Two topographic maps for data visualisation

We review a new form of self-organizing map which is based on a nonlinear projection of latent points into data space, identical to that performed in the Generative Topographic Mapping (GTM) [Bishop et al. (1997) Neurl Comput 10(1): 215–234]. But whereas the GTM is an extension of a mixture of experts, our new model is an extension of a product of experts [Hinton (2000) Technical report GCNU TR 2000-004, Gatsby Computational Neuroscience Unit, University College, London]. We show visualisation results on some real data sets and compare with the GTM. We then introduce a second mapping based on harmonic averages and show that it too creates a topographic mapping of the data. We compare these mappings on real and artificial data sets. Responsible editor: Soumen Chakrabarti.     

Spectral color reproduction minimizing spectral and perceptual color differences

In this article, we are combining minimization criteria in the colorant separation process for spectral color reproduction. The colorant separation is performed by inverting a spectral printer model: the spectral Yule‐Nielsen modified Neugebauer model. The inversion of the spectral printer model is an optimization operation in which a criterion is minimized at each iteration. The approach we proposed minimizes a criterion defined by the weighted sum of a spectral difference and a perceptual color difference. The weights can be tuned with a parameter α ∞ [0, 1]. Our goal is to decrease the spectral difference between the original data and its reproduction and also to consider perceptual color difference under different illuminant conditions. In order to find the best α value, we initially compare a pure colorimetric criterion and a pure spectral criterion for the reproduction, then we combine them. We perform four colorant separations: the first separation will minimize the 1976 CIELAB color difference where four illuminants are tested, the second separation will minimize an equally weighted summation of 1976 CIELAB color difference with the four illuminants tested independently, the third colorant separation will minimize a spectral difference, and the fourth colorant separation will combine a weighted sum of a spectral difference and one of the two first colorimetric differences previously introduced. This last colorant separation can be tuned with a parameter in order to emphasize on spectral or colorimetric difference. We use a six colorants printer with artificial inks for our experiments. The prints are simulated by the spectral Yule‐Nielsen modified Neugebauer model. Two groups of data are used for our experiments. The first group describes the data printed by our printing system, which is represented by a regular grid in colorant space of the printer and the second group describes the data which is not originally produced by our printing system but mapped to the spectral printer gamut. The Esser test chart and the Macbeth Color Checker test chart have been selected for the second group. Spectral gamut mapping of this data is carried out before performing colorant separation. Our results show improvement for the colorant separations combining a sum of 1976 CIELAB color difference for a set of illuminants and for the colorant separation combining a sum of 1976 CIELAB color difference and spectral difference, especially in the case of spectral data originally produced by the printer. © 2008 Wiley Periodicals, Inc. Col Res Appl, 33, 494–504, 2008     

Perceptual evaluation of color gamut mapping algorithms

The recommendation of the CIE has been followed as closely as possible to evaluate the accuracy of five color gamut mapping algorithms (GMAs)—two nonspatial and three spatial algorithms—by psychophysical experiments with 20 test images, 20 observers, one test done on paper and a second one on display. Even though the results do not show any overall “winner,” one GMA is definitely perceived as not accurate. The importance of a high number of test images to obtain robust evaluation is underlined by the high variability of the results depending on the test images. Significant correlations between the percentage of out‐of‐gamut pixels, the number of distinguishable pairs of GMAs, and the perceived difficulty to distinguish them have been found. The type of observers is also important. The experts, who prefer a spatial GMA, show a stronger consensus and look especially for a good rendering of details, whereas the nonexperts hardly make a difference between the GMAs. © 2008 Wiley Periodicals, Inc. Col Res Appl, 33, 470–476, 2008     

河南油田泌阳凹陷稠油地化录井评价方法

河南油田泌阳凹陷分布有古城、井楼、杨楼、新庄4个稠油油田，各油田油质复杂，查清各区块、各层系稠油油质是开发生产的重要工作之一。通过对稠油层基本特征分析，应用地化录井参数建立了TPI评价法、原油密度评价法及原油黏度评价法。TPI评价法主要是利用原油中气态烃和液态烃与全烃比值大小划分油质类型；原油密度评价法主要利用油质重，TPI值小，反之TPI值大的关系划分油质类型；原油黏度评价法主要利用TPI反映油质组分的综合性参数的特点，建立TPI与黏度的关系。这套评价评价方法提供了快速精细评价稠油油质的新手段。     

In Search of the "Ideal" Pear (pyrus spp.): Results of a Multidisciplinary Exploration

Preference mapping with 10 pears identified 3 segments among New Zealand consumers. While 1 segment preferred ripe European cultivars, another rejected only the seedling with strong off‐flavors. A 3rd segment combined the 2 former segments, but also rejected 2 hybrid samples. Survey responses to the question “To me, the ideal pear is ?” from a 2nd consumer sample confirmed the general preference for juicy and sweet pears, the key characteristics of ripeness. A separate appearance evaluation revealed 4 segments based on color and shape. Combining information from several sources resulted in suggestions for new breeding directions for pears, while highlighting the importance of appearance and the need for more extensive measurements.     

Mapping the Characteristics of a 'Good' Play Therapist.

In this pilot study, concept mapping, a methodological approach combining qualitative and quantitative analytic strategies, was used to identify the therapist qualities, competencies, and skills necessary for effective play therapy outcomes as perceived by a sub-sample of 28 experienced play therapists who are members of the Association for Play Therapy (APT). The clusters associated with the therapeutic relationship and facilitative skills (e.g., empathy, warmth, and genuineness) were rated as the most essential skills to possess and also as the most difficult to develop. In contrast, the clusters associated with play therapy interventions and theories were rated as the least important skills to possess but as the easiest to acquire. The findings are discussed, with implications for therapeutic practice, research, and policy. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Mapping of the Saccharomyces cerevisiae CDC3, CDC25, and CDC42 genes to chromosome XII by chromosome blotting and tetrad analysis

CDC3, CDC25 and CDC42 were localized to chromosome XII by hybridizing the cloned genes to Southern blots of chromosomes separated by orthogonal-field-alternation gel electrophoresis. Meiotic tetrad analyses further localized these genes to the region distal to the RDN1 locus on the right arm of the chromosome. The STE11 gene, which had previously been mapped to chromosome XII (Chaleff and Tatchell, 1985), was found to be tightly linked to ILV5. The data suggest a map order of CEN12-RDN1-CDC42-(CDC25-CDC3)-(ILV5- STE11)-URA4. Certain oddities of the data set raise the possibility that there may be constraints on the patterns of recombination in this region of chromosome XII.     

Monitoring water quality in reservoirs with IRS-1A-LISS-I

An attempt has been made to quantify the relationship between the variation in IRS-IA-LISS-I (Indian Remote Sensing Satellite-1A Linear Imaging Self-Scanning System) radiance data and field measured change in secchi disc depth. Secchi disc depth was measured for 47 predetermined sampling locations on reservoir surface water. At extinction depth (secchi depth), water samples were collected from all the sampling locations. Suspended sediments of eight locations representing various reaches of the reservoir were selected for mineralogical, particle size and optical properties analysis. The LISS-I radiance value in band 1 (0.45–0.52µm) band 2 (0-52–0.59 µm) and band 3 (0.62–0.68 µm) were used in a regression analysis. The absorption infrared band 4 (0.77–0.86 µm) was not included in the analysis. In these, the dependable variable was secchi depth (SD) and the LISS-I-radiance data was the estimator variable. Forty-seven data sets of 20 October 1988 from Tawa reservoir surface water were used to obtain an estimator equation for SD. The verification of the estimator equation was tested by applying it to a data set of 21 measurements of 28 September 1988 for this reservoir. The coefficient of correlation between observed and estimated values for the 28 September 1988 data set wasr=0.92 for SD, indicating that the equation could accurately predict the water clarity (SD) for this reservoir on new occasions from IRS-IA-LISS-I spectral data. It is shown that mineral composition and optical properties of suspended sediments influence the reflected radiance of water quality. It is concluded that IRS-IA-LISS-I data provide a useful means of mapping water quality in reservoir.     

2006年中国钨工业发展报告

综述了2006年我国钨工业发展现状,分析了钨工业经济运行的政策环境、产业结构、市场供需、竞争态势,指出了当前钨工业发展中的几个突出问题,并提出了相应的对策建议。     

Improved wetland remote sensing in Yellowstone National Park using classification trees to combine TM imagery and ancillary environmental data

The U.S. Fish and Wildlife Service uses the term palustrine wetland to describe vegetated wetlands traditionally identified as marsh, bog, fen, swamp, or wet meadow. Landsat TM imagery was combined with image texture and ancillary environmental data to model probabilities of palustrine wetland occurrence in Yellowstone National Park using classification trees. Model training and test locations were identified from National Wetlands Inventory maps, and classification trees were built for seven years spanning a range of annual precipitation. At a coarse level, palustrine wetland was separated from upland. At a finer level, five palustrine wetland types were discriminated: aquatic bed (PAB), emergent (PEM), forested (PFO), scrub-shrub (PSS), and unconsolidated shore (PUS). TM-derived variables alone were relatively accurate at separating wetland from upland, but model error rates dropped incrementally as image texture, DEM-derived terrain variables, and other ancillary GIS layers were added. For classification trees making use of all available predictors, average overall test error rates were 7.8% for palustrine wetland/upland models and 17.0% for palustrine wetland type models, with consistent accuracies across years. However, models were prone to wetland over-prediction. While the predominant PEM class was classified with omission and commission error rates less than 14%, we had difficulty identifying the PAB and PSS classes. Ancillary vegetation information greatly improved PSS classification and moderately improved PFO discrimination. Association with geothermal areas distinguished PUS wetlands. Wetland over-prediction was exacerbated by class imbalance in likely combination with spatial and spectral limitations of the TM sensor. Wetland probability surfaces may be more informative than hard classification, and appear to respond to climate-driven wetland variability. The developed method is portable, relatively easy to implement, and should be applicable in other settings and over larger extents.