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Geographic cluster based routing in ad-hoc wireless sensor networks is a current field of research. Various algorithms to route in wireless ad-hoc networks based on position information already exist. Among them algorithms that use the traditional beaconing approach as well as algorithms that work beaconless (no information about the environment is required besides the own position and the destination). Geographic cluster based routing with guaranteed message delivery can be carried out on overlay graphs as well. Until now the required planar overlay graphs are not being constructed reactively.
This thesis proposes a reactive algorithm, the Beaconless Cluster Based Planarization (BCBP) algorithm, which constructs a planar overlay graph and noticeably reduces the number of messages required for that. Based on an algorithm for cluster based planarization it beaconlessly constructs a planar overlay graph in an unit disk graph (UDG). An UDG is a model for a wireless network in which every participant has the same sending radius. Evaluation of the algorithm shows it to be more efficient than the non beaconless variant. Another result of this thesis is the Beaconless LLRAP (BLLRAP) algorithm, for which planarity but not continued connectivity could be proven.
Motion capture refers to the process of capturing, processing and trans- lating real motions onto a 3D model. Not only in the movie and gaming industries, motion capture creates an indispensable realism of human and animal movement. Also in the context of robotics, medical movement therapy, as well as in AR and VR, motion capture is used extensively. In addition to the well established optical processes, especially in the last three areas, alternative systems based on inertial navigation (IMUs) are being used in-creasingly, because they do not rely on external cameras and thus limit the area of movement considerably less.
Fast evolving technical progress in the manufacturing of such IMUs allows building small sensors, wearable on the body which can transfer movements to a computer. The development of applying inertial systems to a motion capture context, however, is still at an early state. Problems like drift can currently only be minimized by adding additional hardware for correcting the read data.
In the following master thesis an IMU based motion capture system is designed and constructed. This contains the assembly of the hardware components as well as processing of the received movement data on the software side and their application to a 3D model.
Using semantic data from general-purpose programming languages does not provide the unified experience one would want for such an application. Static error checking is lacking, especially with regards to static typing of the data. Based on the previous work of λ-DL, which integrates semantic queries and concepts as types into a typed λ-calculus, this work takes its ideas a step further to meld them into a real-world programming language. This thesis explores how λ-DL's features can be extended and integrated into an existing language, researches an appropriate extension mechanism and produces Semantics4J, a JastAdd-based Java language semantic data extension for type-safe OWL programming, together with examples of its usage.