Table of Content

23 January 2018, Volume 0 Issue 01

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An Energy Consumption Estimation Algorithm for Applications of Mobile Phones

TANG Jia-bo1， WANG Yu-ran1， CHENG Ru-jie1， LU Jian1， JIANG Hou-ming2， HU Mu2， WU Jia3

2018, 0(01):  1-7.  doi:10.3969/j.issn.1006-2475.2018.01.001

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The paper is to establish a model of the energy consumption of mobile phones. The energy consumption of mobile phones is divided into four different parts, namely, system energy consumption, application energy consumption, periodic jump and white noise. Based on the model established, the energy consumption estimation algorithm for applications is proposed to analyze the energy consumption of the functions included in the application, and to locate the code segment which consumes energy abnormally. The model for the energy consumption mainly consists of the energy consumption evaluation of the operation system, the removal of noise arisen caused by the periodic jump, and the evaluation of functional average energy consumption. The denoising model for the noise caused by the periodic jump is based on DBSCAN algorithm, and the hyper parameters of the denoising model are selected by scanning hyper parameters combined with the theory of machine learning. Based on the results of the model above and verification of varied mobile phones combined with trace files, the average error is only 5.58% when evaluating the energy consumption of mobile phones, which means the model has good generalization ability in the calculation of energy consumption of functions and code segments.

An Algorithm for Simulation of Flight Track Simulation

WU Zhi-qing1， CAI Wei-jia2

2018, 0(01):  8-10.  doi:10.3969/j.issn.1006-2475.2018.01.002

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In flight simulation, the aircraft track simulation does not take into account the aircraft is uniform speed or change speed. It is usually represented by a simple combination of straight lines and circles. This algorithm is generally ideal or simplified. In order to establish a realistic implementation of complex air situation and flight simulation, mathematical model of aircraft motion is studied. The aircraft linear flight algorithm is summarized, and a new simulation algorithm is proposed to simulate the turning track of aircraft in order to simplify the turning track of aircraft. A new method of turning and increasing the diversity of aircraft tracks is achieved by using an algorithm for uniform and variable speed turns of an aircraft. The application and simulation of the new algorithm in ATC simulation training system, compared with the track data of the real aircraft, confirm that the new algorithm can simulate the transmission turning track, and make the whole track closer to the true.

A Feature Selection Algorithm of Battery SOH Based on ACCA-FCM and SVM-RFE

LIU Wei, YANG Hui-jie, LIU Shou-yin

2018, 0(01):  11-18.  doi:10.3969/j.issn.1006-2475.2018.01.003

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In the prediction of the lead-acid battery state of health (SOH), the selection of representative feature set based on small sample plays an important role, considering the various factors resulting in the battery aging and the restriction of the battery aging experiment that the full charge and discharge time and the number of samples are limited. Therefore, based on the analysis of battery characteristics, an SOH feature selection algorithm based on unsupervised ACCA-FCM and supervised SVM-RFE is proposed. The algorithm, first, utilizes the improved ant colony clustering algorithm (ACCA) to select the effective eigenvalue clustering center from the global feature set, which overcame the clustering center sensitivity and local optimal problem of fuzzy C-means clustering algorithm (FCM), and removes the redundant features by the features correlation; second, according to the SVM-RFE feature sorting algorithm, rules out the non-critical interference (Low predictive) features; and finally, obtains the low-dimensional eigenvector with the largest correlation as well as the minimum redundancy of the test result, and avoids the process of complete discharge under the premise of ensuring the accuracy. The SOH model of the battery is verified by the support vector machine (SVM), which has been improved significant and accurate.

Application of Parallel Genetic Algorithm Based on Spark in Logistics Distribution

WANG Long， YAO Wen-ming

2018, 0(01):  19-22.  doi:10.3969/j.issn.1006-2475.2018.01.004

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The traditional genetic algorithm may be premature in the case of insufficient data, it has a strong dependence on the search range, and the genetic algorithm with large search range often has a better performance. In order to solve the above problems, we can use the Spark mass storage and parallel computing ability to solve the genetic algorithm, implementing a coarse-grained parallel model, executing genetic algorithm selection, crossover and mutation operations in parallel using Spark. Executing genetic algorithm in parallel with Spark can greatly improve the search scope and parallel running speed. The application of improved genetic algorithm to the logistics and distribution problems and the experimental results show that compared with the serial and traditional parallel program, running time of genetic algorithm based on Spark is significantly reduced, and premature phenomenon is eased also.

Intelligent Dormitory Allocation Method Based on Greedy Algorithm

CAO Xue-xue

2018, 0(01):  23-26.  doi:10.3969/j.issn.1006-2475.2018.01.005

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For the problem issued in the traditional method of dormitory allocation that lacking of consideration about student’s own situation, a new method of dormitory allocation is proposed in this paper. Based on the greedy algorithm, before the dormitory allocation, we survey sleep habits, get up habits, character and living expense of students, and students can give weight to each option based on individual situation. This method can calculate the degree of match between students according to the results of questionnaire, and assign the students with the high degree of match to same room. Compared with the traditional method, this method takes into account the circumstances of students, contributing to the students to live in harmony.

Application of Data Mining C4.5 Algorithm in Municipal Engineering Cost

FU Ze-heng

2018, 0(01):  27-31.  doi:10.3969/j.issn.1006-2475.2018.01.006

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The paper improved the C4.5 algorithm, and then used C4.5 algorithm and an improved C4.5 algorithm through comparative analysis on the quantities bill valuation of municipal road engineering case, extracted classification rules of general applicability at random verification of classification rules. It can be found that the classification rules have universal applicability, which can help the project cost related practitioners to quickly predict and improve the efficiency of decision analysis.

Chatterbots Based on RNN Sentence Auto-encoder

ZHU Jing-jing, HAN Li-xin

2018, 0(01):  32-35.  doi:10.3969/j.issn.1006-2475.2018.01.007

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Man-machine dialogue is a realistic application scenario which derived from the field of natural language processing. Based on the large amount of short text knowledge obtained from reality, the man-made short dialogue intelligent response chatterbot is constructed. Based on the traditional information retrieval typed chatterbot, the Recurrent Neural Network (RNN) is introduced to characterize the semantic vector of short text in the interactive knowledge base and reconstructs the expression semantic space. Experiments show that the effect of the method of using the coding vector is improved compared with the traditional method of using TF-IDF vector.

Real-time Brain-controlled Avatar System Based on SSVEP and Motor Imagery

LIN Ming-duo, OU Zu-hong

2018, 0(01):  36-39.  doi:10.3969/j.issn.1006-2475.2018.01.008

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Aiming at solving the problem that the accuracy rate of recognition system is relatively low, the model is simple and the complexity of the algorithm is high, the real-time brain control real-time algorithm based on SSVEP and motion imagination is designed and applied to the brain-controlled Avatar system. By conducting off-line training and online testing of six subjects, the experimental results show that the system better reflects the control intention of the subject. All subjects can basically control the robot and achieve multi-instruction control with high recognition accuracy. The system steps to promote the brain-computer interface in the practical application and development.

Analog Circuit Fault Diagnosis Based on Modified Fruit Fly Optimization Algorithm

SHAO Xin-tian， LI Zhi-hua， WANG Zhen

2018, 0(01):  40-43.  doi:10.3969/j.issn.1006-2475.2018.01.009

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Aiming at the problem of the localization of nonlinear components in analog circuits, an improved Drosophila algorithm is proposed to optimize the support vector machine (SVM) fault diagnosis method. Firstly, the output signal of the diagnosed circuit is sampled, the characteristics of the output signal are extracted by the Volterra series, and then the improved fruit fly algorithm is used to optimize the kernel function parameters and structural parameters of the SVM. The diagnosis model is established and the fault is established in the logarithmic amplifier circuit for diagnostic classification. Using MATLAB software to carry out simulation experiments, through experiments we can see that this method can effectively avoid the random selection of support vector machine parameters, help to improve the diagnostic accuracy and diagnostic speed.

Vector Data Visualization System Based on Browser

WANG Nan, FENG Lei

2018, 0(01):  44-50.  doi:10.3969/j.issn.1006-2475.2018.01.010

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Using a server and client mixed construction model, WEBGIS is a combination of network technology and GIS technology product. The vector map pre-rendered is based on the server to draw a rasterized tile map currently, and then the browser obtains and displays it. This method is unable to meet the vector map dynamic mapping on the browser, vector map promise zoom and other functions of the demand. By studying for the display control frame of vector map, the rendering of vector objects and annotations along with symbolic library and map symbolization researched, the HTML5 technology is used to build a browser-based vector data visualization system prototype. This system is verified in key technologies of the vector data rendering and map interactive, and meet the user’s growing needs of RIA (rich Internet application).

An Improved ViBe Algorithm Based on Ghost Judgment #br# Suppression and Local Motion Compensation

ZHANG Wei-ming, ZHOU Wu-neng

2018, 0(01):  51-55.  doi:10.3969/j.issn.1006-2475.2018.01.011

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The traditional ViBe algorithm has a “ghost” phenomenon in the detection of moving targets, and it cant detect the complete result for the target with only local motion. Most improved algorithms cant determine the types of defects in overcoming the above defects which reduces the performance of the algorithm. Therefore, for the “ghost” phenomenon, this paper uses edge similarity to make “the ghost judgment”, then combines the three frame difference method to eliminate ghosting. Aiming at local moving target, this paper proposes a new method to determine the existence of local motion, then the whole moving object is obtained by combining the scan line filling algorithm. Experiments show that this algorithm can effectively overcome the defects of “ghost” and local motion, and improve the efficiency and accuracy of the target detection.

A Heterogeneous Mixed Fast Drawing Framework Based on Vec-map Data

LI Jia-qi， ZHENG Hao

2018, 0(01):  56-61.  doi:10.3969/j.issn.1006-2475.2018.01.012

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With the development of mapping, remote sensing and related technology, the data scale and detail level of vector map are increasing rapidly. They contain a lot of complicated geospatial elements, and there are complex topological geometries among the elements. This makes high-performance parallel computing is very urgent for the rapid visualization of large-scale vector maps. Aiming at this problem, this paper introduces a GPU-accelerated operation based on the original CPU multi-core processing, and proposes a heterogeneous hybrid parallel rendering technique based on CPU-GPU cooperative work. The experimental results show that this kind of processing frame plays a more important role in the rapid visualization of vector data, and the parallel acceleration ratio achieves higher values under large scale data.

Visualization and Visual Analysis System of Environmental Quality Data

LIU Ge1， LIU Yun-fei2

2018, 0(01):  62-68.  doi:10.3969/j.issn.1006-2475.2018.01.013

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 With the increasingly severe global environmental climate， it is urgent to provide decision support for relevant government departments to protect the environment and social development by means of environmental information. Environmental quality data visualization and visual analysis technology play an important role in the process of environmental information. In this paper， the design and implementation of the system function and architecture are introduced from the point of view of visualization and visual analysis， and the key technology of the system is discussed. The results show that， the system in visual modeling， two or three dimensional visualization， data organization of the environmental quality of multi-source data and data scheduling， 3D scene real-time rendering and other aspects have special solutions. The system can display the information of environmental quality data in all directions， and realizes the analysis of multi-source environmental quality data.

Visualization and Re-extraction Technology of 2D Radar Envelope Data

FU Cheng， NIE Ying

2018, 0(01):  69-73.  doi:10.3969/j.issn.1006-2475.2018.01.014

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Radar information visualization is one of the most important aspects of modern battlefield visualization, it is a crucial role for the control of the overall situation of the battlefield. Aimed at the problem of data loss after visualization of two-dimensional radar envelope data, in this paper, the radar envelope detection algorithm is proposed to extract the multi-radar envelope, and the algorithm can accurately retrieve the original data corresponding to each boundary line. In addition, for the slow problem of radar envelope drawing, this paper uses bitmap technology to quickly maping the envelope. The experimental results show that the method can quickly update the radar envelope.

Static Hand Gesture Recognition Based on RGBD Data

WEN Fang， KANG Cai-qin， CHEN Li-wen， DING Hui， XU Kun， WANG Ning-ning

2018, 0(01):  74-77.  doi:10.3969/j.issn.1006-2475.2018.01.015

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This paper proposes a hand gesture recognition algorithm based on RGBD data. Firstly, the gesture segmentation algorithm which combines depth data with color data is used to segment the hand gesture area more precisely. Secondly, circularity,convex hull points and convex defect points, 7Hu moment features of the segmented static gestures are extracted. Lastly, SVM are used to recognize different static hand gesture. The experimental results show that the proposed method can effectively identify the five kinds of static gestures, and has strong adaptability to the environment.

WAPM: A Web Accessibility Evaluation Metric Based on Improved AHP

LI Fei1， LI Han-jing1,2， YAO Deng-feng2， LYU Hui-hua2

2018, 0(01):  78-83.  doi:10.3969/j.issn.1006-2475.2018.01.016

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In the Web accessibility evaluation, the comprehensive value of the accessibility measurement reflects the accessibility of the Web. Existing research has shown that finding the right weight for different checkpoints is a challenging problem. Although some indicators derive checkpoint weights from WCAG 2.0 priorities, previous surveys have shown that WCAG 2.0 priorities are not significant related to the accessibility of the site’s accessibility, operability, comprehensibility, and robustness. In addition, the results of our website’s accessibility assessment also confirm that sites of using existing metrics do not match the four principles. In order to overcome this limitation, we propose a Web accessibility principle metric, which is called the Web Accessibility Principle Metric（WAPM）, so as to better match the evaluation results of the auxiliary function with the four principles, that is, using the analytic hierarchy process to analyze the four principles, because the association mapping between the detection point and the four principles is not exactly the case, we improve the analytic hierarchy process to derive the optimal detection point weights from the four principles. The actual website accessibility assessment data experiment verifies the effectiveness of WAPM.

Implementation of Key Technology Based on Cross-regional #br# Command and Communication System

ZHOU Xue-han, ZHENG Yang-fei

2018, 0(01):  84-88.  doi:10.3969/j.issn.1006-2475.2018.01.017

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Considering the special application scenario of the cross-regional operation, we have studied the group function of the communication system aiming at the problem in the development process of cross-regional command and communication system. Due to the characteristics of confidentiality and secrecy of operation, we propose and design the reliable information guidelines. After our approach has come to use, a good effect is gained in practice. It proves the effectiveness of group function which improves the communication efficiency. And the function of reliable information guidelines greatly enhances the security of the communication process.

A IoT Distributed Discovery System Based on DHT

ZHANG Bing-kun, LI Xiao-hui, WANG Zhi-qian

2018, 0(01):  89-94.  doi:10.3969/j.issn.1006-2475.2018.01.018

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The Internet of Things (IoT) is envisioned to adapt massive of devices accessing or exiting and frequent network changes, which brings lot of pressure to nodes management. Structured P2P network can effectively relieve this pressure. But most P2P networks simply support to search node with node ID. This paper improves Distributed Hash Table (DHT) and realizes searching and managing with node properties and range of properties. Based on improved DHT, this paper realizes a new kind of IoT resource discovery system. This system could organize all kinds of resource in IoT and form a distributed and loosely coupled system for IoT system. Experiment showes the search system could realize effective nodes search in distributed IoT.

A Semi-centralized SDN Routing Strategy in Data Center Network

TIAN Ye1， SUN Yan-tao1,2， XIONG Ke1,2

2018, 0(01):  95-101.  doi:10.3969/j.issn.1006-2475.2018.01.019

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 In software defined network (SDN) architecture, the network control function is separated from network devices (switches/routers) and integrated to the central node controller, while switches are used to implement functions on the data plane (data forwarding based on the flow table). On large-scale data center networks, calculation and distribution of the routing/flow table are completely processed by the central controller, and the controller has become the bottleneck and vulnerability for network performance. To solve these problems, the essay proposes a semi-centralized SDN routing technology based on the data center network. Its main idea is that each switch node constructs a basic flow table for itself without involving the controller so that the switch can implement basic data forwarding based on the flow table. Meanwhile, the controller is responsible for routing (troubleshooting) of a higher level, thus greatly reducing controller’s loads. In this paper, advanced routing for the controller, a partial roundabout troubleshooting mechanism is designed based on the basic flow table through the analysis of the characteristics and limitations of the fault recovery mechanism in the existing SDN network. In this way, the controller can detect network failures in a timely manner and can recover the failures in short time to implement troubleshooting in advanced routing on controllers.

Research on Network Traffic Prediction and Early Warning in Complex Networks

MA Jia-yan, WANG Ping,XIA Wei, SHEN Hong-wei

2018, 0(01):  102-106.  doi:10.3969/j.issn.1006-2475.2018.01.020

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Aiming at the shortcomings of the traditional network traffic prediction method in complex network environment, such as large prediction error and low precision, this paper proposes a network traffic prediction model based on EMFOA_LSSVM. EMD is used to extract the trend and detail features of the network traffic data, and the input and output matrix of the prediction model is constructed. The network traffic prediction in complex network environment is realized by MFOA_LSSVM. The experimental results show that, compared with MFOA_LSSVM, FOA_LSSVM, PSO_LSSVM and LSSVM, EMFOA_LSSVM has higher prediction accuracy and convergence speed, and provides the basis for network traffic prediction and early warning.

Research on Origin of Micro-blog Rumors Based on Longest Common Subsequence

LI Cheng， SHA Jun-song， WU Wen

2018, 0(01):  107-112.  doi:10.3969/j.issn.1006-2475.2018.01.021

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Mobile phones and other mobile devices, make micro-blog and other social networks become an important channel for information dissemination and sharing. But at the same time, a large number of reactionary, false and pornographic information filled the entire network, and the rumors of the increasingly prominent adverse effects. Furthermore, the emergence of some rumors has seriously affected people’s access to network information and normal use. How to detect all kinds of rumors in the network, and to find out the source of the rumor and the way of communication has become an urgent problem for public security network department to be solved. Micro-blog rumors, for example, according to the existing longest common subsequence(LCS) algorithm, the corresponding improvement is made in the construction of sequence table. The preliminary experiments show that the improved algorithm can be more efficient to compare and originate micro-blog rumors, so as to help public security network department to find the source of micro-blog rumors.

Method of Developing Database Driven by Golang

LIU Yan-ping

2018, 0(01):  113-115.  doi:10.3969/j.issn.1006-2475.2018.01.022

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 Golang is a new open source language released by Google, which makes it easy to develop efficient software. High performance concurrency makes Go play an important role in data processing. This paper makes a study of the Go standard packages, database/sql, driver and the working principle of database, and focuses on the realization of the core interfaces of the driver package. At last, the method of database operation in Go program is studied.

A New Access Control Model for Real Time Database #br# Backup System Based on Quantified Action

LIU Sai1, NIE Qing-jie1, LIU Jun1, LI Dong-min2, LI Jing2

2018, 0(01):  116-122.  doi:10.3969/j.issn.1006-2475.2018.01.023

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Real time backup system has a high restriction on the dynamic. Due to the shortages of the existing access control models in the granularity of the model elements and the dynamic allocation of rights, the security of backup system will be influenced. The concepts of temporal and environment and the definition of action are given to describe the access activities, a quantified action-based access control (QABAC) model for real time database backup system is proposed. The concepts of quantified attribute and trust degree are introduced firstly, the security degree of the access behavior is calculated by using the quantitative function to dynamically quantify the attributes, and then the trust degree of the access behavior is allocated according to the quantitative results. Finally authorization policy determines the access behavior through the trust degree. Compared with other traditional models, the QABAC model is more flexible， more secure, and more suitable for the current open network environment to protect the backup database security.

Chinese Agricultural Named Entity Recognition Based on Conditional Random Fields

ZHANG Jian, WU Qing, YANG Xin-yi, WANG Bin-cong, WU Xuan-wei, XU Xiang-ying, LYU Qiang

2018, 0(01):  123-126.  doi:10.3969/j.issn.1006-2475.2018.01.024

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To meet the requirement of diversification, the paper introduces named entities model based on conditional random fields, divides agricultural named entities into 4 classes, which are diseases and pests, crops, chemical fertilizer, pesticide and annotates. These entities are labeled with custom annotation set. It is segmented collected corpus with ICTCLAS segment system and added features to raise the recognition rate. Ultimately, the accuracy rate reaches over 93% and the recalling rate reaches over 84%. This result confirms that recognizing multiple entities after classifying them is feasible.