Development of a hyphenated microanalytical system for the investigation of leaching kinetics of heavy metals in environmental samples

A fast and convenient method for on-line monitoring of the extraction of heavy metals from solid (environmental) matrixes was developed. By the incorporation of microcartridges filled with dried and pulverized solid samples into the conduits of a flow system and appropriate selection of the liquid flowing through the cartridge, information about the degree of leaching and in particular of the kinetics of the leaching process are obtained. The method was optimized for determination of different metals of environmental concern using in-line detection by FAAS and ICPMS.     

Collegial verbalisation-a case study on a new method on information acquisition

The purpose of this paper is to propose and discuss a new method for information acquisition called collegial verbalisation. The method is explored in an empirical case study, and it consists of vehicle operators being videotaped while driving, followed by some of their colleagues making verbal reports while watching the video data. These colleagues have previously experienced exactly the same driving task as the operators, that is, they have travelled the same route, with the same craft, and used the same instrumentation. Thus, they are very familiar with the driving task and the driver environment. The empirical study is carried out on a high-speed ferry. The method is explored in relation to three rather open hypotheses: the amount of information provided in general; the reliability of the data; and how it contributes to the detection of 'buggy mental models' within the operators. The method is discussed in relation to the more traditional forms of verbal reports: concurrent and retrospective verbalisations, respectively. From the results of the empirical exploration, it is suggested that the method of collegial verbalisation may have combinatorial advantages that makes it more powerful as an analytical tool than the traditional forms of verbalisation, specifically if one wants to analyse work tasks that are dynamic and where the operators' behaviours are highly automated. However, more elaborate and systematic investigations must be conducted on the topic, and the paper therefore ends with a suggestion on an experimental design for this purpose.     

Assessing the Impacts of Climate Change on Hydrology of the Upper Reach of the Spree River: Germany

The aim of this study was to assess the potential impacts of future climate change on the hydrological response in the upper reach of the Spree River catchment using the Soil and Water Assessment Tool (SWAT). The model was calibrated for ten years (1997–2006) and validated with the data from four years (2007–2010) using average monthly stream flow. The impact of future climate change on precipitation, temperature, evapotranspiration and stream flow was then investigated from two different downscaled climate models (CLM and WETTREG2010) under SRES A1B scenarios for two future periods (2021–2030 and 2041–2050). Besides that, sensitivity analysis was carried out with and without observations, to test robustness of the sensitivity algorithm used in the model. Results of the determination coefficient R² and Nasch-Sutcliff efficiency E_NC were 0.81 and 0.80, respectively, during the calibration; 0.71 and 0.70, respectively, during the validation. Although some parameters were changed their sensitiveness ranking when the model run with observations, the SWAT model was, however, able to predict the top influential parameters without observations. According to 12 realizations from the two downscaled climate models, annual stream flow from 2021–2030 (2041–2050) is predicted to decrease by 39 % (43 %). This corresponds to an increase in annual evapotranspiration from 2021–2030 (2041–2050) of 36 % (38 %). The upper reach of the Spree River catchment will likely experience a significant decrease in stream flow due to the increasing in the evapotranspiration rates. This study could be of use for providing insight into the availability of future stream flow, and to provide a planning tool for this area.     

Towards Systematic Achievement of Compliance in Service-Oriented Architectures: The MASTER Approach

Service-oriented architectures (SOA) have been successfully adapted by agile businesses to support dynamic outsourcing of business processes and the maintenance of business ecosystems. Still, businesses need to comply with applicable laws and regulations. Abstract service interfaces, distributed ownership and cross-domain operations introduce new challenges for the implementation of compliance controls and the assessment of their effectiveness. In this paper, we analyze the challenges for automated support of the enforcement and evaluation of IT security controls in a SOA. We introduce these challenges by means of an example control, and outline a methodology and a high-level architecture that supports the phases of the control lifecycle through dedicated components for observation, evaluation, decision support and reaction. The approach is model-based and features policy-driven controls. A monitoring infrastructure assesses observations in terms of key indicators and interprets them in business terms. Reaction is supported through components that implement both automated enforcement and the provision of feedback by a human user. The resulting architecture essentially is a decoupled security architecture for SOA with enhanced analysis capabilities and will be detailed and implemented in the MASTER project.     

MIMO system identification: state-space and subspace approximationsversus transfer function and instrumental variables

The identification of multi-input multi-output (MIMO) linear systems has previously received a new impetus with the introduction of the state-space (SS) approach based on subspace approximations. This approach has immediately gained popularity, owing to the fact that it avoids the use of canonical forms, requires the determination of only one structural parameter, and has been empirically shown to yield MIMO models with good accuracy in many cases, However, the SS approach suffers from several drawbacks: there is no well-established rule tied to this approach for determining the structural parameter, and, perhaps more important the SS parameter estimates depend on the data in a rather complicated way, which renders almost futile any attempt to analyze and optimize the performance of the estimator. In this paper, we consider a transfer function (TF) approach based on instrumental variables (IV), as an alternative to the SS approach. We use the simplest canonical TF parameterization in which the denominator is equal to a scalar polynomial times the identity matrix. The analysis and optimization of the statistical accuracy of the TF approach is straightforward. Additionally, a simple test tailored to this approach is devised for estimating the single structural parameter needed. A simulation study, in which we compare the performances of the SS and the TF approaches, shows that the latter can provide more accurate models than the former at a lower computational cost     

Array interpolation and DOA MSE reduction

Interpolation or mapping of data from a given real array to data from a virtual array of more suitable geometry is well known in array signal processing. This operation allows arrays of any geometry to be used with fast direction-of-arrival (DOA) estimators designed for linear arrays. In an earlier companion paper , a first-order condition for zero DOA bias under such mapping was derived and was also used to construct a design algorithm for the mapping matrix that minimized the DOA estimate bias. This bias-minimizing theory is now extended to minimize not only bias, but also to consider finite sample effects due to noise and reduce the DOA mean-square error (MSE). An analytical first-order expression for mapped DOA MSE is derived, and a design algorithm for the transformation matrix that minimizes this MSE is proposed. Generally, DOA MSE is not reduced by minimizing the size of the mapping errors but instead by rotating these errors and the associated noise subspace into optimal directions relative to a certain gradient of the DOA estimator criterion function. The analytical MSE expression and the design algorithm are supported by simulations that show not only conspicuous MSE improvements in relevant scenarios, but also a more robust preprocessing for low signal-to-noise ratios (SNRs) as compared with the pure bias-minimizing design developed in the previous paper.     

Preparation and Thermoelectric Characterization of SiC-B<Subscript>4</Subscript>C Composites

SiC-B₄C composites with various values of SiC-to-B₄C ratio and grain size were fabricated by pressureless sintering. This paper presents the results of current investigations of this composite material. This includes the parameters of manufacture (shrinkage, density, and open porosity), thermoelectric properties (electrical and thermal conductivity, and thermopower), and material characterization (x-ray diffraction, scanning electron microscopy, oxidation resistance, and thermal expansion). The results indicate high potential of this composite as an alternative material for thermoelectric applications at high temperatures. The Seebeck coefficient of the composite was higher than that of the single-component materials B₄C and SiC and reached 400 μV/K at 500°C.     

Further results and insights on subspace based sinusoidal frequencyestimation

Subspace-based methods for parameter identification have received considerable attention in the literature. Starting with a scalar-valued process, it is well known that subspace-based identification of sinusoidal frequencies is possible if the scalar valued data is windowed to form a low-rank vector-valued process. MUSIC and ESPRIT-like estimators have, for some time, been applied to this vector model. In addition, a statistically attractive Markov-like procedure for this class of methods has been proposed. Herein, the Markov-like procedure is reinvestigated. Several results regarding rank, performance, and structure are given in a compact manner. The large sample equivalence with the approximate maximum likelihood method by Stoica et al. (1988) is also established     

Exploiting arrays with multiple invariances using MUSIC and MODE

This paper describes several new techniques for direction of arrival (DOA) estimation using arrays composed of multiple translated and uncalibrated subarrays. The new algorithms can be thought of as generalizations of the MUSIC, Root-MUSIC, and MODE techniques originally developed for fully calibrated arrays. The advantage of these new approaches is that the DOAs can be estimated using either a simple one-dimensional (1-D) search or by rooting a polynomial, as opposed to the multidimensional search required by multiple invariance (MI)-ESPRIT. When it can be applied, the proposed MI-MODE algorithm shares the statistical optimality of MI-ESPRIT. While MI-MUSIC and Root-MI-MUSIC are only optimal for uncorrelated sources, they perform better than a single invariance implementation of ESPRIT and are thus better suited for finding the initial conditions required by the MI-ESPRIT search