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IEEE Conference on Industrial Electronics and Applications

作者： Junhuai Li Yang An Rong Fei Huaijun Wang Shaanxi Key Laboratory for Network Computing and Security Technology School of Computer Science and Engineering Xi'an University of Technology Xi'an China

ISBN: (纸本)9781467386456

Find a car in a large parking lot is a challenge in our daily life. In this paper, a novel car-searching approach based on smartphone for a large parking lot is presented. In the new approach, some QR codes are set up in each area which can identify the parking spots. In addition, shortest path algorithm is used to plan the optimal car-searching path. Considering that some parkers with poor sense of direction may lose in the parking lot, a real-time navigation method is proposed for parker to search the car, which is based on the built-in sensors in smartphone and pedometer principle. The new approach is tested in a large indoor parking lot, and the experimental results show the efficiency of the proposed car-searching system.

关键词： Intelligent car-searching system QR code Smartphone Pedometer

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An Adaptively Disperse Centroids K-Means Algorithm Based on MapReduce Model

An Adaptively Disperse Centroids K-Means Algorithm Based on ...

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International Conference on Computational Intelligence and security

作者： Bin Wang Zheng Lv Jinwei Zhao Xiaofan Wang Tong Zhang Shaanxi Key Laboratory for Network Computing and Security Technology Xi'an University of Technology Xi'an China Faculty of Computer Science and Engineering

ISBN: (纸本)9781509048410

K-means is a clustering algorithm which is used widely. Its clustering results heavily depend on the initial centroids. An adaptive method for disperse centroids is proposed to improve the stability and accuracy of the clustering result. The Adaptively Disperse Centroids K-means Algorithm (ADC-K-means) is implemented using MapReduce model on hadoop platform, and it is compared with the k-means of Mahout which is a sub-project of hadoop. The experimental result shows that proposed algorithm is effective.

关键词： Clustering algorithms Algorithm design and analysis Iris Computational modeling Adaptation models Data models Computer science

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Strongly average-case secure obfuscation: achieving input privacy and circuit obscurity

Strongly average-case secure obfuscation: achieving input pr...

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作者： Zhang, Mingwu Mu, Yi Shen, Jian Huang, Xinyi School of Computer Science Hubei University of Technology Wuhan430068 China School of Computer and Software Nanjing University of Information Science and Technology Nanjing China Fujian Provincial Key Laboratory of Network Security and Cryptology Fujian Normal University China School of Computing and Information Technology University of Wollongong NSW2522 Australia

A program obfuscator is a compiling algorithm that takes a program/circuit as input and generates a new garbled circuit to implement the same functionality as before while obtaining hard-to-understand in some sense, that is, infeasible to learn information from the garbled circuit. In order to obtain a practical application, an obfuscation should satisfy equivalent in functionality, polynomial slowdown in efficiency, and virtual black-box in security. In this paper, we model a stronger cryptographic obfuscation that does not only achieves the obfuscated circuit obscurity but also supports input re-key privacy. In order to implement the re-encryption obfuscation, we at first propose a key-privacy two-level encryption mechanism that implicitly supports the transformation from level-2 ciphertext into level-1 one, which provides an efficient method to re-encrypt the ciphertext without explicitly decryption procedure. Under the mechanism of two-level encryption and function of re-encryption, we construct an obfuscation of re-encryption that takes as input a probabilistic (keys) circuit and outputs a transformed circuit. We also give the proof that the obfuscator achieves the average-case security for the circuit family under the extended DBDH assumption and Decisional Linear assumption in the standard model. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

关键词： Timing circuits

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Performance analysis of parallel replica molecular dynamics

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AIP Conference Proceedings 2018年第1期1978卷

作者： Boyao Zhang Jue Wang Yangde Feng Ji Xiang Lei Wang 1Computer Network Information Center Chinese Academy of Science Department of High Performance Computing Technology and Application Development Beijing China 2University of Chinese Academy of Sciences Beijing China 3State Key Laboratory of Information Security Institute of Information Engineering Chinese Academy of Sciences China 4School of cybersecurity Chinese Academy of Sciences China

Molecular dynamics simulation is an important tool for studying materials microstructure evolution under radiation effects. It is difficult to simulate atomic diffusion in materials owing to the time-scale limitations of the molecular dynamics method. Accelerated molecular dynamics has been developed as a solution and the parallel replica method is the simplest and most accurate of the accelerated dynamics techniques. The simulation time scale can reach several orders more than the direct molecular dynamics, while retaining the complete atomic detail. In parallel replica method, the entire system is replicated on each of M available parallel or distributed processors, it is in line with the characteristics of high-performance parallel computing and can be optimized from the program level.

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Learning to segment with image-level annotations

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Pattern Recognition 2016年 59卷 234-244页

作者： Wei, Yunchao Liang, Xiaodan Chen, Yunpeng Jie, Zequn Xiao, Yanhui Zhao, Yao Yan, Shuicheng Institute of information Science Beijing Jiaotong University Beijing 100044 China Beijing Key Laboratory of Advanced Information Science and Network Technology Beijing 100044 China School of Advanced Computing Sun Yat-Sen University Guangzhou 510006 China Vision and Machine Learning Lab National University of Singapore 117583 Singapore People׳s Public Security University of China Beijing 100038 China

Recently, deep convolutional neural networks (DCNNs) have significantly promoted the development of semantic image segmentation. However, previous works on learning the segmentation network often rely on a large number of ground-truths with pixel-level annotations, which usually require considerable human effort. In this paper, we explore a more challenging problem by learning to segment under image-level annotations. Specifically, our framework consists of two components. First, reliable hypotheses based localization maps are generated by incorporating the hypotheses-aware classification and cross-image contextual refinement. Second, the segmentation network can be trained in a supervised manner by these generated localization maps. We explore two network training strategies for achieving good segmentation performance. For the first strategy, a novel multi-label cross-entropy loss is proposed to train the network by directly using multiple localization maps for all classes, where each pixel contributes to each class with different weights. For the second strategy, the rough segmentation mask can be inferred from the localization maps, and then the network is optimized based on the single-label cross-entropy loss with the produced masks. We evaluate our methods on the PASCAL VOC 2012 segmentation benchmark. Extensive experimental results demonstrate the effectiveness of the proposed methods compared with the state-of-the-arts. © 2016 Elsevier Ltd

关键词： Deep learning Semantic segmentation Weakly supervised

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An improved Fuzzy C-Means algorithm based on MapReduce

An improved Fuzzy C-Means algorithm based on MapReduce

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International Conference on BioMedical Engineering and Informatics (BMEI)

作者： Qing Yu Zhimin Ding Tianjin Key Laboratory of Intelligence Computing and Network Security Tianjin University of Technology Tianjin China

In order to solve the problem that the Fuzzy C-Means algorithm is sensitive to the initial clustering center, we use the Canopy algorithm to carry out the quick and rough clustering. At the same time, to avoid the blindness of the Canopy algorithm, we put forward an improved Canopy-FCM algorithm based on a max-min principle. In allusion to the problem that the FCM algorithm has high time complexity, this article use the parallel computing frame of MapReduce to design and realize the improved Canopy-FCM algorithm. Experimental results show: the improved Canopy-FCM algorithm based on MapReduce has better clustering quality and running speed than the Canopy-FCM and the FCM algorithm based on MapReduce, and the improved Canopy-FCM algorithm based on Hadoop has better speed-up ratio than the Canopy-FCM based on the Standalone mode.

关键词： Clustering algorithms Algorithm design and analysis Data collection Convergence Classification algorithms Blindness Time complexity

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Paralleled Extraction Method for Content of Invoice Image Based on TPL

Paralleled Extraction Method for Content of Invoice Image Ba...

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2015 International Conference on Advanced Management Science and Information Engineering(AMSIE 2015)

作者： H.Y.Jin B.Xing X.H.Hei School of Computer Science & Engineering Xi'an University of Technology Shaanxi Key Laboratory for Network Computing and Security Technology

The paper mainly uses a mixed strategy of data and task parallelism to realize parallel extraction date information of *** at the deficiency of ordinary pipeline mode for parallel extraction date information from invoice,we explore a new method of load balanced pipeline based on multiple producers,using parallelism model of mixed data and task provided by TPL(the Task Parallel Library).Finally,it shows this load balanced pipeline program can almost get a linear speedup,which can reach 7.2x in a 8 cores system.

关键词： paralleled TPL pipeline load balanced

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Research on Storage and Retrieval Method of Mass Data for High-Speed Train

Research on Storage and Retrieval Method of Mass Data for Hi...

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International Conference on Computational Intelligence and security

作者： Bin Wang Fan Li Xinhong Hei Weigang Ma Lei Yu Shaanxi Key Laboratory for Network Computing and Security Technology Xi'an University of Technology Xi'an China School of Computer Science and Engineering Xi'an University of Technology Xi'an China

In order to ensure the safeties of high-speed train, a lot of sensors are installed in the train to real-time monitor its operation status. These sensors collect amounts of data which may be several GBs for one time operation of one train. Such big amount data need to be stored and managed with high efficiency. In this paper, a hybrid storage architecture by combine database and file system is proposed, in which the separation on the row and column is performed respectively when storing the raw monitored data. Further, an improved compression algorithm is used to compress double float data in the monitored data. The simulation result shows that the proposed method is effective and feasible.

关键词： Memory Indexes File systems Monitoring Sensors Servers

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A method of oversized image generation based on stitching JPEG file streams

International Journal of Signal Processing, Image Processing...

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International Journal of Signal Processing, Image Processing and Pattern Recognition 2015年第8期8卷 159-168页

作者： Sun, Qindong Hua, Wu Tian, Minying Wang, Yan School of Computer Science and Engineering Xi’an University of Technology Xi’an China Shaanxi Key Laboratory of Network Computing and Security Xi’an University of Technology Xi’an China

Due to memory limitation, the displaying and processing of the oversized images have been a bottleneck for various applications, which is a hot research spot in the image processing field. The traditional methods are almost based on the BMP format to generate oversized images, of which the time and space complexity are very high. In this paper, we have deeply analyzed the encoding scheme of JPEG image and proposed an oversized image generation method based on stitching JPEG file streams. According to this method, the oversized images are block plotted and then transformed and saved as JPEG format files respectively. In the end, the block JPEG files are then combined into an integrated JPEG image. The experiment results show that, our method can effectively improve the speed of oversized image generation and reduce the memory consumption. The time and space performance of our method are better than existing methods. © 2015 SERSC.

关键词： Image enhancement

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Research on the design of the effective transmission scheduling algorithm based on the factory wireless sensor network

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Open Automation and Control Systems Journal 2014年第1期6卷 1426-1434页

作者： Zhang, Yunyi Liu, Shuru Zhang, Ran Wei, Wei College of Computer and Communication Engineering Zhengzhou University of Light Industry Zhengzhou China School of Computer Science and Engineering Xi’an University of Technology Xi’an China Shaanxi Key Laboratory for Network Computing and Security Technology China

In order to make the sensing data in the monitoring equipment’s sensor nodes reach to the monitoring center as soon as possible and deal with the equipment which has some problems, the network time delay should be guaranteed in the accessible Time Delay Bound. The paper mainly researches the transmission scheduling algorithm with the chain framework, which adopts the Token to do the transmission in the chain and then arranges the transmission order in each node for avoiding the occurrence of the collision and offering the guarantee of the time delay. The node order in each chain is the order of data packets which are transmitted by nodes, while the route of the data packet transmission is according to the shortest route in the Sink Tree for reducing the time delay. © Zhang et al.;Licensee Bentham Open.

关键词： Scheduling algorithms

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