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2018 International Conference on Advanced Control, Automation and Artificial Intelligence (ACAAI2018)

作者： Zhiying Gao Lijun Sun Zhihua Wei Department of Computer Science and Technology Tongji University Research Center of Big Data and Network Security Tongji University Key Laboratory of Embedded System and Service Computing Tongji University

Nowadays, with the increasing number of protein sequences all over the world, more and more people are paying their attention to predicting protein subcellular location. Since wet experiment is costly and time-consuming, the automatic computational methods are urgent. In this paper, we propose a variant model based on Long Short-Term Memory(LSTM) to predict protein subcellular location. In this model, we employ LSTM to capture long distance dependency features of the sequence data. Moreover, we adjust the loss function of the loss layer to solve multi-label classification problem. Experimental results demonstrate that, compared with the traditional machine learning methods, our method achieves the best performance in various evaluation metrics.

关键词： LSTM multi-label classification protein subcellular localization

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Ciphertext-Policy Attribute Based Encryption Supporting Any Monotone Access Structures Without Escrow

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Chinese Journal of Electronics 2017年第3期26卷 640-646页

作者： ZHAO Qianqian ZHANG Yuqing ZHANG Guanghua WANG He State Key Laboratory of Integrated Services Networks Xidian University National Computer Network Intrusion Protection Center University of Chinese Academy of Sciences Beijing Key Laboratory of IOT Information Security Technology Institute of Information Engineering CAS

Ciphertext policy attribute-based encryption(CP-ABE)is becoming a new primitive for finegrained access *** neither produces multiple encrypted copies of the same data nor suffers from the severe burden of key distribution and *** escrow problem that the central authority could decrypt any ciphertexts addressed to all the specific users is still a challenge for CP-ABE *** new CP-ABE scheme without escrow is proposed,and furthermore the proposed scheme achieves fully security in the standard *** performance and security analysis results indicate that the proposed CP-ABE scheme is extremely appropriate for cloud storage system.

关键词： CP-ABE The escrow problem Fully security In the standard model

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A New Construction Method of Regeneration Tree for Single Node Fault Repair Mechanism in Distributed Storage System

A New Construction Method of Regeneration Tree for Single No...

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International Conference on Computational Intelligence and security

作者： Wei Guo Yong Wang Miao Ye School of Computer Science and Information Security Guilin University of Electronic Technoloay Guilin Guangxi China Guangxi Cooperative Innovation Center of Cloud Computing and Big Data Guilin University of Electronic Technology Guilin Guangxi China Guangxi Colleges and Universities Key Laboratory of Cloud Computing and Complex Systems Guilin University of Electronic Technology Guilin Guangxi China School of Information and Communication Guilin University of Electronic Technology Guilin Guangxi China

ISBN: (数字)9781728160924

ISBN: (纸本)9781728160931

Comparing with the classic redundancy policy of multi-replica technology, Erasure code is preferred due to its higher utilization rate of storage space in distributed storage system. As one kind of the important Erasure code, the traditional regeneration code with star recovery topology cost more time and more network bandwidth in the data recovery process. An efficient approach to reduce the delay time and network consumption is to construct an optimal recovery tree with the best possible bottleneck bandwidth, which is proved to be a Non-deterministic Polynomial problem. To solve this problem, this paper proposed a hybrid genetic algorithm which utilizes the designed crossover operation and mutation operation according to the problem property. A series of experiments have been conducted and the results show that our proposed method has good convergent ability and reduce the regeneration time.

关键词： Topology Bandwidth Genetic algorithms Encoding network topology Sociology Statistics

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Multimodal data fusion algorithm applied to robots

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Journal of Physics: Conference Series 2020年第1期1453卷

作者： Xin Zhang Zhiquan Feng Jinglan Tian Xiaohui Yang College of Information Science and Engineering University of Jinan Jinan Shandong 250022 China Shandong Provincial Key Laboratory of Network Environment Intelligent Computing Technology University of Jinan Jinan Shandong 250022 China

In recent years, the use of multimodal human-computer interaction technology to achieve the enhancement of human intelligence has become a new topic in human-computer interaction research. When the robot can't react correctly in a single mode, it is necessary to realize multimodal fusion. To this end, this paper proposes a multimodal fusion algorithm that applies the data obtained by the CNN feature layer to the decision-level. The speech recognition text is semantically matched with the text in the text library, and the similar probability vector is returned. At the same time, the similarity probability vector of the gesture recognition is obtained, and the data is filtered by the threshold, and the set of high probability data codes is assigned to the two modes. The intersection operation, and the final instruction is sent to the robot. The experimental results show that the influence of environmental factors on the single channel result is reduced, and the single mode ambiguity problem is eliminated. The multi-channel fusion algorithm with additional weight is more accurate than the common multi-channel fusion algorithm. At the same time, it has also been well received by many test users.

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Generalized Association and Deep Understanding Method for Big Video Data Processing

Generalized Association and Deep Understanding Method for Bi...

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IEEE International Symposium on Parallel and Distributed Processing with Applications and IEEE International Conference on Ubiquitous computing and Communications (ISPA/IUCC)

作者： Lin Xu Wei Wu Wanghan Lv Dong Wang Science and Technology in Information System Engineering Lab Nanjing Research institute of Electronic Engineering Nanjing China School of Information Science and Engineering University of Jinan Jinan China Shandong Provincial Key Laboratory of Network Based Intelligent Computing University of Jinan Jinan China

ISBN: (纸本)9781728152103

In Big Data Era, it is becoming more and more important to timely and efficient processing of massive videos, and mining of the value information contained in them. This paper studies chaotic compressed sensing theory and uses Long-term and short-term memory networks (LSTM) algorithm to generate a summary of the content of video behavior track. It has already to apply the proposed method in target recognition and tracking, and the recognition rate achieves more than 86%.

关键词： Big Data compressed sensing data compression data mining video coding big data Compressed sensing Data compression Video coding data mining video data Target recognition

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Multimodal Fusion of Speech and Gesture Recognition based on Deep Learning

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Journal of Physics: Conference Series 2020年第1期1453卷

作者： Xiaoyu Qiu Zhiquan Feng Xiaohui Yang Jinglan Tian College of Information Science and Engineering University of Jinan Jinan Shandong 250022 China Shandong Provincial Key Laboratory of Network Environment Intelligent Computing Technology University of Jinan Jinan Shandong 250022 China

This paper proposes a multimodal fusion architecture based on deep learning. The architecture consists of two forms: speech command and hand gesture. First, the speech and gesture commands input by users are recognized by CNN for speech command recognition and LSTM for hand gesture recognition respectively. Secondly, the obtained results are searched by keywords and compared by similarity degree to obtain recognition results. Finally, the two results are fused to output the final instructions. Experiments show that the proposed multi-mode fusion model is superior to the single-mode fusion model.

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Real-time multimodal emotion recognition system based on elderly accompanying robot

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Journal of Physics: Conference Series 2020年第1期1453卷

作者： Shaosong Dou Zhiquan Feng Xiaohui Yang Jinglan Tian College of Information Science and Engineering University of Jinan JinanShandong 250022 China Shandong Provincial Key Laboratory of Network Environment Intelligent Computing Technology University of Jinan Jinan Shandong 250022 China

In recent years, people have been paying more attention to the impact of technological development on human emotion recognition. At the same time, China has become the country with the most elderly population in the world. However, due to the lack of real-time multimodal emotion recognition technology for the elderly accompany robots, this paper proposes a deep learning decision-level fusion of real-time emotion analysis model which is based on the background of the elderly care. The results of image and audio recognition are used for intersection and union operation to get emotional classification result, and the obtained emotional result is corresponding to the feedback behavior of the accompany *** after the experiment, the recognition algorithm proposed in this paper accuracy can reach about 90%, which is nearly 10% higher than the single mode, and the feedback of the robot has achieved the expected effect.

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Unsupervised person re-identification by deep asymmetric metric embedding

arXiv

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arXiv 2019年

作者： Yu, Hong-Xing Wu, Ancong Zheng, Wei-Shi School of Data and Computer Science Sun Yat-sen University Guangzhou510275 China Guangdong Province Key Laboratory of Information Security China School of Electronics and Information Technology Sun Yat-sen University Guangzhou510275 China Collaborative Innovation Center of High Performance Computing NUDT China School of Data and Computer Science Sun Yat-sen University Guangzhou510275 China Key Laboratory of Machine Intelligence and Advanced Computing Ministry of Education China

Person re-identification (Re-ID) aims to match identities across non-overlapping camera views. Researchers have proposed many supervised Re-ID models which require quantities of cross-view pairwise labelled data. This limits their scalabilities to many applications where a large amount of data from multiple disjoint camera views is available but unlabelled. Although some unsupervised Re-ID models have been proposed to address the scalability problem, they often suffer from the view-specific bias problem which is caused by dramatic variances across different camera views, e.g., different illumination, viewpoints and occlusion. The dramatic variances induce specific feature distortions in different camera views, which can be very disturbing in finding cross-view discriminative information for Re-ID in the unsupervised scenarios, since no label information is available to help alleviate the bias. We propose to explicitly address this problem by learning an unsupervised asymmetric distance metric based on cross-view clustering. The asymmetric distance metric allows specific feature transformations for each camera view to tackle the specific feature distortions. We then design a novel unsupervised loss function to embed the asymmetric metric into a deep neural network, and therefore develop a novel unsupervised deep framework named the DEep Clustering-based Asymmetric MEtric Learning (DECAMEL). In such a way, DECAMEL jointly learns the feature representation and the unsupervised asymmetric metric. DECAMEL learns a compact cross-view cluster structure of Re-ID data, and thus help alleviate the view-specific bias and facilitate mining the potential cross-view discriminative information for unsupervised Re-ID. Extensive experiments on seven benchmark datasets whose sizes span several orders show the effectiveness of our framework. Copyright © 2019, The Authors. All rights reserved.

关键词： Deep neural networks

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Lattice QCD package GWU-code and QUDA with HIP 37

Lattice QCD package GWU-code and QUDA with HIP

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37th International Symposium on Lattice Field Theory, LATTICE 2019

作者： Bi, Yu-Jiang Xiao, Yi Guo, Wei-Yi Gong, Ming Sun, Peng Xu, Shun Yang, Yi-Bo Institute of High energy Physics Chinese Academy of Sciences Beijing100049 China Institute of Computing Technology Chinese Academy of Sciences Beijing100190 China Department of Physics University of Warwick CoventryCV4 7AL United Kingdom Nanjing Normal University Nanjing Jiangsu210023 China Computer Network Information Center Chinese Academy of Sciences Beijing100190 China CAS Key Laboratory of Theoretical Physics Institute of Theoretical Physics Chinese Academy of Sciences Beijing100190 China

The open source HIP platform for GPU computing provides an uniform framework to support both the NVIDIA and AMD GPUs, and also the possibility to porting the CUDA code to the HIP-compatible one. We present the porting progress on the Overlap fermion inverter (GWU-code) and also the general Lattice QCD inverter package - QUDA. The manual of using QUDA on HIP and also the tips of porting general CUDA code into the HIP framework are also provided. © Copyright owned by the author(s) under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND 4.0).

关键词： Quantum theory

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Lattice QCD package GWU-code and QUDA with HIP

arXiv

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arXiv 2020年

作者： Bi, Yu-Jiang Xiao, Yi Gong, Ming Guo, Wei-Yi Sun, Peng Xu, Shun Yang, Yi-Bo Institute of High energy Physics Chinese Academy of Sciences Beijing100049 China Institute of Computing Technology Chinese Academy of Sciences Beijing100190 China Department of Physics University of Warwick CoventryCV4 7AL United Kingdom Nanjing Normal University Nanjing Jiangsu210023 China Computer Network Information Center Chinese Academy of Sciences Beijing100190 China CAS Key Laboratory of Theoretical Physics Institute of Theoretical Physics Chinese Academy of Sciences Beijing100190 China

The open source HIP platform for GPU computing provides an uniform framework to support both the NVIDIA and AMD GPUs, and also the possibility to porting the CUDA code to the HIP-compatible one. We present the porting progress on the Overlap fermion inverter (GWU-code) and also the general Lattice QCD inverter package - QUDA. The manual of using QUDA on HIP and also the tips of porting general CUDA code into the HIP framework are also provided. Copyright © 2020, The Authors. All rights reserved.

关键词： Quantum theory

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