图库——CAD成图率上升的途径之一

图库——ＣＡＤ成图率上升的途径之一刘希宏（甘肃兰州铁道部第一勘测设计院桥隧处７３００００）收稿日期：１９９７年４月８日目前，ＣＡＤ技术在设计领域中得到了广泛应用，设计单位也从中受益非浅。主要是减轻了手工绘图的工作量，提高了工效。而且设计图纸质量高，设...

An ECT System Based on Improved RBF Network and Adaptive Wavelet Image Enhancement for Solid/Gas Two-phase Flow

Electrical capacitance tomography(ECT) is a non-invasive imaging technique that aims at visualizing the cross-sectional permittivity distribution and phase distribution of solid/gas two-phase flow based on the measured capacitance.To solve the nonlinear and ill-posed inverse problem:image reconstruction of ECT system,this paper proposed a new image reconstruction method based on improved radial basis function(RBF) neural network combined with adaptive wavelet image enhancement.Firstly,an improved RBF network was applied to establish the mapping model between the reconstruction image pixels and the capacitance values measured.Then,for better image quality,adaptive wavelet image enhancement technique was emphatically analyzed and studied,which belongs to a space-frequency analysis method and is suitable for image feature-enhanced.Through multi-level wavelet decomposition,edge points of the image produced from RBF network can be determined based on the neighborhood property of each sub-band;noise distribution in the space-frequency domain can be estimated based on statistical characteristics;after that a self-adaptive edge enhancement gain can be constructed.Finally,the image is reconstructed with adjusting wavelet coefficients.In this paper,a 12-electrode ECT system and a pneumatic conveying platform were built up to verify this image reconstruction algorithm.Experimental results demonstrated that adaptive wavelet image enhancement technique effectively implemented edge detection and image enhancement,and the improved RBF network and adaptive wavelet image enhancement hybrid algorithm greatly improved the quality of reconstructed image of solid/gas two-phase flow [pulverized coal(PC)/air].

Allocation of fixed transmission cost based on power flow tracing algorithm

In the electricity market, charging based on the traditional spot electricity price often results in the payment imbalance of electric network, and goes against the development of the power system. So, it is necessary to modify the spot price. The key of the modification lies in how to calculate the fixed unit transmission cost of each node, that is how to allocate the fixed transmission cost to users.To solve this problem, we develop a power flow tracing algrithm to modify the spot price. We put forward a path searching method based on the graph theory after studying the fundamental principle of power flow tracing and apply the method to the downstream tracing algorithm and upstream tracing algorithm according to the proportional distribution principle. Furthermore, to improve the computational efficiency of the algorithm, we introduce the branch expunction method to optimize the node order. By using the result of power flow tracing to get fixed node transmission cost and introducing it to modify the spot price, we obtain the synthetical price.The application to a 5-bus system prove the algorithm feasible.

An Image Analysis of Breast Thermograms

Thermography （infrared imaging） is a non-invasive technique applied for the detection breast cancer. We consider the problem of automatically recognition malignant breast from frontal view thermography image presented as gray scale image. This framework provides insights into several issues： breast Region of Interest （ROI） detection, extraction statistical features, extraction features based on texture and co-occurrence matrix.

Neural Mechanism in Emotion Regulation by Simultaneous Recording of EEG and fMRI

The combination of electroencephalogram (EEG) and functional magnetic resonance imaging(fMRI) is a very attractive aim in neuroscience in order to achieve both high temporal and spatial resolution for the non-invasive study of cognitive brain function. In this paper, we record simultaneous EEG-fMRI of the same subject in emotional processing experiment in order to explore the characteristics of different emotional picture processing, and try to find the difference of the subjects' brain hemisphere while viewing different valence emotional pictures. The late positive potential(LPP) is a reliable electrophysiological index of emotional perception in humans. According to the analysis results, the slow-wave LPP and visual cortical blood oxygen level-dependent (BOLD) signals are both modulated by the rated intensity of picture arousal. The amplitude of the LPP correlate significantly with BOLD intensity in visual cortex, amygdala, temporal area, prefrontal and central areas across picture contents.

Contribution of Ground-Based Cloud Observation to Satellite-Based Cloud Discrimination

One of the biggest factors to deteriorate the satellite product quality is cloud coverage. Therefore, cloud masking process is important to improve the quality of various satellite products. However, satellite-based cloud discrimination algorithm has been developing and efficient ground-based cloud observations are necessary to validate satellite-based cloud discrimination. The purpose of this study is to develop the efficient ground-based cloud observation methodology using whole sky camera. This paper deals with methods how to discriminate cloud portions on whole sky image, how to apply the ground-based cloud observation to the validations for satellite products. For the cloud discrimination on whole sky image, we propose SI （sky index） and BI （brightness index） calculated from RGB （red, green and blue） channels. SI shows the extent of the blueness and gray scale and BI indicates the extent of the brightness. Sun, cloud and blue sky portions are divided by SI and BI threshold. As an application of ground-based cloud observation for the validation of satellite products, clouds portions discriminated from whole sky image are projected onto ground surface with map coordinate. We also examine to compare with cloud portions on whole sky images and MODIS （MODerate resolution Imaging Spectroradiometer） image as one of experiments. The proposed ground-based cloud observation method and its extension to satellite-based cloud discrimination should be connected to improve the quality of satellite products.

Multi-scale MSDT inversion based on LAI spatial knowledge

Quantitative remote sensing inversion is ill-posed. The Moderate Resolution Imaging Spectroradiometer at 250 m resolution （MODIS_250m） contains two bands. To deal with this ill-posed inversion of MODIS_250m data, we propose a framework, the Multi-scale, Multi-stage, Sample-direction Dependent, Target-decisions （Multi-scale MSDT） inversion method, based on spa- tial knowledge. First, MODIS images （1 km, 500 m, 250 m） are used to extract multi-scale spatial knowledge. The inversion accuracy of MODIS_lkm data is improved by reducing the impact of spatial heterogeneity. Then, coarse-scale inversion is taken as prior knowledge for the fine scale, again by inversion. The prior knowledge is updated after each inversion step. At each scale, MODIS_lkm to MODIS_250m, the inversion is directed by the Uncertainty and Sensitivity Matrix （USM）, and the most uncertain parameters are inversed by the most sensitive data. All remote sensing data are involved in the inversion, during which multi-scale spatial knowledge is introduced, to reduce the impact of spatial heterogeneity. The USM analysis is used to implement a reasonable allocation of limited remote sensing data in the model space. In the entire multi-scale inversion process field data, spatial knowledge and multi-scale remote sensing data are all involved. As the multi-scale, multi-stage inversion is gradually refined, initial expectations of parameters become more reasonable and their uncertainty range is effectively reduced, so that the inversion becomes increasingly targeted. Finally, the method is tested by retrieving the Leaf Area Index （LAI） of the crop canopy in the Heihe River Basin. The results show that the proposed method is reliable.