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13th IEEE International Conference on Industrial Informatics (INDIN)

作者： Abbass, Jabbar K. Al-Habaibeh, Amin Minist Sci & Technol Ctr Space Applicat Baghdad Iraq Nottingham Trent Univ Adv Design & Mfg Engn Ctr Nottingham NG1 4BU England

ISBN: (纸本)9781479966493

This paper investigates the use of the power of the driving motor of a CNC spindle in comparison to two perpendicular eddy current sensors for the detection of tool wear in milling processes. Monitoring the power through the current profile is a low cost system which has been utilised in this study as an attempt to detect the fluctuation in the motor load as a result of the conditions of the cutting tool. Eddy current sensors are dedicated sensors that are installed on the spindle to measure the vibration of the rotating spindle in two axes. Experimental work has been conducted using fresh and worn tools to investigate the effect of tool conditions on the two sensory systems. Time domain features are utilised to compare between the two sensors in relation to this application. The results indicate that Eddy current sensors are found to be more successful and sensitive, in general, than the power of the motor in detecting the changes of the cutting tools during the machining operation. However, the kurtosis value of the power of the spindle has been found to be successful in predicting the tool conditions with high sensitivity.

关键词： Condition Monitoring Motor power eddy current sensor Tool wear linear regression method

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Bend strength variation of ceramics in serial fabrication

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JOURNAL OF THE EUROPEAN CERAMIC SOCIETY 2014年第7期34卷 1873-1879页

作者： Ambrozic, Milan Gorjan, Lovro Gomilsek, Masa Univ Maribor Fac Nat Sci & Math SLO-2000 Maribor Slovenia Jozef Stefan Inst Ljubljana 1000 Slovenia

We have performed a statistical evaluation of more than 10 000 experimental strength values of test pieces from a serial production of alumina products where in each production series 12 samples were broken. The Weibull parameters were obtained by three different methods: linear regression, maximum-likelihood and moments' method. The methods give different values of parameters even for this large number of data, but all the correlation coefficients are high and similar. Evaluating Weibull parameters for each testing group gives expected systematically different values of particular Weibull modulus as compared to the whole population of collected data. However, when the order of experimental data is mixed, the average Weibull modulus is lower than that corresponding to time ordered data. This difference can be served as an indication for variation of products' quality from series to series. (C) 2014 Elsevier Ltd. All rights reserved.

关键词： Bend strength Weibull statistics linear regression method Maximum-likelihood method Moments' method

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Dissecting estimation of conductances in subthreshold regimes

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BMC Neurosci 2014年第SUPPL 1期15卷 P151-P151页

作者： Catalina Vich Antoni Guillamon Dept. of Mathematics and Computer Science Universitat de les Illes Balears Palma 07122 Spain Dept. of Applied Mathematics I EPSEB Universitat Politècnica de Catalunya 08028 Barcelona Spain

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Uncovering QTL for resistance and survival time to Philasterides dicentrarchi in turbot (Scophthalmus maximus)

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ANIMAL GENETICS 2013年第2期44卷 149-157页

作者： Rodriguez-Ramilo, S. T. Fernandez, J. Toro, M. A. Bouza, C. Hermida, M. Fernandez, C. Pardo, B. G. Cabaleiro, S. Martinez, P. Univ Vigo Fac Biol Dept Bioquim Genet & Inmunol Vigo 36310 Spain Inst Nacl Invest & Tecnol Agr & Alimentaria Dept Mejora Genet Anim Madrid 28040 Spain Univ Politecn Madrid Dept Anim Prod ETS Ingenieros Agronomos E-28040 Madrid Spain Univ Santiago de Compostela Fac Vet Dept Genet Lugo 27002 Spain Cluster Acuicultura Galicia CETGA La Coruna 15965 Spain

Disease resistance-related traits have received increasing importance in aquaculture breeding programs worldwide. Currently, genomic information offers new possibilities in breeding to address the improvement of this kind of traits. The turbot is one of the most promising European aquaculture species, and Philasterides dicentrarchi is a scuticociliate parasite causing fatal disease in farmed turbot. An appealing approach to fight against disease is to achieve a more robust broodstock, which could prevent or diminish the devastating effects of scuticociliatosis on farmed individuals. In the present study, a genome scan for quantitative trait loci (QTL) affecting resistance and survival time to *** in four turbot families was carried out. The objectives were to identify QTL using different statistical approaches [linear regression (LR) and maximum likelihood (ML)] and to locate significantly associated markers for their application in genetic breeding strategies. Several genomic regions controlling resistance and survival time to *** were detected. When analyzing each family separately, significant QTL for resistance were identified by the LR method in two linkage groups (LG1 and LG9) and for survival time in LG1, while the ML methodology identified QTL for resistance in LG9 and LG23 and for survival time in LG6 and LG23. The analysis of the total data set identified an additional significant QTL for resistance and survival time in LG3 with the LR method. Significant association between disease resistance-related traits and genotypes was detected for several markers, a single one explaining up to 22% of the phenotypic variance. Obtained results will be essential to identify candidate genes for resistance and to apply them in marker-assisted selection programs to improve turbot production.

关键词： linear regression method maximum likelihood method quantitative trait loci scuticociliatosis turbot

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Optimal Operation Study of Qing River Cascade Reservoirs Based on GA with Uncertainty and Flow Transmission Considered

Optimal Operation Study of Qing River Cascade Reservoirs Bas...

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International Conference on Modern Hydraulic Engineering (CMHE)

作者： Zhou, Ran Yang, Kan Hohai Univ Coll Hydrol & Water Resources Nanjing 210098 Jiangsu Peoples R China

This paper presented a simulation method which considers the uncertainty and flow transmission in optimal operation of Qing River cascade reservoirs. Latin hypercube method was applied to simulate the uncertain inflow, and its sampling frequency and accuracy were very satisfied. linear regression method was used to deal with the damping and deformation in the process of flow transmission. And Genetic algorithm(GA) was found application for solving the optimal operation model of Qing River cascade reservoirs. According to the method presented we could obtain the scheduling scheme of cascade reservoirs under different risk rates which were helpful to the decision-making. The result showed that the method is practical. (C) 2012 Published by Elsevier Ltd. Selection and/or peer-review under responsibility of Society for Resources, Environment and Engineering

关键词： Qing River cascade reservoirs Latin hypercube Flow transmission linear regression method Genetic algorithm

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Optimal Operation Study of Qing River Cascade Reservoirs Based on GA with Uncertainty and Flow Transmission Considered

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Procedia Engineering 2012年 28卷 448-452页

作者： Ran Zhou Kan Yang College of Hydrology and Water Resources Hohai UniversityNo.1Xikang RoadGulou District Nanjing 210098China

关键词： Qing River cascade reservoirs Latin hypercube Flow transmission linear regression method Genetic algorithm

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Determination of alcohol content in water alcohol hydrates using near-infrared spectroscopy and segmentation regression model

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TRANSACTIONS OF THE INSTITUTE OF MEASUREMENT AND CONTROL 2011年第5期33卷 479-493页

作者： Jin, X. D. Zhao, Z. M. Zhang, L. Yu, X. L. Nanjing Univ Aeronaut & Astronaut Coll Sci Nanjing 210016 Peoples R China CSIRO Mat Sci & Engn Highett Vic 3190 Australia Nanjing Univ Aeronaut & Astronaut Coll Automat Engn Nanjing 210016 Peoples R China

This paper puts forward a measurement method of alcohol content in the mixture of water and alcohol based on near-infrared spectroscopy and segmentation regression model. The wavelengths, which are 1580, 2081 and 2309 nm, are picked out as three characteristic absorption wavelengths of alcohol, whereas 1206, 1456 and 1936 nm are picked out as three characteristic absorption wavelengths of water. The characteristic absorbance has a linear relationship to the alcohol concentration in the sample according to the principle of Lambert. Multiple linear regression equations 1 and 2 are built respectively based on the characteristic absorbance of alcohol and water, and the alcohol concentration is calculated using these two equations. However, the representative characteristic of overtone and combination absorption will change as the concentration of composing component changes so that the measuring effects of different regression equations, which are built by characteristic absorption values of different component, are different in the measurement of different concentration samples. In order to improve the prediction accuracy, this paper adopts the segmentation regression model equation to calculate the alcohol concentration in the sample, ie, we use equation 2 to calculate the alcohol concentration for the low alcohol content samples and use equation 1 to calculate the alcohol concentration for the samples of alcohol concentration between 50% and 70%;on the other hand, we use the mean calculation of equations 1 and 2 as prediction for the high alcohol concentration samples. The adoption of the regression model equation can reduce the mean prediction error for the samples in different alcohol concentrations without increasing the complexity of the equation. Nevertheless, we need to obtain the approximate value of alcohol concentration first in order to determine the distribution range of alcohol concentration.

关键词： alcohol concentration characteristic absorption wavelength linear regression method near-infrared analysis segmentation regression model

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Convergence and uncertainty analyses in Monte-Carlo based sensitivity analysis

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ENVIRONMENTAL MODELLING & SOFTWARE 2011年第4期26卷 444-457页

作者： Yang, Jing Univ Guelph Dept Geog Guelph ON N1G 2W1 Canada

Sensitivity analysis plays an important role in model development, calibration, uncertainty analysis, scenario analysis, and, hence, decision making. With the availability of different sensitivity analysis techniques, selecting an appropriate technique, monitoring the convergence and estimating the uncertainty of the sensitivity indices are very crucial for environmental modelling, especially for distributed models due to their high non-linearity, non-monotonicity, highly correlated parameters, and intensive computational requirements. It would be useful to identify whether some techniques outperform others with respect to computational requirements, reliability, and other criteria. This paper proposes two methods to monitor the convergence and estimate the uncertainty of sensitivity analysis techniques. One is based on the central limit theorem and the other on the bootstrap technique. These two methods are implemented to assess five different sensitivity analysis techniques applied to an environmental model. These techniques are: the Sobol' method, the Morris method, linear regression (LR), Regionalized Sensitivity Analysis (RSA), and non-parametric smoothing. The results show that: (i) the Sobol' method is very robust in quantifying sensitivities and ranking parameters despite a large number of model evaluations;(ii) the Morris method is efficient to rank out unimportant parameters at a medium cost;(iii) the non-parametric smoothing is reliable and robust in quantifying the main effects and low-order interactions while requiring a small number of model evaluations;finally (iv) the other two techniques, that is, LR and RSA, should be used with care. (C) 2010 Elsevier Ltd. All rights reserved.

关键词： Sensitivity analysis Uncertainty analysis Sobol' method Morris method linear regression method Regionalized sensitivity analysis Non-parametric smoothing

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Application of thermal sums concept to estimate the time to harvest new banana hybrids for export

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SCIENTIA HORTICULTURAE 2011年第1期129卷 52-57页

作者： Umber, Marie Paget, Benedicte Hubert, Olivier Salas, Irene Salmon, Frederic Jenny, Christophe Chillet, Marc Bugaud, Christophe CIRAD UMR QUALISUD F-97285 Lamentin Martinique France CIRAD UR Ameliorat Genet Especes Multiplicat Vegetat F-97130 Capesterre Belle Eau Guadeloupe France CIRAD UMR QUALISUD F-97130 Capesterre Belle Eau Guadeloupe France CIRAD UMR QUALISUD Sao Paulo Brazil Univ Sao Paulo Dpto Alimentos & Nutr Expt USP FCF Sao Paulo Brazil

Application of the thermal sum concept was developed to determine the optimal harvesting stage of new banana hybrids to be grown for export. It was tested on two triploid hybrid bananas, FlhorBan 916 (F916) and FlhorBan 918 (F918), created by CIRAD's banana breeding programme, using two different approaches. The first approach was used with F916 and involved calculating the base temperature of bunches sampled at two sites at the ripening stage, and then determining the thermal sum at which the stage of maturity would be identical to that of the control Cavendish export banana. The second approach was used to assess the harvest stage of F918 and involved calculating the two thermal parameters directly, but using more plants and a longer period. Using the linear regression model, the estimated thermal parameters were a thermal sum of 680 degree-days (dd) at a base temperature of 17.0 degrees C for cv. F916, and 970 dd at 13.9 degrees C for cv. F918. This easy-to-use method provides quick and reliable calculations of the two thermal parameters required at a specific harvesting stage for a given banana variety in tropical climate conditions. Determining these two values is an essential step for gaining insight into the agronomic features of a new variety and its potential for export. (C) 2011 Elsevier B.V. All rights reserved.

关键词： Musa Hybrid linear regression method Base temperature Thermal sum Green life

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STUDY ON QUANTITATIVE RETRIEVAL OF SOIL NUTRIENTS

STUDY ON QUANTITATIVE RETRIEVAL OF SOIL NUTRIENTS

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IEEE International Geoscience and Remote Sensing Symposium (IGARSS)

作者： Dong, Heng Chen, Chao Wang, Jinliang Qin, Qiming Jiang, Hongbo Zhang, Ning Liu, Mingchao Peking Univ Inst Remote Sensing & Geog Informat Syst Beijing 100871 Peoples R China

ISBN: (纸本)9781457710056

Soil spectral reflectance is affected by soil physicochemical characteristics and the physical basis of the soil remote sensing. Generally, the impact factors of the soil spectral features include water content, organic matter content, iron oxides content, physical composition and the parent material. In this study, a portable ASD FieldSpec Pro FR was used to collect the spectra of soil samples. The sensitive bands were selected by analyzing the relationship between nutrients and soil spectral features. Then the inversion models of soil nitrogen and organic were established by linear regression separately. The result showed that the content of soil nitrogen and soil organic can be well retrieved from remote sensing.

关键词： Soil spectral reflectance Soil nutrients linear regression method

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