Multi-Channel-Learning (MCL)

Lerneinheiten müssen stark variierenden Anforderungen gerecht werden. Neben unterschiedlichen Lerntypen spielen vor allem auch die Umfeldbedingungen eine wesentliche Rolle, in denen Lernprozesse stattfinden. Faktoren wie z. B. die Tagesform führen letztlich dazu, dass nicht einmal für eine einzelne Person konstante Lernpräferenzen herrschen. Mit diesem Beitrag wird vorgeschlagen, zur Lösung des Problems einer Mehrkanalstrategie zu folgen. Allerdings sind spezifische Eigenschaften von Learning-Content-Systemen (LCS) notwendig, um ein sog. Multi-Channel-Learning (MCL) zu ermöglichen. Diese Eigenschaften werden im Beitrag anhand von Informationsmodellen beschrieben werden. Sie sollen als Referenzmodell dienen, das sowohl bei der Entwicklung als auch bei der Auswahl und Anpassung von LCS hilfreich sein kann. Das Referenzmodell wird deduktiv abgeleitet und anhand praktischer Anwendungen geprüft. Vorgestellt werden sowohl Anwendungs- als auch Organisationssysteme, die nach dem Modell realisiert worden sind. Auf dieser Grundlage kann schließlich eine Nutzenabschätzung des Modells für das Multi-Channel-Learnings vorgenommen werden.

Registration of Sub-Sequence and Multi-Camera Reconstructions for Camera Motion Estimation

This paper presents different application scenarios for which the registration of sub-sequence reconstructions or multi-camera reconstructions is essential for successful camera motion estimation and 3D reconstruction from video. The registration is achieved by merging unconnected feature point tracks between the reconstructions. One application is drift removal for sequential camera motion estimation of long sequences. The state-of-the-art in drift removal is to apply a RANSAC approach to find unconnected feature point tracks. In this paper an alternative spectral algorithm for pairwise matching of unconnected feature point tracks is used. It is then shown that the algorithms can be combined and applied to novel scenarios where independent camera motion estimations must be registered into a common global coordinate system. In the first scenario multiple moving cameras, which capture the same scene simultaneously, are registered. A second new scenario occurs in situations where the tracking of feature points during sequential camera motion estimation fails completely, e.g., due to large occluding objects in the foreground, and the unconnected tracks of the independent reconstructions must be merged. In the third scenario image sequences of the same scene, which are captured under different illuminations, are registered. Several experiments with challenging real video sequences demonstrate that the presented techniques work in practice.

Fuzzy Multi-Objective Linear Programming and Simulation Approach to the Development of Valid and Realistic Master Production Schedule

Master production schedule (MPS) plays an important role in an integrated production planning system. It converts the strategic planning defined in a production plan into the tactical operation execution. The MPS is also known as a tool for top management to control over manufacture resources and becomes input of the downstream planning levels such as material requirement planning (MRP) and capacity requirement planning (CRP). Hence, inappropriate decision on the MPS development may lead to infeasible execution, which ultimately causes poor delivery performance. One must ensure that the proposed MPS is valid and realistic for implementation before it is released to real manufacturing system. In practice, where production environment is stochastic in nature, the development of MPS is no longer simple task. The varying processing time, random event such as machine failure is just some of the underlying causes of uncertainty that may be hardly addressed at planning stage so that in the end the valid and realistic MPS is tough to be realized. The MPS creation problem becomes even more sophisticated as decision makers try to consider multi-objectives; minimizing inventory, maximizing customer satisfaction, and maximizing resource utilization. This study attempts to propose a methodology for MPS creation which is able to deal with those obstacles. This approach takes into account uncertainty and makes trade off among conflicting multi-objectives at the same time. It incorporates fuzzy multi-objective linear programming (FMOLP) and discrete event simulation (DES) for MPS development.

OCTAVIS: Optimization Techniques for Multi-GPU Multi-View Rendering

We present a high performance-yet low cost-system for multi-view rendering in virtual reality (VR) applications. In contrast to complex CAVE installations, which are typically driven by one render client per view, we arrange eight displays in an octagon around the viewer to provide a full 360° projection, and we drive these eight displays by a single PC equipped with multiple graphics units (GPUs). In this paper we describe the hardware and software setup, as well as the necessary low-level and high-level optimizations to optimally exploit the parallelism of this multi-GPU multi-view VR system.