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2018 3rd International Conference on Modelling, Simulation and Applied Mathematics(MSAM 2018)

作者： Wanli Song School of Information Engineering Nanjing Xiaozhuang University Key Laboratory of Trusted Cloud Computing and Big Data Analysis Nanjing XiaoZhuang University

The application of online examination is used more and more widely. Test paper composition is the core function in this application. Online examination system requires that the test paper should be quick and flexible, and the composition of questions should be reasonable and random. Test paper should not only meet the specific needs of users, ensure fairness, impartiality, but also be accurate and efficient. The intelligent test paper composition algorithm based on genetic algorithm is studied in this paper. Then this method is used to organize the structure of the test paper automatically, composites the examination content. Proposals are put forward to examines the degree of students' mastery of knowledge based on this method. This algorithm can automatically composite test papers according to the conditions of difficulty degree, knowledge coverage, and the proportion of questions. It can automatically composite test papers for online assessment. The practice of online testing system based on this algorithm shows that the algorithm is scientific and effective. On the premise of guaranteeing the quality of the test paper, it greatly improves the efficiency and pertinence of online testing. It is beneficial to improve students' learning efficiency and intellectualization of education.

关键词： test paper composition education intellectualization genetic algorithm E-learning

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Unsupervised feature selection based on Markov blanket and particle swarm optimization

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Journal of Systems engineering and Electronics 2017年第1期28卷 151-161页

作者： Yintong Wang Jiandong Wang Hao Liao Haiyan Chen College of Computer Science and Technology Nanjing University of Aeronautics and Astronautics Key Laboratory of Trusted Cloud Computing and Big Data Analysis Nanjing Xiaozhuang University College of Computer Science and Software Engineering Shenzhen University

Feature selection plays an important role in data mining and recognition, especially in the large scale text, image and biological data. Specifically, the class label information is unavailable to guide the selection of minimal feature subset in unsupervised feature selection, which is challenging and interesting. An unsupervised feature selection based on Markov blanket and particle swarm optimization is proposed named as UFSMB-PSO. The proposed method seeks to find the high-quality feature subset through multi-particles' cooperation of particle swarm optimization without using any learning algorithms. Moreover, the features' relevance will be computed based on an information metric of relevance gain, which provides an information theoretical foundation for finding the minimization of the redundancy between features. Our results on several benchmark datasets demonstrate that UFSMB-PSO can achieve significant improvement over state of the art unsupervised methods. © 1990-2011 Beijing Institute of Aerospace Information.

关键词： Character recognition data mining Feature extraction Information theory

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Towards Practical and Robust DNA-Based data Archiving Using ‘Yin-Yang Codec’ System

Research Square

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Research Square 2021年

作者： Ping, Zhi Chen, Shihong Zhou, Guangyu Huang, Xiaoluo Zhu, Sha Joe Zhang, Haoling Lee, Henry H. Lan, Zhaojun Cui, Jie Chen, Tai Zhang, Wenwei Yang, Huanming Xu, Xun Church, George M. Shen, Yue BGI-Shenzhen Shenzhen518083 China Guangdong Provincial Key Laboratory of Genome Read and Write BGI-Shenzhen Shenzhen518120 China George Church Institute of Regenesis BGI-Shenzhen Shenzhen518120 China China National GeneBank BGI-Shenzhen Shenzhen518120 China Shenzhen Institute of Synthetic Biology Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China Department of Genetics Harvard Medical School BostonMA United States Department of Molecular and Cellular Biology Harvard University CambridgeMA United States Wyss Institute for Biologically Inspired Engineering Harvard University BostonMA United States Big data Institute University of Oxford Li Ka Shing Centre for Health Information and Discovery Old Road Campus Oxford United Kingdom School of Mathematical Science Capital Normal University Beijing100048 China

DNA is a promising data storage medium due to its remarkable durability and space-efficient storage. Early bit-to-base transcoding schemes have primarily pursued information density, at the expense however of introducing biocompatibility challenges or at the risk of decoding failure. Here, we propose a robust transcoding algorithm named the "Yin-Yang Codec" (YYC), using two rules to encode two binary bits into one nucleotide, to generate DNA sequences highly compatible with synthesis and sequencing technologies. We encoded two representative file formats and stored them in vitro as 200-nt oligo pools and in vivo as an ~54-kb DNA fragment in yeast cells. Sequencing results show that YYC exhibits high robustness and reliability for a wide variety of data types, with. an average recovery rate of 99.94% at 104 molecule copies and an achieved recovery rate of 87.53% at 100 copies. In addition, the in vivo storage demonstration achieved for the first time an experimentally measured physical information density of 198.8 EB per gram of DNA (44% of the theoretical maximum for DNA). © 2021, CC BY.

关键词： DNA

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Directional shuffled frog leaping algorithm 1st

Directional shuffled frog leaping algorithm

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1st International Conference on Smart Vehicular Technology, Transportation, Communication and Applications, VTCA 2017

作者： Kong, Lingping Pan, Jeng-Shyang Chu, Shu-Chuan Roddick, John F. Innovative Information Industry Research Center Harbin Institute of Technology Shenzhen Graduate School Shenzhen China Fujian Provincial Key Laboratory of Big Data Mining and Applications College of Information Science and Engineering Fujian University of Technology FuzhouFujian China School of Computer Science Engineering and Mathematics Flinders University Adelaide Australia

ISBN: (纸本)9783319707297

Shuffled frog leaping algorithm is one of the popular used optimization algorithms. This algorithm includes the local search and global search two solving modes, but in this method only the worst frog from divided group is considered for improving location. In this paper, we propose a directional shuffled frog leaping algorithm (DSFLA) by introducing the directional updating and real-time interacting concepts. A direction flag is set for a frog before moving, if the frog goes better in a certain direction, it will get better in a big probability by moving a little further along that direction. The movement counter is set for preventing the frog move forward infinite. Real-time interacting works by sharing the currently optimal positions from the other groups. There should have some similarities among the best ones, and the worst individual could be improved by using those similarities. The experimental results show that the proposed approach is a very effective method for solving test functions. © Springer International Publishing AG 2018.

关键词： Swarm intelligence

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A Robust Region Control Approach for Simultaneous Trajectory Tracking and Compliant Physical Human-Robot Interaction

TechRxiv

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TechRxiv 2021年

作者： Li, Xiangyun Lu, Qi Chen, Jiali Jiang, Ning Li, Kang West China Biomedical Big Data Center West China Hospital Sichuan University Sichuan Chengdu610041 China Med-X Center for Informatics Sichuan University Sichuan Chengdu610041 China Department of Mechanical Engineering Sichuan University-Pittsburgh Institute Sichuan University Sichuan Chengdu610207 China Nursing Key Laboratory of Sichuan Province Sichuan University Sichuan Chengdu610207 China Evidence-based Nursing Center West China Hospital Sichuan University Sichuan Chengdu610041 China Department of Orthopedics West China Hospital Sichuan University Sichuan Chengdu610041 China West China School of Nursing Sichuan University Sichuan Chengdu610041 China National Clinical Research Center for Geriatrics West China Hospital Sichuan University Sichuan Chengdu610041 China Med-X Center for Manufacturing Sichuan University Sichuan Chengdu610041 China

The robot manipulator is widely used in healthcare tasks owning to its advantages of the virus immunity, the intensive service capability, etc. For the safe and smooth robot-assisted healthcare task execution, real-time motion tracking controls and compliant physical human-robot interactions are concurrently important control objectives. In this work, the uncertainty and disturbance estimator (UDE)-based robust region tracking controller for a robot manipulator is developed. The regional feedback error is derived from the potential function to drive the robot manipulator end-effector converging into the target region, where the safe and compliant physical human-robot interaction can be achieved. Utilizing the back-stepping control approach, the regional feedback error is seamlessly integrated into the UDE-based control framework, where the UDE is employed to estimate and compensate unknown payloads, unmodeled dynamics and frictions. Due to the simple structure and strong robustness of the proposed method, only the minimum model information, i.e., a constant inertia matrix, is needed for implementation on multi-degrees of freedom robot manipulators without additional force/torque sensors. The Lyapunov method is used to analyze the stability of the closed-loop control system. With two 7 degrees of freedom(DoFs) redundant manipulators and one 6 DoFs nonredundant manipulator, experimental studies including 3D lemniscate trajectory tracking, human–robot interaction for bilateral rehabilitation and temperature measurement are carried out for controller effectiveness validation. Compared to benchmark adaptive region control method, the proposed approach achieves better robustness with 0.022 m less mean absolute errors and 0.022 m less root mean squared errors in the presence of model uncertainties. © 2021-03-25, CC BY-NC-SA.

关键词： Degrees of freedom (mechanics)

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Visual Analytics for Temporal and Spatial Feature of TV Drama Viewing data

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Jisuanji Fuzhu Sheji Yu Tuxingxue Xuebao/Journal of Computer-Aided Design and Computer Graphics 2018年第5期30卷 816-823页

作者： Chen, Hongqian Yang, Qianyu Wen, Yulin Li, Hui Chen, Yi Beijing Key Laboratory of Big Data Technology for Food Safety School of Computer and Information Engineering Beijing Technology and Business University Beijing100048 China College of Management Beijing Union University Beijing100101 China

To analysis the influence factors of the TV drama view ratings, we proposed a visual analytic method for the temporal and spatial feature of broadcasting. Heat map was adopted firstly to show the temporal features of the ratings of different TV drama themes. Bar graph was used to compare the average ratings of each category. The location offset mapping was introduced to display different TV stations' spatial characteristics such as broadcast volume, average ratings, gender, age and occupational distribution of viewers. We selected the representative TV stations' drama ratings data from March 2015 to December 2015 as an example. The experimental results show that the method can assist efficiently to visual comparison of ratings and viewers for different TV stations and TV drama categories. The method can help making decisions in TV drama making, buying and arranging for TV stations. © 2018, Beijing China Science Journal Publishing Co. Ltd. All right reserved.

关键词： Visualization

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Chinese Named Entity Recognition in Power Domain Based on Bi-LSTM-CRF

Chinese Named Entity Recognition in Power Domain Based on Bi...

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作者： Zhenqiang Zhao Zhenyu Chen Jinbo Liu Yunhao Huang Xingyu Gao Fangchun Di Lixin Li Xiaohui Ji School of Information Engineering China University of Geosciences Beijing Key Laboratory of Research and System Evaluation of Power Dispatching Automation Technology(China Electric Power Research Institute) Big Data Center State Grid Corporation of China Power Dispatching and Control Center State Grid Corporation of China Institute of Microelectronics Chinese Academy of Sciences

Efficient recognition of proprietary entities is an important basic work for text data mining and intelligent application in power *** power domain Named Entity Recognition(NER) methods rely on feature engineering seriously,which unable to learn power entity features *** order to learn entity features automatically and extract power domain named entities efficiently,a model based on Bidirectional Long Short-Term Memory Neural Networks(Bi-LSTM) and Conditional Random Field(CRF) was proposed in this *** representations were fed into the neural networks as an additional feature and Skip-gram embeddings were trained on power domain *** results showed the precision rate reaches higher than 88.25% and the recalling rate reaches higher than 88.04%,which confirm the method based on BiLSTM and CRF is effective for named entity recognition in the power domain.

关键词： Named Entity Recognition Power Domain Bi-LSTM CRF

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A novel cloud game framework in dual Gigabit Network

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Journal of Physics: Conference Series 2020年第1期1684卷

作者： Kai Sun Tao Xu Shanghai Urban Construction Vocational College Shanghai 201415 China Henan Key Laboratory of Big Data Analysis and Processing Henan University Kaifeng 475004 China. School of Computer and Information Engineering Henan University Kaifeng 475004 China.

With the development of 5G, cloud computing, and artificial intelligence (AI) technology, cloud game has become a hotspot about application and innovation of Gigabit bandwidth. This paper, firstly, analyses the present situation and development of cloud game to clarify the key business and key technology of cloud game, then, proposes an operational framework of cloud game, finally, the feasibility of the proposed framework is discussed and several suggestions about the operation of cloud game are given.

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The approximate parallelity of complex fuzzy sets

The approximate parallelity of complex fuzzy sets

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作者： Hu, Bo Bi, Lvqing Dai, Songsong Li, Sizhao School of Mechanical and Electrical Engineering Guizhou Normal University Guiyang China School of Electronics and Communication Engineering Guangxi Colleges Universities Key Laboratory of Complex System Optimization and Big Data Processing Yulin Normal University Yulin China School of Information Science and Engineering Xiamen University Xiamen361005 China College of Computer Science and Technology Harbin Engineering University Harbin China

A complex fuzzy set is a set whose membership grades are complex values in the unit circle in the complex plane. This paper introduces the concept of approximate parallelity between complex fuzzy sets based on the phase of complex-valued membership grade. After that, the property of approximate parallelity preserving for complex fuzzy operators and complex fuzzy inference are investigated. © 2018 - IOS Press and the authors. All rights reserved.

关键词： Fuzzy inference

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New level scheme and shell model description of Rn212

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Physical Review C 2020年第4期101卷 044313-044313页

作者： C. B. Li (李聪博) G. L. Zhang (张高龙) C. X. Yuan (袁岑溪) G. X. Zhang (张广鑫) S. P. Hu (胡世鹏) W. W. Qu (屈卫卫) Y. Zheng (郑云) H. Q. Zhang (张焕乔) D. Mengoni D. Testov J. J. Valiente-Dobón H. B. Sun (孙慧斌) N. Wang (王楠) X. G. Wu (吴晓光) G. S. Li (李广生) M. Mazzocco A. Gozzelino C. Parascandolo D. Pierroutsakou M. La Commara F. Recchia A. I. Sison S. Bakes I. Zanon S. Aydin D. Bazzacco China Institute of Atomic Energy Beijing 102413 China School of Physics Beihang University Beijing 100191 China Beijing Advanced Innovation Center for Big Data-Based Precision Medicine School of Medicine and Engineering Beihang University Beijing 100191 China and Key Laboratory of Big Data-Based Precision Medicine (Beihang University) Ministry of Industry and Information Technology Beijing 100191 China Sino-French Institute of Nuclear Engineering and Technology Sun Yat-Sen University Zhuhai 519082 China Dipartimento di Fisica e Astronomia dell'Universita di Padova I-35131 Padova Italy Istituto Nazionale di Fisica Nucleare Sezione di Padova I-35131 Padova Italy College of Physics and Optoelectronic Engineering Shenzhen University Shenzhen 518060 China School of Radiation Medicine and Protection Medical College of Soochow University Soochow 215123 China INFN Laboratori Nazionali di Legnaro I-35020 Legnaro Italy INFN-Sezione di Napoli via Cintia I-80126 Napoli Italy Dipartimento di Farmacia Università di Napoli “Federico II” via D. Montesano I-80131 Napoli Italy Department of Physics University of Aksaray 68100 Aksaray Turkey

Level structures of Rn212 have been studied by in-beam γ-ray spectroscopic methods using the Bi209(Li6,3n)Rn212 reaction at beam energies of 28, 30, and 34 MeV. A number of new nonyrast states based on πh9/24 and πh9/23f7/2 configurations have been identified. A 3(−) collective state is also proposed at 2121 keV, which is most likely formed by mixing the octupole vibration with the 3− member of the πh9/23i13/2 multiplet. The level scheme is compared with large-scale shell model calculations and discussed in terms of excitations of valence protons and without contributions from the Pb208 core. An overall excellent agreement is obtained for states that can be described in this model space.

关键词： Electromagnetic transitions Energy levels & level densities Nuclear structure & decays Shell model 190 ≤ A ≤ 219

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