旋转扫描超声心脏图像的中轴匹配与图像插值

研究旋转扫描超声医学图像多维重建中图像中轴匹配方法和插值算法。首先 ,根据图像中轴的特征点分析其时域曲线 ,实现中轴的轴向匹配 ;相似矩阵用来寻找两幅图像中轴附近匹配的像素线。自相关函数和 Fouri-er谱用来对图像中轴的匹配进行评价。其次 ,针对旋转扫描原始图像空间分布的特殊性 ,提出了分区插值法。实验结果表明 :我们提出的图像中轴匹配方法切实可行 ,插值算法快速、精确 。

Gr92与低合金钢的焊接

根据Gr92钢与低合金钢焊接的特点,提出采用中匹配或低匹配来焊接Gr92钢与低合金钢。重点分析了焊接难点,采取合适的工艺措施,保证Gr92钢侧焊缝和热影响区的性能。

Middle matching mining algorithm

A new algorithm for fast discovery of sequential patterns to solve the problems of too many candidate sets made by SPADE is presented, which is referred to as middle matching algorithm. Experiments on a large customer transaction database consisting of customer_id, transaction time, and transaction items demonstrate that the proposed algorithm performs better than SPADE attributed to its philosophy to generate a candidate set by matching two sequences in the middle place so as to reduce the number of the candidate sets.

A KNN-based two-step fuzzy clustering weighted algorithm for WLAN indoor positioning

Although k-nearest neighbors （KNN） is a popular fingerprint match algorithm for its simplicity and accuracy, because it is sensitive to the circumstances, a fuzzy c-means （FCM） clustering algorithm is applied to improve it. Thus, a KNN-based two-step FCM weighted （KTFW） algorithm for indoor positioning in wireless local area networks （WLAN） is presented in this paper. In KTFW algorithm, k reference points （RPs） chosen by KNN are clustered through FCM based on received signal strength （RSS） and location coordinates. The right clusters are chosen according to rules, so three sets of RPs are formed including the set of k RPs chosen by KNN and are given different weights. RPs supposed to have better contribution to positioning accuracy are given larger weights to improve the positioning accuracy. Simulation results indicate that KTFW generally outperforms KNN and its complexity is greatly reduced through providing initial clustering centers for FCM.

Estimation of Durability of Profit of Small and Medium Enterprises by Statistical Matching

This study computes the durability of Return on Assets （ROA） in small and medium enterprises from different sample datasets. Utilizing information from the Financial Statements Statistics of Corporations by Industry, it verifies the precision of correlation coefficients using the Non-iterative Bayesian-based Imputation （NIBAS） and multiple imputation method for all combinations of common variables with auxiliary files. The following are the three important findings of this paper. First, statistical matching estimates of higher precision can be obtained using key variable sets with higher canonical correlation coefficients. Second, even if the key variable sets have high canonical correlation coefficients, key variables that are correlated extremely strongly with target variables and have high kurtosis should not be used. Finally, using auxiliary flies can improve the precision of statistical matching estimates. Accordingly, the durability of ROA in small and medium enterprises is computed. The author finds that the series of ROA correlation fluctuates for smaller enterprises compared to larger ones, and thus, the vulnerability of ROA in small and medium enterprises can be clarified via statistical matching.

A novel method for integrating chromatographic fingerprint analytical units of Chinese materia medica:the matching frequency statistical moment method

Objective To facilitate the quality evaluation suitable for the unique characteristics of Chinese materia medica(CMM)by developing and implementing a novel approach known as the matching frequency statistical moment(MFSM)method.Methods This study established the MFSM method.To demonstrate its effectiveness,we applied this novel approach to analyze Danxi Granules(丹膝颗粒,DXG)and its constituent herbal materials.To begin with,the ultra-performance liquid chromatography(UPLC)was applied to obtain the chromatographic fingerprints of DXG and its constituent herbal materi-als.Next,the MFSM was leveraged to compress and integrate them into a new fingerprint with fewer analytical units.Then,we characterized the properties and variability of both the original and integrated fingerprints by calculating total quantum statistical moment(TQSM)parameters,information entropy and information amount,along with their relative standard deviation(RSD).Finally,we compared the TQSM parameters,information entropy and infor-mation amount,and their RSD between the traditional and novel fingerprints to validate the new analytical method.Results The chromatographic peaks of DXG and its 12 raw herbal materials were divided and integrated into peak families by the MFSM method.Before integration,the ranges of the peak number,three TQSM parameters,information entropy and information amount for each peak or peak family of UPLC fingerprints of DXG and its 12 raw herbal materials were 95.07−209.73,9390−183064μv·s,5.928−21.33 min,22.62−106.69 min^(2),4.230−6.539,and 50530−974186μv·s,respectively.After integration,the ranges of these parameters were 10.00−88.00,9390−183064μv·s,5.951−22.02 min,22.27−104.73 min^(2),2.223−5.277,and 38159−807200μv·s,respectively.Correspondingly,the RSD of all the aforementioned pa-rameters before integration were 2.12%−9.15%,6.04%−49.78%,1.15%−23.10%,3.97%−25.79%,1.49%−19.86%,and 6.64%−51.20%,respectively.However,after integration,they changed to 0.00%,6.04%−49.87%,1.73%−23.02%,3.84%−26.85%,1.17%−16.54%,and 6.40%−48.59%,respectively.The results demonstrated that in the newly integrated fingerprint,the analytical units of constituent herbal materials,information entropy and information amount were significantly reduced(P<0.05),while the TQSM parameters remained unchanged(P>0.05).Additionally,the RSD of the TQSM parameters,information entropy,and information amount didn’t show significant difference before and after integration(P>0.05),but the RSD of the number and area of the integrated analytical units significantly decreased(P<0.05).Conclusion The MFSM method could reduce the analytical units of constituent herbal mate-rials while maintain the properties and variability from their original fingerprint.Thus,it could serve as a feasible and reliable tool to reduce difficulties in analyzing multi-compo-nents within CMMs and facilitating the evaluation of their quality.