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Liying Yuan,Hongqi Wang 대한기계학회 2023 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.37 No.5
Bearing fault diagnosis is essential for reducing equipment operating and maintenance costs. We propose a bearing fault diagnosis method that combines hierarchical symbolic fuzzy entropy (HSFE) and sparse Bayesian extreme learning machine (SBELM). Multiscale symbolic fuzzy entropy (MSFE) is a recently proposed fault diagnosis method. Compared with multiscale sample entropy (MSE), multiscale permutation entropy (MPE), and multiscale fuzzy entropy (MFE), MSFE has high noise resistance and computational efficiency. The multiscale analysis method using the average operator can only extract information in the low frequency component, but cannot use the feature information in the high frequency component. Aiming at this defect, symbolic fuzzy entropy is formed by combining the hierarchical decomposition with the symbolic fuzzy entropy. Hierarchical decomposition uses average and difference operators to decompose the sequence, which can extract the fault information of highfrequency and low-frequency components at the same time. Then, the extracted fault information is efficiently identified and classified using the SBELM. The effectiveness and superiority of the HSFE method are verified by simulation signals and experimental vibration signals. At the same time, experimental comparisons were carried out using MPE, HPE, MSE, HSE, MSFE and HSFE. The experimental results indicate that the HSFE method has the best effect on the identification of rotating machinery fault types.
Based on the Improved Fusion Algorithm of Wavelet Image Contrast and Canny Operator
Liying Yuan,Xue Xu 보안공학연구지원센터 2016 International Journal of Multimedia and Ubiquitous Vol.11 No.8
Aiming at the visual effect and the fusion quality is poor of the traditional image fusion algorithm, the new fusion algorithm is adopted that combining the Canny operator with taking big window contrast. The algorithm uses wavelet transform to the original images are decomposed firstly, the process will be based on the frequency characteristics of the image information to form two pieces of information, low frequency and high frequency information. Low frequency subband uses weighted average fusion algorithm, while high frequency subband uses the algorithm which combines Canny operator with taking big window contrast, the last fusion image is got from the wavelet reconstruction in contrast to the principle of wavelet decomposition . The corresponding simulation analysis was carried out on the fusion algorithm, and the visual effect is more clear. Also the object evaluation standard increased significantly.
Mi Xie,Liying Gao,Zhiming Liu,RuiYing Yuan,Dongzhi Zhuoma,Dikye Tsering,Yuefei Wang,Shan Huang,Bin Li 한국식품영양과학회 2022 Journal of medicinal food Vol.25 No.12
Diabetic patients are more prone to developing nonalcoholic fatty liver disease (NAFLD) compared with healthy people. As a plant homologous to both medicine and food, Malus toringoides (Rehd.) Hughes has been used as an intervention for both NAFLD and diabetes. However, the effect and mechanism of M. toringoides on NAFLD on type 2 diabetes mellitus (T2DM) is unclear. The current investigation was designed to evaluate the ameliorative effects and mechanism of M. toringoides ethanol extract (CBTM-E375) on T2DM, and to identify the compounds in these extracts. The effects of CBTM-E375 on T2DM were verified using a high-fat diet-/streptozotocin-induced diabetic rat and free fatty acid (0.5 mM)-induced human hepatocellular carcinoma cell (HepG2) models. The components of CBTM-E375 were identified by high performance liquid chromatography-mass spectrometry/mass spectrometry. Our results demonstrate that CBTM-E375 ameliorated lipid accumulation (total cholesterol, triglyceride), oxidative stress (superoxide dismutase, catalase, malondialdehyde, glutathione peroxidase), and inflammation (tumor necrosis factor-α [TNF-α], interleukin [IL]-1β, IL-6, C-reactive protein [CRP]) in vivo and in vitro, these effects were associated with a CBTM-E375-mediated downregulation of SREBP-1c (sterol regulatory element binding protein 1c) and the NF-κB (nuclear factor κB) signaling pathway. A total of 20 chemical compounds were identified in CBTM-E375, including phlorizin, isoquercitrin, chlorogenic acid, quercetin, naringenin, and trigonelline, which have been reported to have positive effects on diabetes or on NAFLD.
SM-RCNV: a statistical method to detect recurrent copy number variations in sequenced samples
Yaoyao Li,Xiguo Yuan,Junying Zhang,Liying Yang,Jun Bai,Shan Jiang 한국유전학회 2019 Genes & Genomics Vol.41 No.5
Background Copy number variation (CNV) is an important form of genomic structural variation and is linked to dozens of human diseases. Using next-generation sequencing (NGS) data and developing computational methods to characterize such structural variants is significant for understanding the mechanisms of diseases. Objective The objective of this study is to develop a new statistical method of detection recurrent CNVs across multiple samples from genomic sequences. Methods A statistical method is carried out to detect recurrent CNVs, referred to as SM-RCNV. This method uses a statistic associated with each location by combining the frequency of variation at one location across whole samples and the correlation among consecutive locations. The weights of the frequency and correlation are trained using real datasets with known CNVs. P-value is assessed for each location on the genome by permutation testing. Results Compared with six peer methods, SM-RCNV outperforms the peer methods under receiver operating characteristic curves. SM-RCNV successfully identifies many consistent recurrent CNVs, most of which are known to be of biological significance and associated with diseased genes. The validation rate of SM-RCNV in the CEU call set and YRI call set with Database of Genomic Variants are 258/328 (79%) and (157/309) 51%, respectively. Conclusion SM-RCNV is a well-grounded statistical framework for detecting recurrent CNVs from multiple genomic sequences, providing valuable information to study genomes in human diseases. The source code is freely available at https ://sourc eforg e.net/proje cts/sm-rcnv/.
전표진(Jeon Pyo Jin),Yuan Liying, 김우주(Kim Woo Ju) 한국IT서비스학회 2009 한국IT서비스학회 학술대회 논문집 Vol.2009 No.1
XBRL(eXtensible Business Reporting Language)은 컴퓨터가 데이터의 의미와 데이터간의 관계를 자동으로 인식해서 처리할 수 있도록 설계된 XML(eXtensible Markup Language)기반의 기업업무보고용 언어이다. 이는 각 데이터에 정황적 요소를 포함하는 태그(Tag)를 추가함으로써 정보수요자로 하여금 정확한 정보를 이용ㆍ생성할 수 있게 하고, 정보공급자와 수요자간의 효율적 정보이동을 가능하게 하는 국제표준이다. 하지만 한국의 경우 XBRL의 도입이 규제기관을 중심으로 이루어지고 있어서 XBRL관련 시장이 한정적으로만 확장되고 있는 실정이다. 또한 규제기관 마다 특화된 도입방법으로 인하여 재무데이터 등의 원활한 흐름에 방해가 되어서 XBRL정보 가공 서비스업체의 등장을 어렵게 하고 정보수요자들에게도 실질적인 도움을 주지 못하고 있다. 이 논문은 Innovation Adoption모형을 이용하여, 개별 기업이 XBRL을 도입하는데 유효한 영향을 주는 요인을 찾고 함의하는 바를 알아 보는데 목적이 있다. IFRS(International Financial Reporting Standards)의 도입으로 인해 그 필요성이 커질, XBRL의 본연의 목적을 달성하기 위해 도움이 되는 연구가 될 것이다.