoren dieses Buchs haben daher einen anderen Ansatz entwickelt:
Veränderung ja, aber in kleinen, nachhaltigen Schritten. In einem solchen kontinuierlichen Veränderungsprozess geht es darum, nach und nach stabil laufende Prozesse einzuführen bzw. bestehende Prozesse zu optimieren. Mit dieser Methode wird die Akzeptanz der Mitarbeiter erreicht. Sie bietet Führungskräften die Möglichkeit, Veränderungen und Prozesse mitzugestalten und sich im Rahmen ihrer Linienverantwortung gezielt einzubringen.
Pedestrian movement analysis at airports - videobased analysis across multiple camera systems
(2013)
Die Entwicklung des automobilen HMI verläuft in immer kürzer werdenden Zyklen. Nichtsdestoweniger läßt sich kaum erahnen, inwieweit sich die Zukunft automobilen HMIs darstellen wird. Im Rahmen eines Experten-Workshops wurden verschiedene zukünftige Szenarien in 5, 10 und 20 Jahren auf Basis von Cockpitskizzen bearbeitet. Als Hilfestellung dienten hierbei drei unterschiedliche Personas, basierend auf verschiedenen prototypischen Kunden.
Das Automobil wird weltweit von verschiedensten Nutzergruppen in Anspruch genommen. Die Notwendigkeit der Anpassung der Benutzerschnittstelle ergibt sich für Automobilhersteller, die weite Kundenkreise erschließen möchten. Dies zielt zum einen auf ältere Autofahrer, aber auch auf Anpassungen, die für andere Märkte nötig sind. Nicht zu vergessen ist auch der generelle Wunsch von Kunden, die Benutzerschnittstelle im Fahrzeug an die eigenen Vorlieben anzupassen. Diese Herausforderungen werden im folgenden erörtert.
One of the latest hypes in IT is the well-known Cloud
Computing paradigm. This paradigm that showed up in recent years
is a paradigm for the dynamic usage of computational power, memory and other computational resources. With respect to hypes, the author strongly believes that the
Cloud Computing paradigm has the potential to survive the hype and to become a usual technology used for the provision of IT based services. Therefore, it will be necessary to deploy Cloud Computing based infrastructures in a professional, stable and reliable way. This would lead to the idea that the Cloud Computing paradigm needs to be concerned with respect to IT Service Management, since cloud based infrastructures have to be managed differently in comparison to a usual infrastructure. This paper discusses, based on the IT Infrastructure Library (ITIL), as the de-facto standard for IT Service Management, whether this de-facto standard might also be able to manage Cloud Computing based infrastructures, how the according processes might change and whether ITIL supports a division of labor between the customer and the service provider
of a Cloud Computing based infrastructure.
The role of mobile devices as Web Service consumers is widely accepted and a large number of mobile applications already consumes Web Services in order to fullfill their task. Nevertheless, the growing number of powerful mobile devices, e.g. mobile phones, tablets even raise the question whether these devices can not only be used as Web Service consumers but at the same time also as Web Service providers. Therefore, this paper presents an approach that allows to deploy Web Services on mobile devices by the usage of the well-known protocols and standards, e.g. SOAP/REST and WSDL.
Collaboration and Technology
(2012)
This book constitutes the proceedings of the 18th Collaboration Researchers' International Working Group Conference on Collaboration and Technology, held in Raesfeld, Germany, in September 2012. The 9 revised papers presented together with 12 short papers were carefully reviewed and selected from numerous submissions. They are grouped into five themes that represent collaborative learning, social media analytics, conceptual and design models, formal modeling and technical approaches and collaboration support in emergency scenarios.
Applications and research efforts in Mobile Learning constitute a growing field in the area of Technology Enhanced Learning. However, despite a permanent increase of mobile internet accessibility and availability of mobile devices over the past years, a mobile learning environment that is easy to use, widely accepted by teachers and learners, uses widespread off-the-shelf software, and that covers various application scenarios and mobile devices, is not yet available. In this paper, we address this issue by presenting an approach and technical framework called "Mobile Contributions" ("MoCo"). MoCo supports learners to create and send contributions through various channels (including third-party solutions like Twitter, SMS and Facebook), which are collected and stored in a central repository for processing, filtering and visualization on a shared display. A set of different learning and teaching scenarios that can be realized with MoCo are described along with first experiences and insights gained from qualitative and quantitative evaluation.
Das Studienbuch gibt einen praxisorientierten Einstieg in die Thematik des E-Learnings. Neben Grundlagenkenntnissen werden die Funktionen von Learning-Management.Systemen diskutiert und praxisnah am Beispiel Moodle vertieft. In weiteren Kapiteln wird auf die Administration und den Aufbau von E-Learning-Kursen eingegangen. Neben der Vorstellung unterschiedlicher Contentformen liegt der Schwerpunkt hierbei auf der systematischen Vorgehensweise zur Erstellung. Abschließend werden Möglichkeiten behandelt, die mobile Endgeräte heute zum Lernen bieten.
Zahlreiche praktische Übungen mit Musterlösungen begleiten den Text und erleichtern das Selbststudium. Wiederholungsfragen am Ende jedes Kapitels dienen der Vertiefung des Erlernten.
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.
In this paper we describe a session management system for setting up various collabora- tive classroom ,scenarios. The approach ,is addressing the additional workload ,of administrating classroom networks on the teacher, which is an important aspect for teachers' willingness to im- plement technology enhanced,learning in schools. The system facilitates preparation of classroom scenarios and the adhoc installation of networked collaborative sessions. We provided a graphical interface, which is usable for administration, monitoring, and for specification of a wide variety of different classroom ,situations with group work. The resulting graphical specifications are well suited to be re-used in the more formal learning design format IMS/LD; this is achieved by a auto- matable transformation of the scenarios to LD documents. Keywords: Collaborative classroom scenarios, lightweight classroom orchestration, learning de- sign, shared workspaces.
Das übergeordnete Forschungsgebiet, in das sich die vorliegende Arbeit einbettet, befasst sich mit der Erforschung von informationsverabeitenden Prozessen im Gehirn und der Anwendung der resultierenden Erkenntnisse auf technische Systeme. In Analogie zu biologischen Systemen, deren Beschaffenheit aus den Anforderungen der Umwelt an ihr Verhalten resultiert, leitet sich die Anthropomorphie als Entwurfsprinzip für die Struktur des mit den Menschen interagierenden robotischen Assistenzsystemen ab. Der Autor behandelt in der vorliegende Arbeit das Problem der Erzeugung von Motorverhalten im dreidimensionalen Raum am Beispiel eines anthropomorphen Roboterarmes in einem anthropomorphen robotischen Assistenzsystem. Entwickelt wurde hierbei ein allgemeiner Ansatz, der die Konzepte der Erzeugung von Motorverhalten im 3D-Raum, der Voraussimulation dynamischer Systeme zur Systemdiagnose und zur Suche gewünschter Systemzustände, sowie ein Konzept der Organisation von Verhalten enthält und vereinigt. Nichtlineare dynamische Systeme bilden das mathematische Fundament, die einheitlich, formale Sprache des Ansatzes, mit der sowohl das Motorverhalten des Roboters als auch dessen zeitkontinuierliche Teilsysteme rückgekoppelt werden.
Auf gute Zusammenarbeit
(2008)
In diesem Artikel wird eine flexible Architektur vorgestellt, mit deren Hilfe eine modulare Lösung von Fahrerassistenzaufgaben in Kraftfahrzeugen gezeigt werden kann. Es wird eine Objektbezogene Analyse von Sensordaten, eine Verhaltensbasierte Szeneninterpretation und eine Verhaltensplanung vorgestellt. Eine globale Wissensbasis, auf der jedes einzelne Modul arbeitet, beinhaltet die Beschreibung physikalischer Zusammenhänge, Verhaltensregeln für den Straßenverkehr, sowie Objekt- und Szenenwissen. Externes Wissen (z.B. GPS - Global Positioning System) kann ebenfalls in die Wissensbasis eingebunden werden. Als Anwendungsbeispiel der Verhaltensplanung wird ein intelligenter Tempomat vorgestellt.
To reduce the number of traffic accidents and to increase the drivers comfort, the thought of designing driver assistance systems rose in the past years. Principal problems are caused by having a moving observer (ego motion) in predominantly natural surroundings. In this paper we present a solution for a flexible architecture for a driver assistance system. The architecture can be subdivided into four different parts: the object-related analysis, the knowledge base, the behavior-based scene interpretation, and the behavior planning unit. The object-related analysis is fed with data by the sensors (e.g., vision, radar). The sensor data are preprocessed (flexible sensor fusion) and evaluated (saliency map) searching for object-related information (positions, types of objects, etc.). The knowledge base is represented by static and dynamic knowledge. It consists of a set of rules (e.g. , traffic rules, physical laws), additional information (i.e., GPS, lane-information) and it is implicitly used by algorithms in the system. The scene interpretation combines the information extracted by the object related analysis and inspects the information for contradictions. It is strongly connected to the behavior planning using only information needed for the actual task. In the scene interpretation consistent representations (i.e., bird's eye view) are organized and interpreted as well as a scene analysis is performed. The results of the scene interpretation are used for decision making in behavior planning, which is controlled by the actual task. The influence of behavior planning on the behavior of the guided vehicle is limited to advices as no mechanical control (e.g. , control of the steering angle) was implemented. An Intelligent Cruise Control (ICC) is shown as a spin-off for using this architecture.
The scene interpretation and the behavior planning of a vehicle in real world traffic is a difficult problem to be solved. If different hierarchies of tasks and purposes are built to structure the behavior of a driver, complex systems can be designed. But finally behavior planning in vehicles can only influence the controlled variables: steering, angle and velocity. In this paper a scene interpretation and a behavior planning for a driver assistance system aiming on cruise control is proposed. In this system the controlled variables are determined by an evaluation of the dynamics of a two-dimensional neural field for scene interpretation and two one-dimensional neural fields controlling steering angle and velocity. The stimuli of the fields are determined according to the sensor information.
Systems for automated image analysis are useful for a variety of tasks. Their importance is still growing due to technological advances and increased social acceptance. Especially driver assistance systems have reached a high level of sophistication. Fully or partly autonomously guided vehicles, particularly for road traffic, require highly reliable algorithms due to the conditions imposed by natural environments. At the Institut fur Neuroinformatik, methods for analyzing driving relevant scenes by computer vision are developed in cooperation with several partners from the automobile industry. We present a system extracting important information from an image taken by a CCD camera installed at the rear-view mirror in a car. The approach is divided into a sequential and a parallel phase of sensor and information processing. Three main tasks, namely initial segmentation (object detection), object tracking and object classification are realized by integration in the sequential phase and by fusion in the parallel phase. The main advantage of this approach is integrative coupling of different algorithms providing partly redundant information. q 2000 Elsevier Science B.V. All rights reserved.
The influence of national culture on knowledge sharing has important implications for all organizations. However, the existing frameworks only cover a subset of relevant factors or limit the research of the framework to either organizational or national level. Hence, a more encompassing framework is needed. The question this articles answers is how does national culture influence knowledge sharing. Based on extensive literature review and interviews carried out in Finland and Japan, this article sets forth a foundation for a new framework. The framework details how national culture influences individual level and organizational level factors and technical tools. Additionally, the framework includes a new dimension, time-dimension, which is usually disregarded in knowledge sharing research. For researchers and practitioners, the derived framework provides key insight on relevant factors on knowledge sharing and national culture. Finally, future research directions are discussed.
Group-centered framework towards a positive design of digital collaboration in global settings
(2017)
Globally distributed groups require collaborative systems to support their work. Besides being able to support the teamwork, these systems also should promote well-being and maximize the human potential that leads to an engaging system and joyful experience. Designing such system is a significant challenge and requires a thorough understanding of group work. We used the field theory as a lens to view the essential aspects of group motivation and then utilized collaboration personas to analyze the elements of group work. We integrated well-being determinants as engagement factors to develop a group-centered framework for digital collaboration in a global setting. Based on the outcomes, we proposed a conceptual framework to design an engaging collaborative system and recommend system values that can be used to evaluate the system further.
Wissensmanagement (WM) und IT-gestütztes Lernen sind gerade in kleinen Behörden der Öffentlichen Verwaltung (ÖV), wie z.B. in ländlichen
Gemeinden, noch ausbaufähig. Am Beispiel des EU-Projekts EAGLE werden
Projektergebnisse als Verbesserungsansätze für ein arbeitsprozessorientiertes, IT-gestütztes Lernen vorgestellt. Neuartige Plattform-Features und ihr ÖV-spezifischer Nutzen werden erläutert. Die Ergebnisse der Plattformvalidierung werden vorgestellt. Ferner werden Vorschläge gemacht, wie die Ergebnisse aus EAGLE mit WM und weiteren Wissensquellen der ÖV, wie z.B. der Registratur, zu einem Gesamtkonzept mit bereits vorhandenen Fortbildungs- und WM-Ansätzen verbunden werden können.
Simulated reality environment incorporating humans and physically plausible behaving robots, providing natural interaction channels, with the option to link simulator to real perception and motion, is gaining importance for the development of cognitive, intuitive interacting and collaborating robotic systems. In the present work we introduce a head tracking system which is utilized to incorporate human ego motion in simulated environment improving immersion in the context of human-robot collaborative tasks.
Autonomous robots with limited computational capacity call for control approaches that generate meaningful, goal-directed behavior without using a large amount of resources. The attractor dynamics approach to movement generation is a framework that links sensor data to motor commands via coupled dynamical systems that have attractors at behaviorally desired states. The low computational demands leave enough system resources for higher level function like forming a sequence of local goals to reach a distant one. The comparatively high performance of local behavior generation allows the global planning to be relatively simple. In the present paper, we apply this approach to generate walking trajectories for a small humanoid robot, the Aldebaran Nao, that are goal-directed and avoid obstacles. The sensor information is a single camera in the head of the robot. The limited field of vision is compensated by head movements. The design of the dynamical system for motion generation and the choice of state variable makes a computationally expensive scene representation or local map building unnecessary.
Detection of influential actors in social media plays an important role for increasing the quality and efficiency of work and services in many fields such as education, marketing, etc. This work aims to introduce a new approach for the characterization of influential actors in online social media, such as Twitter. We present on a model of influence of an actor that is based on the attractiveness of the actor in terms of the number of other new actors with which he or she has established relations over time. We have used this concept and measure of influence to determine optimal seeds in a simulation of influence maximization using two empirically collected social networks for the underlying graphs.
Industry 4.0 is known as the fourth industrial revolution which refers to the integration of technologies that make the factories interoperable by seamlessly connecting machines, employees and sensors for communication. In Industry 4.0, one of the key features is the use of new technologies to recognize the current context. Thus, the employees are supported with contextual information for speeding up decision-making during various processes related to planning, production, maintenance, etc. As a contribution to this area, the work described here aims to introduce a cyber-physical system (CPS) approach to provide context-based and intelligent support to employees in heavy industries using new technologies, especially in the field of mobile devices. In this work, mobile device sensors and image processing techniques are used to recognize the context which requires specific support. In addition, new scenarios and associated processes are developed to support the employees on the basis of new, flexible, adaptive and mobile technologies.
To enable a robotic assistant to autonomously reach for and transport objects while avoiding obstacles we have generalized the attractor dynamics approach established for vehicles to trajectory formation in robot arms. This approach is able to deal with the time-varying environments that occur when a human operator moves in a shared workspace. Stable fixed points (attractors) for the heading direction of the end-effector shift during movement and are being tracked by the system. This enables the attractor dynamics approach to avoid the spurious states that hamper potential field methods. Separating planning and control computationally, the approach is also simpler to implement. The stability properties of the movement plan make it possible to deal with fluctuating and imprecise sensory information. We implement this approach on a seven degree of freedom anthropomorphic arm reaching for objects on a working surface. We use an exact solution of the inverse kinematics, which enables us to steer the spatial position of the elbow clear of obstacles. The straight-line trajectories of the end-effector that emerge as long as the arm is far from obstacles make the movement goals of the robotic assistant predictable for the human operator, improving man-machine interaction
For any kind of assistant systems, the ability to interact with the human operator and taking into account his or her assumptions and expectations, is the basis for a reasonable behavior. As a consequence the human behavior have to be studied in order to generate driver models that are learned from human driving data. In this work we focus on the improvement of the immersion in driving simulation environment by developing and implementing a cheap and efficient method for head tracking. We also explain why head tracking feedback is crucial for the quality of collected behavioural data, especially for simulators with close screen distances.
In this paper we present an approach for contextual big data analytics in social networks, particularly in Twitter. The combination of a Rich Context Model (RCM) with machine learning is used in order to improve the quality of the data mining techniques. We propose the algorithm and architecture of our approach for real-time contextual analysis of tweets. The proposed approach can be used to enrich and empower the predictive analytics or to provide relevant context-aware recommendations.
Die transurethrale Resektion der Prostata (TUR-P) ist der Gold Standard für die endoskopisch-chirurgische Behandlung der Benignen Prostatahyperplasie (BPH). Unbekannt ist jedoch, ob bei der bipolaren TUR-P die Möglichkeit von elektrothermischen Verletzung von benachbar-
tem nichtopertiertem Gewebe besteht. Grund hierfür könnten höhere Ausgangsleistungen der Chirurgie-Generatoren sein. Deshalb werden experimentell gemessene Werte der räumlichen Verlustleistungsdichte um ein bipolares Resektoskop als Quellterm für die Berechnung der Temperaturänderung im operationsnahen Gewebe verwendet. Die Temperaturberechnung basiert auf der numerischen Lösung der Wärmeleitungsgleichung nach Penne. Für die gewählten Randbedingungen und Eingabeparameter sind keine signifikanten Temperaturerhöhungen im Berechnungsgebiet am proximalen Ende des Resektoskop-Schaftes festzustellen. Um ein umfassendes Verständnis zu gewinnen sollen weiterführende Untersuchungen mit einer Variation der Randbedingungen und Eingabeparameter durchgeführt werden.
The term “Cloud Computing” does not primarily specify new types of core technologies but rather addresses features to do with integration, interoperability and accessibility. Although not new, virtualization and automation are core features that characterize Cloud Computing. In this paper, we intend to explore the possibility of integrating cloud services with educational scenarios without re-defining neither the technology nor the usage scenarios from scratch. Our suggestion is based on certain solutions that have already been implemented and tested for specific cases.
It is common to have a large noise and/or a strong interference around the frequency band of a Power Line Communication (PLC) system due to the fact that the PLC channel is not designed for communication. If there are no efficient operations at the receiver to suppress this out-of-band noise and interference to some extent, the Signal-to-Noise Ratio (SNR) will decrease and system will suffer performance loss consequently. Normally, the effort of Analog Front End (AFE) on the suppression of out-of-band interference is finite and it is uneconomic to change the AFE structure to make a performance improvement. Therefore, an appropriate structure of Digital Front End (DFE) at the receiver is necessary to reduce the impact of out-of-band noise and interference furthermore. In this paper, three different kinds of DFE structure at the receiver are introduced: classic DFE, time domain Nyquist windowing and Equivalent Complex Baseband (ECB) approach. The performance of these DFE structures is compared, not only from the aspect of out-of-band suppression, but also from the system overhead they need.