Computer and Modernization

Security Analysis of Tri-element Peer Authentication Mechanism

XIAO Yue-lei1,2,3, ZHU Zhi-xiang1,2, ZHANG Yong1,2

2015, 0(6): 1-6+31. doi:10.3969/j.issn.1006-2475.2015.06.001

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To analyze the security of Trielement Peer Authentication(TePA) mechanism, the TePA mechanism was analyzed based on Strand Space Model(SSM). According to the analysis, it was known that some cases of the TePA mechanism could not realize full authentication agreement, but they were still secure. Therefore, the TePA mechanism is secure in the SSM. Moreover, two improving methods for the TePA mechanism were proposed, making the improved TePA mechanism realize full authentication agreement.

A Dynamic RBAC Model Based on Multidimensional Trust

YE Chong-yang， ZHUANG Yi

2015, 0(6): 7-11. doi:10.3969/j.issn.1006-2475.2015.06.002

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Rolebased access control technology has been a widely used authorization method since it was proposed. At the aspect of authorization with trust mechanism, the time characteristic problem is not considered in traditional or improved RBAC model. And the global trust is obtained by simply weighting the trust indicator. This kind of algorithm thinks about problem too simply and can’t well reflect the flexibility of dynamic permission. Aiming at this problem, a dynamic RBAC model based on multidimensional trust is proposed, which is an extension of role management model ARBAC97. The model introduces time characteristic factors to improve the existing calculation method of trust. Besides, it synthetically computes a variety of trust characteristics of users, so as to fulfil flexible and dynamic authorization mechanism. The simulation experiments show that for MDTRBAC the effectiveness of preventing malicious nodes from attacking is superior to the existing models.
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Multilevel Protection to Electronic Documents Based on Clipboard Monitoring

ZHANG Lei1,2, LI Qing-bao1,2, JIA Tian-jiang1,2, ZHOU Deng-yuan1,2

2015, 0(6): 12-18. doi:10.3969/j.issn.1006-2475.2015.06.003

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Protection to electronic documents is one of the most important contents to information leakage prevent. Based on the analysis to the existing technologies to protect electronic documents, this paper presents a multilevel protection technology to electronic documents based on the clipboard monitoring. It puts forward a clipboard monitor strategy by which document path can be obtained. And then it puts forward a dynamic adjustable classification protection strategy for document, which can protect documents dynamically according to the information which is obtained by clipboard monitoring. The corresponding prototype system was implemented. The experimental results show that the electronic document protection technology based on the clipboard monitor can avoid the document content leak through the clipboard according to the requirement of protection to electronic document.

Simulation of Landing Gear Hydraulic Retraction/Extension System for Health Management

HE Lin1, LIANG Li-ai2, MA Cun-bao1

2015, 0(6): 19-22+36. doi:10.3969/j.issn.1006-2475.2015.06.004

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The simulation is a normal way to analyze system performance of aircraft landing gear and hydraulic system. Health management of aircraft systems is now a research focus. In this paper, principle and fault characteristics of landing gear hydraulic retraction/extension system were first studied. Simulation model based on AMESim software was established and the factors affecting on the working performance of the system was analyzed. Various outputs of several components vs different health situations were obtained, which lay the foundation for further fault diagnosis and health management.

Application of Wavelet Neural Network Active Disturbance Rejection Controller in Autonomous Underwater Vehicle Depth Control

SHAO Ke-yong, SHEN Yu-xuan

2015, 0(6): 23-26. doi:10.3969/j.issn.1006-2475.2015.06.005

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The purpose of this article is mainly to accomplish the depth control of Autonomous Underwater Vehicles. Because of the disadvantage of BP neural networks and the advantage of wavelet neural network, we desigaed a wavelet neural network active disturbance rejection controller. We used the Matlabsimulink to test the controller. The controller has good control effect and high robustness.

Short-term Traffic Flow Prediction Based on SOALSSVM

ZHAO Wei

2015, 0(6): 27-31. doi:10.3969/j.issn.1006-2475.2015.06.006

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In view of the nonlinear and uncertainty for shortterm traffic flow characteristic, a forecasting model based on SOA-LSSVM is proposed, combining SOA’s advantages of high convergence precision with LSSVM’s superiority in fast solving speed. SOA is used in choosing regular parameter and nucleus parameter for LSSVM, thus, a optimal forecast model is established based on SOA-LSSVM. The model was used in shortterm traffic flow prediction, and the application results shows that compared with traditional ANN, SOA-LSSVM model has a better prediction precision and application effect, and this model is fit for shortterm traffic prediction with a good popularization value.

Application of Water Quality Prediction Based on MEC-BP Neural Network in Aquaculture

YANG Zheng-guang, FAN Liang-zhong

2015, 0(6): 32-36. doi:10.3969/j.issn.1006-2475.2015.06.007

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Dissolved oxygen as the most important and the most easily control water quality parameter of aquaculture relates to the success or failure of aquaculture. If we can accurately grasp the change rule of dissolved oxygen, the risk of breeding will greatly reduce and the breeding success rate will increase. In this paper, considering the related water quality parameters, we established the BP neural network model of water quality prediction. And on this basis, the BP neural network model based on mind evolutionary algorithm (MEC) of water quality prediction was established. Through the simulation of historical data of water quality of Maowei Sea, Guangxi, the results show that the precision and accuracy of predicted value of MECBP neural network is higher than that of the BP neural network. Therefore, it is feasible to apply this algorithm to predict water quality of aquaculture.

A Deep Learning Method for Braille Recognition

LI Ting

2015, 0(6): 37-40. doi:10.3969/j.issn.1006-2475.2015.06.008

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This paper mainly proposes a deep learning method, using Stacked Denoising AutoEncoder (SDAE) to solve the problems of automatic feature extraction and dimension reduction in Braille recognition. In the construction of a network with deep architecture, a feature extractor was trained with unsupervised greedy layerwise training algorithm to initialize the weights for extracting features from Braille images, and then a following classifier was set up for recognition. The experimental results show that comparing to traditional methods, the constructed network based on the deep learning method can easily recognize Braille images with satisfied performance. The deep learning model can effectively solve the Braille recognition problem in automatic feature extraction and dimension reduction with a reduced preprocessing.

Spam Tag Detection Method Based on Collaborative Annotation Image Data

WANG Qi1, DU Juan1, CHENG Bin2, XU Guo-qing1

2015, 0(6): 41-45. doi:10.3969/j.issn.1006-2475.2015.06.009

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The accuracy of the collaborative tagging image retrieval is lower because of the inaccuracy of user’s annotation. Existing spam tag detection methods tend to focus on label itself, ignoring the correlation between collaborative label and image. Analyzing the correlation of collaborative tagging image visual content and image tags, the spam tag detection method of collaboration annotation based on visual content of collaborative tagging image is proposed. The method analyze visual content of images which have the same tag and design different kernel functions for color and SIFT feature subset. The two features will be mapped form low dimensional space to high dimensional character space, while the mixedkernel function is established. Finally, the images which have the same tag is clustered by maxmin distance means, and the tag of images in the class which has a few images are spam tags because of weak correlation. The experimental results show that the method can improve the accuracy of the tag spam detection on collaborative annotation images.

Rotation-Invariant Texture Classification Based on Angular Radial Transform

WANG Gang

2015, 0(6): 46-50. doi:10.3969/j.issn.1006-2475.2015.06.010

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Texture classification is widely used in the fields of medical image analysis etc., as for image rotation caused by factors such as the angle changing during the process of texture image capturing, a method of texture classification based on Angular Radial Transform (ART) is proposed, which is rotationinvariant. Firstly, the ART method is used for image feature extraction to obtain the angular feature vectors and the radial feature vectors, respectively. Then the two extracted feature vectors are combined as a whole. Finally, the K-nearest neighbor feature space distance method is applied for texture classification. Brodatz texture library images are selected for texture classification test. Experimental results show that the proposed algorithm has a good effect on rotation-invariant texture classification.

A Re-Lighting Algorithm to Improve Recall Rate of Face Recognition

LUO Guang-ming

2015, 0(6): 51-54. doi:10.3969/j.issn.1006-2475.2015.06.011

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In escapee hunting, face recognition is applied widely. However, face recognition rate is affected by complex lighting environment. So it is a key problem that how to diminish the effect of illumination for face recognition. A re-lighting algorithm is proposed in this paper. First, the inherent texture features of the input image is extracted by selfquotient image algorithm. Then the illumination of the image is normalized based on an illumination bootstrap set. Finally the re-lighting image is produced by the combining texture image and the normalized illumination image. Experiments on AR, CMU_PIE and CAS_Lighting Face Database demonstrate that the proposed algorithm can improve the recall rate of face recognition algorithm, and further help to chase escapee.

A Fast Image Enhancement Algorithm for Traffic Scene

LI Ling-jie1, TANG Ning2

2015, 0(6): 55-58. doi:10.3969/j.issn.1006-2475.2015.06.012

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In this paper, a night image enhancement method is proposed for intelligent traffic monitoring to improve visual effect of night image. By improving the adaptive function of the adaptive contrast enhancement (ACE) algorithm in the amplification factor, the algorithm can specifically enhance lowbrightness and lowcontrast areas, to prevent excessive image enhancement, and can enhance the details of images, overcoming the shortcomings of traditional contrast enhancement algorithms. Experimental results show that the algorithm enhancement effects are significant, it is of a fast speed while processing nighttime traffic scene image, good adaptive effect with the capacity of weakening “ringing effects”, color fidelity and better retaining and enhancing the image edges and details.

CPU Card Certification System Based on Video Lottery Betting Terminal

WU De-li1, WANG Zhen2, LIU Ze1, YE Lun-shou1, HUANG Xi-kun1， LU Liang-gang2

2015, 0(6): 59-63+96. doi:10.3969/j.issn.1006-2475.2015.06.013

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In view of the difficult situation in identity authentication of the current intelligent lottery betting terminal, this paper proposes an authentication system adopting CPU card. The interaction way of client and server is ased to implement authentication function. The main process are the client reads the CPU card’s authentication information and transmits it to the server, and then the server returns the results to the client after validation. At the same time, stipulating for CPU card’s file structure, and introducing each functional module of CPU card certification system. Finally, through testing, we get the conclusion that the system is of high practicability and reliability.

Hybrid System-Oriented Model Formal Transformation Based on MARTE Language

LI Guo-zheng, CAO Zi-ning

2015, 0(6): 64-68. doi:10.3969/j.issn.1006-2475.2015.06.014

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Hybrid systems are statetransition systems consisting of discrete control mode transformation and continuous real time behavior. Formal modeling and verification for hybrid systems are an important way to ensure the correctness and reliability of the systems. In this paper, we first introduce a Hybrid ZIA formal specification. Then, we expand the MARTE Language with ObjectZ, named OZMARTE, which makes up the shortcoming of formal description aspect of MARTE. Also, to describe the continuous dynamical property in hybrid systems, we propose the transformational rule of the continuous variable, which enhances the capability of modeling hybrid systems. Finally, we give the transformation method from OZMARTE to Hybrid ZIA. So verification techniques for Hybrid ZIA also apply to the verification of MARTE models.

Digital Library Retrieval System Based on ElasticSearch

ZHANG Jian-zhong1, HUANG Yan-fei2, XIONG Yong-jun3

2015, 0(6): 69-73. doi:10.3969/j.issn.1006-2475.2015.06.015

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For the storage and retrieval problem of library works in the era of big data, this paper implemented the massive storage of library works with HDFS and used ElasticSearch to distributed index and retrieval. Test results show that under the large amount of data, this system needs about onetwentieth retrieval time of the traditional Oracle database for searching the same search words, and it has the cache function. So an efficient and distributed digital library retrieval system is built.

Monitoring System Based on Distributed Server

GUO Feng, ZENG Pei-feng

2015, 0(6): 74-77+100. doi:10.3969/j.issn.1006-2475.2015.06.016

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A method for ARMbased distributed Web server is proposed in smartcam to provide easy access with various browsers. Firstly, lightweight Web server runs in ARM processor; Secondly, the users can visit the Web server through the browser in the camera directly, to achieve point to point communication; Finally, through mutual communication and collaboration, cameras constitute a distributed video surveillance system, with the functions of distributed monitoring, distributed computing and distributed storage. System is of high stability, strong security and extensibility.

Fast Algorithm of Large Narcissus Number

WEI Hong-chun

2015, 0(6): 78-81+109. doi:10.3969/j.issn.1006-2475.2015.06.017

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In order to process those integers beyond the scope of computer wordlength, we need to construct suitable data structures for storing big data. This paper studies the characteristics of Narcissus numbers; combines the theory of permutation and combination with functional monotonicity; uses stack which has LIFO character; stores large integer by dynamic array. This method breaks through the traditional design which only considers processing finite length integers, makes the calculation work of finding Narcissus numbers reduce exponentially in the range of positive integers, achieves the purpose of finding all Narcissus numbers quickly in a short period of time within the set of positive integers. This method is a good reference for the processing of large integer.

Cooperative Particle Swarm Optimization Algorithm Based on Huffman Coding

WANG Juan-juan

2015, 0(6): 82-85. doi:10.3969/j.issn.1006-2475.2015.06.018

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Aiming at particle swarm optimization (PSO) algorithm easy to fall into local optimal problems in optimizing a population, a new particle swarm optimization on Huffman Coding (HCPSO) algorithm was put forward. Using Huffman Coding, one population will be divided into two sub populations, and each subpopulation will be optimized independently. At the same time, the two subpopulations cooperatively complete searching the global optimum solution.Through six standard test functions, the experimental results show that the algorithm can effectively avoid the population falling into local optimum, is of better optimization performance and stability, and convergence accuracy is significantly improved.

Hybrid Join Algorithm Based on MapReduce

HU Long, LUO Jun

2015, 0(6): 86-91. doi:10.3969/j.issn.1006-2475.2015.06.019

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Hive, the database on Hadoop, enables more users to process relation data by providing sqllike interface. However, Hive does not provide an efficient approach for join, a common but expensive operator in Hadoop. In order to solve the performance of join, this paper proposes a novel hybrid algorithm, HJA, which can help to automatically choose the relatively better one among several methods, according to the current situation. Experiments results show that HJA can get best performance in most situations.

Wireless Network Channel Access Mechanism Based on Linear Network Coding

REN Xiao-na1, PEI Xiang2

2015, 0(6): 92-96. doi:10.3969/j.issn.1006-2475.2015.06.020

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In order to improve the communication performance of the wireless selforganized network, aiming at the deficiency of current network channel access mechanism, this paper puts forward a channel access mechanism based on linear network coding (LNC). The working principle and the defects of traditional network channel access mechanism are analyzed, and then the linear network coding method is used to improve data packet transmission efficiency, finally Markov chain model is used to construct the mathematical model of LNC, and the performance is tested by simulation experiment. The simulation results show that compared with the traditional network channel access mechanism, LNC not only improves the network throughput and reduces the nodes packet loss rate, but also increases the channel utilization rate.

Adaptive Wavelet Network Equalization Algorithm Based on Iterative Parameter Optimization

QIU Ze-min

2015, 0(6): 97-100. doi:10.3969/j.issn.1006-2475.2015.06.021

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Existing network balancing algorithm has the problems of the slow convergence and the computational redundancy. In response to this phenomenon, through the analysis of traditional adaptive equalization algorithms and wavelet transform, we proposed a network equalization algorithm based on wavelet transform. The robustness of the wavelet transform compensates the slow convergence of the adaptive equalization algorithm. Through analyzing the convergence of the algorithm, the iteration parameters are reset. Experimental results show that the experimental results are basically consistent with the expected results. It is of a good convergence effect and a lower error rate.

A Reliable Routing Algorithm Based on Probabilistic Delivery in Delay Tolerant Networks

ZHOU Hong-jing

2015, 0(6): 101-104. doi:10.3969/j.issn.1006-2475.2015.06.022

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A large number of messages will be dropped when buffer space of network node is limited in delay tolerant networks. A reliable routing algorithm RPROPHET based on probabilistic delivery is proposed. According to the history information of messages replacement in nodes buffer. the reliablity of nodes is evaluated by the routing algorithm. In order to deliver messages to the destination node, the messages are transferred among the reliable nodes. Simulation results show that the proposed algorithm can alleviate ineffective delivery. It can increase the delivery ratio and reduce communication overhead.

A Stress Measurement and Compensation Model Based on PSO-BP Neural Network

HAO Gang， ZHUANG Yi

2015, 0(6): 105-109. doi:10.3969/j.issn.1006-2475.2015.06.023

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For the problem that the stress distribution of flexible material is difficult to directly and accurately measure in the working process, this paper proposes a stress measurement and compensation model based on BP neural network with particle swarm optimization. In order to avoid trapping in local optimum, we use particle swarm optimization algorithm to optimize the model’s initial weights and threshold in the process of the training of the model. Through the contrast experiment with flexible material’s standard curve, effectiveness and accuracy of the model is verified when it is applied in stress measurement on the flexible fabric.

Upper Computer for Roundness Checking of Super Large Type Crankshaft Connecting Rod

LI Ling-chen

2015, 0(6): 110-113+118. doi:10.3969/j.issn.1006-2475.2015.06.024

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Function demand aiming at roundness error detection of a large crankshaft connecting rod was described. Based on .NET platform and SQLite database, using three layers architecture and RS232 communication standard, the design of roundness instrument detection upper computer software was completed. The software realizes detection crankshaft roundness error and resolves large parts of the roundness error detection and calculation problems in the current manufacturing enterprises. In the practical application of the verification process, the detection achieves the purpose of realtime, high efficiency and accuracy, which effectively improves the machining quality of oversize crankshaft connecting rod,reduces assembly time, and solves economy, and safety problems caused by the work piece roundness error.

Remote Monitoring System of Smart Hotel Based on ARM and Wechat Masses Platform

ZHANG Miao1, LIAO Hao-chen2, LIANG Jie-min3

2015, 0(6): 114-118. doi:10.3969/j.issn.1006-2475.2015.06.025

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Given the disadvantage on network controlling, poor mobility as well as high consumption in conventional monitoring system of smart hotel, a remote monitoring system of smart hotel based on ARM controller and Wechat masses platform is designed. After adding Wechat masses account of the hotel, which authorized by the administrators, guests can remotely check the status of guestrooms appliances and control them through Wechat. The smart controller in the system uses ARM CortexA7 processor as the core and runs on an embedded Linux operating system. Monitoring systems intranet is constructed by ZigBee wireless communication technology, because it has the advantages of building network flexibility at low cost and low power consumption. In the meantime, Web Server is added to ARM controller connected external network so that it can achieve the function of remotely encrypted date communication by Internet. The test results show that the system possesses the merit in excellent mobility, higher scalability and security.

Design of Wireless Environment Detection Car Based on Arduino

XU Yuan-wen, ZHANG Jing-jing, CHEN Ning

2015, 0(6): 119-121+126. doi:10.3969/j.issn.1006-2475.2015.06.026

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Aiming at the bad environment, we designed and implemented the wireless environment detection system based on Arduino hardware and software development platform, which has been installed in intelligent car. By the mobile car, circuit data acquisition in the bad environment such as temperature, humidity, illumination and perception of smoke warning prompt is sent to the control terminals in real time, that making it easy for users to analyze and decide environmental data. This design of automatically environment detection system is of important guiding significance on the application and popularization.

CUDA-based Real-time Face Recognition System

LIU Duo

2015, 0(6): 122-126. doi:10.3969/j.issn.1006-2475.2015.06.027

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Through the optimization of the two important part of face recognition system, we proposed a CUDA-based real-time face recognition system. In the face detection phase with Viola-Jones cascade classifier, we implemented and improved novel parallel methodologies of image integral, calculation scan window processing and the amplification and correction of classifiers. In the face recognition phase, we explored the parallelizing of the algorithm and parallelized some part of the testing phase. In comparison with traditional CPU program, the proposed approach running on an NVIDIA GTX 570 graphics card could respectively achieve 22.42 times speedup in detection phase and 1668.56 times speedup in recognition phase. The recognition speed will increase until it reaches the hardware resource limit. The experimental results demonstrate that the system achieves a good real-time performance.

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