ON THE DANGLING-BOND RELAXATION PROBLEM IN HYDROGENATED AMORPHOUS-SILICON

The influence of pulsed bias light excitation on the absorption in the defect region of undoped a-Si:H film has been investigated. Ac constant photocurrent method has been used to measure the absorption spectrum. The absorption in the defect region increases with the light pulse duration.The analysis of obtained results does not support the existence of a long time relaxation process of dangling-bond states in a-Si:H.

Solving MIN UR problem by triangle evolution algorithm with archiving and niche techniques

In this paper, as an extension of minimum unsatisfied linear relations problem (MIN ULR), the minimum unsatisfied relations (MIN UR) problem is investigated. A triangle evolution algorithm with archiving and niche techniques is proposed for MIN UR problem. Different with algorithms in literature, it solves MIN problem directly, rather than transforming it into many sub-problems. The proposed algorithm is also applicable for the special case of MIN UR, in which it involves some mandatory relations. Numerical results show that the algorithm is effective for MIN UR problem and it outperforms Sadegh's algorithm in sense of the resulted minimum inconsistency number, even though the test problems are linear.

Solving the coastal eutrophication problem by large scale seaweed cultivation

Eutrophication is becoming a serious problem in coastal waters in many parts of the world. It induces the phytoplankton blooms including 'Red Tides', followed by heavy economic losses to extensive aquaculture area. Some cultivated seaweeds have very high productivity and could absorb large quantities of N, P, CO2, produce large amount of O-2 and have excellent effect on decreasing eutrophication. The author believes that seaweed cultivation in large scale should be a good solution to the eutrophication problem in coastal waters. To put this idea into practice, four conditions should be fulfilled: (a) Large-scale cultivation could be conducted within the region experiencing eutrophication. (b) Fundamental scientific and technological problems for cultivation should have been solved. (c) Cultivation should not impose any harmful ecological effects. (d) Cultivation must be economically feasible and profitable. In northern China, large-scale cultivation of Laminaria japonica Aresch. has been encouraged for years to balance the negative effects from scallop cultivation. Preliminary research in recent years has shown that Gracilaria lemaneiformis (Bory) Daws. and Porphyra haitanensis Chang et Zheng are the two best candidates for this purpose along the Chinese southeast to southern coast from Fujian to Guangdong, Guangxi and Hong Kong. Gracilaria tenuistipitata var. liui Chang et Xia is promising for use in pond culture condition with shrimps and fish.

Evaluation of a combined wavelet and a combined principal component analysis classification system for BCG diagnostic problem

Heart disease is one of the main factor causing death in the developed countries. Over several decades, variety of electronic and computer technology have been developed to assist clinical practices for cardiac performance monitoring and heart disease diagnosis. Among these methods, Ballistocardiography (BCG) has an interesting feature that no electrodes are needed to be attached to the body during the measurement. Thus, it is provides a potential application to asses the patients heart condition in the home. In this paper, a comparison is made for two neural networks based BCG signal classification models. One system uses a principal component analysis (PCA) method, and the other a discrete wavelet transform, to reduce the input dimensionality. It is indicated that the combined wavelet transform and neural network has a more reliable performance than the combined PCA and neural network system. Moreover, the wavelet transform requires no prior knowledge of the statistical distribution of data samples and the computation complexity and training time are reduced.

Summer diet of two sympatric species of raptors Upland Buzzard (Buteo hemilasius) and Eurasian Eagle Owl (Bubo bubo) in alpine meadow: problem of coexistence

Summer diets of two sympatric raptors Upland Buzzards (Buteo hemilasius Temminck et Schlegel) and Eurasian Eagle Owls (Bubo bubo L. subsp. Hemachalana Hume) were studied in an alpine meadow (3250 m a.s.l.) on Qinghai-Tibet Plateau, China. Root voles Microtus oeconomus Pallas, plateau pikas Ochotona curzoniae Hodgson, Gansu pikas O. cansus Lyon and plateau zokors Myospalax baileyi Thomas were the main diet components of Upland Buzzards as identified through the pellets analysis with the frequency of 57, 20, 19 and 4%, respectively. The four rodent species also were the main diet components of Eurasian Eagle Owls basing on the pellets and prey leftovers analysis with the frequency of 53, 26, 13 and 5%, respectively. The food niche breadth indexes of Upland Buzzards and Eurasian Eagle Owls were 1.60 and 1.77 respectively (higher value of the index means the food niche of the raptor is broader), and the diet overlap index of the two raptors was larger (C-ue = 0.90) (the index range from 0 - no overlap - to I - complete overlap). It means that the diets of Upland Buzzards and Eurasian Eagle Owls were similar (Two Related Samples Test, Z = -0.752, P = 0.452). The classical resource partitioning theory can not explain the coexistence of Upland Buzzards and Eurasian Eagle Owls in alpine meadows of Qinghai-Tibet Plateau. However, differences in body size, predation mode and activity rhythm between Upland Buzzards and Eurasian Eagle Owls may explain the coexistence of these two sympatric raptors.

多尺度分解与相位反褶积提高海上地震资料分辨率和信噪比

Offshore seismic exploration is full of high investment and risk. And there are many problems, such as multiple. The technology of high resolution and high S/N ratio on marine seismic data processing is becoming an important project. In this paper, the technology of multi-scale decomposition on both prestack and poststack seismic data based on wavelet and Hilbert-Huang transform and the theory of phase deconvolution is proposed by analysis of marine seismic exploration, investigation and study of literatures, and integration of current mainstream and emerging technology. Related algorithms are studied. The Pyramid algorithm of decomposition and reconstruction had been given by the Mallat algorithm of discrete wavelet transform In this paper, it is introduced into seismic data processing, the validity is shown by test with field data. The main idea of Hilbert-Huang transform is the empirical mode decomposition with which any complicated data set can be decomposed into a finite and often small number of intrinsic mode functions that admit well-behaved Hilbert transform. After the decomposition, a analytical signal is constructed by Hilbert transform, from which the instantaneous frequency and amplitude can be obtained. And then, Hilbert spectrum. This decomposition method is adaptive and highly efficient. Since the decomposition is based on the local characteristics of the time scale of data, it is applicable to nonlinear and non-stationary processes. The phenomenons of fitting overshoot and undershoot and end swings are analyzed in Hilbert-Huang transform. And these phenomenons are eliminated by effective method which is studied in the paper. The technology of multi-scale decomposition on both prestack and poststack seismic data can realize the amplitude preserved processing, enhance the seismic data resolution greatly, and overcome the problem that different frequency components can not restore amplitude properly uniformly in the conventional method. The method of phase deconvolution, which has overcome the minimum phase limitation in traditional deconvolution, approached the base fact well that the seismic wavelet is phase mixed in practical application. And a more reliable result will be given by this method. In the applied research, the high resolution relative amplitude preserved processing result has been obtained by careful analysis and research with the application of the methods mentioned above in seismic data processing in four different target areas of China Sea. Finally, a set of processing flow and method system was formed in the paper, which has been carried on in the application in the actual production process and has made the good progress and the huge economic benefit.

反假频重建理论及其在储层预测中的应用

To extend the cross-hole seismic 2D data to outside 3D seismic data, reconstructing the low frequency data to high frequency data is necessary. Blind deconvolution method is a key technology. In this paper, an implementation of Blind deconvolution is introduced. And optimized precondition conjugate gradient method is used to improve the stability of the algorithm and reduce the computation. Then high-frequency retrieved Seismic data and the cross-hole seismic data is combined for constraint inversion. Real data processing proved the method is effective. To solve the problem that the seismic data resolution can’t meet the request of reservoir prediction in the river face thin-layers in Chinese eastern oil fields, a high frequency data reconstruction method is proposed. The extrema of the seismic data are used to get the modulation function which operated with the original seismic data to get the high frequency part of the reconstruction data to rebuild the wide band data. This method greatly saves the computation, and easy to adjust the parameters. In the output profile, the original features of the seismic events are kept, the common feint that breaking the events and adding new zeros to produce alias is avoided. And the interbeded details are enhanced compared to the original profiles. The effective band of seismic data is expended and the method is approved by the processing of the field data. Aim to the problem in the exploration and development of Chinese eastern oil field that the high frequency log data and the relative low frequency seismic data can’t be merged, a workflow of log data extrapolation constrained by time-phase model based on local wave decomposition is raised. The seismic instantaneous phase is resolved by local wave decomposition to build time-phase model, the layers beside the well is matched to build the relation of log and seismic data, multiple log info is extrapolated constrained by seismic equiphase map, high precision attributes inverse sections are produced. In the course of resolve the instantaneous phase, a new method of local wave decomposition --Hilbert transform mean mode decomposition(HMMD) is raised to improve the computation speed and noise immunity. The method is applied in the high resolution reservoir prediction in Mao2 survey of Daqing oil field, Multiple attributes profiles of wave impedance, gamma-ray, electrical resistivity, sand membership degree are produced, of which the resolution is high and the horizontal continuous is good. It’s proved to be a effective method for reservoir prediction and estimation.

数据驱动型多次波衰减方法的研究

In the practical seismic profile multiple reflections tend to impede the task of even the experienced interpreter in deducing information from the reflection data. Surface multiples are usually much stronger, more broadband, and more of a problem than internal multiples because the reflection coefficient at the water surface is much larger than the reflection coefficients found in the subsurface. For this reason most attempts to remove multiples from marine data focus on surface multiples, as will I. A surface-related multiple attenuation method can be formulated as an iterative procedure. In this essay a fully data-driven approach which is called MPI —multiple prediction through inversion (Wang, 2003) is applied to a real marine seismic data example. This is a pretty promising scheme for predicting a relative accurate multiple model by updating the multiple model iteratively, as we usually do in a linearized inverse problem. The prominent characteristic of MPI method lie in that it eliminate the need for an explicit surface operator which means it can model the multiple wavefield without any knowledge of surface and subsurface structures even a source signature. Another key feature of this scheme is that it can predict multiples not only in time but also in phase and in amplitude domain. According to the real data experiments it is shown that this scheme for multiple prediction can be made very efficient if a good initial estimate of the multiple-free data set can be provided in the first iteration. In the other core step which is multiple subtraction we use an expanded multi-channel matching filter to fulfil this aim. Compared to a normal multichannel matching filter where an original seismic trace is matched by a group of multiple-model traces, in EMCM filter a seismic trace is matched by not only a group of the ordinary multiple-model traces but also their adjoints generated mathematically. The adjoints of a multiple-model trace include its first derivative, its Hilbert transform and the derivative of the Hilbert transform. The third chapter of the thesis is the application for the real data using the previous methods we put forward from which we can obviously find the effectivity and prospect of the value in use. For this specific case I have done three group experiments to test the effectiveness of MPI method, compare different subtraction results with fixed filter length but different window length, invest the influence of the initial subtraction result for MPI method. In terms of the real data application, we do fine that the initial demultiple estimate take on a great deal of influence for the MPI method. Then two approaches are introduced to refine the intial demultiple estimate which are first arrival and masking filter respectively. In the last part some conclusions are drawn in terms of the previous results I have got.

HHT在电磁信号处理中的应用

In modem signal Processing，non－linear，non－Gaussian and non－stable signals are usually the analyzed and Processed objects，especially non－stable signals. The convention always to analyze and Process non－stable signals are： short time Fourier transform，Wigner－Ville distribution，wavelet Transform and so on. But the above three algorithms are all based on Fourier Transform，so they all have the shortcoming of Fourier Analysis and cannot get rid of the localization of it. Hilbert－Huang Transform is a new non－stable signal processing technology，proposed by N. E. Huang in 1998. It is composed of Empirical Mode Decomposition (referred to as EMD) and Hilbert Spectral Analysis (referred to as HSA). After EMD Processing，any non－stable signal will be decomposed to a series of data sequences with different scales. Each sequence is called an Intrinsic Mode Function (referred to as IMF). And then the energy distribution plots of the original non－stable signal can be found by summing all the Hilbert spectrums of each IMF. In essence，this algorithm makes the non－stable signals become stable and decomposes the fluctuations and tendencies of different scales by degrees and at last describes the frequency components with instantaneous frequency and energy instead of the total frequency and energy in Fourier Spectral Analysis. In this case，the shortcoming of using many fake harmonic waves to describe non－linear and non－stable signals in Fourier Transform can be avoided. This Paper researches in the following parts： Firstly，This paper introduce the history and development of HHT，subsequently the characters and main issues of HHT. This paper briefly introduced the basic realization principles and algorithms of Hilbert－Huang transformation and confirms its validity by simulations. Secondly, This paper discuss on some shortcoming of HHT. By using FFT interpolation, we solve the problem of IMF instability and instantaneous frequency undulate which are caused by the insufficiency of sampling rate. As to the bound effect caused by the limitation of envelop algorithm of HHT, we use the wave characteristic matching method, and have good result. Thirdly, This paper do some deeply research on the application of HHT in electromagnetism signals processing. Based on the analysis of actual data examples, we discussed its application in electromagnetism signals processing and noise suppression. Using empirical mode decomposition method and multi-scale filter characteristics can effectively analyze the noise distribution of electromagnetism signal and suppress interference processing and information interpretability. It has been founded that selecting electromagnetism signal sessions using Hilbert time-frequency energy spectrum is helpful to improve signal quality and enhance the quality of data.