Advanced Materials Research Vol. 1014

Abstract: Splicing broken files played an important role in judicial evidence reconstruction, historical documents repair and military information obtainment and other fields. In this paper, we analyzed the reconstruction of broken pieces, which was modeled as an optimal matching problem. The Hamming distance was used as the matching degree of edge splicing. Firstly, we use the iterative threshold selection method to determine the gray scale threshold. Secondly, we chose the minimum summation of and as objective function. Then we use clustering analysis to classify the pieces into different lines, and selected the top and bottom position of the first line on each piece as decision variables. Finally, we took word width and column spacing into consideration and used row matching algorithm to splice lines into a complete image.

Abstract: Two-dimensional NMR has obvious advantages that it is fast and intuitive on identification of reservoir fluid, and it can estimate physical parameters accurately on evaluation, while inversion method of the two-dimensional NMR is the important basis of the logging interpretation work. Through studies about the previous TSVD inversion methods, the truncated standard of the singular value matrix has been improved in order to retain more singular values on the condition number reducing of the inversed equations, meanwhile in iterative process, variable parameter iteration algorithm is proposed to make computing more quick and efficient. In method validation, the inversed diffusion-relaxation two-dimensional NMR spectrum is fitting well with the construct spectrum and the spending time is 57 seconds. The inversed effect of variable parameter iteration method indicates that compared with the TSVD, the new method can give the reliable results very quickly which is highly beneficial for the identification and evaluation of the reservoir fluid, and has certain significance in practical petroleum exploration.

Abstract: Big data is another disruptive technological revolution following cloud computing and Internet of Things (IOT) in IT field. Its dramatic growth makes enterprises gradually facing unprecedented challenges in storage architecture, and brings subversive innovation for IT enterprises. This paper presents five challenges in computer professional education under big data environment in IT field, and discusses the corresponding measures of computer specialized education from different aspects, such as the adjustment of subject content, changes of talent cultivation, innovation of teaching mode, and improvement of teachers’ quality.

Abstract: ] In this information age, “information” is regarded as a very hot and very common word to everyone living in the earth. Its importance and wide application are commonly seen in our daily life by every one. In the paper, the author will research the application of information system in interpretation training, at the same time, the author also exploits some detail roles of information system in interpretation training. The combination of information system and interpretation is very complex course for improving training skills. Therefore, training skills are very important for the good combination of information system and interpretation too. In the study, the author also makes some investigation and statistics to exploit some useful data on the application of information system, which will be useful for effective interpretation training. [key words] information system;information-applied technology; exploration-internalization mode; electronic materials; interpretation training

Abstract: Microblog is one of the most important trends in Internet communication. But since microblog is a new phenomenon, we are still at the very beginning stage of exploring the ways and effects of marketing on microblog. The paper took Tencent enterprise microblog platform as example, using experiment to discover what kind of microblog text can effectively influence users’ attitudes and behaviors. It was found that advertising information can not significantly changed users’ attitudes toward the brand, but non-advertising information can significantly change users’ attitudes toward the company’s microblog, and ultimately change their attitudes toward brand. Some suggestions for business marketing on microblog were also proposed.

Abstract: Bottom dead center (BDC) is an important performance index of press,but how to precisely evaluate the accuracy of BDC is a technical problem faced by the press industry. Based on fuzzy judgment method and analytic hierarchy process (AHP), this paper constructs a comprehensive evaluation index to analyze and evaluate the position of the BDC accuracy.Evaluation step is a system operated by selecting evaluation factors and building evaluation set to determine the comparison matrix, to calculate the weight of each factor, and to establish fuzzy evaluation matrix, and through comprehensive evaluation model to judge the BDC accuracy level. It shows that this evaluation method can effectively evaluate the accuracy of press.

Abstract: As a new nonlinear and non-stationary signal analysis method,local mean decomposition (LMD) has a good adaptability. We decompose the original non-stationary acceleration vibration signals into several stationary production function (PF).But performing LMD will produce end effects which make results distorted. A hidden Markov model (HMM)-based speech recognition system for Chinese spell.After analyzing reasons for end effects of LMD in detail,a new method based on weighted matching similar waveform was proposed.Experiments in speech recognition to the production function as the training model, the more traditional identification method to identify higher rates. LMD is an effective method. It is feasible to extract the feature from speech signals with LMD.

Abstract: Particle filter as a sequential Monte Carlo method is widely applied in stochastic sampling for state estimation in a recursive Bayesian filtering framework. The efficiency and accuracy of the particle filter depends on the number of particles and the relocating method. The automatic selection of sample size for a given task is therefore essential for reducing unnecessary computation and for optimal performance, especially when the posterior distribution greatly varies overtime. This paper presents an adaptive resampling method (IE_KLD_PF) based on interval estimation, and after interval estimating the expectation of the system states, the new algorithm adopts Kullback-Leibler distance (KLD) to determine the number of particles to resample from the interval and update the filter results by current observation information. Simulations are performed to show that the proposed filter can reduce the average number of samples significantly compared to the fixed sample size particle filter.

Abstract: Two-dimensional NMR spectrum can give reliable conclusion when it is used to identify and evaluate the testing fluid, and two-dimensional NMR inversion method is the key to get the spectrum Aiming at the deficiency of inversed results’ accuracy and computing speed in TSVD method, the variable parameter iteration method is proposed which include the singular value packet processing algorithm that mainly used to lay the foundation for the reliability of the results, and the variable parameter iteration algorithm that mainly used to speed up the iteration computing. In numerical simulation test, the variable parameter iteration method can restore the constructional diffusion-relaxation spectrum accurately and quickly compared with TSVD method. In oil-water experimental test, the spectrum inversed from variable parameter iteration method can identify the types of testing fluid correctly, and the relative error of oil saturation is 0.6% or 1.9% when oil water ratio is 3 to 1 or 1 to 2, the error are small that indicates the accuracy of the results got from the method is high. Variable parameter iteration method can process the real two-dimensional NMR data rapidly and efficiently, and the quality of the inversed diffusion-relaxation spectrum is high, which shows that the method has practical capacity and has the role of guiding the research of new inversion methods.

Abstract: Based on the active shape model(ASM) and active appearance model(AAM) algorithm, using the AAM texture matching for global search and ASM feature points localization of local search, a new algorithm that combining the characteristics of both is adopted. This algorithm ensures the accuracy of feature point positioning and enhanced the texture matching accuracy, improved the tracking accuracy and quickness when target partially obscured and nearby background change in the process of face tracking effectively. Experimental results show that the algorithm improved the precision and robustness greatly.