ABSTRACT:The LiDAR mapping carried out using gyrocopters provides a relatively cheap alternative for traditional mapping involving airplanes. The costs of the fuel and the overall maintenance are much lower when compared to planes. At the same time the flight kinematics of the gyrocopter makes it an ideal vehicle for corridor mapping. However a limited payload and a strongly limited space prevent using stabilized platforms dedicated for aerial photogrammetry. As the proper stabilization of the laser scanner during the flight is crucial in order to keep the desirable quality of the LiDAR data, it was decided to develop the prototype of the stabilized, ultra-light mapping platform that can meet the restricted requirements of the gyrocopter. The paper starts with the brief discussion of the legal and practical aspects of the LiDAR data quality, dealing mostly with the influence of the flight imperfections on the point pattern and point density. Afterwards the mapping system prototype is characterized, taking into account three main components: stabilized platform, sensors and control. Subsequently first in-flight tests are described. Though the data are still not perfect mostly due to vibrations, the stabilization provides a substantial improvement of their geometry, reducing both roll and pitch deflections.

Transactional Memory (TM) is an approach to concurrency control that aims to make writing parallel programs both effective and simple. The approach is started in non-distributed multiprocessor systems, but is gaining popularity in distributed systems to synchronize tasks at large scales. Efficiency and scalability are often the key issues in TM research, so performance benchmarks are an important part of it. However, while standard TM benchmarks like the STAMP suite and STMBench7 are available and widely accepted, they do not translate well into distributed systems. Hence, the set of benchmarks usable with distributed TM systems is very limited, and must be padded with microbenchmarks, whose simplicity and artificial nature often makes them uninformative or misleading. Therefore, this paper introduces Helenos, a realistic, complex, and comprehensive distributed TM benchmark based on the problem of the Facebook inbox, an application of the Cassandra distributed store.