A stereophonic acoustic signal extraction scheme for noisy and reverberant environments

In this contribution, a novel two-channel acoustic front-end for robust automatic speech recognition in adverse acoustic environments with nonstationary interference and reverberation is proposed. From a MISO system perspective, a statistically optimum source signal extraction scheme based on the multichannel Wiener filter (MWF) is discussed for application in noisy and underdetermined scenarios. For free-field and diffuse noise conditions, this optimum scheme reduces to a Delay & Sum beamformer followed by a single-channel Wiener postfilter. Scenarios with multiple simultaneously interfering sources and background noise are usually modeled by a diffuse noise field. However, in reality, the free-field assumption is very weak because of the reverberant nature of acoustic environments. Therefore, we propose to estimate this simplified MWF solution in each frequency bin separately to cope with reverberation. We show that this approach can very efficiently be realized by the combination of a blocking matrix based on semi-blind source separation (‘directional BSS’), which provides a continuously updated reference of all undesired noise and interference components separated from the desired source and its reflections, and a single-channel Wiener postfilter. Moreover, it is shown, how the obtained reference signal of all undesired components can efficiently be used to realize the Wiener postfilter, and at the same time, generalizes well-known postfilter realizations. The proposed front-end and its integration into an automatic speech recognition (ASR) system are analyzed and evaluated in noisy living-room-like environments according to the PASCAL CHiME challenge. A comparison to a simplified front-end based on a free-field assumption shows that the introduced system substantially improves the speech quality and the recognition performance under the considered adverse conditions.     

3D deep X-ray lithography for producing a multi-channel Fourier transform interferometer

We introduce a modified LIGA process architecture to manufacture a static lamellar grating Fourier-transform spectrometer invented by Moser and Möller (European patent EP 0 765 488 B1, 1994). Such spectrometers hold unique advantages over common Michelson-type FTIRs including high time resolution, speed, compactness, and robustness. To cope with the spectrometer’s demand for precise high-aspect-ratio micro-fabrication, we present a modified LIGA process which enhances the X-ray lithography by means of a moving mask technique (Heussler and Moser Lithography method and apparatus PCT/SG2011/000376, 2011). The technique relies on independently moving multiple masks stacked on top of each other during the lithographic step and thus allows to locally vary the deposited dose in a positive tone photoresist. First manufacturing results as well as a performance test of a prototype spectrometer are reported.     

Biogeochemical processes and microbial characteristics across groundwater-surface water boundaries of the Hanford Reach of the Columbia River

Biogeochemical processes within riverbed hyporheic zones (HZ) can potentially impact the fate and transport of contaminants. We evaluated a modified freeze core technique for the collection of intact cobble-bed samples from the Columbia River HZ along a stretch of the Hanford Reach in Washington State and investigated microbiological and geochemical parameters of corresponding frozen and unfrozen samples. During three sampling periods (March, May, and November 2000), relatively high numbers of viable aerobic heterotrophic bacteria were recovered from both unfrozen (10(6)-10(7) cfu/g) and frozen samples (10(5)-10(6) cfu/g). Relatively large populations of sulfate-, nitrate-, and iron-reducing bacteria were present, and significant concentrations of acid-volatile sulfide were measured in some samples, indicating that anoxic regions exist within this zone. Cr(VI), a priority groundwater pollutant on adjacent U.S. Department of Energy lands, was probably removed from solution in HZ samples by a combination of microbial activity and chemical reduction, presumably via products of anaerobic microbial metabolism. These results suggest that biogeochemical processes in the Columbia River HZ may contribute to the natural attenuation of Cr(VI). Although freezing modestly diminished recovery of viable bacteria, freeze core techniques proved reliable for the collection of intact hyporheic sediments.     

Evidence for organosulfates in secondary organic aerosol

Recent work has shown that particle-phase reactions contribute to the formation of secondary organic aerosol (SOA), with enhancements of SOA yields in the presence of acidic seed aerosol. In this study, the chemical composition of SOA from the photooxidations of alpha-pinene and isoprene, in the presence or absence of sulfate seed aerosol, is investigated through a series of controlled chamber experiments in two separate laboratories. By using electrospray ionization-mass spectrometry, sulfate esters in SOA produced in laboratory photooxidation experiments are identified for the first time. Sulfate esters are found to account for a larger fraction of the SOA mass when the acidity of seed aerosol is increased, a result consistent with aerosol acidity increasing SOA formation. Many of the isoprene and alpha-pinene sulfate esters identified in these chamber experiments are also found in ambient aerosol collected at several locations in the southeastern U.S. It is likely that this pathway is important for other biogenic terpenes, and may be important in the formation of humic-like substances (HULIS) in ambient aerosol.     

Three‐dimensional localization for the MagneBike inspection robot

The MagneBike inspection robot is a climbing robot equipped with magnetic wheels. The robot is designed to drive on three‐dimensional (3D) complexly shaped pipe structures; therefore it is necessary to provide 3D visualization tools for the user, who remotely controls the robot out of sight. The localization system is required to provide a 3D map of the unknown environment and the 3D location of the robot in the environment's map. The localization strategy proposed in this paper consists of combining 3D odometry with 3D scan registration. The odometry model is based on wheel encoders and a three‐axis accelerometer. Odometry enables the tracking of the robot trajectory between consecutive 3D scans and is used as a prior for the scan matching algorithm. The 3D scan registration facilitates the construction of a 3D map of the environment and refines the robot position computed with odometry. This paper describes in detail the implementation of the localization concept. It presents the lightweight, small‐sized 3D range finder that has been developed for the MagneBike. It also proposes an innovative 3D odometry model that estimates the local surface curvature to compensate for the absence of angular velocity inputs. The different tools are characterized in detail based on laboratory and field experiments. They show that the localization concepts reliably track the robot moving in the specific application environment. We also describe various techniques to optimize the 3D scanning process, which is time consuming, and to compensate for the identified limitations. These techniques are useful inputs for the future automatization of the robot's control and optimization of its localization process. © 2010 Wiley Periodicals, Inc.     

Static analysis and process model transformation for an advanced business process to Petri net mapping

Verification of business processes typically relies on Petri net–based process models. While they allow for natural modeling and analysis of aspects such as parallelism and message exchange, such a process model is seldom complete and precise. This is mainly because the available techniques for deriving a Petri net model from the original model neglect process data in favor of feasible verification. In this paper, we present an approach for deriving more precise process models by leveraging a process‐to‐Petri‐net compiler, which takes as input a business process and generates as output a Petri net model for the process. This can be subsequently used for verification. However, in contrast to a conventional compiler, our compiler's objective is not to create the most efficient code but rather to produce a most precise but still effectively verifiable Petri net–based process model.     

Modeling river water quality parameters using modified adaptive neuro fuzzy inference system

Water quality is always one of the most important factors in human health. Artificial intelligence models are respected methods for modeling water quality. The evolutionary algorithm(EA) is a new technique for improving the performance of artificial intelligence models such as the adaptive neuro fuzzy inference system(ANFIS) and artificial neural networks(ANN). Attempts have been made to make the models more suitable and accurate with the replacement of other training methods that do not suffer from some shortcomings, including a tendency to being trapped in local optima or voluminous computations. This study investigated the applicability of ANFIS with particle swarm optimization(PSO)and ant colony optimization for continuous domains(ACO_R) in estimating water quality parameters at three stations along the Zayandehrood River, in Iran. The ANFIS-PSO and ANFIS-ACO_R methods were also compared with the classic ANFIS method, which uses least squares and gradient descent as training algorithms. The estimated water quality parameters in this study were electrical conductivity(EC), total dissolved solids(TDS), the sodium adsorption ratio(SAR), carbonate hardness(CH), and total hardness(TH). Correlation analysis was performed using SPSS software to determine the optimal inputs to the models. The analysis showed that ANFIS-PSO was the better model compared with ANFIS-ACO_R. It is noteworthy that EA models can improve ANFIS' performance at all three stations for different water quality parameters.     

Complexes between monoclonal antibodies and receptor fragments with a common cold virus: determination of stoichiometry by capillary electrophoresis

Complex formation between monoclonal antibodies or soluble receptor fragments and a human rhinovirus is quantified by relating the concentration of the antibody or receptor under equilibrium conditions to the initial concentration of the virus. Within a given concentration range of the reactants, the shape of the resulting curve depends only on the value of the dissociation constant of the particular system studied. Using antibodies and receptor fragments, cases for high, low, and intermediate affinity were investigated. For high-affinity systems, the curve approximates a decaying straight line and the binding stoichiometry can be accurately determined from the intercept with the x-axis. For the case of intermediate affinity, the curve can be linearized at low virus concentrations with the receptors present in large excess. Extrapolation of this line allows derivation of the binding stoichiometry from the intercept with the x-axis, although with less accuracy. For intermediate affinities, an estimate of the dissociation constant can be obtained from fitting the curve to the data points measured. Finally, in the case of low affinity none of the binding parameters can be quantified, although a rough estimate of the lower limit of the dissociation constant is possible. The method was applied for two different monoclonal antibodies, a Fab fragment and a receptor fragment, binding to human rhinovirus serotype 2. Thirty copies of the monoclonal antibody 8F5 were found to bind to the virion, which is in agreement with data from electron cryomicroscopy. The complex between monovalent human very-low-density lipoprotein receptor encompassing repeats 2 and 3 and human rhinovirus serotype 2 showed 60 receptor molecules bound per virion.     

Superior Thermoelectric Performance of Textured Ca3Co4−xO9+δ Ceramic Nanoribbons

Calcium cobaltite Ca₃Co_4−xO_9+δ (CCO) is a promising p-type thermoelectric (TE) material for high-temperature applications in air. The grains of the material exhibit strong anisotropic properties, making texturing and nanostructuring mostly favored to improve thermoelectric performance. On the one hand multitude of interfaces are needed within the bulk material to create reflecting surfaces that can lower the thermal conductivity. On the other hand, low residual porosity is needed to improve the contact between grains and raise the electrical conductivity. In this study, CCO fibers with 100% flat cross sections in a stacked, compact form are electrospun. Then the grains within the nanoribbons in the plane of the fibers are grown. Finally, the nanoribbons are electrospun into a textured ceramic that features simultaneously a high electrical conductivity of 177 S cm⁻¹ and an immensely enhanced Seebeck coefficient of 200 µV K⁻¹ at 1073 K are assembled. The power factor of 4.68 µW cm⁻¹ K⁻² at 1073 K in air surpasses all previous CCO TE performances of nanofiber ceramics by a factor of two. Given the relatively high power factor combined with low thermal conductivity, a relatively large figure-of-merit of 0.3 at 873 K in the air for the textured nanoribbon ceramic is obtained.