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The Realization of Identification Method for DataMatrix Code 5

The Realization of Identification Method for DataMatrix Code

引用

2017 international conference on progress in informatics and computing(PIC)

作者： YanGe Dai Lizhen Liu Wei Song Chao Du Xinlei Zhao Information and Engineering College Capital Normal University College of Foreign Languages Capital Normal University

ISBN: (纸本)9781538619797;9781538619780

The minimum size of the DataMatrix code is 0.0002 square inches and this size is the smallest of the current onedimensional and two-dimensional codes. So it is particularly suitable for printing on metal parts of circuit boards. However, compared with the general two-dimensional code, there are still many technical difficulties on metal surface DataMatrix code identification technology. The reflection on metal surface is not conducive to the DataMatrix binarization. The large spacing between the codes is not conducive to positioning and identification. There is a distorted or incomplete DataMatrix code on metal surface. In this paper, a DataMatrix code recognition method is proposed by digital image processing technology. Firstly, Binarization is achieved by improving the traditional Otsu algorithm. The binarized image is dilated to solve the problem of large code interval. Secondly, the DataMatrix code region is located. The Hough transform is used to detect the four vertices of the DataMatrix code. The vertex is used to correct the twisty DataMatrix code. Finally, according to the structural characteristics of the DataMatrix code, the incomplete code is completed. According to the encoding rules, the DataMatrix code is decoded. After the above series of steps, we can achieve the purpose of identifying DataMatrix code.

关键词： DataMatrix image processing binarization

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Brain Storm Optimization with Adaptive Search Radius for Optimization 5

Brain Storm Optimization with Adaptive Search Radius for Opt...

引用

2017 international conference on progress in informatics and computing(PIC)

作者： Yang Yu Lei Wu Hang Yu Sheng Li Shi Wang Shangce Gao Faculty of Engineering University of Toyama Hefei Power Supply Co. Ltd.State Grid Corporation of China College of Computer Science and Technology Taizhou University

ISBN: (纸本)9781538619797;9781538619780

Brain storm optimization algorithm is a newly proposed algorithm which is based on the social behaviors of human beings. It gets inspiration from the procedure of brain storming to generate new individuals. The properties of brain storming highly ensure the diversity of the whole population and can efficiently eliminate premature convergence. In this paper, an adaptive search radius method has been proposed to help brain storm optimization to enhance its search ability. The proposed algorithm equipped with adaptive search strategies introduces a success and failure memory to choose the best suitable search strategy to improve the individual quality in each iteration. Three strategies can be chosen in the duration of convergence adaptively and guarantee better solutions compared with traditional brain storm optimization.

关键词： brain storm optimization adaptive search radius memory-based selection meta-heuristic algorithm

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Infrared Remote Sensing Imaging via Asymmetric Compressed Sensing 5

Infrared Remote Sensing Imaging via Asymmetric Compressed Se...

引用

2017 international conference on progress in informatics and computing(PIC)

作者： Zhao-yun Fan Quan-sen Sun Ji-xin Liu School of Computer Science and Engineering Nanjing University of Science and Technology Engineering Research Center of Wideband Wireless Communication Technology Ministry of Education Nanjing University of Posts and Telecommunications

ISBN: (纸本)9781538619797;9781538619780

Compressed sensing（CS） theory provides a new acquisition idea for sparse signals and sparsely-expressed signals. CS-based hardware design has been widely concerned. And related products have been tentatively tried in many fields. The design of remote sensing imaging based on CS mainly includes single pixel multiple exposure imaging and block focal plane coding multi-pixel single exposure imaging. In this paper, a CS asymmetric processing model, which is different from traditional image reconstruction, is proposed. And it is applied to CS hardware design for infrared（IR） remote sensing imaging. This model fully considers the global information of the image, which combines the multiple neighborhood values of the observed results in the CS process, and also combines the multiple measurement matrix blocks to form a new measurement matrix. At the same time, a sparse dictionary construction method suitable for asymmetric patterns is proposed, which can effectively compensate for the local differences caused by image *** experimental results show that the proposed method is superior to the conventional block focal plane coding compression reconstruction both in reconstruction time and in reconstruction quality.

关键词： Compressed Sensing Image Reconstruction Asymmetric Mode Measurement Matrix

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A Preference-based Multi-objective Evolutionary Strategy for Ab Initio Prediction of Proteins 5

A Preference-based Multi-objective Evolutionary Strategy for...

引用

2017 international conference on progress in informatics and computing(PIC)

作者： Zhenyu Song Yajiao Tang Xingqian Chen Shuangbao Song Shuangyu Song Shangce Gao Faculty of Engineering University of Toyama

ISBN: (纸本)9781538619797;9781538619780

Predicting the three-dimensional structure of a protein from its amino acid sequence is an important issue in the field of computational biology and bioinformatics. It remains as an unsolved problem and attract enormous researchers' interests. Different from most conventional methods, we model the protein structure prediction(PSP) problem as a multiobjective optimization problem. A three-objective energy function based on three physical terms is designed to evaluate a protein conformation. A multi-objective evolutionary strategy algorithm coupled with preference information is proposed in this study. The preference information is used in the survival criteria, focusing on the exploration of search process. The experimental results based on five proteins in PDB library demonstrate the effectiveness of proposed method. The analysis of Pareto fronts indicates that the preference information can make solutions diverse in genotypic space. Thus, the proposed method gives a new perspective for solving PSP problems.

关键词： Protein structure prediction multi-objective optimization multi-objective evolutionary algorithm preference information utility function

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Underfloor Heating Users Prediction Based on SVDD 5

Underfloor Heating Users Prediction Based on SVDD

引用

2017 international conference on progress in informatics and computing(PIC)

作者： Xingguang Yang Huiqun Yu Jianmei Guo GuiSheng Fan Kai Shi Department of Computer Science and Engineering East China University of Science and Technology Alibaba Group

ISBN: (纸本)9781538619797;9781538619780

Data analysis and utilization play an important role in the development of enterprises. How to extract valuable information from existing data is the focus of current *** of underfloor heating users is an important and urgent research topic of Gas Co. This paper constructs a prediction model to analyze whether the gas users are underfloor heating users or not based on the gas data sets. Because the training set we obtained only contains one class of data, we adopt the SVDD algorithm, which can effectively solve the oneclass classification problem. In the experiment, we construct the prediction model effectively and estimate the proportion of underfloor heating users in gas users. Considering the sensitivity of the parameters in the SVDD algorithm to the prediction model, we obtained the relationship between the proportion of underfloor heating users and the values of parameters through the parameter tuning, which could provide the reference for Gas Co to select parameters.

关键词： SVDD algorithm underfloor heating users prediction one-class classification

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Design of Low Cost Pedestrian Location System Based on Inertial Navigation 5

Design of Low Cost Pedestrian Location System Based on Inert...

引用

2017 international conference on progress in informatics and computing(PIC)

作者： Xie Shuiqing Li Xiangyuan Li Zhengyi Zhou Hui Yang Dandan College of Electronics and Information Engineering South-Central University for Nationalities College of Biomedical Engineering South-Central University for Nationalities

ISBN: (纸本)9781538619797;9781538619780

When carrying out special services of rescue and firefighting in buildings, underground works, tunnels and mine, where has no GPS signal, it’s important to get location information of special staff, which used by guiding rescue, evacuation and force dispatch. In order to meet the above requirements, this system uses the inertial measurement unit constructed by 3-axis acceleration, 3-axis gyroscope and 3-axis geomagnetic sensor to complete the measurement of pedestrian motion information, calculate the personnel attitude through the cosine matrix, and use the extended Kalman filter the calculation of the speed and position of the personnel is carried out, and the zero speed detection is realized by the gyroscope to reduce the accumulated error of the calculation, thus realizing the key technology of inertial navigation. Using Zig Bee and WIFI modules, the development of portable wireless network nodes, to build a wireless self-organizing network. Using embedded microcontrollers and MEMS inertial sensors to build a wearable wireless navigation and positioning system. Using wireless ad hoc network, implement real-time online monitoring of the staff positions and movement trajectory. The wearable wireless navigation and positioning system can accurately obtain the position and movement trajectory of the rescue personnel. Using the wireless ad hoc network, the position and the trajectory information of the rescue personnel can be transmitted to the control center in real time to provide information for the disaster relief command and decision support service.

关键词： Pedestrian Navigation System Inertial Sensors Zero-Velocity Detection Kalman filter

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English Mispronunciation Detection Based on Improved GOP Methods for Chinese Students 5

English Mispronunciation Detection Based on Improved GOP Met...

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2017 international conference on progress in informatics and computing(PIC)

作者： Guimin Huang Jing Ye Zhenglin Sun Ya Zhou Yan Shen Ruyu Mo Guilin University of Electronic Technology

ISBN: (纸本)9781538619797;9781538619780

In this paper, we proposed two approaches to detect mispronunciation in spoken English for Chinese Students which is based on improved Goodness Of Pronunciation(GOP) algorithm. We adopted a modified Maximum Likelihood Linear Regression(MLLR) to adjust the acoustic model which can reduce the mismatch between native original model and adaptive data from non-native speakers. Then we could calculate the ameliorated GOP value to improve the performance of phonelevel pronunciation error detection. Besides, as Chinese students are likely to be influenced by their mother tongue in their oral English training, we collected the common pronunciation error patterns of Chinese students by introducing priori linguistic knowledge and established a phonemes set that are easy to confuse for optimizing the GOP probability space. The mispronunciation detection system with the above ways could review input speech and detect the flawed phone to allow the non-native learners to correct the mispronunciation duly. The experimental results suggested that the modified GOP method reached good effect of English pronunciation error detection for Chinese students.

关键词： Mispronunciation detection Goodness of pronunciation Maximum likelihood linear regression

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Research on Abnormal Behavior Target Tracking Algorithm in Airport Intelligent Video Surveillance 5

Research on Abnormal Behavior Target Tracking Algorithm in A...

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2017 international conference on progress in informatics and computing(PIC)

作者： Daihao Zhang Xiaoyan Qian Yanlin Zhang College of Civil Aviation Nanjing University of Aeronautics and Astronautics Nanjing University of Aeronautics and Astronautics College of Civil Aviation

ISBN: (纸本)9781538619797;9781538619780

With the rapid development of China's civil aviation industry, the airport is facing increasing pressure on security. In this paper, the target tracking algorithm in Intelligent Video Surveillance(IVS) is studied. It aims to provide ideas and reference for the development and implementation of high performance intelligent video surveillance system. The main contents of this paper are as follows: Aiming at the problem of tracking failure caused by occlusion, deformation and illumination changes, this paper proposes a target tracking algorithm that combines the apparent features and depth characteristics. Firstly, the CNN network is trained by a large number of pedestrian databases, and then the depth characteristics of the target area are extracted by trained CNN network. At the same time, the color histogram of the target area in HSV space is calculated, and the depth feature and color feature are combined to get the whole feature. Finally, a number of hypothetical states are estimated under the framework of particle filter, the optimal position of the target is obtained, the tracking result is obtained, and the template is updated. Finally, the resampling is carried out according to the degeneration of the particle. Experiments show that the tracking algorithm has good tracking robustness. Finally, the target tracking system is designed and simulated on the Matlab platform. The validity and practicability of the algorithm are verified.

关键词： intelligent video surveillance convolution neural network color histogram target tracking

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Gravitational Search Algorithm Combined with Modified Differential Evolution Learning for Planarization in Graph Drawing 5

Gravitational Search Algorithm Combined with Modified Differ...

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2017 international conference on progress in informatics and computing(PIC)

作者： Hang Yu Huisheng Zhu Huiqin Chen Dongbao Jia Yang Yu Shangce Gao College of Computer Science and Technology Taizhou University Department of Agricultural Internet of Things Jiangsu Agri-animal Husbandry Vocational College Faculty of Engineering University of Toyama

ISBN: (纸本)9781538619797;9781538619780

Gravitational search algorithm(GSA) is one of the powerful population based meta-heuristics. It has achieved many successes in various applications derived from optimization, data mining, information security, etc. However, it still suffers from the local optima trapping problem and cannot obtain promising solutions especially for practical problems. Graph planarization arises from many practical applications of VLSI circuit design,automatic graph drawing, etc, and is proved to be *** solve this problem, this study proposes a hybrid GSA by combined with a differential evolution operator. The proposed method GSADE is used to acquire optimal planar subgraphs for a given graph. Experimental results based on thirty graph instances show that GSADE is a very competitive method in comparison with previous state-of-the-art methods.

关键词： gravitational search algorithm differential evolution artificial intelligence VLSI design graph planarization

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Two Dimensional Paraspinal Muscle Segmentation in CT Images 5

Two Dimensional Paraspinal Muscle Segmentation in CT Images

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2017 international conference on progress in informatics and computing(PIC)

作者： Yong Wei Bin Xu Mengyi Ying Junfeng Qu Ryan Duke Dept.of Computer Science&Information Systems University of North Georgia Dept.of Spine Surgery Jinling HospitalSchool of MedicineNanjing University Department of Mathematics University of North Georgia Department of Computer Science Clayton State University Department of Physics University of North Georgia

ISBN: (纸本)9781538619797;9781538619780

Paraspinal muscles support the spine and are the source of movement force. The size, shape, density, and volume of the paraspinal muscles cross-section area(CSA) are affected by many factors, such as age, health condition, exercise, and low back pain. It is invaluable to segment the paraspinal muscle regions in images in order to measure and study them. Manual segmentation of the paraspinal muscle CSA is time-consuming and inaccurate. In this work, an atlas-based image segmentation algorithm is proposed to segment the paraspinal muscles in CT images. To address the challenges of variations of muscle shape and its relative spatial relationship to other organs, mutual information is utilized to register the atlas and target images, followed by gradient vector flow contour deformation. Experimental results show that the proposed method can successfully segment paraspinal muscle regions in CT images in both intrapatient and interpatient cases. Furthermore, using mutual information to register atlas and target images outperforms the method using spine-spine registration. It segments the muscle regions accurately without the need of the computationally expensive iterative local contour optimization. The results can be used to evaluate paraspinal muscle tissue injury and postoperative back muscle atrophy of spine surgery patients.

关键词： CT image segmentation mutual information-based image registration atlas-based image segmentation paraspinal muscle

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