Counting and Integrating Readout for Direct Conversion X-ray Imaging: Concept, Realization and First Prototype Measurements

A novel signal processing concept for X-ray imaging with directly converting pixelated semiconductor sensors is presented. The novelty of this approach compared to existing concepts is the combination of charge integration and photon counting in every single pixel. Simultaneous operation of both signal processing chains extends the dynamic range beyond the limits of the individual schemes and allows determination of the mean photon energy. Medical applications such as X-ray computed tomography can benefit from this additional spectral information through improved contrast and the ability to determine the hardening of the tube spectrum due to attenuation by the scanned object. A prototype chip in 0.35-micrometer technology has been successfully tested. The pixel electronics are designed using a low-swing differential current mode logic. Key element is a configurable feedback circuit for the charge sensitive amplifier which provides continuous reset, leakage current compensation and replicates the input signal for the integrator. This paper will discuss measurement results of the prototype structures and give details on the circuit design     

Response selection and response execution in task switching: Evidence from a go-signal paradigm.

The present study used a go/no-go signal delay (GSD) to explore the role of response-related processes in task switching. A go/no-go signal was presented at either 100 ms or 1,500 ms after the stimulus. Participants were encouraged to use the GSD for response selection and preparation. The data indicate that the opportunity to select and prepare a response (i.e., long GSD) resulted in a substantial reduction of task-shift costs (Experiment 1) and n-2 task-repetition costs (i.e., backward inhibition; Experiment 2) in the current trial. These results suggest that interference from the preceding trial can be resolved during response selection and preparation. Furthermore, the shift costs and the n-2 repetition costs after no-go trials with long GSD (i.e., response selection but no execution) were markedly smaller than after go trials. These findings suggest that the interference that gives rise to shift costs and n-2 repetition costs is related not solely to response selection but also to response execution. Thus, the present study demonstrates dissociable contributions of response selection and response execution to interference effects in task switching. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Extended Tunability in a Two-Chip VECSEL

We demonstrate a widely tunable vertical-external-cavity surface-emitting laser (VECSEL) with a W-shaped cavity, in which two VECSEL chips serve as fold mirrors and a birefringent filter is inserted at Brewster's angle. These two chips provide much higher modal gain and broader bandwidth of the gain than a single chip does, enhancing the VECSEL tuning range and reducing the variation of tunable output power with the tuned wavelength. This two-chip VECSEL configuration makes it possible to shape the modal gain spectra of the laser or to manipulate the tuning curve of the laser by two different chips with certain gain peak detuning (offset). Multiwatts high-brightness linearly polarized output with a tuning range of 33 nm is demonstrated in such a two-chip VECSEL     

A Parallel Dynamic Binary Translator for Efficient Multi-Core Simulation

In recent years multi-core processors have seen broad adoption in application domains ranging from embedded systems through general-purpose computing to large-scale data centres. Simulation technology for multi-core systems, however, lags behind and does not provide the simulation speed required to effectively support design space exploration and parallel software development. While state-of-the-art instruction set simulators (Iss) for single-core machines reach or exceed the performance levels of speed-optimised silicon implementations of embedded processors, the same does not hold for multi-core simulators where large performance penalties are to be paid. In this paper we develop a fast and scalable simulation methodology for multi-core platforms based on parallel and just-in-time (Jit) dynamic binary translation (Dbt). Our approach can model large-scale multi-core configurations, does not rely on prior profiling, instrumentation, or compilation, and works for all binaries targeting a state-of-the-art embedded multi-core platform implementing the ARCompact instruction set architecture (Isa). We have evaluated our parallel simulation methodology against the industry standard Splash-2 and Eembc MultiBench benchmarks and demonstrate simulation speeds up to 25,307 Mips on a 32-core x86 host machine for as many as 2,048 target processors whilst exhibiting minimal and near constant overhead, including memory considerations.     

Security of Water Supply and Electricity Production: Aspects of Integrated Management

The share of renewable resources in electricity generation, e.g. in Germany, is increasing. The power sector is thus becoming more dependent on climate/weather parameters. During the summer months of the last decade, numerous thermal power plants in Europe had to be throttled due to water shortages and high water temperatures. At the same time, Europe was confronted with a reduction in hydropower production. One method of securing a future electricity supply is to increase the reliability of the water supply for power plants. In this paper, scenarios are presented for future electricity production by hydropower and thermal power plants in the Elbe river basin. Electricity production in hydropower plants will decline by approximately 13 % by 2050. This decline is due to climate change and it could be compensated for by optimizing and modernizing existing hydropower plants. Due to higher efficiencies and the conversion of plant cooling systems, no water shortages are expected in most thermal power plants. However, water shortages are expected to affect the plants in the city of Berlin. Inter- and intra-basin water transfers constitute a possible adaptation option. While the transfer of water from the river Oder would be the most cost-efficient solution from Berlin’s perspective, the transfer of water from the river Elbe would have additional positive effects in the upstream Spree river sub-basin.     

An evaluation of Landsat TM spectral data and SAR-derived textural information for lithological discrimination in the Red Sea Hills,Sudan

The effectiveness of spectral and textural information in the identification of surface rock types in an arid region, the Red Sea Hills of Sudan, is evaluated using spectral information from the six Landsat TM optical bands and textural features derived from Shuttle Imaging Radar-C (SIR-C) C-band HH polarization data. An initial classification is derived from Landsat TM data alone using three classification algorithms, Gaussian maximum likelihood, a multi-layer feed-forward neural network and a Kohonen self-organizing feature map (SOM), to generate lithological maps, with classification accuracy being measured using a confusion matrix approach. The feed-forward neural net produced the highest overall classification accuracy of 57 per cent and was, therefore, selected for the second experiment, in which texture measures from SIR-C C-band HH-polarized synthetic aperture radar (SAR) data are added to selected TM spectral features. Four methods of measuring texture are employed, based on the Fourier power spectrum, grey level co-occurrence matrix (GLCM), multi-fractal measures, and the multiplicative autoregressive random field (MAR) model. The use of textural information together with a subset of the TM spectral features leads to an increase in classification accuracy to almost 70 per cent. Both the MAR model and the GLCM matrix approach perform better than Fourier and multi-fractal based methods of texture characterization.     

An optimal approach to the connection admission control problem

The paper considers the connection admission control (CAC), which is a key resource management procedure, and proposes a solution to the problem based on modelling and control methodologies. The CAC problem will be formulated as an optimal control problem subject to a set of constraints. As a matter of fact, the proposed controller, modelling the CAC mechanism, computes the above-mentioned control variables so that (i) a set of proper constraints, which model the quality of service (QoS) requirements (link availability, blocking probability and dropping probability), are respected and (ii) a proper performance index, which models the exploitation degree of the available bandwidth, is maximized. The proposed CAC successfully compares with other CACs proposed in the literature, and in particular significantly extends the upper limit of the accepted traffic rate.     

Evaluation of most similar neighbour and random forest methods for imputing forest inventory variables using data from target and auxiliary stands

We report the results from modelling standing volume, above-ground biomass and stem count with the aim of exploring the potential of two non-parametric approaches to estimate forest attributes. The models were built based on spectral and 3D information extracted from airborne optical and laser scanner data. The survey was completed across two geographically adjacent temperate forest sites in southwestern Germany, using spatially and temporally comparable remote-sensing data collected by similar instruments. Samples from the auxiliary reference stands (called off-site samples) were combined with random, random stratified and systematically stratified samples from the target area for prediction of standing volume, above-ground biomass and stem count in the target area. A range of combinations was used for the modelling process, comprising the most similar neighbour (MSN) and random forest (RF) imputation methods, three sampling designs and two predictor subset sizes. An evolutionary genetic algorithm (GA) was applied to prune the predictor variables. Diagnostic tools, including root mean square error (RMSE), bias and standard error of imputation, were employed to evaluate the results. The results showed that RF produced more accurate results than MSN (average improvement of 3.5% for a single-neighbour case with selected predictors), yet was more biased than MSN (average bias of 5.13% with RF compared to 2.44% with MSN for stem volume in a single-neighbour case with selected predictors). Combining systematically stratified auxiliary samples from the target data set with the reference data set yielded more accurate results compared to those from random and stratified random samples. Combining additional data was most influential when an intensity of up to 40% of supplementary samples was appended to the reference set. The use of GA-selected predictors resulted in reduced bias of the models. By means of bootstrap simulations of RMSE, the simulations were shown to lie within the applied non-parametric confidence intervals. The achieved results are concluded to be helpful for modelling the mentioned forest attributes by means of airborne remote-sensing data.     

Study of Interatomic Potentials in ZnS—Crystal-GRID Experiments Versus Ab Initio Calculations

Crystal-GRID measurements have been performed with ZnS single crystals. For the first time, an asymmetric Crystal-GRID line shape could be observed. The preliminary data evaluation indicates that the reported lifetime of the 3221 keV level in ³³S is too short. A value of about 60 fs has been found. Due to this “long” lifetime the line shape is much less structured than calculated with the reported lifetime.