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Presented Methods (presented + methods)
Selected AbstractsComparison of LiDAR waveform processing methods for very shallow water bathymetry using Raman, near-infrared and green signalsEARTH SURFACE PROCESSES AND LANDFORMS, Issue 6 2010Tristan Allouis Abstract Airborne light detection and ranging (LiDAR) bathymetry appears to be a useful technology for bed topography mapping of non-navigable areas, offering high data density and a high acquisition rate. However, few studies have focused on continental waters, in particular, on very shallow waters (<2,m) where it is difficult to extract the surface and bottom positions that are typically mixed in the green LiDAR signal. This paper proposes two new processing methods for depth extraction based on the use of different LiDAR signals [green, near-infrared (NIR), Raman] of the SHOALS-1000T sensor. They have been tested on a very shallow coastal area (Golfe du Morbihan, France) as an analogy to very shallow rivers. The first method is based on a combination of mathematical and heuristic methods using the green and the NIR LiDAR signals to cross validate the information delivered by each signal. The second method extracts water depths from the Raman signal using statistical methods such as principal components analysis (PCA) and classification and regression tree (CART) analysis. The obtained results are then compared to the reference depths, and the performances of the different methods, as well as their advantages/disadvantages are evaluated. The green/NIR method supplies 42% more points compared to the operator process, with an equivalent mean error (,4·2,cm verusu ,4·5,cm) and a smaller standard deviation (25·3,cm verusu 33·5,cm). The Raman processing method provides very scattered results (standard deviation of 40·3,cm) with the lowest mean error (,3·1,cm) and 40% more points. The minimum detectable depth is also improved by the two presented methods, being around 1,m for the green/NIR approach and 0·5,m for the statistical approach, compared to 1·5,m for the data processed by the operator. Despite its ability to measure other parameters like water temperature, the Raman method needed a large amount of reference data to provide reliable depth measurements, as opposed to the green/NIR method. Copyright © 2010 John Wiley & Sons, Ltd. [source] CAD-based automated robot programming in adhesive spray systems for shoe outsoles and uppersJOURNAL OF FIELD ROBOTICS (FORMERLY JOURNAL OF ROBOTIC SYSTEMS), Issue 11 2004J. Y. Kim Most shoe manufacturing processes are not yet automated; it puts restrictions on increasing productivity. Among them, adhesive application processes particularly are holding the most workers and working hours. In addition, the working environment is very poor due to the toxicity of adhesive agents. In the case of automating an adhesive application process by using a robot, robot teaching by playback is difficult to produce high productivity because the kinds of shoes to be taught mount up to several thousands. To cope with it, it is necessary to generate robot working paths automatically according to the kind, the size, or the right and the left of shoes, and also to teach the generated paths to a robot automatically. This paper presents a method to generate three-dimensional robot working paths off-line based on CAD data in an automatic adhesive spray system for shoe outsoles and uppers. First, this paper describes how to extract the three-dimensional data of an outsole outline from a two-dimensional CAD drawing file. Second, it describes how to extract the three-dimensional data of an upper profiling line from the three-dimensional scanning data that is opened in a three-dimensional CAD program. Third, it describes how to generate robot working paths based on the extracted data and the nozzle setting parameters for adhesive spray. Also, a series of experiments for adhesive spray is performed to verify the effectiveness of the presented methods. This study will do much for increasing productivity in shoe manufacturing as a core work of a robotic adhesive spray system. © 2004 Wiley Periodicals, Inc. [source] Prediction of Microporous Aluminophosphate AlPO4 -5 Based on Resampling Using Partial Least Squares and Logistic DiscriminationMOLECULAR INFORMATICS, Issue 3 2010Miao Qi Abstract In this paper, Partial Least Squares (PLS) regression and Logistic Discrimination (LD) are employed to predict the formation of microporous aluminophosphate AlPO4 -5 based on the database of AlPO synthesis, which aims to provide a useful guidance to the rational synthesis of microporous materials as well as other inorganic crystalline materials. To deal with the problem of class imbalance, four guided resampling methods considering not only the between-class imbalance but also the within-class imbalance are proposed. Experimental results indicate that the presented methods are competent for predicting the formation of microporous aluminophosphate AlPO4 -5. Specially, compared with some existing resampling methods, our proposed resampling methods exhibit much better predictive results. [source] Some remarks on characterization and application of stationary phases for RP-HPLC determination of biologically important compoundsBIOMEDICAL CHROMATOGRAPHY, Issue 1 2006Sylwia Kowalska Abstract Biologically active compounds such as vitamins, steroids, nucleosides, peptides and proteins play a very important role in coordinating living organism functions. Determination of those substances is indispensable in pathogenesis. Their complex structure and physico-chemical properties cause many analytical problems. Chromatography is the most common technique used in pharmaceutical and biomedical analysis. The interaction between analyte and stationary phase plays a major role in the separation process. The structure of the packing has a significant influence on the results of the separation process. Various types of spectroscopic techniques, such as nuclear magnetic resonance spectroscopy, infrared spectroscopy, fluorescence spectroscopy and photoacoustic spectroscopy can be useful tools for the characterization of packings. Surface area measurements, elemental analysis, thermal analysis and microcalorimetric measurements are also helpful in this field. Part of the paper contains a description of chromatographic tests used for the determination of column properties. The description of the possibilities of surface characterization is not complete, but is focused on the most popular techniques and practical chromatographic tests. All the presented methods made possible the design and quality control of a new generation stationary phases, which are the future of high-performance liquid chromatography. Copyright © 2005 John Wiley & Sons, Ltd. [source] | ||||||||||