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arXiv 2018年

作者： Hao, Guang-Yuan Yu, Hong-Xing Zheng, Wei-Shi School of Data and Computer Science Sun Yat-sen University China Key Laboratory of Machine Intelligence and Advanced Computing Ministry of Education China Collaborative Innovation Center of High Performance Computing NUDT China Guangdong Key Laboratory of Big Data Analysis and Processing Guangzhou China

In this work, we present an interesting attempt on mixture generation: absorbing different image concepts (e.g., content and style) from different domains and thus generating a new domain with learned concepts. In particular, we propose a mixture generative adversarial network (MIXGAN). MIXGAN learns concepts of content and style from two domains respectively, and thus can join them for mixture generation in a new domain, i.e., generating images with content from one domain and style from another. MIXGAN overcomes the limitation of current GAN-based models which either generate new images in the same domain as they observed in training stage, or require off-theshelf content templates for transferring or translation. Extensive experimental results demonstrate the effectiveness of MIXGAN as compared to related state-of-the-art GAN-based models. Copyright © 2018, The Authors. All rights reserved.

关键词： Generative adversarial networks

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Online Test Paper Composition Based on Genetic Algorithm

Online Test Paper Composition Based on Genetic Algorithm

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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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Integrating MOOCs with Traditional Classroom Instruction to Improve Teaching Effectiveness

Integrating MOOCs with Traditional Classroom Instruction to ...

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2017 2nd International Seminar on Education Innovation and Economic Management(SEIEM 2017)

作者： Xiaodong Wu Yuzhu Zeng Faculty of Mathematics and Computer Science Quanzhou Normal University Fujian Provincial Key Laboratory of Data Intensive Computing Key Laboratory of Intelligent Computing and Information Processing Fujian Province University

Massive Open Online Course(MOOC) is a new teaching mode appeared in recent years and its emergence has constituted some challenge to the traditional teaching. However, MOOCs teaching mode has both advantages and disadvantages. In this paper, both the merits and the demerits of MOOC education are analyzed. We point out that the MOOC education mode and the traditional face-to-face classroom instruction should be combined together so as to improve the teaching effectiveness in modern education. Finally, how to blend the MOOC mode and the traditional classroom teaching and further utilize the network platform to improve the teaching efficiency in several learning phases are examined.

关键词： MOOCs face-to-face teaching traditional teaching network teaching platform

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Design of intelligent Robot Platform based on Multi-sensor Fusion

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Journal of Physics: Conference Series 2020年第1期1606卷

作者： Ya Dajin Lei Xiaochun Li Yue Chen Junyan Huang Rongcun Lan Lin School of computer and information security Guilin University of Electronic Technology Guilin 541004 China Guangxi Colleges and Universities Key Laboratory of Intelligent Processing of Computer Images and Graphics Guilin 541004 China Guangxi Cooperative Innovation Center of cloud computing and Big Data Guilin University of Electronic Technology Guilin 541004 China

The mobile robot adapts to the more complicated indoor and outdoor environments, and can expand its scope of application. In order to reduce the influence of the cumulative error caused by navigation in complex environments, the indoor mobile robot that combines Inertial Measurement Unit (IMU) and encoder fusion is designed and implemented. In view of the limitations of the traditional single lidar scheme, a Multi-sensor Fusion scheme is proposed to achieve indoor map construction, path planning, multi-point navigation and other functions, and a MSIF KartoSLAM (Multi-sensor Information Fusion) algorithm is proposed, which combines the KartoSLAM algorithm and Multi-sensor information to achieve map construction in complex environments. Through comprehensive testing in the indoor environment, the results show that the Multi-sensor Fusion scheme is superior to the traditional single lidar scheme, and can achieve higher accuracy in mapping and navigation. At the same time, the robot platform can also be combined with the Internet of Things technology and integrated into intelligent housing system.

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Design of People Flow Monitoring System in Public Place based on MD-MCNN

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Journal of Physics: Conference Series 2020年第1期1606卷

作者： Xiong Tianmin Lei Xiaochun Zheng Xingwen Chen Junyan Feng Yizhou School of computer and information security Guilin University of Electronic Technology Guilin 541004 China Guangxi Colleges and Universities Key Laboratory of Intelligent Processing of Computer Images and Graphics Guilin 541004 China Guangxi Cooperative Innovation Center of cloud computing and Big Data Guilin University of Electronic Technology Guilin 541004 China

Due to the limitation of hardware resources, the traditional people flow monitoring system based on computer vision in public places can't meet different crowd-scale scenarios. Therefore, a people flow monitoring system based on MD-MCNN algorithm is designed, which is an application system combining the improved SSD object detection algorithm MNSSD and MCNN density map regression algorithm. In the initial stage, the system uses MNSSD for accurate detection and counting. If the people flow gradually reaches a certain threshold, the system automatically uses MCNN to estimate people flow until the people flow falls below the threshold. Through the experimental verification, the system can realize the people flow statistics of low-density and high-density people in different scenarios, and can be applied on the existing embedded platform. This scheme can be extended to smart cities, smart scenic spots, smart transportation and other fields.

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Predicting ICU mortality by supervised bidirectional LSTM networks 1

Predicting ICU mortality by supervised bidirectional LSTM ne...

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1st Joint Workshop on AI in Health, AIH 2018

作者： Zhu, Yao Fan, Xiaoliang Wu, Jinzhun Liu, Xiao Shi, Jia Wang, Cheng Fujian Key Laboratory of Sensing and Computing for Smart Cities Xiamen University Xiamen China First Affiliated Hospital Xiamen University Xiamen China School of Information Technology Deakin University Melbourne Australia Digital Fujian Institute of Healthcare and Biomedical Big Data Research Xiamen University Xiamen China School of Information Science and Engineering Lanzhou University Lanzhou China

Mortality prediction in the Intensive Care Unit (ICU) is considered as one of critical steps for the treatment of patients in serious condition. It is a big challenge to model time-series variables for mortality prediction in ICU, because physiological variables such as heart rate and blood pressure are sampled with inconsistent time frequencies. In addition, it is difficult to capture the timing changes of clinical data and to interpret the prediction result of ICU mortality. To deal with these challenges, in this paper, we propose a novel ICU mortality prediction algorithm combining bidirectional LSTM (Long Short-Term Memory) model with supervised learning. First, we preprocess 37 time-series variables related to patients’ signs. Second, we construct the Bidirectional LSTM model with supervision technique to accurately reflect significant changes in patients’ signs. Finally, we train and evaluate our model using a real-world dataset containing 4,000 ICU patients. Experimental results show that our proposed method can significantly outperform many baseline methods. © CEUR-WS. All rights reserved.

关键词： Forecasting

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Exploiting Gabor Feature Extraction Method for Chinese Character Writing Quality Evaluation

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Journal of Physics: Conference Series 2020年第1期1575卷

作者： Zhixiao Wang Wenyao Yan Mingtao Guo Jiulong Zhang School of Computer Science and Engineering Xi'an University of Technology Xi'an 710048 China Shaanxi Key Laboratory Xi'an of Network Computing and Security Technology China School of Data Science and Computer Xi'an innovation college of Yan'an University Xi'an 710100 China

The automatic evaluation of Chinese character writing quality has a wide application prospect. Most of the existing evaluation methods of Chinese character writing quality are based on radical segmentation and feature judgment, which require the high accuracy of Chinese character segmentation. However, there are many problems in the real handwriting, such as continuous writing, uneven strength of writing, personalized writing style and so on, which lead to the difficulty of segmentation in the ordinary handwriting. To solve the above problems, we propose an effective method based on image texture where the uniformity of writing lines and writing style is taken as an effective criterion. In our method, Gabor transform is used to extract the image features of writing samples, and finally the statistical learning method of support vector machine is used to effectively evaluate the writing quality. Experiments on multiple real datasets including CHAED show that our method is effective and accurate. The advantage of this method is that it does not need to segment fonts, and the cost of global feature extraction is small.

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MFPR: A Personalized Ranking Recommendation with Multiple Feedback

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ACM Transactions on Social computing 2018年第2期1卷 1–22页

作者： Shi, Chuan Liu, Jian Zhang, Yiding Hu, Binbin Liu, Shenghua Yu, Philip S. Beijing Key Lab of Intelligent Telecommunication Software and Multimedia Beijing University of Posts and Telecommunications No. 10 Xi Tu Cheng Road Beijing China Cas Key Laboratory of Network Data Science and Technology Institute of Computing Technology Chinese Academy of Sciences No.6 Kexueyuan South Road Zhongguancun Beijing China Department of Computer Science University of Illinois at Chicago 851 South Morgan Street Chicago United States

Recently, recommender systems have played an important role in improving web user experiences and increasing profits. Recommender systems exploit users' behavioral history (i.e., feedback on items) to build models. The feedback usually includes explicit feedback (e.g., ratings) and implicit feedback (e.g., browsing history, click logs), which are both useful for improving recommendations. However, as far as we are concerned, no existing works have integrated both explicit and multiple implicit feedback simultaneously. Therefore, we propose a unified and flexible model, named Multiple Feedback-based Personalized Ranking (MFPR), to make full use of multiple feedback, which uses a personalized ranking framework. To train model MFPR, we design an algorithm to generate ordered item pairs as labeled data, with consideration of both rating scores and multiple implicit feedback. Extensive experiments on two real-world datasets validate the effectiveness of the MFPR model. With the integration of multiple feedback, MFPR significantly improves recommendation performance. © 2018 ACM.

关键词： Recommender systems

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Pan-genome and Haplotype Map of Cassava Cultivars and Wild Ancestors Provide Insights into its Adaptive Evolution and Domestication

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Molecular plant 2025年

作者： Zhiqiang Xia Zhenglin Du Xincheng Zhou Sirong Jiang Tingting Zhu Le Wang Fei Chen Luiz Carvalho Meiling Zou Luis Augusto Becerra López-Lavalle Xiaofei Zhang Liangye Xu Zhenyu Wang Meili Chen Xin Guo Shujuan Wang Mengtao Li Yuanchao Li Haiyan Wang Shisheng Liu Yuting Bao Long Zhao Chenji Zhang Jianjia Xiao Fengguang Guo Xu Shen Haozheng Li Cheng Lu Fei Qiao Hernan Ceballos Huabing Yan Xiaochun Qin Ling Ma Huaifang Zhang Shuang He Wenming Zhao Yinglang Wan Yinhua Chen Dongyi Huang Kaimian Li Bin Liu Ming Peng Weixiong Zhang Birger Lindberg Møller Xin Chen Ming-Cheng Luo Jingfa Xiao Wenquan Wang Hainan University Haikou 570228 China National Key Laboratory of Biotechnology and Breeding of Tropical Crops. National Genomics Data Center Beijing Institute of Genomics Chinese Academy of Sciences and China National Center for Bioinformation Beijing 100101 China. Institute of Tropical Bioscience and Biotechnology Chinese Academy of Tropical Agricultural Sciences (CATAS) Haikou 571101 China. Department of Plant Sciences University of California Davis California 95616 USA. Brazilian Enterprise for Agricultural Research (EMBRAPA) Genetic Resources and Biotechnology Brasilia 70770 Brazil. International Center for Tropical Agriculture (CIAT) Cali 6713 Colombia. Institute of Nanfan & Seed Industry Guangdong Academy of Sciences Guangzhou 510316 China. State Key Laboratory for Conservation and Utilization of Subtropical Agro-bioresources/College of Life Science and Technology Guangxi University Nanning 530004 China. The Academy of Agriculture and Forestry Sciences Qinghai University Xining 810016 China. Tropical Crop Genetic Resources Institute Chinese Academy of Tropical Agricultural Sciences (CATAS) Haikou 571700 China. Economic Crop Institute Guangxi Academy of Agricultural Sciences Nanning China. School of Biological Science and Technology University of JINAN Jinan China. Institute of Tropical Bioscience and Biotechnology Chinese Academy of Tropical Agricultural Sciences (CATAS) Haikou 571101 China Department of Health Technology and Informatics Department of Computing The Hong Kong Polytechnic University Hong Kong China. Plant Biochemistry Laboratory Department of Plant and Environmental Sciences University of Copenhagen DK-1871 Frederiksberg C Denmark. Institute of Tropical Bioscience and Biotechnology Chinese Academy of Tropical Agricultural Sciences (CATAS) Haikou 571101 China. Electronic address: xiaojingfa@***. National Genomics Data Center Beijing Institute of Genomics Chinese Academy of Sciences and China National Center for Bioinformation Beijing 100101

Cassava is an important, resilient tropical crop that produces large starchy storage roots and high biomass. But how did cassava´s remarkable environmental adaptability and key economic traits evolve from its wild species? We constructed nearly T2T genomes and their haplotype forms for the cultivar AM560, wild ancestors FLA4047 and W14, a graphic pan-genome of 30 representatives with 1.15 Gb, and built a clarified evolutionary tree of 486 accessions. A comparison of structural variations (SVs) and single-nucleotide variations (SNVs) between the ancestors and cultivated cassavas reveals predominant expansions and contractions of genes and gene families, which are mainly driven by transposons. Significant selective sweeping occurred in 122 footprints of genomes and affects 1,519 domesticated genes. We identify selective mutations in MeCSK and MeFNR2 that could promote photoreactions associated with MeNADP-ME in C photosynthesis in modern cassava. Co-evolution of retard floral primordia and initiation of storage roots may arise from MeCOL5 variants with altered bindings to MeFT1, MeFT2, and MeTFL2. Mutations of MeMATE1 and MeGTR occur in sweet cassava, and MeAHL19 has evolved to regulate the biosynthesis, transport, and endogenous remobilization of cyanogenic glucosides in cassava. These extensive genomic and gene resources provided here and the findings of the evolutionary mechanisms responsible for beneficial traits in modern cultivars represent a stepping-stone in future breeding of cassava.

关键词： Cassava Evolution and Domestication Genome Pan-genome Selective sweeping Structural Variations

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A java code protection scheme via dynamic recovering runtime instructions 18th

A java code protection scheme via dynamic recovering runtime...

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18th International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2018

作者： Jiajia, Sun Jinbao, Gao Yu-an, Tan Yu, Zhang Xiao, Yu School of Computer Science and Technology Beijing Institute of Technology Beijing100081 China School of Electrical and Information Engineering Beijing Key Laboratory of Intelligent Processing for Building Big Data Beijing University of Civil Engineering and Architecture Beijing100044 China China University of Mining and Technology Beijing100083 China Department of Computer Science and Technology Shandong University of Technology ZiboShandong255022 China

ISBN: (纸本)9783030050627

As Android operating system and applications on the device play important roles, the security requirements of Android applications increased as well. With the upgrade of Android system, Android runtime mode (ART mode) has gradually become the mainstream architecture of the Android operating system. ART introduces several improvements in Android, but it also introduces new ways to enhance malicious activities. This paper proposed a confidential finer granularity protection scheme for application programs under ART mode of ROOT Android devices. Taking Java method as the protection granularity, the protection scheme increased the accuracy of protecting targets. In addition, the protection scheme provided a more thorough protection for applications by combining dynamic loading technology and encryption technology in ART mode, and improved the security of Android applications. Experiments showed that the proposed protection scheme is effective. © Springer Nature Switzerland AG 2018.

关键词： Android (operating system)

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