Lars Hildebrand

Adaptive approach for variable noise suppression on laser-induced breakdown spectroscopy responses using stationary wavelet transform.

Spectral signals are often corrupted by noise during their acquisition and transmission. Signal processing refers to a variety of operations that can be carried out on measurements in order to enhance the quality of information. In this sense, signal denoising is used to reduce noise distortions while keeping alterations of the important signal features to a minimum. The minimization of noise is a highly critical task since, in many cases, there is no prior knowledge of the signal or of the noise. In the context of denoising, wavelet transformation has become a valuable tool. The present paper proposes a noise reduction technique for suppressing noise in laser-induced breakdown spectroscopy (LIBS) signals using wavelet transform. An extension of the Donohos scheme, which uses a redundant form of wavelet transformation and an adaptive threshold estimation method, is suggested. Capabilities and results achieved on denoising processes of artificial signals and actual spectroscopic data, both corrupted by noise with changing intensities, are presented. In order to better consolidate the gains so far achieved by the proposed strategy, a comparison with alternative approaches, as well as with traditional techniques, is also made.

Knowledge-based fuzzy color processing

This paper concerns the application of digital image processing in combination with rulebased reasoning as a nondestructive quality testing method for resistance spot welding. The use of fuzzy logic gives the possibility to characterize colors by linguistic terms rather than by names for wavelength or wavelength intervals. The presented method supplements Lotfi Zadehs idea of soft computing and computing with words. It can be applied to many problems in which color carries important information.

An approach to automated frequency-domain feature extraction in nuclear magnetic resonance spectroscopy

For the analysis of metabolite systems, nuclear magnetic resonance (NMR) spectroscopy has become an important quantitative monitoring technology. Automated quantitation methods are highly desired and mainly characterized by the tasks of model selection and parameter approximation. This paper proposes a promising automated two stage approach in the frequency-domain, in which signaling peaks are first identified and filtered from noise based on curvature properties of the spectrum, and then proportionally approximated based on the analytical solution of a Lorentz-function. Remarkably, in opposition to common least-squares approaches, the proposed approximation scheme does not rely on partial derivatives, and furthermore, the runtime is independent to the number of spectral datapoints. Simulations provide promising empirical evidence for successful peak selection and parameter approximation, with the results for the latter highly outperforming the Levenberg-Marquardt algorithm in terms of error minimization and robustness.

Fuzzy Color Processing

Fuzzy logic has proven its applicability in solving many control problems mainly in engineering and financial applications. If fuzzy control is extended towards fuzzy rule-based reasoning, the number of successful applications is smaller and some topics have only rarely been examined. The processing of color is one of these. Reasons for this are given in this chapter, as well as a new approach for linguistic color processing based on fuzzy logic. The methods developed and presented here for fuzzy color processing can be directly embedded in existing fuzzy rulebased systems.

Vision systems for the inspection of resistance welding joints

Many automated quality inspection systems make use of brightness and contrast features of the objects being inspected. This reduces the complexity of the problem solving methods, as well as the demand for computational capacity. Nevertheless a lot of significant information is located in color features of the objects. This paper describes a method, that allows the evaluation of color information in a very compact and efficient way. The described method uses a combination of multi-valued logic and a special color model. We use fuzzy logic as multi-valued logic, and the HSI color model, but any multi-valued logic, that allows rule-based reasoning can be used. The HSI color model can also be exchanged with other color models, if special demands require this.

Using fuzzy logic to increase the performance of FEM modules

Highly stressed engineering parts and components often require material properties that cannot be found within one specific material. This mismatch between requirement and material properties has drastic consequences: reduced functionability of the mechanical parts or a need for superior materials, which results in high material costs. Computer-based systems, such as rule-based systems, finite-element methods, and material databases, provide a way out of this situation. A first prototype of such a system was developed at the University of Dortmund, Department of Computer Science, Chair I, and Department of Mechanical Engineering, Chair of Material Technology, in the scope of Special Research Field 316. This article describes the fuzzy logic-based extensions of that system. The extensions provide an improvement in speed, a better user interface, and the ability to handle lack of knowledge.

Intelligent design methods for smart materials

The design process of modern smart materials often require the use of complex system models. These models cannot be derived easily due to the complex knowledge that describe the process. In some cases, model parameters can be gained using neural networks, but these systems allow only a one-way simulation from input values to learned output values. If evaluation in the other direction is needed, these models allow no direct evaluation. This task can be solved using modern techniques like evolutionary algorithms and fuzzy logic. The use of such a combination allows evaluation of the learned simulation models in the direction from output to the input. An example can be given from the field of screw rotor design.

Wireless transmission of vital signs of entrapped victims during search and rescue operations in collapsed buildings

During Urban Search and Rescue (USaR) operations in collapsed buildings, once the entrapped victims are located the extrication starts. The latter is always time consuming whilst in most cases medical monitoring and support of the victim is needed. Monitoring vital signs of victim is quite important but due to the particular post-collapse conditions of the building (fires, gas leaks, tremors/instability), the preferred method would be remote medical monitoring. In this work a commercial off-the-shelf system for victims vital signs wireless transmission is tested as part of a feasibility study in which non-invasive methods such as breath or sweat analysis can be used for medical monitoring. The capabilities and the limitations of the tested technology are presented and discussed.

Image Based Analysis of Microstructures Using Texture Detection and Fuzzy Classifiers

Modern steel products are manufactured using many different production steps. One step is the hardening by heat treatment. To assess the quality of the processed steel products, the microstructure can be analyzed. This article describes all necessary steps, beginning from image capturing from microscopes to the classification using fuzzy logic based classifiers.

A bottom-up approach to the biclustering-problem.

The biclustering problem adresses the discovery of locally significant correlation within a data matrix and has recently become quite popular in the field of microarray data analysis. The preservation of a particularly defined degree of homogeneity between elements within a bicluster plays a key role in the search procedure. This work proposes a pairwise distance function related to the mean squared residue to introduce multiple enrichment algorithms. Based on a theoretical framework, the impact is demonstrated empirically by the enrichment of commonly available and also on artificially generated bicluster sets.