Experimental identification of physical parameters of fluid-filled pipes using acoustical signal processing

A method is formulated for the identification of an unknown physical parameter of a fluid-filled pipe using the measurement of sound speed in the pipe. The method uses a simple formula which provides the relationship between the sound speed and a few physical parameters of the pipe: thickness, diameter, wall material constants and fluid constants. Once the sound speed in the pipe is measured, the simple formula can be used to extract one of the unknown parameters providing the remaining ones are known.The sound speed in the pipe is measured using a 3-transducer array. In order to demonstrate the potential of the technique the results of several measurements obtained in a water-filled steel pipe are presented.The required accuracy of the measurement of sound speed and of the specification of known parameters is analysed. The accuracy depends on the unknown parameter which is to be identified. For example, if the pipe thickness is the unknown parameter, the other parameters have to be known within a very narrow margin of error. On the contrary, if the fluid properties have to be identified the needed accuracy of known parameters gets much lower.     

Temperature effect on deposition rate of silicon nitride films

Temperature effects on deposition rate of silicon nitride films were characterized by building a neural network prediction model. The silicon nitride films were deposited by using a plasma enhanced chemical vapor deposition system and process parameter effects were systematically characterized by 2⁶⁻¹ fractional factorial experiment. The process parameters involved include a radio frequency power, pressure, temperature, SiH₄, N₂, and NH₃ flow rates. The prediction performance of generalized regression neural network was drastically improved by optimizing multi-valued training factors using a genetic algorithm. Several 3D plots were generated to investigate parameter effects at various temperatures. Predicted variations were experimentally validated. The temperature effect on the deposition rate was a complex function of parameters but N₂ flow rate. Larger decreases in the deposition rate with the temperature were only noticed at lower SiH₄ (or higher NH₃) flow rates. Typical effects of SiH₄ or NH₃ flow rate were only observed at higher or lower temperatures. A comparison with the refractive index model facilitated a selective choice of either SiH₄ or NH₃ for process optimization.     

On-line arbitrarily vertex decomposable trees

A tree T is arbitrarily vertex decomposable if for any sequence τ of positive integers adding up to the order of T there is a sequence of vertex-disjoint subtrees of T whose orders are given by τ. An on-line version of the problem of characterizing arbitrarily vertex decomposable trees is completely solved here.     

喷气式Z箍缩等离子体辐射软X射线能谱的研究

研制了一台五通道ROSS-FILTER-PIN软X射线能谱仪，能谱范围为0.28—1.56keV.它由5个连续能段组成，每个能段的起止边由罗斯滤片对(ROSS-FILTERS)的L或K吸收边确定.罗斯滤片对的厚度通过优化计算得到，为了使每个通道的灵敏区外响应(即所测能段外响应)与通道总响应之比最小，在滤片对的第二滤片上镀上了一定厚度的第一滤片材料；为了缩减滤片表面积以增强低能滤片的抗冲击能力及方便滤片加工，能谱仪采用了小探测面积的PIN探测器(1mm²).借助此能谱仪，测量得到了喷气式Z箍缩(Z-pinch)等离子体辐射软X射线能谱的分布，并研究了软X射线产额随箍缩状况的变化趋势. 关键词： Z箍缩等离子体 罗斯滤片 软X射线能谱     

Formation of functional groups on graphite during oxygen plasma treatment

Improved sample wettability was obtained by oxygen plasma functionalization of pyrolytic graphite. The samples were exposed to highly dissociated oxygen plasma with the density of 1 × 10¹⁶ m⁻³, the electron temperature of about 5.5 eV and the density of neutral oxygen atoms of 8 × 10²¹ m⁻³ for 20 s. The surface wettability was measured by a contact angle of water drop. The contact angle dropped from original 112° down to about 1°. The functional groups were detected by XPS analyses. The survey spectrum showed a substantial increase of oxygen concentration on the surface, while high-resolution analyses showed additional oxygen was bonded onto the graphite surface in the form of C-O polar functional group responsible for the increase of the surface energy.     

Theoretical and numerical analysis on multispectral bioluminescence tomography

Recently, molecular imaging has been rapidly developed to studyphysiological and pathological processes in vivo at the cellularand molecular levels. Among molecular imaging modalities, opticalimaging has attracted a major attention for its unique advantages.In this paper, we establish a mathematical framework for multispectralbioluminescence tomography (BLT) that allows simultaneous studiesof multiple optical reporters. We show solution existence, uniquenessand continuous dependence on data as well as the limiting behaviourswhen the regularization parameter approaches zero or when thepenalty parameter approaches infinity. Then, we propose twonumerical schemes for multispectral BLT and derive error estimatesfor the corresponding solutions.     

Students’ Reasoning About One-Object Stochastic Phenomena in an ICT-Environment

This paper focuses on the different ways in which students in lower secondary school (14–16 year olds) experience compound random events, presented to them in the form of combined junctions. A carefully designed ICT environment was developed enabling the students to interact with different representations of such structures. Data for the analysis was gathered from two interview sessions. The analysis of the interaction is based on constructivist principles on learning; i.e. we adopted a student-oriented perspective, taking into consideration the different ways students try to make sense of chance encounters. Our results show how some students give priority to geometrical and physical concerns, and we discuss how seeking causal explanations of random phenomena may have encouraged this. With respect to numerically oriented models a division strategy appears to stand out as the preferred one.     

A note on model diagnostics in longitudinal data analysis

Longitudinal study has become one of the most commonly adopted designs in medical research. The generalized estimating equations (GEE) method and/or mixed effects models are employed very often in causal inferences. The related model diagnostic procedures are not yet fully formalized, and perhaps never will be. The potential causes of major problems are the high variety of the dependence within subjects and/or the number of repeated measurements. A single testing procedure, e.g., run test, is not possible to resolve all model diagnostics problems in longitudinal data analysis. Multiple quantitative indexes for model diagnostics are needed to take into account this variety. We propose eight testing procedures for randomness accompanied with some conventional and/or non-conventional plots to remedy model diagnostics in longitudinal data analysis. The proposed issue in this paper is well illustrated with four clinical studies in Taiwan.