222 resultados para Automatic rule extraction


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To pick velocity automatically is not only helpful to improve the efficiency of seismic data process, but also to provide quickly the initial velocity for prestack depth migration. In this thesis, we use the Viterbi algorithm to do automatic picking, but the velocity picked usually is immoderate. By thorough study and analysis, we think that the Viterbi algorithm has the function to do quickly and effectually automatic picking, but the data provided for picking maybe not continuous on derivative of its curved surface, viz., the curved face on velocity spectrum is not slick. Therefore, the velocity picked may include irrational velocity information. To solve the problem above, we develop a new method to filter signal by performing nonlinear transformation of coordinate and filter of function. Here, we call it as Gravity Center Preserved Pulse Compressed Filter (GCPPCF). The main idea to perform the GCPPCF as follows: separating a curve, such as a pulse, to several subsection, calculating the gravity center (coordinate displacement), and then assign the value (density) on the subsection to gravity center. When gravity center departure away from center of its subsection, the value assigned to gravity center is smaller than the actual one, but non other than gravity center anastomoses fully with its subsection center, the assigned value equal to the actual one. By doing so, the curve shape under new coordinate breadthwise narrows down compare to its original one. It is a process of nonlinear transformation of coordinate, due to gravity center changing with the shape of subsection. Furthermore, the gravity function is filter one, because it is a cause of filtering that the value assigned from subsection center to gravity center is obtained by calculating its weight mean of subsetion function. In addition, the filter has the properties of the adaptive time delay changed filter, owing to the weight coefficient used for weight mean also changes with the shape of subsection. In this thesis, the Viterbi algorithm inducted, being applied to auto pick the stack velocity, makes the rule to integral the max velocity spectrum ("energy group") forward and to get the optimal solution in recursion backward. It is a convenient tool to pick automatically velocity. The GCPPCF above not only can be used to preserve the position of peak value and compress the velocity spectrum, but also can be used as adaptive time delay changed filter to smooth object curved line or curved face. We apply it to smooth variable of sequence observed to get a favourable source data ta provide for achieving the final exact resolution. If there is no the adaptive time delay-changed filter to perform optimization, we can't get a finer source data and also can't valid velocity information, moreover, if there is no the Viterbi algorithm to do shortcut searching, we can't pick velocity automatically. Accordingly, combination of both of algorithm is to make an effective method to do automatic picking. We apply the method of automatic picking velocity to do velocity analysis of the wavefield extrapolated. The results calculated show that the imaging effect of deep layer with the wavefield extrapolated was improved dominantly. The GCPPCF above has achieved a good effect in application. It not only can be used to optimize and smooth velocity spectrum, but also can be used to perform a correlated process for other type of signal. The method of automatic picking velocity developed in this thesis has obtained favorable result by applying it to calculate single model, complicated model (Marmousi model) and also the practical data. The results show that it not only has feasibility, but also practicability.

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Urinary 8-hydroxydeoxyguanosine (80HdG) has been considered as an excellent marker of individuals at high risk of developing cancer. Until now, urinary 80HdG has largely been measured by high-performance liquid chromatography with electrochemical detection. A new method for the analysis of urinary 80HdG by high-performance capillary electrophoresis has been developed and optimized in our laboratory. A single step solid-phase extraction procedure was optimized and used for extracting 80HdG from human urine. Separations were performed in an uncoated silica capillary (50 cm x 50 tm i.d.) using a P/ACE MDQ system with UV detection. The separation of 80HdG from interfering urinary matrix components is optimized with regard to pH, applied voltage, pressure injection time and concentration of SDS in running buffer. The detection limit of this method is 0.4 mug/ml, the linear range is 0.8-500 mug/ml, the correlation coefficients levels is better than 0.999. The developed method is simple, fast and good reproducibility, furthermore, it requires a very small injection volumes and low costs of analysis, which makes it possible to provide a new noninvasive assay for an indirect measurement of oxidative DNA damage.

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A data manipulation method has been developed for automatic peak recognition and result evaluation in the analysis of organic chlorinated hydrocarbons with dual-column gas chromatography. Based on the retention times of two internal standards, pentachlorotoluene and decachlorobiphenyl, the retention times of chlorinated hydrocarbons can be calibrated automatically and accurately. It is very convenient to identify the peaks by comparing the retention times of samples with the calibrated retention times calculated from the relative retention indices of standards. Meanwhile, with a suggested two-step evaluation method the evaluation coefficients and the suitable quantitative results of each component can be automatically achieved for practical samples in an analytical system using two columns with different polarities and two internal standards. (C) 2002 Elsevier Science B.V. All rights reserved.

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Self-regulation has recently become an important topic in cognitive and developmental domain. According to previous theories and experimental studies, it is shown that self-regulation consist of both a personality (or social) aspect and a behavioral cognitive aspect of psychology. Self-regulation can be divided into self-regulation personality and self-regulation ability. In the present study researches have been carried out from two perspectives: child development and individual differences. We are eager to explore the characteristics of self-regulation in terms of human cognitive development. In the present study, we chose two groups of early adolescences one with high intelligence and the other with normal intelligence. In Study One Questionnaires were used to compare whether the highly intelligent group had had better self-regulation personality than the normal group. In Study Two experimental psychology tasks were used to compare whether highly intelligent children had had better self-regulation cognitive abilities than their normal peers. Finally, in Study Three we combined the results of Study One and Study Two to further explore the neural mechanisms for highly intelligent children with respect to their good self-regulation abilities. Some main results and conclusions are as follows: (1) Questionnaire results showed that highly intelligent children had better self-regulation personalities, and they got higher scores on the personalities related to self-regulation such as, self-reliance, stability, rule-consciousness. They also got higher scores on self-consciousness which meant that they could know their own self better than the normal children. (2) Among the three levels of cognitive difficulties in self-regulation abilities, the highly intelligent children had faster reaction speed than normal children in the primary self-regulation tasks. In the intermediate self-regulation tasks, highly intelligent children’s inhibition processing and executive processing were both better than their normal peers. In the advanced self-regulation tasks, highly intelligent children again had faster reaction speed and more reaction accuracy than their normal peers when facing with conflict and inconsistency experimental conditions,. Regression model’s results showed that primary and advanced self-regulation abilites had larger predictive power than intermediate self-regualation ability. (3) Our neural experiments showed that highly intelligent children had more efficient neural automatic processing ability than normal children. They also had better, faster and larger neural reaction to novel stimuli under pre-attentional condition which made good and firm neural basis for self-regualation. Highly intelligent children had more mature frontal lobe and pariental functions for inhibition processing and executive processing. P3 component in ERP was closely related to executive processing which mainly activated pariental function. There were two time-periods for inhibition processing—first it was the pariental function and later it was the coordination function of frontal and pariental lobes. While conflict control task had pariental N2 and frontal-pariental P3 neural sources, highly intelligent children had much smaller N2 and shorter P3 latency than normal children. Inconsistency conditions induced larger N2 than conditions without inconsistency, and conditions without inconsistency (or Conflict) induced higher P3 amplitudes than with Inconsistency (or Conflict) conditions. In conclusion, the healthy development of self-regulation was very important for children’s personality and cognition maturity, and self-regulation had its own specific characteristics in ways of presentation and ways of development. Better understanding of self-regulation can further help the exploration of the nature of human intelligence and consciousness.

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A method with carbon nanotubes functioning both as the adsorbent of solid-phase extraction (SPE) and the matrix for matrix assisted laser desorption/ ionization mass spectrometry (MALDI-MS) to analyze small molecules in solution has been developed. In this method, 10 muL suspensions of carbon nanotubes in 50% (vol/vol) methanol were added to the sample solution to extract analytes onto surface of carbon nanotubes because of their dramatic hydrophobicity. Carbon nanotubes in solution are deposited onto the bottom of tube with centrifugation. After removing the supernatant fluid, carbon nanotubes are suspended again with dispersant and pipetted directly onto the sample target of the MALDI-MS to perform a mass spectrometric analysis. It was demonstrated by analysis of a variety of small molecules that the resolution of peaks and the efficiency of desorption/ ionization on the carbon nanotubes are better than those on the activated carbon. It is found that with the addition of glycerol and sucrose to the dispersant, the intensity, the ratio of signal to noise (S/N), and the resolution of peaks for analytes by mass spectrometry increased greatly. Compared with the previously reported method by depositing sample solution onto thin layer of carbon nanotubes, it is observed that the detection limit for analytes can be enhanced about 10 to 100 times due to solid-phase extraction of analytes in solution by carbon nanotubes. An acceptable result of simultaneously quantitative analysis of three analytes in solution has been achieved. The application in determining drugs spiked into urine has also been realized. (C) 2004 American Society for Mass Spectrometry.

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Organophosphorus pesticides (OPPs) in vegetables were determined by stir bar sorptive extraction (SBSE) and capillary gas chromatography with thermionic specific detection (TSD). Hydroxy-terminated polydimethylsioxane (PDMS) prepared by sol-gel method was used as extraction phase. The effects of extraction temperature, salting out, extraction time on extraction efficiency were studied. The detection limits of OPPs in water were <= 1.2 ng/l. This method was also applied to the analysis of OPPs in vegetable samples and matrix effect was studied. Linear ranges of OPPs in vegetable samples were 0.05-50 ng/g with detection limits <= 0. 15 ng/g and the repeatability of the method was less than 20% relative standard deviation. (c) 2005 Elsevier B.V. All rights reserved.