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A Survey on Machine Learning Algorithms in Little-Labeled data for Motor Imagery-Based Brain-Computer Interfaces

Journal of Information Hiding and Privacy Protection 2019年第1期1卷 11-21页

作者： Yuxi Jia Feng Li Fei Wang Yan Gui School of Computer and Communication Engineering Changsha University of Science and TechnologyChangsha410114China Hunan Provincial Key Laboratory of Intelligent Processing of Big Data on Transportation Changsha University of Science and TechnologyChangsha410114China School of Mechanical and Aerospace Engineering Nanyang Technological UniversitySingapore639798Singapore

The Brain-Computer Interfaces(BCIs)had been proposed and used in therapeutics for ***,the need of time-consuming calibration phase and the lack of robustness,which are caused by little-labeled data,are restricting the advance and application of BCI,especially for the BCI based on motor imagery(MI).In this paper,we reviewed the recent development in the machine learning algorithm used in the MI-based BCI,which may provide potential solutions for addressing the *** classified these algorithms into two categories,namely,and enhancing the representation and expanding the training ***,these methods of enhancing the representation of features collected from few EEG trials are based on extracting features of multiple bands,regularization,and so *** methods of expanding the training dataset include approaches of transfer learning(session to session transfer,subject to subject transfer)and generating artificial EEG *** result of these techniques showed the resolution of the challenges to some *** a developing research area,the study of BCI algorithms in little-labeled data is increasingly requiring the advancement of human brain physiological structure research and more transfer learning algorithms research.

关键词： Brain-Computer interface electroencephalography(EEG) machine learning

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Adaptive multi-graph hashing for scalable multimedia retrieval

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Pattern Recognition Letters 2019年

作者： Xiang, Lingyun Zhao, Guohan Shen, Xiaobo Li, Feng Hunan Provincial Key Laboratory of Intelligent Processing of Big Data on Transportation Changsha University of Science and Technology Changsha410114 China School of Computer and Communication Engineering Changsha University of Science and Technology Changsha410114 China Hunan Provincial Key Laboratory of Smart Roadway and Cooperative Vehicle-Infrastructure Systems Changsha410114 China School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing210094 China

Hashing has become a promising technique to be applied to the large-scale visual retrieval tasks. Multi-view data has multiple views, providing more comprehensive information. Existing hashing methods measure the similarity among the data points by the pre-defined graph Laplacian in each view separately, and thus ignore the underlying common structures across different views. In this paper, we propose a novel hashing method, called adaptive multi-graph hashing (AMGH) to address the above issue. AMGH uses the adaptive weights among the data points, and the weights of each view to characterize the common structure of multi-view data. In addition, AMGH further minimizes the quantization errors. We develop an efficient alternating algorithm to solve the formulated optimization problem. The experiments on three large-scale datasets demonstrate the superiority of the proposed method over the existing multi-view hashing methods. © 2019

关键词： Large dataset

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Geo-spatial ontology matching through compact evolutionary algorithm 2nd

Geo-spatial ontology matching through compact evolutionary a...

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2nd International Conference on Smart Vehicular Technology, transportation, Communication and Applications, VTCA 2018

作者： Xue, Xingsi Liu, Jianhua College of Information Science and Engineering Fujian University of Technology FuzhouFujian350118 China Intelligent Information Processing Research Center Fujian University of Technology FuzhouFujian350118 China Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of Technology FuzhouFujian350118 China Fujian Key Lab for Automotive Electronics and Electric Drive Fujian University of Technology FuzhouFujian350118 China

ISBN: (纸本)9783030045845

Geo-spatial ontologies can provide a formal description of concepts, relationships, activities, features and rules in GIS domain. However, simply use them only allows to partially solve semantic conflicts, and does not completely solve heterogeneity issues that are caused by themselves. Geo-spatial ontology matching technique can find the correspondences between semantic identical entities, and solve the heterogeneous problem between two geo-spatial ontologies. Be inspired by the successful application of Evolutionary Algorithm (EA) in instance matching domain, in this paper, it is utilized to match the heterogeneous geo-spatial ontologies. To reduce the runtime and memory consumption required by EA, a compact version of it is presented, which does not work on the whole population but a probability representation on it. In addition, a geo-spatial similarity measure is presented to determine the identical geo-spatial entities, and an optimal model is constructed for geo-spatial ontology matching problem. The experimental results show that cEA-based geo-spatial ontology matching technique can efficiently determine the alignment. © Springer Nature Switzerland AG 2019.

关键词： Evolutionary algorithms

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Adversarial Learning for Distant Supervised Relation Extraction

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Computers, Materials & Continua 2018年第4期55卷 121-136页

作者： Daojian Zeng Yuan Dai Feng Li R.Simon Sherratt Jin Wang Hunan Provincial Key Laboratory of Intelligent Processing of Big Data on Transportation School of Computer&Communication EngineeringChangsha University of Science&TechnologyChangsha410114P.R.China Department of Biomedical Engineering University of ReadingUK. School of Computer&Communication Engineering Changsha University of Science&TechnologyChangsha410114P.R.China.

Recently,many researchers have concentrated on using neural networks to learn features for Distant Supervised Relation Extraction(DSRE).These approaches generally use a softmax classifier with cross-entropy loss,which inevitably brings the noise of artificial class NA into classification *** address the shortcoming,the classifier with ranking loss is employed to *** randomly selecting a relation or heuristically selecting the highest score among all incorrect relations are two common methods for generating a negative class in the ranking loss ***,the majority of the generated negative class can be easily discriminated from positive class and will contribute little towards the *** by Generative Adversarial Networks(GANs),we use a neural network as the negative class generator to assist the training of our desired model,which acts as the discriminator in *** the alternating optimization of generator and discriminator,the generator is learning to produce more and more discriminable negative classes and the discriminator has to become better as *** framework is independent of the concrete form of generator and *** this paper,we use a two layers fully-connected neural network as the generator and the Piecewise Convolutional Neural Networks(PCNNs)as the *** results show that our proposed GAN-based method is effective and performs better than state-of-the-art methods.

关键词： Relation extraction generative adversarial networks distant supervision piecewise convolutional neural networks pair-wise ranking loss

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Reversible Natural Language Watermarking Using Synonym Substitution and Arithmetic Coding

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Computers, Materials & Continua 2018年第6期55卷 541-559页

作者： Lingyun Xiang Yan Li Wei Hao Peng Yang Xiaobo Shen Hunan Provincial Key Laboratory of Intelligent Processing of Big Data on Transportation Changsha University of Science and TechnologyChangsha 410114HunanChina School of Computer and Communication Engineering Changsha University of Science and TechnologyChangsha 410114HunanChina School of Traffic&Transportation Engineering Changsha University of Science&TechnologyChangsha 410114HunanChina Hunan Branch of CNCERT/CC Changsha 410004HunanChina School of Computer Science and Engineering Nanyang Technological University639798Singapore

For protecting the copyright of a text and recovering its original content harmlessly,this paper proposes a novel reversible natural language watermarking method that combines arithmetic coding and synonym substitution *** analyzing relative frequencies of synonymous words,synonyms employed for carrying payload are quantized into an unbalanced and redundant binary *** quantized binary sequence is compressed by adaptive binary arithmetic coding losslessly to provide a spare for accommodating additional ***,the compressed data appended with the watermark are embedded into the cover text via synonym substitutions in an invertible *** the receiver side,the watermark and compressed data can be extracted by decoding the values of synonyms in the watermarked text,as a result of which the original context can be perfectly recovered by decompressing the extracted compressed data and substituting the replaced synonyms with their original *** results demonstrate that the proposed method can extract the watermark successfully and achieve a lossless recovery of the original ***,it achieves a high embedding capacity.

关键词： Arithmetic coding synonym substitution lossless compression reversible watermarking.

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Efficient trajectory data privacy protection scheme based on laplace's differential privacy

Efficient trajectory data privacy protection scheme based on...

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作者： Gu, Ke Yang, Lihao Liu, Yongzhi Yin, Bo School of Computer and Communication Engineering Changsha University of Science and Technology Changsha410114 China Hunan Provincial Key Laboratory of Intelligent Processing of Big Data on Transportation Changsha University of Science and Technology Changsha410114 China School of Information Science and Engineering Central South University Changsha410083 China

Now many applications of trajectory (location) data have facilitated people's daily life. However, publishing trajectory data may divulge individual sensitive information so as to influence people's normal life. On the other hand, if we cannot mine and share trajectory data information, trajectory data will lose its value to serve our society. Currently, because the records of trajectory data are discrete in database, some existing privacy protection schemes are difficult to protect trajectory data. In this paper, we propose a trajectory data privacy protection scheme based on Laplace's differential privacy mechanism. In the proposed scheme, the algorithm first selects the protected points from the user's trajectory data;secondly, the algorithm builds the polygons according to the protected points and the adjacent and high frequent accessed points selected from the accessed point database, then the algorithm calculates the polygon centroids;finally, the noises are added to the polygon centroids by the Laplace's differential privacy method, and the new polygon centroids are used to replace the protected points, and then the algorithm constructs and issues the new trajectory data. The experiments show that the running time of the proposed algorithms is fast, the privacy protection of the scheme is effective and the data usability of the scheme is higher. © 2018 Slovene Society Informatika. All rights reserved.

关键词： Trajectories

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Separable reversible data hiding and encryption for HEVC video

Separable reversible data hiding and encryption for HEVC vid...

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作者： Long, Min Peng, Fei Li, Han-yun College of Computer and Communication Engineering Changsha University of Science and Technology ChangshaHunan China Hunan Provincial Key Laboratory of Intelligent Processing of Big Data on Transportation Changsha University of Science and Technology ChangshaHunan410114 China College of Computer Science and Electronic Engineering Hunan University ChangshaHunan China

A separable reversible data hiding and encryption for high efficiency video coding (HEVC) video is proposed in this paper. In the encoding phase, one can encrypt the signs and amplitudes of motion vector differences and the signs of residual coefficients with an encryption key by using RC4, while another can hide data into nonzero AC residual coefficients with a hiding key. For the decoding phase, one can decrypt the HEVC video and obtain a HEVC video similar to the original one if he only has the encryption key;he can extract the hiding data, but he does not know the HEVC video content if he only has the hiding key;he can extract the hiding data and recover the original HEVC video if he has both the encryption key and hiding key. Experimental results and analysis show that the proposed scheme can obtain a good security performance and keep the HEVC video stream format compliant. © 2017, Springer-Verlag GmbH Germany.

关键词： Steganography

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Analysis of SET pulses propagation probabilities in sequential circuits

Analysis of SET pulses propagation probabilities in sequenti...

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2017年第二届可靠性工程国际会议

作者： Shuo Cai Fei Yu Yiqun Yang School of Computer and Communication Engineering Changsha University of Science and Technology Hunan Provincial Key Laboratory of Intelligent Processing of Big Data on Transportation Changsha University of Science and Technology

As the feature size of CMOS transistors scales down, single event transient（SET） has been an important consideration in designing logic circuits. Many researches have been done in analyzing the impact of SET. However, it is difficult to consider numerous factors. We present a new approach for analyzing the SET pulses propagation probabilities（SPPs）. It considers all masking effects and uses SET pulses propagation probabilities matrices（SPPMs） to represent the SPPs in current cycle. Based on the matrix union operations, the SPPs in consecutive cycles can be calculated. Experimental results show that our approach is practicable and efficient.

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Trajectory data privacy protection based on differential privacy mechanism

Trajectory data privacy protection based on differential pri...

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2017年第二届可靠性工程国际会议

作者： Ke Gu Lihao Yang Yongzhi Liu Niandong Liao School of Computer and Communication Engineering Changsha University of Science and Technology Hunan Provincial Key Laboratory of Intelligent Processing of Big Data on Transportation Changsha University of Science and Technology

In this paper, we propose a trajectory data privacy protection scheme based on differential privacy mechanism. In the proposed scheme, the algorithm first selects the protected points from the user’s trajectory data;secondly, the algorithm forms the polygon according to the protected points and the adjacent and high frequent accessed points that are selected from the accessing point database, then the algorithm calculates the polygon centroids;finally, the noises are added to the polygon centroids by the differential privacy method, and the polygon centroids replace the protected points, and then the algorithm constructs and issues the new trajectory data. The experiments show that the running time of the proposed algorithms is fast, the privacy protection of the scheme is effective and the data usability of the scheme is higher.

关键词：

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Survey of key technologies on millimeter-wave CMOS integrated circuits

Survey of key technologies on millimeter-wave CMOS integrate...

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2017年第二届可靠性工程国际会议

作者： Fei Yu Lei Gao Lixiang Li Shuo Cai Wei Wang Chunhua Wang Hunan Provincial Key Laboratory of Intelligent Processing of Big Data on Transportation & School of Computer and Communication Engineering Changsha University of Science and Technology College of Information Science and Engineering Hunan University

In order to provide guidance for the development of high performance millimeter-wave complementary metal oxide semiconductor(MMW-CMOS) integrated circuits(IC), this paper provides a survey of key technologies on MMW-CMOS IC. Technical background of MMW wireless communications is described. Then the recent development of the critical technologies of the MMW-CMOS IC are introduced in detail and compared. A summarization is given, and the development prospects on MMWCMOS IC are also discussed.

关键词： Survey of key technologies on millimeter-wave CMOS integrated circuits

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