Theoretical measurement uncertainty of white-light interferometry on rough surfaces

A great advantage of the white-light interferometry is that it can be used for profile objects with a rough surface. A speckle pattern that arises in the image plane allows one to observethe interference; however, this pattern is also the source of the measurement uncertainty. We derive the theoretical limits of the longitudinal uncertainty by virtue of the first-order statistics of thespeckle pattern. It is shown that this uncertainty depends on the surface roughness of the measured object only; it does not depend on the setup parameters.     

Aerosol counterflow two-jets unit for continuous measurement of the soluble fraction of atmospheric aerosols

A new type of aerosol collector employing a liquid at laboratory temperature for continuous sampling of atmospheric particles is described. The collector operates on the principle of a Venturi scrubber. Sampled air flows at high linear velocity through two Venturi nozzles "atomizing" the liquid to form two jets of a polydisperse aerosol of fine droplets situated against each other. Counterflow jets of droplets collide, and within this process, the aerosol particles are captured into dispersed liquid. Under optimum conditions (air flow rate of 5 L/min and water flow rate of 2 mL/min), aerosol particles down to 0.3 microm in diameter are quantitatively collected in the collector into deionized water while the collection efficiency of smaller particles decreases. There is very little loss of fine aerosol within the aerosol counterflow two-jets unit (ACTJU). Coupling of the aerosol collector with an annular diffusion denuder located upstream of the collector ensures an artifact-free sampling of atmospheric aerosols. Operation of the ACTJU in combination with on-line detection devices allows in situ automated analysis of water-soluble aerosol species (e.g., NO2-, NO3-)with high time resolution (as high as 1 s). Under the optimum conditions, the limit of detection for particulate nitrite and nitrate is 28 and 77 ng/m(3), respectively. The instrument is sufficiently rugged for its application at routine monitoring of aerosol composition in the real time.     

Conditions and features of matrix and bulk carbonization of the organic precursors

Comparative research of matrix and bulk carbonization of some organic precursors (sucrose, acetonitrile) in silica mesoporous materials SBA-15 and KIT-6 was conducted. X-ray diffraction, nitrogen adsorption analysis, Raman spectroscopy were used for determination of the structural-sorption characteristics of the obtained materials. It was shown that the carbon mesoporous materials CMK-8 obtained in the mesopores of KIT-6 had higher adsorption characteristics because of features of three-dimensional cubic structure, larger pore volume and framework’s wall thickness. It was established that partially graphitized spatially well-organized carbon materials were formed as a result of pyrolysis of acetonitrile in the silica matrices SBA-15 and KIT-6. It was conditioned by the absence of considerable spatial limitations for growth of graphite structures on the initial stage of the synthesis when the pores of the matrix were not filled up with the organic precursor. Product of bulk carbonization of sucrose is compact carbon microporous framework with low sorption characteristics (micropore volume is 0.09 cm³/g).     

Fault-tolerant data management in the gaston peer-to-peer file system

Gaston is a peer-to-peer large-scale file system designed to provide a fault-tolerant and highly available file service for a virtually unlimited number of users. Data management in Gaston disseminates and stores replicas of files on multiple machines to achieve the requested level of data availability and uses a dynamic tree-topology structure to connect replication schema members. We present generic algorithms for replication schema creation and maintenance according to file user requirements and autonomous constraints that are set on individual nodes. We also show specific data object structure as well as mechanisms for secure and efficient update propagation among replicas with data consistency control. Finally, we introduce a scalable and efficient technique improving fault-tolerance of the tree-topology structure connecting replicas.     

Cascade Generalization

Using multiple classifiers for increasing learning accuracy is an active research area. In this paper we present two related methods for merging classifiers. The first method, Cascade Generalization, couples classifiers loosely. It belongs to the family of stacking algorithms. The basic idea of Cascade Generalization is to use sequentially the set of classifiers, at each step performing an extension of the original data by the insertion of new attributes. The new attributes are derived from the probability class distribution given by a base classifier. This constructive step extends the representational language for the high level classifiers, relaxing their bias. The second method exploits tight coupling of classifiers, by applying Cascade Generalization locally. At each iteration of a divide and conquer algorithm, a reconstruction of the instance space occurs by the addition of new attributes. Each new attribute represents the probability that an example belongs to a class given by a base classifier. We have implemented three Local Generalization Algorithms. The first merges a linear discriminant with a decision tree, the second merges a naive Bayes with a decision tree, and the third merges a linear discriminant and a naive Bayes with a decision tree. All the algorithms show an increase of performance, when compared with the corresponding single models. Cascade also outperforms other methods for combining classifiers, like Stacked Generalization, and competes well against Boosting at statistically significant confidence levels.     

Computing Color Transforms with Applications to Image Editing

In this paper, we present a unified approach for the problem of computing color transforms, applications of which include shadow removal and object recoloring. We propose two algorithms for transforming colors. In the first algorithm, the detection of source and target regions is performed using a Bayesian classifier. Given these regions, the computed transform alters the color properties of the target region so as to closely resemble those of the source region. The proposed probabilistic formulation leads to a linear program (similar to the classic Transportation Problem), which computes the desired transformation between the target and source distributions. In the second algorithm, the detection and transformation steps are united into a single unified approach; furthermore, the continuity of the transformation arises more intrinsically within this algorithm. Both formulations allow the target region to acquire the properties of the source region, while at the same time retaining its own look and feel. Promising results are shown for a variety of applications.     

On optimal node spacing for immersed boundary–lattice Boltzmann method in 2D and 3D

A computational study on optimal spacing of Lagrangian nodes discretizing a rigid and immobile immersed body boundary in 2D and 3D is presented in order to show how the density of the Lagrangian points affects the numerical results of the Immersed Boundary–Lattice Boltzmann Method (IB–LBM). The study is based on the implicit velocity correction-based IB–LBM proposed by Wu and Shu (2009, 2010) that allows computing the fluid–body interaction force. However, the (original) method fails for densely spaced Lagrangian points due to ill-conditioned or even singular linear systems that arise from the derivation of the method. We propose a modification that improves the solvability of the linear systems and compare the performance of both methods using several benchmark problems. The results show how the spacing of the Lagrangian points affects the numerical results, mainly the permeability of the discretized body boundary in applications to fluid flows over rigid obstacles and blood flows in arteries in 2D and 3D.     

Diffusion-Inspired Shrinkage Functions and Stability Results for Wavelet Denoising

We study the connections between discrete one-dimensional schemes for nonlinear diffusion and shift-invariant Haar wavelet shrinkage. We show that one step of a (stabilised) explicit discretisation of nonlinear diffusion can be expressed in terms of wavelet shrinkage on a single spatial level. This equivalence allows a fruitful exchange of ideas between the two fields. In this paper we derive new wavelet shrinkage functions from existing diffusivity functions, and identify some previously used shrinkage functions as corresponding to well known diffusivities. We demonstrate experimentally that some of the diffusion-inspired shrinkage functions are among the best for translation-invariant multiscale wavelet denoising. Moreover, by transferring stability notions from diffusion filtering to wavelet shrinkage, we derive conditions on the shrinkage function that ensure that shift invariant single-level Haar wavelet shrinkage is maximum–minimum stable, monotonicity preserving, and variation diminishing.First online version published in June, 2005     

南极冰钻钻井液应用性试验研究

钻井液的性质及性能参数对于南极科学钻探有着重要的影响。钻井液除了必须要具备合适的粘度和密度,以满足冷却钻头、平衡孔壁压力、携带冰屑、清洁孔底的要求外,钻井液的性质如导电性、导热性及其腐蚀性对于保证钻具的正常工作、输送孔内信息也有着重要的影响。根据目前已经在南极使用的钻井液类型,分别对6种介质(国产硅油-3cst、KF96硅油-2cst、丁酸乙酯、丁酸丁酯、丁酸戊酯、丙酸丙酯)在不同温度下的电导率、导热系数和对密封件的腐蚀性进行了试验测试,选出了适合南极应用的钻井液类型及在钻具中使用的密封件材质,可供极地钻探选择钻井液类型及钻具设计提供重要的参考。