会议名称：
2nd International Conference on Security with Intelligent Computing and Big-data Services (SICBS)
会议时间：
DEC 14-16, 2018
会议地点：
Guilin, PEOPLES R CHINA
会议主办单位：
[Xia, Zhe;Yang, Zhen;Xiong, Shengwu] Wuhan Univ Technol, Sch Comp Sci, Wuhan 430071, Hubei, Peoples R China.^[Hsu, Ching-Fang] Cent China Normal Univ, Comp Sch, Wuhan 430079, Hubei, Peoples R China.
会议论文集名称：
Advances in Intelligent Systems and Computing
摘要：
Secret sharing schemes allow the secret to be shared among a group of parties, so that a quorum of these parties can work together to recover the secret, but less number of parties cannot learn any information of the secret. In the literature, secret sharing schemes are normally analysed using heuristic arguments rather than strict security proofs. However, such a method may overlook some security flaws, especially when it is used to analyse the secrecy property. In this paper, we illustrate this issue using some concrete examples. We show that in two existing secret sharing schemes, the secrecy property was originally conjectured to be satisfied, but the adversary still can employ some security flaws to violate this property. We then introduce a game-based model that can be used to formally analyse the secrecy property in secret sharing schemes. We prove that our model captures the definition of the secrecy property. And as an example, we show how our method can be used to analyse Shamir secret sharing scheme. Note that our method might find applications in other secret sharing schemes as well.<br/> ©2020, Springer Nature Switzerland AG.
作者机构：
[Yuan, Shuai] Cent China Normal Univ, Natl Engn Res Ctr E Leaming, Wuhan 430079, Peoples R China.;[He, Tingting] Cent China Normal Univ, Sch Comp, Wuhan 430079, Peoples R China.;[He, Tingting] Cent China Normal Univ, Informat Retrieval & Knowledge Management Res Lab, Wuhan 430079, Peoples R China.;[Huang, Huan] South Cent Univ Nationalities, Sch Educ, Wuhan 430074, Peoples R China.;[Hou, Rui] South Cent Univ Nationalities, Coll Comp Sci, Wuhan 430074, Peoples R China.
通讯机构：
[He, Tingting] C;Cent China Normal Univ, Sch Comp, Wuhan 430079, Peoples R China.;Cent China Normal Univ, Informat Retrieval & Knowledge Management Res Lab, Wuhan 430079, Peoples R China.
作者机构：
[Chi, Jun; Liu, Hui] Huazhong University of Science and Technology, School of Artificial Intelligence and Automation, Wuhan;430074, China;[Li, Zengyang] Central China Normal University, School of Computer Science, Wuhan;430079, China;[Chi, Jun; Liu, Hui] 430074, China
作者机构：
[Teh, Je Sen; Samsudin, Azman] Univ Sains Malaysia, Sch Comp Sci, George Town 11800, Malaysia.;[Teng, Weijian] INTI Int Coll Penang, Sch Engn & Technol, George Town 11900, Malaysia.;[Chen, Jiageng] Cent China Normal Univ, Sch Comp, Wuhan 430079, Peoples R China.
通讯机构：
[Teh, Je Sen] U;Univ Sains Malaysia, Sch Comp Sci, George Town 11800, Malaysia.
关键词：
audio;chaos theory;chaotic map;entropy;hyperchaos;post-processing;random number generator;security
摘要：
Emotional conversation generation has elicited a wide interest in both academia and industry. However, existing emotional neural conversation systems tend to ignore the necessity to combine topic and emotion in generating responses, possibly leading to a decline in the quality of responses. This paper proposes a topic-enhanced emotional conversation generation model that incorporates emotional factors and topic information into the conversation system, by using two mechanisms. First, we use a Twitter latent Dirichlet allocation (LDA) model to obtain topic words of the input sequences as extra prior information, ensuring the consistency of content between posts and responses for emotional conversation generation. Second, the system uses a dynamic emotional attention mechanism to adaptively acquire content-related and affective information of the input texts and extra topics. The advantage of this study lies in the fact that the presented model can generate abundant emotional responses, with the contents being related and diverse. To demonstrate the effectiveness of our method, we conduct extensive experiments on large-scale Weibo post–response pairs. Experimental results show that our method achieves good performance, even outperforming some existing models.
期刊：
SPML '19: Proceedings of the 2019 2nd International Conference on Signal Processing and Machine Learning,2019年:Pages 73–78
作者机构：
[Liu, Ming; Zhang, Caiming; Zhang, Zhao] School of Computer, Central China Normal University, Wuhan, China
会议名称：
2nd International Conference on Signal Processing and Machine Learning, SPML 2019
会议时间：
November 27, 2019 - November 29, 2019
会议地点：
Hangzhou, China
会议论文集名称：
SPML '19: Proceedings of the 2019 2nd International Conference on Signal Processing and Machine Learning
摘要：
Although Convolutional Neural Networks are effective visual models that generate hierarchies of features, there still exist some shortcomings in the application of Deep Convolutional Neural Networks to semantic image segmentation. In this work, our algorithm incorporates multi-scale atrous convolution, attention model and Conditional Random Fields to tackle this problem. Firstly, our method replaces deconvolutional layers with atrous convolutional layers to avoid reducing feature resolution when the Deep Convolutional Neural Networks is employed in a fully convolutional fashion. Secondly, multi-scale architecture and attention model are used to extract the existence of features at multiple scales. Thirdly, we use Conditional Random Fields to prevent the built-in invariance of Deep Convolutional Neural Networks reducing localization accuracy. Moreover, our network completely integrates Conditional Random Fields modelling with Deep Convolutional Neural Networks, making it possible to train the deep network end-to-end. In this paper, our method is used to the matters of semantic image segmentation and is demonstrated the effectiveness of our model with experiments on PASCAL VOC 2012.
作者机构：
[Cui, Jianqun; Cao, Shuqin; Chang, Yanan] Cent China Normal Univ, Comp Sch, Wuhan 430079, Hubei, Peoples R China.;[Wu, Libing] Wuhan Univ, Comp Sch, Wuhan 430072, Hubei, Peoples R China.;[Liu, Dan] Wuhan Univ Technol, Sch Comp Sci & Technol, Wuhan 430070, Hubei, Peoples R China.;[Yang, Yi] Fontbonne Univ, Dept Math & Comp Sci, St Louis, MO 63105 USA.
通讯机构：
[Chang, Yanan] C;[Wu, Libing] W;Cent China Normal Univ, Comp Sch, Wuhan 430079, Hubei, Peoples R China.;Wuhan Univ, Comp Sch, Wuhan 430072, Hubei, Peoples R China.
关键词：
Connection strength;delay tolerant network;message handling capacity;quality of node;spray and wait
摘要：
The Internet of Things is one of the new emerging application domains that require delay tolerant network (DTN) support, where an end-to-end path between the source and the destination may not always exist. Due to the intermittent connectivity of DTN, the design of an efficient routing algorithm is the main challenge. In this paper, we first define a metric called message handling capacity to determine the ability of a node to forward messages. Then, we introduce a concept called connection strength to reflect the connection time between nodes and then integrate the concept into delivery predictability used by Prophet to determine the chance of a node completely delivering a message to the destination. Subsequently, we present a metric called quality of node (QoN), which is calculated by combining the relative weights of the message handling capacity and the improved delivery predictability. Finally, we present an adaptive spray and wait routing algorithm based on QoN (QoN-ASW). The QoN-ASW adaptively allocates the number of message copies between the encountered nodes according to the proportion of quality of node in the spray phase, which avoids the blindness of replica distribution. In addition, a forwarding scheme is implemented in the wait phase, which takes full advantage of encounter opportunities. In the simulation, we demonstrate the efficiency of integrating the connection strength into delivery predictability and compare the QoN-ASW with four existing DTN routing algorithms from four aspects. The simulation results show that the QoN-ASW can significantly improve the delivery rate and reduce the average delay while achieving a relatively low overhead.
摘要：
Financial technology(FinTech) is a new item in the financial industry, which has become a popular item that describes novel technologies adopted by the financial service institutions. This term covers a large range of techniques, from data security to financial service. Specially, user privacy protection is generally considered one of the most significant aspects in the financial security domain and preserving data carrying privacy is a critical task in producing a privacy protection strategy, e.g., one of the crucial issues in mobile finance is to ensure the legitimate mobile device users can efficiently search inclusive information from servers without leaking the user privacy. More precisely, more and more mobile finance APP(e.g., AliPay, China Unionpay Quick Pass) has the auxiliary tool or third-party services function that enable users make a location-based services(LBS) query, while the LBS usually carry users' location privacy and that data of service providers should be accessed by legitimate users. In order to address this problem, in this paper, we propose a privacy-preserving LBS framework which supports the query area is a square area based on the user's location, and achieves fine-grained access control on the financial service provider data, user's privacy(especially location privacy), confidentiality of the service provider data, and accurate query result. More precisely, our framework also uses redundant point-of-interesting(POI) records to protect privacy against LBS provider(LBSP), but employs a semi-trusted third party(called proxy) to filter out redundant POI records. We propose a novel blind filter protocol based on comparable attribute-based encryption(CABE) and "transformation" technique, which can filter out the encrypted POI records under the condition that both LBSP and proxy without knowing the user's location information. In comparison with existing solutions, our framework not only realize access control on service provider data innately, but also incurs lower communication and computation overhead on the user side. The analysis and the experiments indicate that our framework is secure and efficient for mobile devices in terms of computation and the communication overhead. (C) 2019 Elsevier B.V. All rights reserved.
摘要：
In this paper, the weak derivatives (WD) criterion is introduced to solve the frequency estimation problem of multi-sinusoidal signals corrupted by noises. The problem is therefore modeled as a new least squares optimization task combined with WD. To overcome the potential basis mismatch effect caused by discretization of the frequency parameters, a modified orthogonal matching pursuit algorithm is proposed to solve the optimization problem by coupling it with a novel multi-grid dictionary training strategy. The proposed algorithm is validated on a set of simulated datasets with white noise and stationary colored noise. The comprehensive simulation studies show that the proposed algorithm can achieve more accurate and robust estimation than state-of-the-art algorithms.
作者机构：
[Jiang, Xingpeng; He, Tingting; Fu, Chengcheng; Li, Xusheng; Zhong, Duo] Cent China Normal Univ, Sch Comp, Wuhan, Hubei, Peoples R China.;[Jiang, Xingpeng; He, Tingting; Fu, Chengcheng; Li, Xusheng; Zhong, Duo] Cent China Normal Univ, Hubei Prov Key Lab Artificial Intelligence & Smar, Wuhan, Hubei, Peoples R China.;[Zhong, Ran] Cent China Normal Univ, Collaborat & Innovat Ctr, Wuhan, Hubei, Peoples R China.
通讯机构：
[Jiang, Xingpeng] C;Cent China Normal Univ, Sch Comp, Wuhan, Hubei, Peoples R China.;Cent China Normal Univ, Hubei Prov Key Lab Artificial Intelligence & Smar, Wuhan, Hubei, Peoples R China.
会议名称：
IEEE International Conference on Bioinformatics and Biomedicine (BIBM) - Bioinformatics and Systems Biology
会议时间：
DEC 03-06, 2018
会议地点：
Madrid, SPAIN
会议主办单位：
[Li, Xusheng;Fu, Chengcheng;Zhong, Duo;He, Tingting;Jiang, Xingpeng] Cent China Normal Univ, Sch Comp, Wuhan, Hubei, Peoples R China.^[Li, Xusheng;Fu, Chengcheng;Zhong, Duo;He, Tingting;Jiang, Xingpeng] Cent China Normal Univ, Hubei Prov Key Lab Artificial Intelligence & Smar, Wuhan, Hubei, Peoples R China.^[Zhong, Ran] Cent China Normal Univ, Collaborat & Innovat Ctr, Wuhan, Hubei, Peoples R China.
关键词：
Named entity recognition;Biomedical text mining;Conditional random field;Deep learning
期刊：
ICBDE '19: Proceedings of the 2019 International Conference on Big Data and Education,2019年:43-47
通讯作者：
Zhang, Yong
作者机构：
[Li, Yu; Zhao, Jingjing; Yang, Liping; Zhang, Yong] Cent China Normal Univ, Comp Sch, Wuhan, Hubei, Peoples R China.
通讯机构：
[Zhang, Yong] C;Cent China Normal Univ, Comp Sch, Wuhan, Hubei, Peoples R China.
会议名称：
International Conference on Big Data and Education (ICBDE)
会议时间：
MAR 30-APR 01, 2019
会议地点：
Univ Greenwich, London, ENGLAND
会议主办单位：
Univ Greenwich
会议论文集名称：
ICBDE'19: Proceedings of the 2019 International Conference on Big Data and Education
关键词：
Knowledge Graph;Entity Relation Extraction;Normalized Google Distance;Intelligent Education;Graph Visualization
摘要：
To make full use of specialized vocabulary in computer science and discover relationships among these words, a Chinese knowledge graph of computer science major is constructed based on the internet web pages, and then the knowledge graph visualization and application for learning guidance based on it are developed. For the construction of computer science knowledge graph, a small amount of important specialized words in computer science are collected manually, and then these words are extended based on Baidu Baike (baike.baidu.com). Thus we get about 3000 specialized words (called entries). The similarity between two entries is calculated based on the Normalized Google Distance (NGD). Once the similarity is greater than a setting value, a link between the two entries is created. Finally the knowledge graph is constructed by these words and links between them. Here the relation type of link is ignored for simplicity. Furthermore the graph visualization is implemented by a tool called sigma.js, and an application for learning guidance is developed by J2EE. Through the application, students can get a visualized overview of computer science major and make a learning plan efficiently. Moreover the application and method of knowledge graph construction can be applied for other majors easily.
摘要：
A low complexity carrier phase estimation (CPE) algorithm for M-ary quadrature amplitude modulation (m-QAM) optical communication systems is investigated in this paper. In the proposed CPE algorithm, a two-stage CPE method is adopted. In the first stage, the QPSK points of the constellation are picked out to achieve a coarse phase estimation using the traditional Viterbi and Viterbi algorithm. In the second stage, all the points of the constellation are used for a fine phase estimation. In addition, the fourth-power operation is replaced by the 4-level absolute operation for the removal of modulated data phase, which greatly reduced the complexity. The proposed method was investigated through simulation, with 16-QAM, 32-QAM and 64-QAM modulation formats, respectively. The simulation results show that the proposed algorithm has both good linewidth tolerance and amplified spontaneous emission noise tolerance as well as low complexity. Moreover, when the equalization enhanced phase noise is considered, the proposed method also has better performance than traditional algorithm.
