Pub Date : 2022-01-01DOI: 10.32604/cmes.2022.016924
H. Aydi, Ashish Verma, J. A. Younis, Jung Rye Lee
{"title":"Some Formulas Involving Hypergeometric Functions in Four Variables","authors":"H. Aydi, Ashish Verma, J. A. Younis, Jung Rye Lee","doi":"10.32604/cmes.2022.016924","DOIUrl":"https://doi.org/10.32604/cmes.2022.016924","url":null,"abstract":"","PeriodicalId":10451,"journal":{"name":"Cmes-computer Modeling in Engineering & Sciences","volume":"75 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87804304","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-01-01DOI: 10.32604/cmes.2022.017822
W. A. Shaikh, S. F. Shah, S. M. Pandhiani, M. A. Solangi
{"title":"Wavelet Decomposition Impacts on Traditional Forecasting Time Series Models","authors":"W. A. Shaikh, S. F. Shah, S. M. Pandhiani, M. A. Solangi","doi":"10.32604/cmes.2022.017822","DOIUrl":"https://doi.org/10.32604/cmes.2022.017822","url":null,"abstract":"","PeriodicalId":10451,"journal":{"name":"Cmes-computer Modeling in Engineering & Sciences","volume":"10 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89363032","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-01-01DOI: 10.32604/cmes.2022.018130
Bei Liu, Xian Zhang
During high-intensity focused ultrasound (HIFU) treatment, the accurate identification of denatured biological tissue is an important practical problem. In this paper, a novel method based on the improved variational mode decomposition (IVMD) and autoregressive (AR) model was proposed, which identified denatured biological tissue according to the characteristics of ultrasonic scattered echo signals during HIFU treatment. Firstly, the IVMD method was proposed to solve the problem that the VMD reconstruction signal still has noise due to the limited number of intrinsic mode functions (IMF). The ultrasonic scattered echo signals were reconstructed by the IVMD to achieve denoising. Then, the AR model was introduced to improve the recognition rate of denatured biological tissues. The AR model order parameter was determined by the Akaike information criterion (AIC) and the characteristics of the AR coefficients were extracted. Finally, the optimal characteristics of the AR coefficients were selected according to the results of receiver operating characteristic (ROC). The experiments showed that the signal-to-noise ratio (SNR) and root mean square error (RMSE) of the reconstructed signal obtained by IVMD was better than those obtained by variational mode decomposition (VMD). The IVMD-AR method was applied to the actual ultrasonic scattered echo signals during HIFU treatment, and the support vector machine (SVM) was used to identify the denatured biological tissue. The results show that compared with sample entropy, information entropy, and energy methods, the proposed IVMD-AR method can more effectively identify denatured biological tissue. The recognition rate of denatured biological tissue was higher, up to 93.0%.
在高强度聚焦超声(HIFU)治疗中，变性生物组织的准确识别是一个重要的现实问题。本文提出了一种基于改进变分模态分解(IVMD)和自回归(AR)模型的方法，根据HIFU治疗过程中超声散射回波信号的特征识别变性生物组织。首先，针对固有模态函数(IMF)数量有限导致VMD重构信号仍然存在噪声的问题，提出了IVMD方法;利用IVMD对超声散射回波信号进行重构，实现去噪。然后，引入AR模型，提高变性生物组织的识别率。利用赤池信息准则(Akaike information criterion, AIC)确定AR模型阶数参数，提取AR系数的特征。最后，根据受试者工作特征(ROC)结果选择最佳的AR系数特征。实验表明，IVMD得到的重构信号信噪比(SNR)和均方根误差(RMSE)优于变分模态分解(VMD)得到的重构信号。将IVMD-AR方法应用于HIFU治疗过程中的实际超声散射回波信号，并利用支持向量机(SVM)识别变性生物组织。结果表明，与样本熵、信息熵和能量方法相比，所提出的IVMD-AR方法能更有效地识别变性生物组织。对变性生物组织的识别率较高，达93.0%。
{"title":"Identification of Denatured Biological Tissues Based on Improved Variational Mode Decomposition and Autoregressive Model during HIFU Treatment","authors":"Bei Liu, Xian Zhang","doi":"10.32604/cmes.2022.018130","DOIUrl":"https://doi.org/10.32604/cmes.2022.018130","url":null,"abstract":"During high-intensity focused ultrasound (HIFU) treatment, the accurate identification of denatured biological tissue is an important practical problem. In this paper, a novel method based on the improved variational mode decomposition (IVMD) and autoregressive (AR) model was proposed, which identified denatured biological tissue according to the characteristics of ultrasonic scattered echo signals during HIFU treatment. Firstly, the IVMD method was proposed to solve the problem that the VMD reconstruction signal still has noise due to the limited number of intrinsic mode functions (IMF). The ultrasonic scattered echo signals were reconstructed by the IVMD to achieve denoising. Then, the AR model was introduced to improve the recognition rate of denatured biological tissues. The AR model order parameter was determined by the Akaike information criterion (AIC) and the characteristics of the AR coefficients were extracted. Finally, the optimal characteristics of the AR coefficients were selected according to the results of receiver operating characteristic (ROC). The experiments showed that the signal-to-noise ratio (SNR) and root mean square error (RMSE) of the reconstructed signal obtained by IVMD was better than those obtained by variational mode decomposition (VMD). The IVMD-AR method was applied to the actual ultrasonic scattered echo signals during HIFU treatment, and the support vector machine (SVM) was used to identify the denatured biological tissue. The results show that compared with sample entropy, information entropy, and energy methods, the proposed IVMD-AR method can more effectively identify denatured biological tissue. The recognition rate of denatured biological tissue was higher, up to 93.0%.","PeriodicalId":10451,"journal":{"name":"Cmes-computer Modeling in Engineering & Sciences","volume":"17 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81381301","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-01-01DOI: 10.32604/cmes.2022.019440
Asad Ejaz, Y. Nawaz, Muhammad Shoaib Arif, Daoud S. Mashat, K. Abodayeh
{"title":"Stability Analysis of Predator-Prey System with Consuming Resource and Disease in Predator Species","authors":"Asad Ejaz, Y. Nawaz, Muhammad Shoaib Arif, Daoud S. Mashat, K. Abodayeh","doi":"10.32604/cmes.2022.019440","DOIUrl":"https://doi.org/10.32604/cmes.2022.019440","url":null,"abstract":"","PeriodicalId":10451,"journal":{"name":"Cmes-computer Modeling in Engineering & Sciences","volume":"240 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73063044","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-01-01DOI: 10.32604/cmes.2022.019245
Da Xu, Haijian Shao, X. Deng, Xia Wang
{"title":"The Hidden-Layers Topology Analysis of Deep Learning Models in Survey for Forecasting and Generation of theWind Power and Photovoltaic Energy","authors":"Da Xu, Haijian Shao, X. Deng, Xia Wang","doi":"10.32604/cmes.2022.019245","DOIUrl":"https://doi.org/10.32604/cmes.2022.019245","url":null,"abstract":"","PeriodicalId":10451,"journal":{"name":"Cmes-computer Modeling in Engineering & Sciences","volume":"1 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80827784","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-01-01DOI: 10.32604/cmes.2022.016212
J. Kao, Y. Liao
{"title":"Discussion of the Fluid Acceleration Quality of a Ducted Propulsion System on the Propulsive Performance","authors":"J. Kao, Y. Liao","doi":"10.32604/cmes.2022.016212","DOIUrl":"https://doi.org/10.32604/cmes.2022.016212","url":null,"abstract":"","PeriodicalId":10451,"journal":{"name":"Cmes-computer Modeling in Engineering & Sciences","volume":"12 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90409379","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-01-01DOI: 10.32604/cmes.2022.018313
Wuqin Tang, Qiang Yang, W. Yan
{"title":"Deep Learning-Based Algorithm for Multi-Type Defects Detection in Solar Cells with Aerial EL Images for Photovoltaic Plants","authors":"Wuqin Tang, Qiang Yang, W. Yan","doi":"10.32604/cmes.2022.018313","DOIUrl":"https://doi.org/10.32604/cmes.2022.018313","url":null,"abstract":"","PeriodicalId":10451,"journal":{"name":"Cmes-computer Modeling in Engineering & Sciences","volume":"39 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86537068","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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