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International Conference on Cloud computing, Big Data and Blockchain (ICCBB)

作者： Xianghan Zheng Wei Wu Chunming Rong Tao Zhang Fujian Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou China Department of Computer Science and Electronic Engineering University of Stavanger Stavanger Norway College of Mathematics and Computer Science Fuzhou University Fuzhou China

ISBN: (纸本)9781728112787

Recently, both academia and industry have initiated research projects directed on fog computing. Fog computing is not composed of a powerful server, but by the relatively weak and scattered computers, processing appliances, factories, cars, street lamps and other equipment data. In this paper, we survey fog computing recently both in the academic and industrial research. We introduce it and consider case study that include In-vehicle network, NextGen Manufacturing, Wireless sensor network, and technical challenges. Our survey is based on recent research publications..

关键词： cloud computing Cloud computing street light industrial research research project OTHER EQUIPMENT

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SPESC: A Specification Language for Smart Contracts

SPESC: A Specification Language for Smart Contracts

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IEEE Annual International Computer Software and Applications Conference (COMPSAC)

作者： Xiao He Bohan Qin Yan Zhu Xing Chen Yi Liu School of Computer and Communication Engineering University of Science and Technology Beijing Beijing China Fujian Provincial Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou University Fuzhou China National Computer Network Emergency Response Technical Team Coordination Center of China

ISBN: (纸本)9781538626672

The smart contract is an interdisciplinary concept that concerns business, finance, contract law and information technology. Designing and developing a smart contract may require the close cooperation of many experts coming from different fields. How to support such collaborative development is a challenging problem in blockchain-oriented software engineering. This paper proposes SPESC, a specification language for smart contracts, which can define the specification of a smart contract for the purpose of collaborative design. SPESC can specify a smart contract in a similar form to real-world contracts using a natural-language-like grammar, in which the obligations and rights of parties and the transaction rules of cryptocurrencies are clearly defined. The preliminary study results demonstrated that SPESC can be easily learned and understood by both IT and non-IT users and thus has greater potential to facilitate collaborative smart contract development.

关键词： Contracts Cryptography Contract law Syntactics Collaboration Software

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A hierarchical correlation model for multi-model sentiment analysis on social media 12

A hierarchical correlation model for multi-model sentiment a...

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12th Chinese Conference on Computer Supported Cooperative Work and Social computing, ChineseCSCW 2017

作者： Lin, Dazhen Li, Lingxiao Cao, Donglin Li, Shaozi Cognitive Science Department Xiamen University Xiamen China Fujian Key Laboratory of Brain-inspired Computing Technique and Applications Xiamen University Xiamen China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Minjiang University Fuzhou China

ISBN: (纸本)9781450353526

We address the challenge of multi-modal sentiment analysis. To solve the problem of the sentiment correlations among different modalities, we propose a Multi-modal Correlation Model (MCM). In contrast to other methods, MCM considers the hierarchical sentiment correlations among modalities. Specifically, a probabilistic graphical model (PGM) is subsequently built upon the proposed MCM model, which considers the correlations and simultaneously preserves the classification ability of each modality. In order to compute the posterior probabilities of sentiments in PGM, we optimize the model by Maximum Likelihood Estimation. Experimental results show that MCM achieves accuracy of 84.2% and beats existing multi-modal methods with 1.2-4% improvement. Results demonstrate: 1) the sentiment correlations among modalities are hierarchical;2) the importance of the correlations for multi-modal sentiment analysis. © 2017 Association for computing Machinery.

关键词： Sentiment analysis

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Anatomy of an online misinformation network

arXiv

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arXiv 2018年

作者： Shao, Chengcheng Hui, Pik-Mai Wang, Lei Jiang, Xinwen Flammini, Alessandro Menczer, Filippo Ciampaglia, Giovanni Luca College of Computer National University of Defense Technology China School of Informatics Computing and Engineering Indiana University Bloomington United States MOE Key Laboratory of Intelligent Computing and Information Processing Xiangtan University China Indiana University Network Science Institute Bloomington United States

Massive amounts of fake news and conspiratorial content have spread over social media before and after the 2016 US Presidential Elections despite intense fact-checking efforts. How do the spread of misinformation and fact-checking compete? What are the structural and dynamic characteristics of the core of the misinformation diffusion network, and who are its main purveyors? How to reduce the overall amount of misinformation? To explore these questions we built Hoaxy, an open platform that enables large-scale, systematic studies of how misinformation and fact-checking spread and compete on Twitter. Hoaxy filters public tweets that include links to unverified claims or fact-checking articles. We perform k-core decomposition on a diffusion network obtained from two million retweets produced by several hundred thousand accounts over the six months before the election. As we move from the periphery to the core of the network, fact-checking nearly disappears, while social bots proliferate. The number of users in the main core reaches equilibrium around the time of the election, with limited churn and increasingly dense connections. We conclude by quantifying how effectively the network can be disrupted by penalizing the most central nodes. These findings provide a first look at the anatomy of a massive online misinformation diffusion network. Copyright © 2018, The Authors. All rights reserved.

关键词： Social networking (online)

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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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Framework for adaptive computation offloading in IoT applications 17

Framework for adaptive computation offloading in IoT applica...

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9th Asia-Pacific Symposium on Internetware, Internetware 2017

作者： Chen, Shihong Liu, Bichun Chen, Xing Zhang, Ying Huang, Gang College of Mathematics and Computer Science Fuzhou University Fuzhou China Fujian Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou China Institute of Software School of Electronics Engineering and Computer Science Peking University Beijing China Key Laboratory of High Confidence Software Technologies Ministry of Education Beijing China

ISBN: (纸本)1595930361

The internet of things (IoT) attracts great interest in many application domains concerned with monitoring and control of physical phenomena. IoT applications try to provide more and more functionality and then they inevitably become so complex as to make the limits of devices worse, which may lead to poor performance of applications. Computation offloading is a promising way to improve the performance of an IoT application by executing some parts of the application on remote devices or servers. However, supporting such capability is not easy for application developers due to (1) adaptability: IoT applications often face changes of runtime environments so that the adaptation on offloading is needed. (2) effectiveness: when the device context changes, it needs to dynamically decide the deployment plan of computation tasks, and the reduced execution time must be greater than the network delay and extra overheads caused by offloading. This paper proposes a framework which supports IoT applications with adaptive computation offloading capability. First, a design pattern is proposed to enable an application to be computation offloaded on-demand. Second, an estimation model is presented to automatically decide the deployment plan for offloading. Third, a framework is implemented to support the design pattern and the estimation model. A thorough zxevaluation on the real-world application is proposed, and the results show that our approach can help reduce execution time by over 45% in most scenarios.

关键词： computation offloading

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Learning knowledge representation across knowledge graphs 31

Learning knowledge representation across knowledge graphs

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31st AAAI Conference on Artificial Intelligence, AAAI 2017

作者： Cai, Pengshan Li, Wei Feng, Yansong Wang, Yuanzhuo Jia, Yantao CAS Key Laboratory of Network Data Science and Technology Institute of Computing Technology Chinese Academy of Science Beijing China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Science Beijing China Institute of Computer Science and Technology Peking University Beijing China

ISBN: (纸本)9781577357865

Distributed knowledge representation learning (KRL) methods encode both entities and relations in knowledge graphs (KG) in a lower-dimensional semantic space, which model relatively dense knowledge graphs well and greatly improve the performance of knowledge graph completion and knowledge reasoning. However, existing KRL methods including Trans(E, H, R, D and Sparse) hardly obtain comparative performances on sparse KGs where most of entities and relations have very low frequencies. Furthermore, all existing methods target at KRL on one knowledge graph independently. The embeddings of different KGs are independent with each other. In this paper, we propose a novel cross-knowledge- graph (cross-KG) KRL method which learns embeddings for two different KGs simultaneously. Through projecting semantic related entities and relations in two KGs to a uniform semantic space, our method could learn better embeddings for sparse KGs by incorporating information from another relatively larger and denser KG. The learned embeddings are also helpful for downstream cross-KGs or cross-linguals tasks like ontology alignment. The experiment results show that our method could significandy outperform corresponding baseline methods on knowledge graph completion on single KG and cross-KG entity prediction and mapping tasks. © 2017, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Knowledge graph

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Color correction for stereoscopic image based on matching and optimization

Color correction for stereoscopic image based on matching an...

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International Conference on 3D Imaging (IC3D)

作者： Xiaohua Zheng Yuzhen Niu Junhao Chen Yuzhong Chen College of Mathematics and Computer Science Fuzhou University Fujian Provincial Key Lab of the Network Computing and Intelligent Information Processing Fujian China

Stereoscopic 3D (S3D) image color correction is a major issue in the field of image processing. However, existing color correction algorithms have limitations. Global color correction algorithms cannot handle local color discrepancies, and local color correction algorithms are sensitive to matching quality between reference and target images. In this study, we propose an S3D image color correction algorithm that combines global and local color information to correct color discrepancies between S3D images. Sparse feature matching usually generates only a few matching features, producing error correction results in some local regions. Our algorithm uses dense stereo matching and global color correction algorithms to initialize color values, and improves the local color smoothness and global color consistency of the resulting image, while maintaining the initial color in that image as much as possible. Experimental results show that our algorithm performs better than do five state-of-the-art color correction algorithms.

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Anisotropic energy accumulation for stereoscopic image seam carving

Anisotropic energy accumulation for stereoscopic image seam ...

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International Conference on 3D Imaging (IC3D)

作者： Yuqing Lin Yuzhen Niu Shuai Zhang Junhao Chen College of Mathematics and Computer Science Fuzhou University Fujian Provincial Key Lab of the Network Computing and Intelligent Information Processing Fujian China

Seam carving is an image resizing method that aims at adapting the image to various display screens while reducing the distortion as much as possible. Severe visual distortion may be introduced by repeated removal or insertion of seams within a concentrated region of the image. To reduce such visual distortion, we propose a new AESSC method. First, we distribute the energy of each pixel on the seam to its adjacent 8-connected pixels when removing or inserting a seam. Second, since the information of each pixel is anisotropic, we use the Sobel operator to detect the direction that has the maximum edge information and continue the energy accumulation along this direction. Besides, we incorporate a 3D structure consistency constraint in the energy function and adopt a pixel visibility maintenance method. Experimental results show that the proposed method can effectively reduce visual distortion for stereo images while maintaining the geometric consistency.

关键词： Distortion Visualization Three-dimensional displays Stereo image processing Image edge detection Histograms Maintenance engineering

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Semantic keyword searchable proxy re-encryption for postquantum secure cloud storage

Semantic keyword searchable proxy re-encryption for postquan...

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作者： Yang, Yang Zheng, Xianghan Chang, Victor Tang, Chunming College of Mathematics and Computer Science Fuzhou University Fuzhou350108 China Fujian Province University Key Laboratory of Information Security of Network Systems Fuzhou University Fuzhou350108 China Key Laboratory of Information Security School of Mathematics and Information Science Guangzhou University Guangzhou510006 China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Minjiang University Fuzhou350121 China IBSS Xian Jiaotong-Liverpool University Suzhou215123 United Kingdom

With the advent of cloud computing, more and more consumers prefer to use the cloud services with the pay-as-you-consume mode. The cloud storage brings about great convenience to users, who store data in cloud and access to it using the smart devices anytime and anywhere. Consumers' information should be encrypted to guarantee the data privacy. Flexible searching on ciphertext is a critical challenge to be solved for effective data utilization. In this paper, we propose a novel semantic keyword searchable proxy re-encryption scheme for secure cloud storage. A highlight of this work is that the scheme is quantum attack resistant, while most of the available searchable encryption schemes are not. It supports not only exact keyword search but also synonym keyword search. Moreover, the data owner is capable to delegate his search right to another user using the proxy re-encryption mechanism. In the generation process of re-encryption key, the delegator and delegatee do not need to be interactive with each other. The scheme is also collusion resistant. Under the learning with errors hardness problem, this scheme is proved secure in standard model. Copyright © 2017 John Wiley & Sons, Ltd.

关键词： Semantics

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