Multipoint Vibration Response Prediction under Uncorrelated Multiple Sources Load Based on Elastic-Net Regularization in Frequency Domain

In order to solve the problems of large number of conditions at inherent frequencies and low prediction accuracy when using multiple multivariate linear regression methods for vibration response prediction alone, an elastic-net regularization method is proposed. Firstly, a multi-input and multioutput linear regression model of the multipoint frequency domain vibration response is trained using historical data at each frequency point. Secondly, the trained model under each frequency point is improved by the elastic regularization. Finally, the model is used in a working situation. The predicted vibration response on the experimental dataset of cylindrical shell acoustic vibration showed that the improvement of the multivariate regression vibration response prediction model by elastic regularization can better improve the accuracy and reduce the large number of conditions at some frequencies.

Deblurring of Motion Blurred Images Using GLCM and Elastic Net Regularization

An image deburring algorithm consists of rich edge area mining with a gray-level co-occurring matrix and elastic net regularisation is proposed in this paper. First, the luminance channel of an image is removed from the blurred image. The frequency layer is highthat can be derived from the blurred image by converting the 2D haar wavelet in the luminance channel.By the way, measurements were made using area and the richest edge region information is then collected. Finally, the extracted rich edge field, instead full motion blurred image, approximate the blur kernel elastic net regularisation and the image is returned. A measurement of image mechanism and running time measures the proposed system. Result suggestedto recommended strategy would improve efficiency and ensure continuity in recovery.

New computational model for miRNA-mediated repression reveals novel regulatory roles of miRNA bindings inside the coding region

Motivation MicroRNAs (miRNAs) are short (∼24nt), non-coding RNAs, which downregulate gene expression in many species and physiological processes. Many details regarding the mechanism which governs miRNA-mediated repression continue to elude researchers. Results We elucidate the interplay between the coding sequence and the 3′UTR, by using elastic net regularization and incorporating translation-related features to predict miRNA-mediated repression. We find that miRNA binding sites at the end of the coding sequence contribute to repression, and that weak binding sites are linked to effective de-repression, possibly as a result of competing with stronger binding sites. Furthermore, we propose a recycling model for miRNAs dissociated from the open reading frame (ORF) by traversing ribosomes, explaining the observed link between increased ribosome density/traversal speed and increased repression. We uncover a novel layer of interaction between the coding sequence and the 3′UTR (untranslated region) and suggest the ORF has a larger role than previously thought in the mechanism of miRNA-mediated repression. Availability and implementation The code is freely available at https://github.com/aescrdni/miRNA_model. Supplementary information Supplementary data are available at Bioinformatics online.

Elastic-net regularization based multi-point vibration response prediction in situation of unknown uncorrelated multiple sources load

In order to reduce the influence of ill-posed inverse on response prediction in the situation of unknown uncorrelated multiple sources load, a response prediction method based on elastic-net regularization in the frequency domain was proposed. This method utilized the linear relationship between known responses and the unknown responses instead of the transfer function to predict the response. Moreover, the elastic-net regularization model has two regularization parameters combining l1, l2 regularization to reduce the influence of ill-posed inverse. The experiment results on the data of acoustic and vibration sources on cylindrical shells showed that the elastic-net regularization in predicting response could obtain higher accurate results compared with the method of transfer function and the method of ordinary least squares, and predict vibration response effectively and satisfy industrial requirements.