Did the Japanese Patient Follow the Doctor's Orders? Mostly no! A Public Choice Analysis of Greenhouse Gas Emissions Trading Schemes in Japan before and after the Earthquake

The Great Tôhoku-Earthquake and the following nuclear meltdown in Fukushima called the world’s attention to Japans’ energy and climate policy. Japan is one of the biggest emitters of greenhouses gases in the world and still far away from reaching its Kyoto target. Emissions trading systems have been used in Japanese climate policy since 2005. However, experiences have been disillusioning: Major emission reductions have not been achieved, and a function-ing market does not exist. Hence, we ask what the political reasons for the failure of carbon markets in Japan are and how they can be overcome. We use Public Choice arguments, but also analyze actual climate policy making in Japan on a case study basis. Thus, on the one hand, we identify the political obstacles of implementing ambitious greenhouse gas emissions trading systems in Japan, and, on the other hand, we evaluate Public Choice’s arguments and environmental policy making.Japan, climate policy, emissions trading, Public Choice, case study

Model Based Sensor System for Temperature Measurement in R744 Air Conditioning Systems

The goal is the development of a novel principle for the temperature acquisition of refrigerants in CO2 air conditioning systems. The new approach is based on measuring the temperature inside a pressure sensor, which is also needed in the system. On the basis of simulative investigations of different mounting conditions functional relations between measured and medium temperature will be derived.Comment: Submitted on behalf of EDA Publishing Association (http://irevues.inist.fr/handle/2042/16838

A probablistic framework for classification and fusion of remotely sensed hyperspectral data

Reliable and accurate material identification is a crucial component underlying higher-level autonomous tasks within the context of autonomous mining. Such tasks can include exploration, reconnaissance and guidance of machines (e.g. autonomous diggers and haul trucks) to mine sites. This thesis focuses on the problem of classification of materials (rocks and minerals) using high spatial and high spectral resolution (hyperspectral) imagery, collected remotely from mine faces in operational open pit mines. A new method is developed for the classification of hyperspectral data including field spectra and imagery using a probabilistic framework and Gaussian Process regression. The developed method uses, for the first time, the Observation Angle Dependent (OAD) covariance function to classify high-dimensional sets of data. The performance of the proposed method of classification is assessed and compared to standard methods used for the classification of hyperspectral data. This is done using a staged experimental framework. First, the proposed method is tested using high-resolution field spectrometer data acquired in the laboratory and in the field. Second, the method is extended to work on hyperspectral imagery acquired in the laboratory and its performance evaluated. Finally, the method is evaluated for imagery acquired from a mine face under natural illumination and the use of independent spectral libraries to classify imagery is explored. A probabilistic framework was selected because it best enables the integration of internal and external information from a variety of sensors. To demonstrate advantages of the proposed GP-OAD method over existing, deterministic methods, a new framework is proposed to fuse hyperspectral images using the classified probabilistic outputs from several different images acquired of the same mine face. This method maximises the amount of information but reduces the amount of data by condensing all available information into a single map. Thus, the proposed fusion framework removes the need to manually select a single classification among many individual classifications of a mine face as the `best' one and increases the classification performance by combining more information. The methods proposed in this thesis are steps forward towards an automated mine face inspection system that can be used within the existing autonomous mining framework to improve productivity and efficiency. Last but not least the proposed methods will also contribute to increased mine safety

Nonlinear spectroscopy of exciton-polaritons in a GaAs-based microcavity

We present a systematic investigation of two-photon excitation processes in a GaAs-based microcavity in the strong-coupling regime. We observe second harmonic generation resonant to the upper and lower polariton level, which exhibits a strong dependence on the photonic fraction of the corresponding polariton. In addition we have performed two-photon excitation spectroscopy to identify $2p$ exciton states which are crucial for the operation as a terahertz lasing device, which was suggested recently [A. V. Kavokin et al., Phys. Rev. Lett. \textbf{108}, 197401 (2012)]. However, no distinct signatures of a $2p$ exciton state could be identified, which indicates a low two-photon pumping efficiency