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International Conference on intelligent System and Knowledge Engineering, ISKE

作者： Xuemin Yang Zhifei Zhang Ronggen Yang Daoyu Huang Geng Yang Lejun Gong Jiangsu Key Laboratory of Big Data Security &Intelligent Processing Nanjing University of Posts and Telecommunications Nanjing China Faculty Intelligent Science and Control Engineering Jinling Institute of Technology Nanjing China

With the rapid growth of the high-throughput biological technology, it brings biomedical big omics' data containing literature and annotated data. Especially, a wealth of relevant information exists in various types of biomedical literature. Text mining has emerged as a potential solution to achieve knowledge for bridging between the free text and structured representation of biomedical information. In this work, we used deep learning to recognize biomedical entities. We obtained 84.0% precision, 69.5% recall, and 76.1% F-score aiming at the GENIA corpus, and obtained 91.3% precision, 91.1% recall, and 91.2% F-score aiming at the BioCreAtIvE II Gene Mention corpus. Experimental results show that our proposed approach is promising for developing biomedical text mining technology in biomedical entity recognition.

关键词： Machine learning Neural networks Text mining Dictionaries Distributed databases Biological system modeling Telecommunications

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Secrecy performance analysis of SIMO underlay cognitive radio systems with outdated CSI

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IET Communications 2017年第12期11卷 1961-1969页

作者： Lei, Hongjiang Zhang, Jianming Park, Ki-Hong Ansari, Imran Shafique Pan, Gaofeng Alouini, Mohamed-Slim Chongqing Key Lab of Mobile Communications Technology Chongqing University of Posts and Telecommunications Chongqing 400065 China Computer Electrical and Mathematical Science and Engineering (CEMSE) Division King Abdullah University of Science and Technology (KAUST) Thuwal 23955-6900 Saudi Arabia Department of Electrical and Computer Engineering (ECEN) Texas A and M University at Qatar (TAMUQ) Education City Doha Qatar Chongqing Key Laboratory of Non-linear Circuits and Intelligent Information Processing Southwest University Chongqing 400715 China

This study investigates the secrecy outage performance of a single-input multiple-output underlay cognitive radio network (CRN) with outdated channel state information (CSI). The confidential messages are transmitted from transmitter to the destination, while a multi-antenna eavesdropper exists. The maximal ratio combining and selection combining schemes are utilised at the receivers to improve the quality of the received signal-to-noise ratio. The exact and asymptotic closed-form expressions of secrecy outage probability are derived, and simulation results are provided to verify the authors' proposed analytical results. The results reveal that imperfect CSI of main channels deteriorates the secrecy outage performance while that of eavesdropping and interfering channels has contrary effect, and only a unity diversity order can be obtained in underlay CRNs with imperfect CSI. © The Institution of Engineering and technology.

关键词： antenna arrays cognitive radio diversity reception probability radio networks telecommunication security

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FPGA Optimal Implementation of PRINCE against Power Analysis Attacks

FPGA Optimal Implementation of PRINCE against Power Analysis...

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ISCC 2017-the 5th International Conference on Information Science and Cloud Computing

作者： Yi Zou Lang Li College of Computer Science and Technology Hengyang Normal University Hunan Provincial Key Laboratory of Intelligent Information Processing and Application College of Computer Science and Technology Hengyang Normal University

The algorithm PRINCE proposed in ASIACRYPT 2012 is a lightweight cipher, currently suitable for the implementation on RFID Smart Card of the Io T. It's studied to achieve the optimal implementation of PRINCE encryption algorithm, and to add a fixed random mask to enhance the anti power attacking ability of PRINCE. In this paper, we constructed the same operations into a module called Prince Round, and used counter to control the Prince Round module, while the same round operation runs repeatedly. As a result, it can save registers and effectively reduce the amount of computation. Furthermore, we used a special method by adding the random mask to S-box. The experimental results show that the optimized PRINCE occupies area 9.8% fewer than original PRINCE on FPGA and the encryption with a fixed random mask can run correctly. Last but not least, our research is the first one about the implementation of PRINCE algorithm on FPGA, and can serve as a reference for further application of IOT encryption.

关键词： Matrix FPGA Optimal Implementation of PRINCE against Power Analysis Attacks

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Predicting essential proteins based on gene expression data, subcellular localization and PPI data 1

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12th International Conference on Bio-Inspired Computing: Theories and Applications, BIC-TA 2017

作者： Lei, Xiujuan Wang, Siguo Pan, Linqiang School of Computer Science Shaanxi Normal University Xi’anShaanxi710119 China Key Laboratory of Image Information Processing and Intelligent Control School of Automation Huazhong University of Science and Technology WuhanHubei430074 China School of Electric and Information Engineering Zhengzhou University of Light Industry ZhengzhouHenan450002 China

ISBN: (数字)9789811071799

ISBN: (纸本)9789811071782

Predicting essential proteins is indispensable for understanding the minimal requirements of cellular survival and development. In recent years, many methods combined with the topological features of PPI networks have been proposed. However, most of these approaches ignored the intrinsic characteristics of biological attributes. This paper integrates Gene expression data, Subcellular localization and PPI networks to identify essential proteins, named GSP. We use local average connectivity and edge clustering coefficient unite with gene expression data to measure centralities of nodes. Compared with non-essential proteins, essential proteins appear more frequently in some subcellular localizations such as Nucleus and considering that different compartments play different roles, thus we integrate subcellular localization information to identify essential proteins. The computational experiment results on the yeast PPI networks show that the proposed method GSP outperforms other state-of-art methods including DC, EC, IC, SC, NC, LAC, PeC, WDC and UDoNC. © Springer Nature Singapore Pte Ltd 2017.

关键词： Proteins

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Research on Ship Automatic Modeling and Identification System

Research on Ship Automatic Modeling and Identification Syste...

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2017 2nd International Conference on Mechatronics and Information technology(ICMIT 2017)

作者： Yao-jie Chen Xin Yuan Shu-lin Du Can Song School of Computer Science and Technology Wuhan University of Science and Technology School of Navigation Wuhan University of Technology Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System

When the ship sails in different water situation, it is necessary to forecast the movement state of the ship according to the real-time ship motion state parameters. The traditional method uses the classical MMG(mathematical model group) three-degree-of-freedom motion mathematical model to predict the modeling. For the existence of less detection parameters, the error is relatively large, the accuracy is not enough and so on. In this paper, a six-degree-of-freedom ship motion model based on sway, surge, heave, roll, pitch and yawing is proposed, combined with the least square method to achieve the automatic identification modeling method. Using this method, according to the GPS inertial navigation and positioning module to collect the data to simulate, and contrast with the traditional modeling method. The experimental results show that the improved automatic identification modeling method has better effect than the traditional modeling method, which greatly improves the accuracy of ship motion prediction.

关键词： automatic identification six degrees of freedom least square method

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Stability Analysis for Memristive Recurrent Neural Network Under Different External Stimulus

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Neural processing Letters 2017年第2期47卷 601-618页

作者： Gang Bao Zhigang Zeng Hubei Key Laboratory of Cascaded Hydropower Stations Operation and Control China Three Gorges University Yichang China School of Automation Huazhong University of Science and Technology Wuhan China Key Laboratory of Image Information Processing and Intelligent Control of Education Ministry of China Wuhan China

Memristor is the fourth missing element. This paper discusses dynmacis memristive recurrent neural network with memristors as synapses. Firstly, it analyzes variation property of memristance under different external inputs with memristor simulation model. It concludes that memristance will be stable at one value if the direction of voltage is not changed and be varying periodically under periodically variable voltage. Next, it presents the memristive recurrent neural network model and gives local attractive region, one sufficient condition for memristive recurrent neural network under periodic voltage source. At last, an illustrative example is given for verifying our result.

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VEHICLE DATA processing AND ANALYSIS PLATFORM BASED ON SPARK

VEHICLE DATA PROCESSING AND ANALYSIS PLATFORM BASED ON SPARK

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2017 2nd World Symposium on Mechanical and Control Engineering（WSMCE 2017）

作者： Xiaolan Xie Tianwei Yuan Xiao Zhou College of Information Science and Engineering Guilin University of Technology Guangxi Universities Key Laboratory of Embedded Technology and Intelligent Information Processing Guilin University of Technology College of Mechanical and Control Engineering Guilin University of Technology

Based on the Spark big data analysis platform, using Yarn management resource scheduling problem, using Hbase as the storage mode of distributed data. Through the mass of car data, dig out the key factors that affect the safety of car performance, and show in the form of visualization. An effective scheme is put forward for the maintenance and fault detection of the user's vehicle. The experimental results show that the analysis method based on Spark platform can quickly, effectively and accurately analyze the key information and play a guiding and analytical role for users.

关键词： Vehicle Spark Hbase Platform

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RESEARCH ON CLOUD PLATFORM OF CASTINGS QUALITY MANAGEMENT BASED ON SPARK

RESEARCH ON CLOUD PLATFORM OF CASTINGS QUALITY MANAGEMENT BA...

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2017 2nd World Symposium on Mechanical and Control Engineering（WSMCE 2017）

作者： Xiaolan Xie Xiao Zhou Tianwei Yuan College of Information Science and Engineering Guilin University of Technology Guangxi Universities Key Laboratory of Embedded Technology and Intelligent Information Processing Guilin University of Technology College of Mechanical and Control Engineering Guilin University of Technology

The casting quality management costs too much manpower, material and financial resources and is still lack of scientific status. In view of these conditions, this paper builds the casting quality management cloud platform based on Spark. Build and deploy Spark Standalone on the local computer. Parallel computing and cloud storage mechanism are implemented by Spark. Task management scheduling is implemented by Standalone. The foundry enterprise uses this platform to carry on the big data analysis to the influence factors of casting quality in the casting production. According to the results of the analysis, the scientific guidance and efficient scheduling of the manufacturing process are carried out. The quality management of castings is standardized and scientific. The scrap rate of castings is reduced. Through the large data analysis of various factors affecting the quality of casting, a set of scientific and efficient management scheme is provided.

关键词： Castings quality management Spark Cloud platform Big data

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Research on high-accuracy gait recognition technique based on parallel genetic algorithm

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Journal of Information Hiding and Multimedia Signal processing 2018年第1期9卷 244-255页

作者： Lin, Xiao Jia Zhang, Fu Quan Xu, Lin Department of Computing and Information Technology Fujian Business University No. 19 Huang Pu Road Gulou District Fuzhou350012 China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Minjiang University School of Software Beijing Institute of Technology Room A9. 301 Juyuan Jinshan Jiyuan Fuzhou350008 China Innovative Information Industry Research Institute Fujian Normal University Fuqing Brunch of Fujian Normal University Campus County 1. Longjiang Road Fuqing Fuzhou350300 China

In the field of sports science, gait recognition has a wide range of applications. However, compared to other biometric technologies, it has the problem of low recognition accuracy. Therefore, a technique combining the parallel genetic algorithm based on hierarchical fair competition with neural network ensemble is proposed to be applied in gait recognition. First, parallel genetic algorithm is adopted to increase individual diversity, and only appropriate features are selected to train each neural network candidate. Then, a set of individual neural networks are selected to complete the neural network ensemble so as to minimize the generalization error and maximize the negative correlation. Experiments on the CASIA gait database demonstrate the effectiveness of the proposed gait recognition method. The results show that the proposed method has a higher recognition rate than the existing methods. © 2018, Ubiquitous International. All rights reserved.

关键词： Genetic algorithms

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INTERNET OF VEHICLES DATA SERVICE SYSTEM BASED ON CLOUD PLATFORM

INTERNET OF VEHICLES DATA SERVICE SYSTEM BASED ON CLOUD PLAT...

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2017 2nd World Symposium on Mechanical and Control Engineering（WSMCE 2017）

作者： Xiaolan Xie Qiangqing Zheng Zhihong Guo College of Information Science and Engineering Guilin University of Technology Guangxi Universities key Laboratory of Embedded Technology and Intelligent Information Processing (Guilin University of Technology) College of Mechanical and Control Engineering Guilin University of Technology

The technology of Internet of automobile is designed to solve problems in field of transportation about safety, efficiency and environment. The system is based on data supplied by hardware in vehicles, design a mobile client APP and a management system for sellers through cloud computing, mass data distribution technology, which achieve the automobile driving data collection and analysis, fault reminders, track search, vehicle positioning, tips information release and other functions, and also achieve the intelligent analysis of automobile driving data. To some extent, the technology solves the problems such as automobile mileage not clear, hard to locate the automobile location, complicated ownership transfer, unable to self-help troubleshooting, hard to find the nearest repair point and so on.

关键词： Internet of vehicles BDS Automotive hardware Hadoop

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