An optimization approach to estimate and calibrate column water vapour for hyperspectral airborne data

The article describes a novel approach to estimate and calibrate column water vapour (CWV), a key parameter for atmospheric correction of remote-sensing data. CWV is spatially and temporally variable, and image-based methods are used for its inference. This inference, however, is affected by methodological and numeric limitations, which likely propagate to reflectance estimates. In this article, a method is proposed to estimate CWV iteratively from target surface reflectances. The method is free from assumptions for at sensor radiance-based CWV estimation methods. We consider two cases: (a) CWV is incorrectly estimated in a processing chain and (b) CWV is not estimated in a processing chain. To solve (a) we use the incorrect estimations as initial values to the proposed method during calibration. In (b), CWV is estimated without initial information. Next, we combined the two scenarios, resulting in a generic method to calibrate and estimate CWV. We utilized the hyperspectral mapper (HyMap) and airborne prism experiment (APEX) instruments for the synthetic and real data experiments, respectively. Noise levels were added to the synthetic data to simulate real imaging conditions. The real data used in this research are cloud-free scenes acquired from the airborne campaigns. For performance assessment, we compared the proposed method with two state-of-the-art methods. Our method performed better as it minimizes the absolute error close to zero, only within 8–10 iterations. It thus suits existing operational chains where the number of iterations is considerable. Finally, the method is simple to implement and can be extended to address other atmospheric trace gases.     

Towards carbon-free flame spray synthesis of homogeneous oxide nanoparticles from aqueous solutions

Flame-assisted spray pyrolysis (FASP) is a versatile process for synthesis of nanoparticles from a broad choice of precursors and solvents. Water is an attractive solvent particularly for inexpensive inorganic precursors (e.g. metal nitrates) as it can effectively reduce the process cost. Furthermore when water usage is combined with a carbon-free fuel (e.g. H₂), nanoparticles can be made without forming CO₂. Here such a FASP process is explored for synthesis of Bi₂O₃ and other oxide nanoparticles from aqueous precursor solutions. The flame temperature was measured by FTIR emission–transmission spectroscopy while powders were characterized by X-ray diffraction and N₂ adsorption. At low FASP fuel gas (H₂ or C₂H₂) flow rates or process temperatures, product powders had a bimodal crystal size distribution. Its large and small modes were made by droplet- and gas-to-particle conversion, respectively. Homogeneous Bi₂O₃ and CeO₂ powders were obtained for sufficiently high flow rates of either C₂H₂ or H₂. Prolonged high temperature residence times promoted precursor evaporation from the spray droplets and yielded homogeneous nanostructured powders by gas-to-particle conversion. In contrast, FASP of aqueous solutions of aluminum nitrate yielded rather large particles by droplet-to-particle conversion at all fuel flows investigated.     

Energy dissipation in laser-based free form heading: a numerical approach

Cold forming generally allows the fast generation of parts with very low tolerances. In addition, mechanical properties are improved, if work hardening materials are used. Transferring the cold forming process to micro range leads to a decrease in the maximum achievable upset ratio so that the forming process becomes inefficient. Therefore, a laser-based free form heading process has been developed to generate preforms which can be calibrated in a secondary cold forming step. The achievable upset ratios reach values of several hundreds instead of 2.1 which is common for single step mechanical upsetting. In this article, heat losses arising in the material accumulation process using laser-based free form heading are analyzed and discussed. For this purpose, the process is modeled within the framework of continuum mechanics and simulated by a finite element method. By using a numerical approach, a systematic study on heat losses is performed in order to identify the influence of radiation, heat transfer due to convection and thermal conduction during laser irradiation time. The simulation results, which are validated with experimental data, show that the radiation is the most important mechanism reducing the efficiency of the accumulation process.     

Probabilistic performance prediction model for Austrian torrent control infrastructure

Due to the growing stock of torrent control structures and decreasing investments, the protection level can be reduced in the long term. Therefore, the focus of the future investments has been shifted on efficiency improvement and maintenance of existing structures. The maintenance of the existing structures is necessary to ensure safety from natural hazards, which are increasing as a consequence of the climate change. Due to the increasing number of structures, there is a strong need to develop a good maintenance management for these infrastructure works. This study is based on data from the condition rating programme of the Austrian Service for Torrent and Avalanche Control. For the structures relevant in this work, 75,343 records were available. The data were examined for different construction type and construction materials. The reliability of the structures was determined by means of the Markov chain. The study describes a homogeneous Markov chain model formed by the data of the condition rating. The result of this study is a proposal for a time to failure (TTF) and a time to repair (TTR) for several construction types with different construction materials as well as the time-dependent use of construction materials in the sector of the Austrian torrent control infrastructure.     

Large scale fabrication of asymmetric 2D and 3D micro/nano array pattern structures using multi-beam interference lithography technique for Solar cell texturing application

Microsystem Technologies - A method for the large scale fabrication of nano/micro array patterned structure for solar Photovoltaics (PV) is demonstrated by the use of laser interference lithography...     

Growing a list

It is easy to find expert knowledge on the Internet on almost any topic, but obtaining a complete overview of a given topic is not always easy: information can be scattered across many sources and must be aggregated to be useful. We introduce a method for intelligently growing a list of relevant items, starting from a small seed of examples. Our algorithm takes advantage of the wisdom of the crowd, in the sense that there are many experts who post lists of things on the Internet. We use a collection of simple machine learning components to find these experts and aggregate their lists to produce a single complete and meaningful list. We use experiments with gold standards and open-ended experiments without gold standards to show that our method significantly outperforms the state of the art. Our method uses the ranking algorithm Bayesian Sets even when its underlying independence assumption is violated, and we provide a theoretical generalization bound to motivate its use.     

Aktuelle Aktivitäten zu den europäischen Rohstoff-Initiativen

The European Initiatives manifested in the Communications of the European Commission on Raw Materials, in the Strategic Implementation Plan of the European Innovation Partnership on Raw Materials and in the 2014 Call of the European Institute for Innovation & Technology (EIT) for a Knowledge and Innovation Community (KIC) on Raw Materials lead to manifold Austrian activities on Government level and on level of the Montanuniversitaet Leoben. The ESEE Region, thus East- and Southeast Europe has a special role.