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21st IEEE International Conference on High Performance Computing and Communications, 17th IEEE International Conference on Smart City and 5th IEEE International Conference on data Science and Systems, HPCC/SmartCity/DSS 2019

作者： Xiong, Bing Wu, Rengeng Liao, Zhuofan Wang, Jin School of Computer AND Communication Engineering Changsha University of Science AND Technology Changsha410114 China Department of Computer and Information Sciences Temple University Philadelphia19122 United States Hunan Provincial Key Laboratory of Intelligent Processing of Big Data on Transportation Changsha University of Science AND Technology Changsha China

ISBN: (纸本)9781728120584

As a novel network paradigm, Software Defined Networking (SDN) decouples control logic functions from data forwarding devices, and introduces a separate control plane to manipulate underlying switches via southbound interfaces like OpenFlow. However, it leads to large-scale flow tables and poses serious challenges on their storage resources and lookup performance in OpenFlow switches. This paper is thus motivated to propose an efficient differentiated storage architecture for large-scale flow tables in OpenFlow networks. Firstly, we investigate into the impact of wildcards in match fields on packet-in-batch property within a flow based on network traffic locality. Then, packet flows are dynamically distinguished into active ones and idle ones in terms of their short-term states. Subsequently, we store the match fields of active flows and idle flows respectively in TCAM and SRAM, and the content fields of both types of flows in DRAM, to effectively relieve the insufficiency of TCAM capacity. Finally, we evaluate the performance of our proposed flow table storage architecture with real network traffic traces by experiments. The experimental results indicate that our proposed storage architecture obviously outperforms the traditional one applying the elephant/mice flow differentiation method in terms of TCAM hit rates and average flow table access time. © 2019 IEEE.

关键词： Software defined networking

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A New Free-Standing Aqueous Zinc-Ion Capacitor Based on MnO2–CNTs Cathode and MXene Anode

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Nano-Micro Letters 2019年第4期11卷 227-238页

作者： Siliang Wang Qiang Wang Wei Zeng Min Wang Limin Ruan Yanan Ma Key Laboratory of Intelligent Computing and Signal Processing Ministry of EducationAnhui UniversityNo.3 Feixi RoadHefei 230039Anhui ProvincePeople’s Republic of China National Engineering Research Center for Agro-Ecological Big Data Analysis and Application School of Electronics and Information EngineeringAnhui UniversityNo.111 Jiulong RoadHefei 230601Anhui ProvincePeople’s Republic of China School of Sciences Hubei University of Automotive TechnologyNo.167 Checheng West RoadShiyan 442002Hubei ProvincePeople’s Republic of China

Restricted by their energy storage mechanism,current energy storage devices have certain drawbacks,such as low power density for batteries and low energy density for ***,the nearest ion capacitors,such as lithium-ion and sodium-ion capacitors containing battery-type and capacitor-type electrodes,may allow achieving both high energy and power *** the inspiration,a new zinc-ion capacitor(ZIC)has been designed and realized by assembling the free-standing manganese dioxide-carbon nanotubes(MnO2-CNTs)battery-type cathode and MXene(Ti3C2Tx)capacitortype anode in an aqueous *** ZIC can avoid the insecurity issues that frequently occurred in lithium-ion and sodium-ion capacitors in organic *** expected,the ZIC in an aqueous liquid electrolyte exhibits excellent electrochemical performance(based on the total weight of cathode and anode),such as a high specific capacitance of 115.1 F g?1(1 mV s?1),high energy density of 98.6 Wh kg?1(77.5 W kg?1),high power density of 2480.6 W kg?1(29.7 Wh kg?1),and high capacitance retention of^83.6%of its initial capacitance(15,000 cycles).Even in an aqueous gel electrolyte,the ZIC also exhibits excellent *** work provides an essential strategy for designing next-generation high-performance energy storage devices.

关键词： Energy storage Zinc-ion capacitor Battery-type and capacitor-type electrodes MXene Electrochemical performance

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MBLLEn: Low-light image/video enhancement using CNNs 29

MBLLEn: Low-light image/video enhancement using CNNs

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29th British Machine Vision Conference, BMVC 2018

作者： Lv, Feifan Lu, Feng Wu, Jianhua Lim, Chongsoon State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and Engineering Beihang University Beijing China Beijing Advanced Innovation Center for Big Data-Based Precision Medicine Beihang University Beijing China Panasonic R and D Center Singapore Singapore City Singapore

We present a deep learning based method for low-light image enhancement. This problem is challenging due to the difficulty in handling various factors simultaneously including brightness, contrast, artifacts and noise. To address this task, we propose the multi-branch low-light enhancement network (MBLLEN). The key idea is to extract rich features up to different levels, so that we can apply enhancement via multiple subnets and finally produce the output image via multi-branch fusion. In this manner, image quality is improved from different aspects. Through extensive experiments, our proposed MBLLEN is found to outperform the state-of-art techniques by a large margin. We additionally show that our method can be directly extended to handle low-light videos. © 2018. The copyright of this document resides with its authors.

关键词： Image enhancement

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Application of dual modality contrast agent combined with multi-scale representation in ultrasound-magnetic resonance imaging registration scheme

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MCB Molecular and Cellular Biomechanics 2020年第4期17卷 105-178页

作者： Hou, Mo Chiang, Weiyu Kevin Hong, Weiqiang Yang, Maoyun Yu, Wenhua School of Computer Science and Technology Jiangsu Normal University Xuzhou221116 China College of Business City University of Hong Kong Hong Kong999077 Hong Kong School of Mathematics Science Jiangsu Normal University Xuzhou221116 China Key Laboratory of Education Big Data Science and Engineering Jiangsu Normal University Xuzhou221116 China

To achieve the image registration/fusion and perfect the quality of the integration, with dual modality contrast agent (DMCA), a novel multi-scale representation registration method between ultrasound imaging (US) and magnetic resonance imaging (MRI) is presented in the paper, and how DMCA influence on registration accuracy is chiefly discussed. Owing to US’s intense speckle noise, it is a tremendous challenge to register US with any other modality images. How to improve the algorithms for US processing has become the bottleneck, and in the short term it is difficult to have a breakthrough. In that case, DMCA is employed in both US and MRI to enhance the region of interest. Then, because multi-scale representation is a strategy that attempts to diminish or eliminate several possible local minima and lead to convex optimization problems to be solved quickly and more efficiently, a multi-scale representation Gaussian pyramid based affine registration (MRGP-AR) scheme is constructed to complete the US-MRI registration process. In view of the above-mentioned method, the comparison tests indicate that US-MRI registration/fusion may be a remarkable method for gaining high-quality registration image. The experiments also show that it is feasible that novel nano-materials combined with excellent algorithm are used to solve some hard tasks in medical image processing field. © 2020 Tech Science Press. All rights reserved.

关键词： Magnetic resonance imaging

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Study on Influence Factors of Water Content of Expansive Soil in Canal Slope Based on Grey Correlation Model 5

Study on Influence Factors of Water Content of Expansive Soi...

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2019 5th International Conference on Hydraulic and Civil engineering, ICHCE 2019

作者： Liu, Zuqiang Li, Mingzhe Yan, Feng Luo, Hongming Changjiang Spatial Information Technology Engineering Co. Ltd Wuhan Hubei430010 China Hubei Province Engineering Technology Research Center for Water Resources Information Perception and Big Data Wuhan Hubei430010 China State Key Laboratory of Geomechanics and Geotechnical Engineering Institute of Rock and Soil Mechanics in Chinese Academy of Science Wuhan Hubei430071 China

The change of water content of expansive soil in canal slope is very unfavorable to the stability of the slope. In order to analyze the influencing factors and laws of water cut, the relationship between water content and voltage of expansive soil, the relationship between initial water content and expansion force, initial water content and disintegration of expansive soil were tested relationship. The gray correlation model was analyzed based on the vertical displacement, water content, suction, rainfall, soil temperature and temperature data collected on the site. It is preliminarily believed that the main influencing factors of the change of water content of expansive soil in the test section are temperature, rainfall, evaporation and suction. The mechanism analysis of the grey relational model is also obtained: due to the lag of the rainfall infiltration process, the atmospheric rainfall can only penetrate into the 1.6m deep strong expansive soil after 3d, and the influence depth is less than 6.1m. The research on the influencing factors of the change of water content of expansive soil provides the basis for the development of prevention and control measures for canal slope soil in the middle route of South-to-North Moisture Diversion Project and the safe management of channel operation. © Published under licence by IOP Publishing Ltd.

关键词： Hydraulic structures

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A novel business model for electric car sharing 1

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13th International Workshop on Frontiers in Algorithmics, FAW 2019

作者： Cheng, Yukun Deng, Xiaotie Zhang, Mengqian Suzhou Key Laboratory for Big Data and Information Service School of Business Suzhou University of Science and Technology Suzhou215009 China School of Electronics Engineering and Computer Science Peking University Beijing100871 China Department of Computer Science Shanghai Jiao Tong University Shanghai200240 China

ISBN: (数字)9783030181260

ISBN: (纸本)9783030181253

Transportation sharing in goods (bike sharing) and services (ride sharing) has been one of the most active sectors of the rising sharing economy. Such a mobile platform, based on a business model, seeks supplies in vehicles for their demands at matched times and rental locations. While its improved efficiency makes vehicle sharing popular over the traditional taxi services, it has attracted more competitors that have created redundancies in suppliers, which creates a new challenge in social efficiency. The problem also becomes for car sharing and will be intensified by the increased competition among all operators. In this work, we present a business solution by setting up a joint venture to provide shared resources as a base for different competitors to operate on. These competitors share the cost of the joint venture and then provide their own differentiated service to their customers through their own mobile apps. We formulate the number of users in the car sharing market as a S-shape function with respect to time and discretize the time into infinite rounds. In each round, we study this business model by formulating it as a two-stage Stackelberg game and apply the backward induction to analyze the equilibria of the leader and the followers in each round. Our results on the equilibria can forecast the car sharing market reasonably and avoid the redundancies in suppliers effectively. We also conduct numerical computation to visualize our theoretical results about the influence of joint venture decisions in the end. © Springer Nature Switzerland AG 2019.

关键词： Redundancy

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Supervised hashing with recurrent scaling 3rd

Supervised hashing with recurrent scaling

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3rd APWeb and WAIM Joint Conference on Web and big data, APWeb-WAIM 2019

作者： Fu, Xiyao Bin, Yi Wang, Zheng Wei, Qin Chen, Si Guizhou Provincial Key Laboratory of Public Big Data Guizhou University GuiyangGuizhou550025 China School of Computer Science and Engineering University of Electronic Science and Technology of China ChengduSichuan611731 China Information Science Academy China Electronics Technology Group Corporation Beijing China

ISBN: (纸本)9783030260743

Learning to hash is a method that can deal with content-based information retrieval efficiently. Traditional learning to hash methods, however, lack the ability to map the generated hash codes to the high-level semantic space. Attributes, as a kind of higher level of visual data representation compared to features, have the potential ability in deep learning to boost the performance. Utilizing attributes from visual data in deep learning to hash can link every bit of the hash codes and a certain type of attributes, therefore giving the hash code an explicit explanation. This paper presents a novel framework, named Deep Recurrent Scaling Hashing (DRSH), to solve the traditional image retrieval problem. The hash codes generated from DRSH are a combination of the outputs of each step of an enhanced LSTM and features generated from convolutional neural nets and are learned through images' attributes. This RNN is reformed to adjust the decorrelation of data flowing between each cell step, which not only makes the learning phase benefit from the ability of recurrent neural nets to learn with recurrent memory but also enable the availability of each hash bit to preserve distinct information. Experiments show that this framework can achieve appreciable performance on major datasets, and also have the ability to explain the meaning of hash codes based on attributes. © 2019, Springer Nature Switzerland AG.

关键词： Long short-term memory

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Cooperative bi-path metric for few-shot learning

arXiv

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arXiv 2020年

作者： Wang, Zeyuan Zhao, Yifan Li, Jia Tian, Yonghong State Key Laboratory of Virtual Reality Technology and Systems SCSE Beihang University Beijing100191 China School of Electronics Engineering and Computer Science Peking University Beijing100871 China Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University Beijing100191 China Peng Cheng Laboratory Shenzhen518066 China

Given base classes with sufficient labeled samples, the target of few-shot classification is to recognize unlabeled samples of novel classes with only a few labeled samples. Most existing methods only pay attention to the relationship between labeled and unlabeled samples of novel classes, which do not make full use of information within base classes. In this paper, we make two contributions to investigate the few-shot classification problem. First, we report a simple and effective baseline trained on base classes in the way of traditional supervised learning, which can achieve comparable results to the state of the art. Second, based on the baseline, we propose a cooperative bi-path metric for classification, which leverages the correlations between base classes and novel classes to further improve the accuracy. Experiments on two widely used benchmarks show that our method is a simple and effective framework, and a new state of the art is established in the few-shot classification field. Copyright © 2020, The Authors. All rights reserved.

关键词： Image classification

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Comparison of immune profiles between hepatocellular carcinoma subtypes

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Biophysics Reports 2020年第1期6卷 19-32页

作者： Xuemin Pan Ping Lin Fangyoumin Feng Jia Li Yuan-Yuan Li Wentao Dai Bo Hu Xin-Rong Yang Jia Fan Hong Li Yixue Li School of Life Sciences and Biotechnology Shanghai Jiao Tong University Bio-Med Big Data Center Key Laboratory of Computational Biology CAS-MPG Partner Institute for Computational Biology Shanghai Institute of Nutrition and Health Shanghai Institutes for Biological Sciences University of Chinese Academy of Sciences Chinese Academy of Sciences University of the Chinese Academy of Sciences School of Life Science and Techonology Shanghai Tech University Shanghai Center for Bioinformation Technology Shanghai Academy of Science & Technology Shanghai Engineering Research Center of Pharmaceutical Translation Department of Liver Surgery Liver Cancer Institute Zhongshan Hospital Fudan University Key Laboratory of Carcinogenesis and Cancer Invasion Ministry of Education Collaborative Innovation Center of Genetics and Development Fudan University

Immunotherapy, especially immune checkpoint inhibitors, is becoming a promising treatment for hepatocellular carcinoma(HCC). However, the response rate remains limited due to the heterogeneity of HCC samples. Molecular subtypes of HCC vary in genomic background, clinical features, and prognosis. This study aims to compare the immune profiles between HCC subtypes and find subtype-specific immune characteristics that might contribute to the prognosis and potential of immunotherapy. The immune profiles consist of immune-related genes, cytolytic activity, immune pathways, and tumorinfiltrating lymphocytes. HCC-c1 samples showed an overall higher activation level of immune genes and pathways, and this pattern was consistent in validation sets. We associated the difference in immune profiles with the activation level of cancer hallmarks and genomic mutations. There was a negative correlation between most of the metabolism pathway and immune-related pathways in HCC samples. CTNNB1/WNT signaling pathway mutation, one of the common mutations in HCC, appears to be associated with the expression of immune genes as well. These results reveal the difference of immune profiles between HCC subtypes and possible reasons and influence, which may also deepen our understanding of the carcinogenesis process.

关键词： Hepatocellular carcinoma Immune Tumor-infiltrating lymphocytes Metabolism CTNNB1 mutation

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A Study on the Differences of Attitude Learning and Learning Behavior Sequences for University Computer MOOC+ SPOC Course

A Study on the Differences of Attitude Learning and Learning...

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International Conference on Computer Science & Education (ICCSE)

作者： Zhao Changhua Mi Chunqiao School of Computer Science and Engineering Huaihua University Huaihua P. R. China Key Laboratory of Wuling-Mountain Health Big Data Intelligent Processing and Application in Hunan Province Universities Huaihua P. R. China Key Laboratory of Intelligent Control Technology for Wuling-Mountain Ecological Agriculture in Hunan Province Huaihua P. R. China

ISBN: (数字)9781728172675

ISBN: (纸本)9781728172682

The outbreak of COVID-19 make University Computer MOOC+SPOC course face opportunities and challenges. There are some problems in MOOC+SPOC course teaching, such as learners' curiosity decreasing, lack of accomplishment and etc. In order to deal with these problems, this study explores the correlation and differences in the learning behavior sequences of learners with different attitudes to high happiness, medium happiness, and low happiness. Through the learners' comments on University Computer MOOC+SPOC course, the learner's attitude information is tapped. By analyzing learning behavior sequences, this study finds out the degree of learning behavior change of learners with different attitudes. The result of this study can improve the existing University Computer MOOC+SPOC instructional design and promote the learning mode to move towards intelligent personalized adaptive learning.

关键词： Interviews Electronic learning data analysis Encoding Correlation

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