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Controlled Source Electromagnetic data Denoising Based on CEEMD and Correlation Analysis 7

Controlled Source Electromagnetic Data Denoising Based on CE...

引用

7th International Conference on Information Science and Control engineering, ICISCE 2020

作者： DI, DIng Guang, Li Zhu-Shi, He Xiao-Qiong, Liu Hao-Hao, Zheng Tian-Ze, Li East China University of Technology Jiangxi Engineering Laboratory on Radioactive Geoscience and Big Data Technology Nanchang330013 China

ISBN: (纸本)9781728164069

Controlled-source electromagnetic method (CSEM) signals are inevitably contaminated by man-made noises. For this reason, a new CSEM data processing method was proposed. First, the 50 Hz powerline interference was removed by FFT method, followed by the CEEMD method to remove baseline drift, and finally the correlation analysis method was used to select the high-quality signal. The method was applied to the processing of measured data in Huidong, Sichuan. As a conclusion, the presented method can effectively remove the strong cultural noise from raw CSEM data and preserve the useful signal completely;the apparent resistivity curves acquired by using the filtered data are improved significantly upon the previous. © 2020 IEEE.

关键词： Quality control

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Research on speech enhancement based on deep neural network

Research on speech enhancement based on deep neural network

引用

2020 International Conference on Applied Physics and Computing, ICAPC 2020

作者： Wang, Yiting Wei, Zhenhua Jiangxi Engineering Laboratory on Radioactive Geoscience and Big Data China School of Information Engineering East China University of Technology Nanchang Jiangxi330013 China

The traditional single-channel speech enhancement algorithm has many unreasonable assumptions, which limit the performance of the algorithm. The speech enhancement based on deep neural network can effectively eliminate the problems such as "music noise" in the traditional methods, thus achieving better results than the traditional single-channel speech enhancement. However, the DNN-based speech enhancement model does not perform well at low SNR. In order to improve the robustness of the model, we used voice activity detection (VAD) to process the training data to obtain a new VAD-DNN speech enhancement model. We added 100 kinds of noise in the training set to improve the ability of the model to deal with the unseen noise. At the same time, in order to prevent the occurrence of overfitting problem, we introduced dropout technology to process the network, and improved the generalization ability of the model by using noise awareness training (NAT). Through experiments, we found that the speech enhancement model based on VAD-DNN improved PESQ index by 0.02 and STOI index by 0.01 on average under the condition of low SNR. © 2020 Institute of Physics Publishing. All rights reserved.

关键词： Speech enhancement

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A method for detecting flower collision based on spherical projection 1

引用

13th Conference on Image and Graphics Technologies and Applications, IGTA 2018

作者： Cao, Tingrong Lu, Ling Wang, Wenli Li, Lihua Wang, Lei Jiangxi Engineering Laboratory on Radioactive Geoscience and Big Data Technology East China University of Technology Nanchang China Jiangxi Engineering Research Center of Nuclear Geoscience Data Science and System East China University of Technology Nanchang China

ISBN: (数字)9789811317026

ISBN: (纸本)9789811317019

In this paper, a method for detecting and mapping the petals of plant petals is presented. Firstly, the parametric equations are used to represent the initial state of the petals surface. The three - dimensional Cartesian coordinates of each point in the petals are projected onto the spherical coordinates respectively, The discrete values of the projection of the petals are converted to the two-dimensional coordinate plane. Secondly, multiple buffers are used to record the result of each petals projection and the distance of the petals from the origin of the spherical coordinates. According to the value of each buffer, it is determined whether the current petal collides with others, the collides result can be determined the range of collision. Finally, the current petals are deformed or moved to avoid collided with others. Through the collision test between the petals in the process of flower generation, it shows that the detection effect is good. © Springer Nature Singapore Pte Ltd., 2018.

关键词： Spheres

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Image Semantic Segmentation Based on Dilated Convolution and Multi-Layer Feature Fusion

Image Semantic Segmentation Based on Dilated Convolution and...

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2021 IEEE International Conference on Artificial Intelligence and Industrial Design, AIID 2021

作者： Liu, Jun Wu, Zhongliang Hong, Yang Zhong, Guoyun Liu, Meifeng East China University of Technology Jiangxi Radioactive Geoscience Large Data Technology Engineering Laboratory Nanchang Jiangxi330013 China

ISBN: (纸本)9780738110837

At present, most of the research methods of image semantic segmentation are based on Fully Convolutional Networks (FCN). However, FCN will cause the loss of image feature information when performing image semantic segmentation, and the details of the output image will not be processed well. Therefore, we propose to take the ResNet network as the encoder basic network. Using dilated convolution to extract context information, and designing a multi-scale feature fusion method in the decoder to make full use of features from each level to enrich representative ability of feature points, so that it can classify image pixels well. Extensive experiments demonstrate that our method shows superior performance over other methods on the PASCAL VOC2012 [10]validation dataset. © 2021 IEEE.

关键词： Convolution

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Analyse the Influence of big data on Students' Learning Behavior 6

Analyse the Influence of Big Data on Students' Learning Beha...

引用

6th Annual 2018 International Conference on Geo-Spatial Knowledge and Intelligence, GSKI 2018

作者： Ai, Jumei Gao, Jinlong Du, Ping Jiangxi Engineering Laboratory on Radioactive Geoscience and Big Data Technology East China University of Technology Nanchang Jiangxi China Fuzhou Teachers' College East China University of Technology Fuzhou Jiangxi China

The application of big data has penetrated into many fields of society, and the education industry is no exception. In this paper, we try to collect and analyze the data related to teaching activities, use data mining technology to construct a mathematical model of the corresponding large teaching data, explore the relationship between representation and substance, provide useful information support for teaching activities, promote and help improve the quality of teaching, and verify the proposed mathematical model through experimental analysis. Better analysis results. © Published under licence by IOP Publishing Ltd.

关键词： big data

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Fine-grained image classification method based on generating adversarial networks with SIFT texture input

Fine-grained image classification method based on generating...

引用

2021 International Conference on Computer engineering and Artificial Intelligence, ICCEAI 2021

作者： Guoyun, Zhong Jun, Liu Yang, Hong Meifeng, Liu Hongyang, Sun East China Institute University of Technology Jiangxi Radioactive Geoscience Large Data Technology Engineering Laboratory Nanchang China

ISBN: (纸本)9781665439602

A fine-grained image classification method based on generating adversarial networks with SIFT (Scale Invariant Feature Transform) texture input is proposed to improve the recognition ratio of fine-grained image classification by deep learning. For the phenomenon of data sets that require a large amount of labeled information for strong supervised learning, active learning capabilities of generative and adversarial networks and excellent image modeling capabilities for target classification images are used to achieve active learning of image features. Then the difficulty of data set construction and the computational complexity are reduced, and the disturbance to the network that may be caused by manually set labeled boxes is lessened. The input method of generating the adversarial network to is fixed to balance the authenticity and diversity of the generated samples. The idea of image restoration is considered. The random input method of the generative adversarial network that combines image feature points and random noise to is used to reduce the training difficulty of the generative and adversarial network. Experiments results show that our method outperformances the current deep learning methods in fine-grained image classification. © 2021 IEEE.

关键词： Image classification

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The application of decision tree in the prediction of winning team

The application of decision tree in the prediction of winnin...

引用

2018 International Conference on Virtual Reality and Intelligent Systems, ICVRIS 2018

作者： Tang, Xiaohu Liu, Zhifeng Li, Taizhao Wu, Wenbin Wei, Zhenhua Jiangxi Engineering Laboratory on Radioactive Geoscience and Big Data Technology East China University of Technology Nanchang Jiangxi330013 China Jiangxi Engineering Technology Research Center of Nuclear Geoscience Data Science and System East China University of Technology Nanchang Jiangxi330013 China Information Engineering College East China University of Technology Nanchang Jiangxi330013 China

ISBN: (纸本)9781538680315

Decision tree algorithm is mainly used for analyzing data and *** algorithm is easy to understand and implement, and it is easy to evaluate the model through static *** this paper, the decision tree algorithm is applied to predict the result of Chinese Football Association Super League(CFASL). In this paper, the data of CFASL 2015, 2016 and 2017 seasons are collected. And 'the result of each team's last match', 'compare of teams' ranking in last season', 'the result of last time the two teams played',etc. are selected as features to predict the winner of a CFASL match. The experiments found that 'two teams' performance in their recent matches', 'whether team A has defeated team B as an away team' and 'whether team B has defeated team A as an away team' played a key role in improving the accuracy of predicting. © 2018 IEEE.

关键词： Forecasting

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The research of data blood relationship analysis on metadata 10th

The research of data blood relationship analysis on metadata

引用

10th International Symposium on Intelligence Computation and Applications, ISICA 2018

作者： Guan, Fenfen Gao, Yongping Cai, Congcong Zhang, Jun Jiangxi Engineering Laboratory on Radioactive Geoscience and Big Data Technology East China University of Technology NanchangJiangxi330013 China School of Foreign Language East China University of Technology Shanghai China Teradata San Diego United States

ISBN: (纸本)9789811364723

In the process of continuous expansion of data and continuous expansion of the system, various data relations and data forms form crisscross connections, forming an extremely complex network diagram. If there is an error in the data, how do we quickly lock the cause of the problem? How do we find out which entities are affected by the implications or changes of the problem? These issues create challenges and pressures for large-scale, enterprise-level data platforms. The paper proposes to use data blood analysis to solve the relationship among tens of millions of tables. To get this kind of more underlying blood information, we need to add embedded parts to the execution engine, which will be fed into the blood relationship collection system using push mode when the job is executed. The paper is to implement field level blood relationship analysis in the data warehouse of China Commercial bank on the architecture of Teradata, and separated it from the ETL process and made it into a single part. By parsing multiple ETL jobs, we get a number of mapping relationship of atoms, and atoms and relationships make up the molecules that form the blood relationship network we need. This experimental scheme can be simply embedded into the data platform by eliminating the complexity of the system and achieving a separate component structure. The blood relationship can be conducted any time and temporary scripts and error logic of related data will have no data pollution on the data blood relationship. © Springer Nature Singapore Pte Ltd. 2019.

关键词： Locks (fasteners)

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Current Status and Development Trend Analysis of Neutron Logging in Uranium Mines in China

Current Status and Development Trend Analysis of Neutron Log...

引用

2021 International Conference on Advances in Optics and Computational Sciences, ICAOCS 2021

作者： Liu, Zhifeng Ding, Chenglong Wang, Ruyang Cao, Junwu Jiangxi Engineering Technology Research Center of Nuclear Geoscience Data Science and System East China University of Technology Nanchang Jiangxi330013 China East China University of Technology China 6th Gas Production Plant of Changqing Oilfield China Jiangxi Engineering Laboratory on Radioactive Geoscience and Big Data Technology East China University of Technology Nanchang Jiangxi330013 China

Neutron logging is a method of measuring uranium fission neutrons by bombarding uranium in ore beds with neutrons emitted by neutron sources or neutron generators. The pulsed neutron logging technology of uranium ore has been popularized and applied in the United States, Russia, Australia and other countries. The key technology is almost monopolized by these countries, but the technology is prohibited in China. In the field of uranium logging, natural gamma logging has always been used in China for uranium quantification, which is characterized by large error, low efficiency, high cost and technical and economic bottlenecks. Due to the fact that the research and application of pulsed neutron log in the field of petroleum exploration and production is relatively mature in China, it is urgent to develop relevant logging instruments and uranium quantitative interpretation methods as independent intellectual property rights. This will lead to a change in the backward appearance of uranium logging. This paper analyzes the research status and development trend of neutron logging in uranium at home and abroad. © Published under licence by IOP Publishing Ltd.

关键词： Uranium

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Clustering ensemble for categorical geological text based on diversity and quality 8th

Clustering ensemble for categorical geological text based on...

引用

8th International Conference on Computer engineering and Networks, CENet 2018

作者： Wang, Hongling He, Yueshun Du, Ping East China University of Technology Nanchang330013 China Jiangxi Engineering Laboratory on Radioactive Geoscience and Big Data Technology East China University of Technology Nanchang330013 China China University of Geosciences Wuhan430074 China

ISBN: (纸本)9783030146795

Clustering analysis for geological text makes the navigation, retrieval or extraction of geological text more effectively. Clustering ensemble can be employed to obtain more robust clustering results. However, most generation approaches focus on the diversity of clustering members rather than their quality. Too much emphasis on the diversity of clustering members reduces the accuracy of clustering results. In order to solve the problem, a new generation method of clustering members is proposed in this paper. Hierarchical clustering algorithm and k-means algorithm alternately combined with random projection method are employed to generate diverse base members and a new selection strategy for the number of clusters is presented to improve the quality of clustering members. Furthermore, a clustering ensemble framework for geological text is constructed. The framework involves geological text preprocessing, geological text feature representation, clustering members generation and ensemble integration. Experimental results on two UCI datasets and one real-world geological text demonstrate that the clustering ensemble based on diversity and quality is superior to those clustering ensemble algorithms that only consider the diversity of clustering members. © Springer Nature Switzerland AG 2020.

关键词： K-means clustering

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