Intelligente Roboter — 2. Österreichisch-Koreanisches Gemeinschaftsseminar

Ohne Zusammenfassung     

Detection of surface defects on raw steel blocks using Bayesian network classifiers

This paper proposes an approach that detects surface defects with three-dimensional characteristics on scale-covered steel blocks. The surface reflection properties of the flawless surface changes strongly. Light sectioning is used to acquire the surface range data of the steel block. These sections are arbitrarily located within a range of a few millimeters due to vibrations of the steel block on the conveyor. After the recovery of the depth map, segments of the surface are classified according to a set of extracted features by means of Bayesian network classifiers. For establishing the structure of the Bayesian network, a floating search algorithm is applied, which achieves a good tradeoff between classification performance and computational efficiency for structure learning. This search algorithm enables conditional exclusions of previously added attributes and/or arcs from the network. The experiments show that the selective unrestricted Bayesian network classifier outperforms the naïve Bayes and the tree-augmented naïve Bayes decision rules concerning the classification rate. More than 98% of the surface segments have been classified correctly.     

Robust DNA microarray image analysis

DNA microarrays are an increasingly important tool that allow biologists to gain insight into the function of thousands of genes in a single experiment. Common to all array-based approaches is the necessity to analyze digital images of the scanned DNA array. The ultimate image analysis goal is to automatically quantify every individual array element (spot), providing information about the amount of DNA bound to a spot. Irrespective of the quantification strategy, the preliminary information to extract about a spot includes the mapping between its location in the digital image and its possibly distorted position in the spot array (gridding). We present a gridding approach divided into a spot-amplification step (matched filter), a rotation estimation step (Radon transform), and a grid spanning step. Quantification of the spots is performed by robustly fitting of a parametric model to pixel intensities with the help of M-estimators. The main advantage of parametric spot fitting is its ability to cope with overlapping spots. If the goodness-of-fit is too bad, a semiparametric spot fitting is employed. We show that our approach is superior to simple quantification strategies such as averaging of the pixel intensities. The system was extensively tested on 1740 images resulting from two DNA libraries.Received: 15 June 2001, Accepted: 21 July 2002, Published online: 3 June 2003 Correspondence to: Norbert Brändle     

The role of the carotenoids,lutein and zeaxanthin,in protecting against age-related macular degeneration: A review based on controversial evidence

Purpose  

A review of the role of the carotenoids, lutein and zeaxanthin, and their function in altering the pathogenesis of age-related macular degeneration (AMD).     

ADONIS — ein Funksystem,eine Plattform für Applikationen,ein neuer Weg

Ohne Zusammenfassung     

Optimal lower bounds on the contribution margin in the case of stochastic order arrival

In customer order driven production, decisions on the acceptance of customer orders usually have to be based on variable costs and contribution margins (abbreviated CM), since in the short term only these quantities can be influenced. If we assume that customer orders arrive according to a stochastic process and that the decisions on order acceptance have to be made on each order separately, a customer order usually should be accepted only if its contribution margin exceeds a positive lower bound. This paper shows by means of a stochastic model that, under certain assumptions, this lower bound on the contribution margin can be determined using full costing, provided that the available capacity (constant over time) and the arrival process are balanced. This insight justifies, to a certain extent, the use of full costs to support decisions on the short-term production volume, which is a behaviour that can be observed in practice rather frequently. We also demonstrate the extension of the modelling approach to state-dependent lower bounds on the contribution margin.     

Screening of Fe–Cu-Zeolites Prepared by Different Methodology for Application in NSR–SCR Combined DeNOx Systems

The NO_x NH₃-SCR performance of several Cu and Fe catalysts supported on BETA and ZSM-5 zeolites has been studied in single SCR and double NSR–SCR configuration, and the activity related to the nature and reducibility of metal species on the catalyst surface. Intermediate ammonia formed in NSR improved greatly NO_x conversion at the exit of the double NSR–SCR configuration, which was practically totally converted to N₂.     

涂料染色技术的开发应用

分析了影响涂料染色的各种因素，对常规染色工艺与涂料染色工艺作了比较，提出了开发涂料染色技术需解决的几大问题及其解决方法。     

重视肿瘤射频消融治疗

射频消融是近年来发展的一种治疗恶性肿瘤的有效手段。随着影像学技术的发展，该方法已广泛应用于多种实体恶性肿瘤，如肝癌、肺癌、肾癌等。射频消融治疗肿瘤因具有创伤小、痛苦少、疗效确切、安全性高、并发症少、恢复快等优点，正越来越得到国内外专家的重视。