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5th International Conference on Geo-Spatial Knowledge and Intelligence, GSKI 2017

作者： Zhang, Yongsheng Li, Nengneng Cui, Ranran Fan, Yueqin School of Information Science and Engineering Shandong Normal University Jinan China Shandong Provincial Key Laboratory for Distributed Computer Software Novel Technology Jinan250358 China Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia Beijing University of Posts and Telecommunications Beijing100876 China

ISBN: (纸本)9789811308925

During the life cycle of the cloud data, the technique of data deterministic deletion is designed to completely destroy the data and ensures that cloud data that is out of date or backed up in the cloud server is completely deleted or will never be decrypted or accessed. However, the existing scheme simply deletes the key or the cipher text. Once the key or the cloud backup of the cipher text is stolen, data privacy will be threatened. For this reason, this paper proposes a data deletion scheme that is dynamic deletion is based on fragmented cipher text and key. The core of this scheme is to use the dynamic characteristics of DHT network to realize the periodic deletion of fragmented cipher text. Using the idea of fragmented cipher text dynamic deletion, in the unauthorized time even if in the case that the key is leaked, illegal user can not get all the cipher text and key, and can not restore the complete data. The theoretical analysis and experimental results show that the scheme can effectively delete some fragmented cipher texts and key, and has low performance cost, which can meet the requirements for deterministic deletion of excessive data or backup files in cloud storage system. © 2018, Springer Nature Singapore Pte Ltd.

关键词： Data privacy

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25th International Conference on Neural Information Processing, ICONIP 2018

作者： Liu, Wenfeng Liu, Peiyu Yi, Jing Yang, Yuzhen Liu, Weitong Li, Nana School of Information Science and Engineering Shandong Normal University Jinan250014 China School of Computer Heze University Heze274015 China Shandong Provincial Key Laboratory for Distributed Computer Software Novel Technology Jinan250014 China School of Computer Science and Technology Shandong Jianzhu University Jinan250101 China

ISBN: (纸本)9783030041816

How to effectively measure the similarity between two sentences is a challenging task in natural language processing. In this paper, we propose a sentence similarity comparison method that combines word embeddings and syntactic structure. First of all, by generating the corresponding syntactic tree, we synthetically analyze the two sentences and block them according to the syntactic components. Secondly, we prune the syntactic tree, remove the stop words and perform morphological restoration. Then, some important operations will be performed, such as passive flipping, negative flipping, and so on. Finally, the similarity of two sentence pairs is calculated by weighting the block embeddings of the syntactic tree. Experiments show the effectiveness of this method. © Springer Nature Switzerland AG 2018.

关键词： Embeddings

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A Transmission Power Control Algorithm for Wireless Body Area Networks

A Transmission Power Control Algorithm for Wireless Body Are...

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International Conference on computer Supported Cooperative Work in Design

作者： Zhuoran Zhengl Xiangwei Zheng Jie Tian Minglei Shu Shandong Provincial Key Laboratory for Distributed Computer Software Novel Technology Ji'nan China Qilu University of Technology Shandong Provincial Key Laboratory of Computer Networks

Energy efficiency is a key issue for wireless sensor nodes, especially for wireless body area networks (WBANs) that operate near the human body or in the human body. Aiming at the problem that WBAN system still has too fast energy consumption, we propose a ZigBee star network model with multiple sensing nodes as end nodes, and design an adaptive transmission power correction control algorithm with adjustment factors to select the appropriate transmit power to reduce the energy consumption. Experiments show that the proposed power control algorithm reduces the overall energy consumption by reasonably controlling the transmission power in the ZigBee star network model.

关键词： Power control Wireless communication Body area networks Prediction algorithms ZigBee Energy consumption Wireless sensor networks

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Feature-Selected and -Preserved Sampling for High-Dimensional Stream Data Summary

Feature-Selected and -Preserved Sampling for High-Dimensiona...

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International Conference on Tools for Artificial Intelligence (ICTAI)

作者： ling Lin Qian Yu Wen Ji Yang Gao State Key Laboratory for Novel Software Technology Nanjing University Nanjing China Electronics and Information Engineering College Yili Normal University Yining Xinjiang China School of Data and Computer Science Shandong Womens University China

Along with the prosperity of the Mobile Internet, a large amount of stream data has emerged. Stream data cannot be completely stored in memory because of its massive volume and continuous arrival. Moreover, it should be accessed only once and handled in time due to the high cost of multiple accesses. Therefore, the intrinsic nature of stream data calls facilitates the development of a summary in the main memory to enable fast incremental learning and to allow working in limited time and memory. Sampling techniques are one of the commonly used methods for constructing data stream summaries. Given that the traditional random sampling algorithm deviates from the real data distribution and does not consider the true distribution of the stream data attributes, we propose a novel sampling algorithm based on feature-selected and -preserved algorithm. We first use matrix approximation to select important features in stream data. Then, the feature-preserved sampling algorithm is used to generate high-quality representative samples over a sliding window. The sampling quality of our algorithm could guarantee a high degree of consistency between the distribution of attribute values in the population (the entire data) and that in the sample. Experiments on real datasets show that the proposed algorithm can select a representative sample with high efficiency.

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Corrigendum to “Rational Protocols and Attacks in Blockchain System”

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Security and Communication Networks 2021年第1期2021卷

作者： Tao Li Yuling Chen Yanli Wang Yilei Wang Minghao Zhao Haojia Zhu Youliang Tian Xiaomei Yu Yixian Yang State Key Laboratory of Public Big Data Guizhou University Guiyang Guizhou 550025 *** College of Computer Science and Technology Guizhou University Guiyang Guizhou 550025 *** School of Information Science and Engineering Qufu Normal University Rizhao 276825 *** School of Software Tsinghua University Beijing 100084 *** School of Information Science and Engineering Shandong Normal University Jinan 250014 ***

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Cooperative Co-evolutionary Artificial Bee Colony Algorithm Based on Hierarchical Communication Model

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Chinese Journal of Electronics 2016年第3期25卷 570-576页

作者： HU Chunyu LIU Hong ZHANG Peng School of Information Science and Engineering Shandong Normal University Shandong Provincial Key Laboratory for Novel Distributed Computer Software Technology

Canonical Artificial bee colony(ABC) algorithm with a single species is insufficient to extend the diversity of solutions and may be trapped into the local optimal solution. This paper proposes a new co-evolutionary ABC algorithm(HABC) based on Hierarchical communication model(HCM). HCM combines advantages of global and local communication pattern. With adjustment strategies on species and groups, HCM can reduce the computational complexity dynamically. Performance tests show that the HABC algorithm exhibit good performance on accuracy, robustness and convergence speed. Compared with ABC and Integrated co-evolution algorithm(IABC),HABC performs better in solving complex multimodal functions.

关键词： Artificial bee colony(ABC) algorithm Multi-species co-evolution Hierarchical communication model(HCM) Dynamical adjustment

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Bayesian multi-hypothesis Wyner-Ziv video coding

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Journal of Information Hiding and Multimedia Signal Processing 2017年第2期8卷 478-485页

作者： Meng, Li Li Zong, Jing Xiu Sun, Gui Na Cheng, Jie Zhang, Jia Zhao, Meng Chen Department of Information Science and Engineering Shandong Provincial Key Laboratory for Novel Distributed Computer Software Technology Shandong Normal University No.88 Wenhua East Road Jinan250014 China

The performance of distributed video coding (DVC) relies heavily on the quality of the side information (SI), and better performance can be expected if multiple SIs are employed. In this paper, we consider the scenario with two SIs, which are obtained by forward and backward predictions respectively. In this case, a couple of ad hoc approaches have been proposed to approximate the conditional probability density function (pdf) of a Wyner-Ziv-coded frame given the two SIs. However, the optimal conditional pdf and the relative performances of these ad hoc approaches with respect to the optimal solution have not been studied. In this paper, using Bayes’ formula, we derive the closed-form expression of the conditional pdf. Experimental results show that the Bayesian solution has similar performance to previous methods. Moreover, simulation results reveal that when better SIs are available, the Bayesian solution could outperform other methods. This analysis sheds some lights on developing future DVC schemes. © 2017 ISSN.

关键词： Probability density function

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Movement Tracking from Monocular Video Based on the Particle Filter

Movement Tracking from Monocular Video Based on the Particle...

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IEEE International Conference on Multimedia Big Data (BigMM)

作者： Lei Lyu Naiqi Ma Hong Liu School of Information Science and Engineering Shandong Normal University Shandong Provincial Key Laboratory for Distributed Computer Novel Technology Jinan China

ISBN: (纸本)9781509065509

Human motion tracking from monocular video has received increasing attention in recent years due to its broad applications. Among these human motion tracking methods, the particle filter is considered as an effective approach for human motion tracking. However, there are still two limitations of current particle filter approaches such as the prior used for the filtering step is often poor due to relatively large, poorly modeled inter-frame motion and the use of the prior as an importance function results in inefficient sampling of the posterior. In this paper, we present a new approach to track 3D human motion from video clips with the assistance of a pre-captured motion library. We studied the application of particle filter to realize the basic principle of 3d human motion tracking, three-dimensional human body model, the evaluation function of the posture and dynamic model of the movement, and the results of the tracking test is given.

关键词： Image edge detection Tracking Acceleration Particle filters Dynamics Biological system modeling Solid modeling

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Correction to: A whitelist and blacklist-based co-evolutionary strategy for defensing against multifarious trust attacks

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Applied Intelligence 2018年第7期48卷 1891-1891页

作者： Shujuan Ji Haiyan Ma Yongquan Liang Hofung Leung Chunjin Zhang Shandong Provincial Key Laboratory of Wisdom Mine Information Technology Shandong University of Science and Technology Qingdao China Shandong Provincial Key Laboratory of Novel Distributed Computer Software Technology Shandong Normal University Jinan China Department of Computer Science and Engineering The Chinese University of Hong Kong Hong Kong China Center of Network Shandong University of Science and Technology Qingdao China

The article A whitelist and blacklist-based co-evolutionary strategy for defensing against multifarious trust attacks, written by Shujuan Ji, Haiyan Ma, Yongquan Liang, Hofung Leung and Chunjin Zhang, was originally p...

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Bilevel genetic algorithm with clustering for large scale traveling salesman problems

Bilevel genetic algorithm with clustering for large scale tr...

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2016 International Conference on Information System and Artificial Intelligence, ISAI 2016

作者： Tan, Yan-Yan Tan, Li-Zhuang Yun, Guo-Xiao Zheng, Wei School of Information Science and Engineering Shandong Provincial Key Laboratory for Novel Distributed Computer Software Technology Shandong Normal University Jinan China

ISBN: (纸本)9781509015856

The Traveling Salesman Problem (TSP) belongs to the class of NP-hard optimization problems. Its solving procedure is complicated, especially for large scale problems. In order to solve the large scale TSPs efficiently, this paper presents a bilevel genetic algorithm with clustering (BLGAC). BLGA-C uses a clustering method to divide a large scale TSP into several subproblems, each subproblem corresponds to a cluster. K-Means clustering method is adopted in this paper. In the lower level, a genetic algorithm is used to find the shortest hamiltonian cycle for each cluster. All these clusters can be handled parallelly. Then, we need to select two nearest vertices between two clusters, and determine which edges will be deleted from the shortest hamiltonian cycle for each cluster, and which edges will be linked for combining two adjacent clusters into one. Repeat this procedure until all clusters are joined into one whole tour. Different combing sequences among clusters will result in different travelling tours, searching for the shortest is our purpose. Therefore, in the higher level, a modified genetic algorithm is designed for integral optimization with the objective of shortest the whole traveling tour. At last in this paper, we trial run a set of experiments on benchmark instances for testing the performance of the proposed BLGAC. Experimental results demonstrate its effective and efficient performance. © 2016 IEEE.

关键词： Genetic algorithms

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