In this paper we present a general strategy for screening discrete variations in organic synthesis. The strategy is based upon principal properties, i.e. principal component characterization of the constituents defining the reaction system. The first step is to select subsets of test items from each class of constituents defining the reaction space, i.e. substrates, reagents, solvents, catalysts, etc., so that the selected items from each class cover the properties considered. The second step is to construct a candidate matrix which contains all possible combinations of the items in the subsets. This matrix is a full multilevel factorial design. The third step is to assign a tentative model for the screening experiment and to construct the corresponding candidate model matrix. The fourth step is to select experiments to yield an experimental design that spans the variable space efficiently and that also gives good estimates of the model parameters. We present an algorithm that uses singular value decomposition to select experiments. The proposed strategy is then illustrated with an example of the Fischer indole synthesis.

Non-invasive measurements of multiphase flows have several important applications in industry. In this paper we present a method that uses pulsed ultrasound and two small receivers to determine the mass concentration of iron ore particles in water. The proposed method is based on the assumption that when ultrasound is transmitted through a scattering medium, the shape of the energy lobe changes. In this paper we use two receivers to monitor how the lobe changes. We show with experiments how the proposed method can be used to determine particle mass fractions from 3 percent and up, with an accuracy of ±1 percent of the mass fraction. In the experiments we used a 3 MHz transmitter and two receivers, one along the acoustical axis and the other 6 mm off-axis, to measure the mass fraction of a polydisperse suspension of iron ore powder in water.

In any experimental science we are sometimes confronted with new experimental situations, where underlying physical models are unknown. After a first attempt at identifying physical variables that could effect the experimental result, we need to perform what is called a screening experiment. The objective is to conduct a small number of experiments that span as much of the experimental space as possible, to merit further experiments in smaller, more promising test systems. In this report we present an algorithm that, given a set of possible experiments, selects a subset of these. The selection is designed to cover as much variation as possible in the experimental space, and to assure a minimized expected mean squared error in the model parameter estimation. We verified the algorithm with an example taken from organic synthesis.

This paper addresses the problem of automatic detection of burn-through in weld joints. Gas metal arc (GMA) welding with pulsed current is used, and welding voltage and current are recorded. As short-circuitings are common between the welding electrode and the work piece during burn-through, a short-circuit detector is developed to detect these events. To detect another specific characteristic of burn-through - this detector is combined with a square-law detector. This second detector is based on a non-linear modification of an autoregressive model with extra input (ARX-model) of the welding process. The results obtained from this compound detector indicate that it is possible to detect burn-through in the welds automatically. The work also indicates that it is possible to design an on-line monitoring system for robotic GMA welding.

The impulse response method is often used to study the ultrasonic field radiated by planar or gently curved transducers. These investigations can be extended to include the reflected echoes from point reflectors, which can be used in syntesizing echoes from reflectors of known shapes. The single point echo can be measured directly but there are however certain problems associated with this. This paper proposes an alternative method to estimate the echo from a point-like reflector by measuring the echoes from sliding halfplanes. Using a tomographic approach, the single point echo is estimated from these measurements. To perform the tomographic inversion, a truncated weighted Singular Value Decomposition (SVD) is used in order to catch essential features of the ultrasonic echoes, where the weight functions are chosen specially to suit our application. Numerical solutions are given for the chosen weight functions and an error analysis is carried out.

This paper treats the problem of clustering multichannel EEG transients occurring in epilepsy, so called spikes. The authors present a new method for feature extraction which is an expansion along an orthonormal set of matrices, obtained from truncated SVD and Gram-Schmidt orthogonalization. The method is compared to a method used earlier where each channel was Hermite function expanded. The result is that using the same expansion order the new method represents a set of spikes with higher fidelity than the Hermite function method. The output from the feature extraction is a vector for each spike in a set. The vectors from a set is clustered with the standard NM algorithm. Two sets of spikes have been investigated, both being clustered in appearance

In many areas the time delay of arrival (TDOA) is desired. Conventional estimators usually have the property of breaking down for low SNR. In the case of narrowbanded signals we propose a fast and simple method to estimate the small time delays. The method is shown to have the same accuracy as conventional methods for small delays and high SNR while it performs better for low SNR. It is based on using the Hilbert transform in correlation between two signals. Apart from using it for better resolution in TDOA, it may also be used in applications with narrowbanded signals where the measurements are repeatable, such as ultrasonic imaging and ECG. In ultrasonic applications, due to fluctuations in the insonified media, a small random time shift may be present causing the signals to be misaligned in time. Averaging signals under these conditions will result in a distortion of the signal shape. We propose an averaging method to avoid this and to accomplish a higher SNR without the distortion. Simulations and experiments from ultrasonic applications are presented.