Wettability and surface energy of parylene F deposited on PDMS

For the first time, the wettability and surface energy of parylene F were investigated. The results showed that parylene F had a hydrophobic surface with an eigen water contact angle of 104.7 ± 0.6°. We found that 3.5 μl probe liquid was an optimal value for the contact angle measurement of parylene F. Moreover, we found that the Lifshitz–van der Waals/acid–base approach was unsuitable for determining the surface energy of parylene F, whereas the Owens–Wendt–Kaelble approach and the limitless liquid–solid interface wetting system were compatible. The surface energy of parylene F was estimated to be 27.06 mJ/m² (Owens–Wendt–Kaelble) and 40.41 mJ/m² (Limitless liquid-solid interface wetting system). Furthermore, this investigation also provided a reference for the applications of empirical and physics-based semi-empirical approaches for the estimation of surface energy.     

The Application of Fractal Transform and Entropy for Improving Fault Tolerance and Load Balancing in Grid Computing Environments

This paper applies the entropy-based fractal indexing scheme that enables the grid environment for fast indexing and querying. It addresses the issue of fault tolerance and load balancing-based fractal management to make computational grids more effective and reliable. A fractal dimension of a cloud of points gives an estimate of the intrinsic dimensionality of the data in that space. The main drawback of this technique is the long computing time. The main contribution of the suggested work is to investigate the effect of fractal transform by adding R-tree index structure-based entropy to existing grid computing models to obtain a balanced infrastructure with minimal fault. In this regard, the presented work is going to extend the commonly scheduling algorithms that are built based on the physical grid structure to a reduced logical network. The objective of this logical network is to reduce the searching in the grid paths according to arrival time rate and path’s bandwidth with respect to load balance and fault tolerance, respectively. Furthermore, an optimization searching technique is utilized to enhance the grid performance by investigating the optimum number of nodes extracted from the logical grid. The experimental results indicated that the proposed model has better execution time, throughput, makespan, latency, load balancing, and success rate.     

A genetic resampling particle filter for freeway traffic-state estimation

On-line estimation of the state of traffic based on data sampled by electronic detectors is important for intelligent traffic management and control.Because a nonlinear feature exists in the traffic state,and because particle filters have good characteristics when it comes to solving the nonlinear problem,a genetic resampling particle filter is proposed to estimate the state of freeway traffic.In this paper,a freeway section of the northern third ring road in the city of Beijing in China is considered as the experimental object.By analysing the traffic-state characteristics of the freeway,the traffic is modeled based on the second-order validated macroscopic traffic flow model.In order to solve the particle degeneration issue in the performance of the particle filter,a genetic mechanism is introduced into the resampling process.The realization of a genetic particle filter for freeway traffic-state estimation is discussed in detail,and the filter estimation performance is validated and evaluated by the achieved experimental data.     

EPR-NMR Signal Enhancement with a Small Computer

A Digital Equipment Corporation PDP 8/S Computer is interfaced with an EPR Spectrameter to achieve signal enhancement.

A computer-based system for spectrum accumulation and noise averaging of EPR or NMR signals has been designed and implemented. The computer-based system was chosen over other perhaps more conventional systems because of its greater flexibility in the processing of spectra, especially after the accumulation is complete.(1)     

Internal inspection of semi-transparent objects by digital holographic micro-tomography

The combined use of digital holographic microscopy and computer tomography, here named digital holographic micro-tomography, is used to examine the interior of transparent channels. The proposed method is used to identify internal obstacles inside of transparent troughs having slightly different refractive index. The method is based in the acquisition of a set of digital holograms of the specimen whereas it is axially rotated from 0° to 180°. The phase differences retrieved from the obtained holograms are the inputs to a computerised axial tomography procedure. The technique has been numerically modelled in order to find the optimal tomographic conditions and also to realise the minimum difference of refractive index the method could detect. The obtained results show the feasibility of the proposed method for the non-destructive evaluation of transparent micro-objects.     

用极值频率法分析数字全息的记录条件

根据全息理论,通过分析全息图光栅结构的极值频率,利用抽样定理以及频谱分离条件,分析了离轴菲涅耳全息的记录条件,得到了不同于以往文献的最小记录距离及参考光源设置表达式,并做了计算机模拟验证.结果表明：用该方法推得的离轴菲涅耳全息最小记录距离和参考光设置表达式是正确的.只有同时满足抽样条件和频谱分离条件,才能得到高质量的再现像.     

Fast Encoding Method for Image Vector Quantization Based on Multiple Appropriate Features to Estimate Euclidean Distance

The encoding process of finding the best-matched codeword (winner) for a certain input vector in image vector quantization (VQ) is computationally very expensive due to a lot of k-dimensional Euclidean distance computations. In order to speed up the VQ encoding process, it is beneficial to firstly estimate how large the Euclidean distance is between the input vector and a candidate codeword by using appropriate low dimensional features of a vector instead of an immediate Euclidean distance computation. If the estimated Euclidean distance is large enough, it implies that the current candidate codeword could not be a winner so that it can be rejected safely and thus avoid actual Euclidean distance computation. Sum (1-D), L₂ norm (1-D) and partial sums (2-D) of a vector are used together as the appropriate features in this paper because they are the first three simplest features. Then, four estimations of Euclidean distance between the input vector and a codeword are connected to each other by the Cauchy–Schwarz inequality to realize codeword rejection. For typical standard images with very different details (Lena, F-16, Pepper and Baboon), the final remaining must-do actual Euclidean distance computations can be eliminated obviously and the total computational cost including all overhead can also be reduced obviously compared to the state-of-the-art EEENNS method meanwhile keeping a full search (FS) equivalent PSNR.     

Efficient inverse radiation analysis in a cylindrical geometry using a combined method of hybrid genetic algorithm and finite-difference Newton method

An inverse radiation problem was considered to estimate boundary conditions such as temperature distribution and emissivity in axisymmetric absorbing, emitting, and scattering medium, given the measured incident radiative heat fluxes. The finite-volume method was employed to solve a direct radiative transfer equation for a two-dimensional axisymmetric geometry. Various parameter estimators, such as conjugate-gradient method, hybrid genetic algorithm, and finite-difference Newton method, were employed to solve the inverse problems, while discussing their performances in terms of estimation accuracy and computational efficiency. Based on this, we proposed, as a best inverse analysis tool, a new combined method that adopted the hybrid genetic algorithm as an initial value selector and used the finite-difference Newton method as a parameter estimator.     

MASS TRANSFER EXPERIMENTS ON SINGLE IRREGULAR-SHAPED PARTICLES

Mass transfer from irregular-shaped naphthalene particles (100-200 inn in size) was studitd in an electrodynamic balance. Charged particles were suspended in an electrostatic field directly in line with a calibrated air jet. Mass and size change histories were obtained under ambient conditions, and under steady- and pulsed-flow conditions. For natural convection, the time-averaged Sherwood number was similar to that for spheres. Forced-convection Sherwood number under steady-flow conditions was strongly dependent on particle shape and panicle Reynolds number, and was consistently higher than values predicted for spheres at comparable Reynolds numbers. This study validates the technique and indicates the shape effect on mass transfer form single particles.     

Investigation of conditional source-term estimation applied to a non-premixed turbulent flame

A turbulent combustion model, Conditional Source-term Estimation (CSE) is applied to a non-premixed turbulent jet methane flame. The conditional chemical source terms are determined on the basis of first order closure and the conditional averaged species concentrations are obtained by inverting an integral equation. The Tikhonov method is implemented for regularisation. Detailed chemistry is tabulated using the trajectory generated low-dimensional manifold method. Radiation due to the gaseous species is included. Reynolds Averaged Navier–Stokes calculations are performed using two different turbulence models. The objectives of the paper are (i) assessment of the impact of the main numerical parameters in CSE and (ii) comparison of the CSE numerical predictions with available experimental data and results from previous simulations for the selected flame. The number of CSE domains and the number of points in each CSE domain are shown to have a significant impact on the results if not selected appropriately. The present CSE calculations always converge to unique and stable predictions. The corrected k–ε model yields mixture fraction profiles in good agreement with the experimental data values for axial locations in the first half of the flame. Farther downstream, the RNG k–ε model performs better. Overall, the current predictions for the mixture fraction are in good agreement with the experimental data. The predicted temperatures using CSE and the k–ε turbulence model with a modified value of C_ε1 = 1.47 are found to be in very good agreement with the experimental data. Further, the current CSE results are of comparable quality with previous simulations using the flamelet model and conditional moment closure. Future work may include further investigation on optimal determination of the regularisation parameter and alternative regularisation techniques, soot modelling within the CSE formulation, and improved formulation of radiation.