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Starting with the automatic gear change, the operation of a vehicle becomes more and more abstract. In the future, we could control vehicles with single, simple commands. For such a maneuver-based vehicle control system, we investigate a head-up display design in a workshop. The aims are to identify common and distinct features of various display designs through mock-ups. First results show that different sizes of GUI elements are preferred by different states. The preferred position of GUI elements in the head-up display (HUD) is the central bottom area. We found two major interface design styles: static interfaces (all elements visible) with fixed layout and dynamic interfaces (only relevant elements visible) with fixed or adaptive layout.
The virtual classroom continues to grow, but it is becoming more and more the norm, and it is fundamentally different from the vocational students at the Indonesian university. With the promised benefits of the virtual classroom, many challenges and difficulties come in the implementation. Although there are already successful design principles for virtual classrooms that support organizations in overcoming the challenges, the approach to implementing the design principles of virtual classroom at the vocational higher education in Indonesia is still lacking. In this study, we aim to answer the research gap and used the design sciences research by interviewing the lecturers to design the solutions. The proposed design approaches were implemented in a course and evaluated with students from two different groups. Overall, the evaluation of the proposed approaches shows1 significant results as an indicator of the benefits of the implementation of a virtual classroom for vocational students in Indonesia.
Systems for automated image analysis are useful for a variety of tasks and their importance is still growing due to technological advances and an increase of social acceptance. Especially in the field of driver assistance systems the progress in science has reached a level of high performance. Fully or partly autonomously guided vehicles, particularly for road-based traffic, pose high demands on the development of reliable algorithms due to the conditions imposed by natural environments. At the Institut für Neuroinformatik methods for analyzing driving relevant scenes by computer vision are developed in cooperation with several partners from the automobile industry. We introduce a system which extracts the important information from an image taken by a CCD camera installed at the rear view mirror in a car. The approach consists of a sequential and a parallel sensor and information processing. Three main tasks namely the initial segmentation (object detection), the object tracking and the object classification are realized by integration in the sequential branch and by fusion in the parallel branch. The main gain of this approach is given by the integrative coupling of different algorithms providing partly redundant information.
This chapter describes our current research efforts related to the contextualization of learners in mobile learning activities. Substantial research in the field of mobile learning has explored aspects related to contextualized learning scenarios. However, new ways of interpretation and consideration of contextual information of mobile learners are necessary. This chapter provides an overview regarding the state of the art of innovative approaches for supporting contextualization in mobile learning. Additionally, we provide the description of the design and implementation of a flexible multi-dimensional vector space model to organize and process contextual data together with visualization tools for further analysis and interpretation. We also present a study with outcomes and insights on the usage of the contextualization support for mobile learners. To conlcude, we discuss the benefits of using contextualization models for learners in different use-cases. Moreover, a description is presented in order to illustrate how the proposed contextual model can easily be adapted and reused for different use-cases in mobile learning scenarios and potentially other mobile fields.
Massive open online courses (MOOCs) become more and more popular. These course formats are typically highly flexible and attract large groups of learners from heterogeneous backgrounds. So far research in this area concentrating on success factors for low dropout rates and high satisfaction on the side of the learners in MOOCs is scarce. In this chapter, we describe experiences of a large online course offered to students of two large German universities. Based on theory drawn from a social psychological perspective on the relevance of social interaction for learning, we describe the background, structure, and specific elements of the MOOC-like course. We outline evaluation results of both small group collaboration (in workshops) and mass interaction (via forum and wiki usage) as well as results of the general evaluation of the overall course concept. We argue that the specific mixture of small and large group interaction as well as teacher- and learner-generated content is especially promising with regard to satisfaction, learning outcomes, and course completion rates.
Sensing and processing of multimedia information is one of the basic traits of human beings. The development of digital technologies and applications allows the production of huge amounts of multimedia data. The rapidly decreasing prices for hardware such as digital cameras/camcorders, sound cards and the corresponding displays led to wide distribution of multimedia-capable input and output devices in all fields of the everyday life, from home entertainment to companies and educational organisations. Thus, multimedia information in terms of digital pictures, videos, and music can be created intuitively and is affordable for a broad spectrum of users.
NewsGrid
(2005)
Film archives—particularly those storing video material on all kinds of news items—are important information sources for TV stations. Each TV station creates and maintains its own archive by storing video material received via satellite and/or internet on tapes in analogue and/or digital form. It cannot be predicted in advance which of this archived material will actually be used. Thus all material received must be catalogued and stored. On average only a small percentage of the material stored is actually used. Due to the increase in data volumes the cost of maintaining such repositories and retrieving particular stored items has become prohibitive. To-day digital videos are increasingly replacing analogue material. Digital videos offer the advantage that the can be stored in distributed databases and then be transferred without loss of quality to the transmitting station. Such digital archives can be made accessible to many TV stations, thus spreading the maintenance cost. Individual stations can retrieve only the material they actually need for particular news casts. In this paper a grid architecture for distributed video archives for news broadcasts is proposed. A crucial aspect of such a grid approach is that advanced methods for retrieving data must be available.
Coming out of the labs, the first robots are currently appearing on the consumer market. Initially they target rather simple application scenarios ranging from entertainment to home convenience. However, one can expect, that they will capture more complex areas soon. These robots will have a higher and higher level and a broad range of functional competence, and will collaborate and interactively communicate with their human users. All this requires considerable cognitive abilities on the robot’s side and appropriate man-machine interaction technologies. Apart from further development of individual functions and technologies it is crucial to build and evaluate fully integrated systems. This paper describes our approach to construct a robotic assistance system. We present experience with an integrated technology demonstration and the exposure of the integrated system to the public.
The continuous evolution of learning technologies combined with the changes within ubiquitous learning environments in which they operate result in dynamic and complex requirements that are challenging to meet. The fact that these systems evolve over time makes it difficult to adapt to the constant changing requirements. Existing approaches in the field of Technology Enhanced Learning (TEL) are generally not addressing those issues and they fail to adapt to those dynamic situations. In this chapter, we investigate the notion of an adaptive and adaptable architecture as a possible solution to address these challenges. We conduct a literature survey upon the state of the art and state of practice in this area. The outcomes of those efforts result in an initial model of a Domain-specific architecture to tackle the issues of adaptability and adaptiveness. To illustrate these ideas, we provide a number of scenarios where this architecture can be applied or is already applied. Our proposed approach serves as a foundation for addressing future ubiquitous learning applications where new technologies constantly emerge and new requirements evolve.
This chapter describes our research efforts related to the design of mobile learning (m-learning) applications in cloud-computing (CC) environments. Many cloud-based services can be used/integrated in m-learning scenarios, hence, there is a rich source of applications that could easily be applied to design and deploy those within the context of cloud-based services. Here, we present two cloud-based approaches—a flexible framework for an easy generation and deployment of mobile learning applications for teachers, and a flexible contextualization service to support personalized learning environment for mobile learners. The framework provides a flexible approach that supports teachers in designing mobile applications and automatically deploys those in order to allow teachers to create their own m-learning activities supported by mobile devices. The contextualization service is proposed to improve the content delivery of learning objects (LOs). This service allows adapting the learning content and the mobile user interface (UI) to the current context of the user. Together, this leads to a powerful and flexible framework for the provisioning of potentially ad hoc mobile learning scenarios. We provide a description of the design and implementation of two proposed cloud-based approaches together with scenario examples. Furthermore, we discuss the benefits of using flexible and contextualized cloud applications in mobile learning scenarios. Hereby, we contribute to this growing field of research by exploring new ways for designing and using flexible and contextualized cloud-based applications that support m-learning.