Similarity evaluation model for the internal defect detection of strip steel

An internal defect meter is an instrument to detect the internal inclusion defects of cold-rolled strip steel.The detection accuracy of the equipment can be evaluated based on the similarity of the multiple detection data obtained for the same steel coil.Based on the cosine similarity model and eigenvalue matrix model,a comprehensive evaluation method to calculate the weighted average of similarity is proposed.Results show that the new method is consistent with and can even replace artificial evaluation to realize the automatic evaluation of strip defect detection results.

Scale Effects and a Method for Similarity Evaluation in Micro Electrical Discharge Machining

Electrical discharge machining（EDM） is a promising non-traditional micro machining technology that offers a vast array of applications in the manufacturing industry. However, scale effects occur when machining at the micro-scale, which can make it difficult to predict and optimize the machining performances of micro EDM. A new concept of ＂scale effects＂ in micro EDM is proposed, the scale effects can reveal the difference in machining performances between micro EDM and conventional macro EDM. Similarity theory is presented to evaluate the scale effects in micro EDM. Single factor experiments are conducted and the experimental results are analyzed by discussing the similarity difference and similarity precision. The results show that the output results of scale effects in micro EDM do not change linearly with discharge parameters. The values of similarity precision of machining time significantly increase when scaling-down the capacitance or open-circuit voltage. It is indicated that the lower the scale of the discharge parameter, the greater the deviation of non-geometrical similarity degree over geometrical similarity degree, which means that the micro EDM system with lower discharge energy experiences more scale effects. The largest similarity difference is 5.34 while the largest similarity precision can be as high as 114.03. It is suggested that the similarity precision is more effective in reflecting the scale effects and their fluctuation than similarity difference. Consequently, similarity theory is suitable for evaluating the scale effects in micro EDM. This proposed research offers engineering values for optimizing the machining parameters and improving the machining performances of micro EDM.

Similarity comprehensive evaluation of humanoid robot arm motion

A suitable comprehensive evaluation method for similarity comprehensive evaluation of humanoid motion(mainly to robotic arm) is proposed.For different robotic arms, a static comprehensive evaluation model is established by projection pursuit evaluation based on indexes of humanoid robot arm motion in robotics and ergonomics field. Based on projection pursuit evaluation with timing information entropy and time degrees, a dynamic comprehensive evaluation method is proposed by linear weighting to each time's static model's indexes weight according to timing weighted vectors. Through comparing similarity comprehensive evaluation result based on static and dynamic comprehensive evaluation model, the results show that similarity based on dynamic comprehensive evaluation model is high. By comparing reliability, similarity and dispersion of static and dynamic comprehensive evaluation models, the results show that dynamic comprehensive evaluation result has better accuracy, stability and lower dispersion, and the result is more reasonable and real. Therefore, the dynamic comprehensive evaluation method proposed in this paper is more suitable for similarity comprehensive evaluation of humanoid robot arm motion.

Similarity measure design and similarity computation for discrete fuzzy data

The similarity computations for fuzzy membership function pairs were carried out.Fuzzy number related knowledge was introduced,and conventional similarity was compared with distance based similarity measure.The usefulness of the proposed similarity measure was verified.The results show that the proposed similarity measure could be applied to ordinary fuzzy membership functions,though it was not easy to design.Through conventional results on the calculation of similarity for fuzzy membership pair,fuzzy membership-crisp pair and crisp-crisp pair were carried out.The proposed distance based similarity measure represented rational performance with the heuristic point of view.Furthermore,troublesome in fuzzy number based similarity measure for abnormal universe of discourse case was discussed.Finally,the similarity measure computation for various membership function pairs was discussed with other conventional results.

An HPLC Fingerprint Identification of Dried Barks of Ilex rotunda and Ilex godajam

[Objectives] A simple and reliable HPLC fingerprint method was developed for the identification of dried barks of Ilex rotunda and I. godajam. [Methods] Nine batches of dried barks of I. rotunda,and seven batches of dried barks of I. godajam collected from different pharmacies and arboretums in different regions of China were used to establish fingerprints. The software Similarity Evaluation System of Chromatographic Fingerprints of Traditional Chinese Medicine( 2004 A Edition) was used to evaluate the fingerprints. [Results]The fingerprints of dried barks of I. rotunda and I. godajam were established. Methodological study met the technical requirements of fingerprints. The similarities of the fingerprints of dried barks of I. rotunda and I. godajam were all more than 0. 8 and 0. 9 respectively. There were 31 and 28 common peaks in I. rotunda and I. godajam,which could be classified into two clusters by principal component analysis( PCA) and hierarchical cluster analysis. [Conclusions] The feasibility and advantages of used HPLC fingerprints were verified,and the results indicated that the HPLC fingerprint as a characteristic distinguishing method combining similarity evaluation,principal component analysis and hierarchical cluster analysis can be successfully used to identify the authenticity of dried barks of I. rotunda and I. godajam.

基于研发和生产视角的生物类似药特点分析

生物类似药近年来得到快速发展,其研发和上市极大地降低了患者使用负担,提高了生物药的可及性。由于生物大分子本身内在的复杂结构和理化特点,生产工艺上的微小区别都可能使生物类似药与参照药间产生安全性、有效性的差异。生物类似药的研发和生产与创新药相比有其独有的特点。结合国内外生物类似药的法规要求,基于研发和生产视角,从工艺开发、生产放大和质量相似性评价等角度探讨生物类似药的特点,以期为生物类似药的开发提供参考。

Study on GC-MS fingerprint of petroleum ether fraction of Shenqi Jiangtang Granules

Objective To establish gas chromatography-mass spectrometry(GC-MS)fingerprint method for the petroleum ether fraction of Shenqi Jiangtang Granules(SQJTG)and evaluate the product quality.Methods The GC-MS fingerprint of petroleum ether fraction of SQJTG was established by GC-MS,and the chemical components corresponding to the fingerprint peaks were structurally identified on NIST2014.The batch consistency of SQJTG products was evaluated based on the chemical composition of petroleum ether parts by using fingerprint similarity evaluation and Principal components analysis(PCA)technology.At the same time,Hotelling's T2 and DMODX statistics are used to set the control range for the quality of different batches of products.Results Twenty-two components were identified from the petroleum ether part of SQJTG,accounting for 60.94%of the total components separated.The similarity of fingerprints of petroleum ether parts of 24 batches of SQJTG was greater than 0.95.The PCA of 24 batches of samples were all under the control limits of Hotellin’s T2 and DMODX statistics,indicating that the petroleum ether parts of different batches of SQJTG were consistent.Conclusion The developed GC-MS fingerprint method can be used to evaluate the quality of SQJTG.

Improved Collaborative Filtering Recommendation Based on Classification and User Trust

When dealing with the ratings from users,traditional collaborative filtering algorithms do not consider the credibility of rating data,which affects the accuracy of similarity.To address this issue,the paper proposes an improved algorithm based on classification and user trust.It firstly classifies all the ratings by the categories of items.And then,for each category,it evaluates the trustworthy degree of each user on the category and imposes the degree on the ratings of the user.Finally,the algorithm explores the similarities between users,finds the nearest neighbors,and makes recommendations within each category.Simulations show that the improved algorithm outperforms the traditional collaborative filtering algorithms and enhances the accuracy of recommendation.