Table of Content

25 August 2018, Volume 46 Issue 8

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Electronics, Communication & Automation Technology

Dual-Sparsity Reconstruction Algorithm based on Multi-dimension Reference Frames in Compressed Video Sensing

YANG Chunling ZHENG Xuewei

2018, 46(8):  1-10.  doi:10.3969/j.issn.1000-565X.2018.08.001

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In order to improve the accuracy of sparse reconstruction based on compressed video sensing and achieve a higher quality of reconstructed video frames，considering videos' sparsity features in different domains，this paper proposes a dualsparsity reconstruction algorithm based on multi-dimension reference frames (MＲF-DSＲ) in compressed video sensing． Firstly，a dualsparsity reconstruction model is proposed that video frames group sparsity and laplacian sparsity are both utilized to restrict the reconstructed videos sparsity． Besides，the concept of multidimension reference frames is elaborated in this paper，where half-pixel dimension reference frames and scaling dimension reference frames based on time dimension reference frames are introduced to obtain match-block groups with higher sparsity． Lastly，a fast diamond searching algorithm is presented to implement largescale regional searching with low complexity，which，through the coarse and fine search process，determines the position of optimal time dimension reference frame similar block，then for quick search a small scale in the same position of dimensional reference frames． Experiment results manifest that the proposed MＲF-DSＲ outperforms the state-ofthe-art compressed video sensing reconstruction algorithm both on subjective and objective criteria．

A Self-Adaptive Ｒestoration Algorithm for Image Corrupted with Strong Noise Based on Group Sparsity Ｒesidual Constraint

高红霞 陈展鸿 曾润浩 罗澜 陈安 马鸽

2018, 46(8):  11-18.  doi:10.3969/j.issn.1000-565X.2018.08.002

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Compressed sensing based on group sparsity has shown great potential in image denoising. However, most existing methods considered Nonlocal Self-Similarity (NSS) prior of noisy images only in a block-wise manner, which reduced reconstruction quality. This paper introduced group sparsity residual and total variance as the supplemental constraint within the framework of compressed sensing based on group sparsity, and transformed the reconstruction problem into two issues: multiscale patch matching and decreasing group sparsity residual. Then, an effective iterative algorithm with adaptive regularization parameter was proposed to recover the noisy images after estimating original images’ group sparse coefficients and matching patches at multiple scales, which improved group sparsity learning’s performance in denoising and restoring fine structure. Experimental results demonstrated that the proposed algorithm outperforms the contrast benchmarking algorithms for images corrupted with strong noise, such as BM3D, WNNM when considering the visual results and the objective evaluation together.

Guaranteed Cost Control for a Class of Cyber-Physical Systems Under DoS Attacks#br#

WANG Mufeng XU Bugong

2018, 46(8):  19-26.  doi:10.3969/j.issn.1000-565X.2018.08.003

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In the past decade, security issues of Cyber-Physical Systems (CPSs) have drawn enormous attention due to the wide spectrum of applications of CPSs and the serious impact of malicious cyber attacks on CPSs. In this paper, an observer-based feedback control method is used. The guaranteed cost control for a class of CPSs under stochastic DoS attacks on the channel between the sensor and the controller (S-C) is studied. A stochastic interference model is established within an unified framework to reflect the stochastic occuring behaviours of SINR-based DoS attacks and inherent packet dropouts. The guaranteed cost controller is designed to exponentially stabilize the CPS under stochastic DoS attacks in mean-square and the corresponding cost function is less than a specified upper bound. Simulation example is used to demonstrate the effectiveness of the guaranteed cost controll strategy.

A Beamforming Method of Nulling Antenna for Impulse Interference Suppression

ZENG Hao FANG Beibei JI Lixia ZHAO Yunxiao DONG Tao

2018, 46(8):  27-32.  doi:10.3969/j.issn.1000-565X.2018.08.004

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Abstract: When the continuous wave interference and impulse interference presence at the same time for the satellite navigation receiver, the nulling antenna will face the problem of low convergence speed and limited suppression performance to impulse interference assuming the classical LMS algorithm is taken to calculate the weight vector. A new strategy with two parallel calculations for weight vector is proposed according to the various signal characteristics on the condition that we can detect the impulse interference correctly. The new method choose only one weight vector from the two results as the last output of the antenna according whether the impulse interference exits. The theoretic analysis and computer simulation illustrate that the proposed approach could obtain a faster convergence speed and better suppression to the impulse interference compared with the classical LMS algorithm.

A new Structure Placement: Effective Method to Solve the Crossbar Structure Issue in Physical Design

WU Zhaohui ZHOU Xiaoyang HE Sudong LI Bin

2018, 46(8):  33-37,45.  doi:10.3969/j.issn.1000-565X.2018.08.005

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Abstract: In some of the process of dealing with high performance chip physical design, there may encounter the problem caused by crossbar structure. These paths generated by crossbar cause logic cluster together and always lead to congestion or badly timing. These features of crossbar structure make it difficult for P&R tools (ICC, ICC2, Encounter, innovus, etc.) to obtain a satisfied result. This is especially serious in advanced node design with tension routing resource. In this paper, we propose a new structural placement method to solve the problem caused by the crossbar. In the previous structural placement studies, the focus is often on the timing optimization of the data path, and does not involve the requirement of inserting a large number of buffers. The proposed new structural placement method, can successfully solve the routing congestion and the induced timing problem through inserting the buffer tree by fully considering the characteristics of the crossbar. After using the proposed structural placement, the crossbar module TNS (total negative slack) was decreased from -29 ns to -1.7 ns, the WNS (worst negative slack) was increased from -53 ps to -38 ps, the total DRC errors number was decreased from 7094 to 352 and the total net length of crossbar was decreased from 772076 mm to 442066 mm. And considerable improvement was also achieved to other modules of the design.

Dual-Band ＲF Energy Harvesting System Design

JIN Guiping ZENG Guangde DENG Chuhong

2018, 46(8):  38-45.  doi:10.3969/j.issn.1000-565X.2018.08.006

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In order to absorb and rectify as efficiently as possible the radio frequency energy distributed in the sur- rounding environment，this paper proposes a dual-band ＲF energy harvesting system operating in GSM1800 and UMTS2100 frequency bands． The receiving antenna of this system adopts a planar broadband yagi antenna，which has compact structure，high measured average gain and stable directional radiation pattern in the working frequency bands． In the low input power circumstance from －20 dBm to －5 dBm，the rectifying circuit of this system can achieve good dual-band resonance at 1. 8GHz and 2. 1GHz． The maximum rectification efficiency can reach 45% in －5dBm． Finally，the overall system has been tested in the laboratory and ambience． The results show that the proposed dual-band system can achieve 45% ＲF-DC conversion efficiency in －5 dBm in the laboratory measure- ment，and the proposed system is qualified for harvesting ＲF energy and achieves a certain amount of DC power on the resistance load in ambient environment．

Design of a Power Amplifier with a Folded Proportional Series Combining Transformer

 

WU Haigang LI Bin WU Zhaohui WANG Kun LIU Yang

2018, 46(8):  46-51.  doi:10.3969/j.issn.1000-565X.2018.08.007

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In order to improve the power-added efficiency (PAE) without increasing chip size，a novel power amplifier (PA) with folded proportional series combining transformer used for wireless radio frequency (ＲF) is presented． Due to the cross coupling coefficient introduced by the folded structure，the primary to secondary winding electromagnetic coupling is enhanced，thus the power delivery efficiency is improved． Using the proposed folded proportional combining structure，the power amplifier is designed and implemented in standard 0. 18 μm CMOS process at the operating frequency of 2. 4 GHz． The measurement results show that，with a 2. 5 V power supply， the PA can achieve a peak output power of 28. 3dBm and a maximum linear output power (P1-dB) of 27. 2dBm in high power mode，with PAE of 33. 5% and 31. 6%，respectively，and a P1-dB of 19. 8dBm with PAE of 24. 1% in low power mode． It is demonstrated that the proposed design is suitable for the complicated wireless system with high efficiency and multi modulation requirements． 

Modeling Approach Based on Ｒate-Dependent Hysteresis for Piezoelectric Actuating Mechanism with Load

 

FENG Ying FENG Junjie Subhash Ｒakheja JIANG Hui

2018, 46(8):  52-56，63.  doi:10.3969/j.issn.1000-565X.2018.08.008

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 As a class of smart material-based actuators，piezoelectric actuators have been widely applied in the micro-nano actuating equipment． However，the nonlinearities existing in the smart materials become the main

obstacle for the improvement of actuating precision． Considering the electromechanical characteristics of the piezoelectric actuator，a modeling method is proposed to characterize the input-output relationship of the

piezoelectric actuating system with an external mechanical load in a wide working frequency range． The proposed

model is based on the rate-dependent PrandtlIshlinskii (ＲDPI) hysteresis model and shows an effective way to work around the limitation of ＲDPI hysteresis model，representing the effects analytically caused by the mechanical load with an increase in actuating frequency． With the mechanical load 2. 94N，the experiments for the piezoelectric actuating system are conducted in the frequency range 1 ～80 Hz． Good agreement is found between the mea

sured and predicted input-output curves to show the effectiveness of the proposed modeling method． 

Modeling Approach Based on Ｒate-Dependent Hysteresis for Piezoelectric Actuating Mechanism with Load

FENG Ying FENG Junjie Subhash Rakheja JIANG Hui

2018, 46(8):  57-63.  doi:10.3969/j.issn.1000-565X.2018.08.009

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As a class of smart material-based actuators，piezoelectric actuators have been widely applied in the micro-nano actuating equipment． However，the nonlinearities existing in the smart materials become the main

obstacle for the improvement of actuating precision． Considering the electromechanical characteristics of the piezoelectric actuator，a modeling method is proposed to characterize the input-output relationship of the

piezoelectric actuating system with an external mechanical load in a wide working frequency range． The proposed

model is based on the rate-dependent PrandtlIshlinskii (ＲDPI) hysteresis model and shows an effective way to work around the limitation of ＲDPI hysteresis model，representing the effects analytically caused by the mechanical load with an increase in actuating frequency． With the mechanical load 2. 94N，the experiments for the piezoelectric actuating system are conducted in the frequency range 1 ～80 Hz． Good agreement is found between the mea

sured and predicted input-output curves to show the effectiveness of the proposed modeling method． 

Parameter Identification Method of PMSM Considering Temperature Influence

CAO Xiaohua WEI Heng WANG Xin

2018, 46(8):  64-71.  doi:10.3969/j.issn.1000-565X.2018.08.010

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The accuracy of parameter identification has important influence on the performance and control method of permanent magnet synchronous motor(PMSM). Most of the previous parameter identification methods such as least square method failed to consider the influence of temperature on parameters which lead to low parameter identification accuracy and poor control performance. In this paper, the influence of temperature on PMSM parameters is analyzed by calculation and simulation. It is proved that the temperature has great influence on the parameter identification results. Thus, a parameter identification model of PMSM considering temperature was established, and an improved parameter identification algorithm considering both resistance and inductance with temperature was proposed. Finally, simulation experiments show that this method can improve the speed and accuracy of parameter identification, and reduce the identification error.

Computer Science & Technology

Classification of Benign and Malignant Pulmonary Nodules Based on Radiomics and Random Forests Algorithm

LI Xiangxia LI Bin TIAN Lianfang ZHU Wenbo ZHANG Li

2018, 46(8):  72-80.  doi:10.3969/j.issn.1000-565X.2018.08.011

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Currently, lung cancer is one of the leading causes of morbidity and mortality worldwide. Accurate classification of benign and malignant pulmonary nodules will help the clinicians to accurately diagnose in stages and make the optimal treatment planning in time. To address the low accuracy rate problem for the existing classification algorithms of benign and malignant pulmonary nodules, a classification algorithm based on radiomic feature and random forests model for the classification of benign and malignant pulmonary nodules is proposed in this paper. Firstly, a novel multiscale dot enhancement filter is proposed for pulmonary nodule enhancement. Then, seeds are accurately acquired based on shape index and texture features in enhanced pulmonary nodules, and the acquired seeds are injected into the RW algorithm to accurately segment pulmonary nodules. Secondly, the intensity, texture, shape, wavelet, and clinical features are extracted in the segmented pulmonary nodules. Finally, random forests (RFs) are employed to build the predictive model for classifying benign and malignant pulmonary nodules. The LIDC database is used to train the predictive model. The experiments demonstrate the effectiveness of the proposed algorithm for the classification of benign and malignant pulmonary nodules. The accurate classification results can provide a reference for the clinical diagnosis of lung cancer and a good prognostic value.

Detection of Unlink Attack Based on Symbolic Execution

HUANG Ning HUANG Shuguang LIANG Zhichao

2018, 46(8):  81-87.  doi:10.3969/j.issn.1000-565X.2018.08.012

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Unlink attack is a kind of attack against heap-based overflow vulnerability in Linux. Existed detection technology of the buffer overflow attack find the vulnerability trigger point and generate testcase by checking the control flow state. However, the heap-based overflow data seldom lead to the control flow hijack and the protection mechanisms limit the trigger condition, it is hard to judge the program whether or not the conditions of unlink attack is satisfied through existed detection technology. To improve the security of software, and detect the unlink attack, this paper summarized the features of unlink attack according to analyzing the instances, built the detection model of unlink attack, and proposed the unlink detection method based on the model. This method monitored the input data and sensitive cooperation of program by using taint analysis; built the path constraint of tainted data and data constraint which is satisfied the condition of unlink attack by selective symbolic execution; through solving the constraints above, judged if the program can be attacked by unlink and generated testcase. The experiments showed that this method can detect the unlink attack effectively.

Video Captioning Based on C3D and visual elements

XIAO Huanhou SHI Jinglun

2018, 46(8):  88-95.  doi:10.3969/j.issn.1000-565X.2018.08.013

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With the development of deep learning, the approach that extracts video feature using convolutional neural network (CNNs) and generates sentences using recurrent neural network (RNNs) is widely used in video caption task. However, this direct translation ignores many intrinsic information of video, such as temporal information, motion information, and abundant visual elements information. This paper proposes an AFCF-MVC model that uses the C3D features containing rich spatio-temporal information as the input to our network. At the same time, the adaptive feature extraction algorithm can exploit the whole video information, and the adaptive frame cycle filling algorithm can provide as many features as possible to the network, which plays the role of repeated learning. In addition, in order to make use of the rich visual elements of video, this paper detects the visual elements of video frames by a visual detector, and encode them into the network as additional supplementary information. Experimental results show that the proposed method has achieved the best performance in M-VAD and MPII-MD datasets.

Automatic Cooperation on Behaviors of Components in Pipelining Mechatronic Systems

YU Mincong QI Deyu WANG Xinyang ZHOU Naqin ZHENG Zhishuo GUO Jing

2018, 46(8):  96-106.  doi:10.3969/j.issn.1000-565X.2018.08.014

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The rapid integration and replacement of components in the pipelining mechatronic systems causing the frequent change of code for component behavior cooperation brings in the bottleneck of development process. Dedicated tools demand explicit design on computation or planning states, which means that it is lack of an automation tool towards component behavior cooperation in pipelining mechatronic systems. Using the entity-flow model, this paper addresses the formal descriptions of the material safety processing conditions firstly; secondly, designs a set of action available for planner, in which actions are not only easy to translate to component instructions, but also to indicate the changes of system states; finally, a case of behavior cooperation automatic generation for two components in a bank card personalization machine is illustrated.

Bagging Ensemble Fault Diagnosis Modeling with Imbalanced classification in Wastewater Treatment Plant

XU Yuge LAI Chunling LUO Fei

2018, 46(8):  107-115.  doi:10.3969/j.issn.1000-565X.2018.08.015

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Operation faults in wastewater treatment plant may lead to reduce effluent water quality, raise operation cost and secondary environmental pollution. The representative imbalanced data for fault diagnosis in wastewater treatment process seriously affects the fault diagnosis performance, especially results in the accuracy of faulty classes lower. To address this problem, this paper proposes an improved Bagging ensemble fault diagnosis method based on weighted extreme learning machine in wastewater treatment process. This method establishes the ensemble classifier in Bagging framework, and the weight extreme learning machine algorithm is selected to build the basic classifiers. Defining adjustable over_sampling rate?formula,the diversity of basic classifiers?is?ensured?by?over_sampling?the?minority?data with?SMOTE method.Based on the imbalance classification performance?index?G_mean, a updating formula of the output weight value in the base classifier is defined to improve the recognition accuracy in?faulty?class. Simulation experiments show that the proposed fault diagnosis model over performs the other algorithms. The proposed method can effectively improve G-mean value and overall classification accuracy on fault diagnosis in wastewater treatment process, in particular raise the recognition accuracy in faulty class.

Visual Saliency Attention Based on 2-dimensional Discrete FrFT

XU Haibo SHI Buhai

2018, 46(8):  116-121.  doi:10.3969/j.issn.1000-565X.2018.08.016

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The visual attention model has become the main approach to simulate the human fixation. in order to improve the deficiency of several pre-existing visual attention models, this paper proposes a visual attention model based on 2-dimensional discrete FrFT. First, we model saliency map mathematically in theoretical background of 2-dimenshional FrFT. Second, we analyze several models feature and provide the comparison of simulation results in the noise interference conditions, and Noise Sensitivity Scale (NSS) is proposed. Third, we analyze the Pre-recall and Roc curves using the image database of MSRA 10K, experiments show that the proposed model can simulate human fixation in some extent.

Collaborative Learning of Word and Character Representation

LIU Huiting LING Chao

2018, 46(8):  122-129.  doi:10.3969/j.issn.1000-565X.2018.08.017

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Abstract: Most word embedding models are based on the theory of distribution hypothesis, which take a word as a basic unit and infer word representation from its external contexts. However, in some languages similar to Chinese, a word is built from several characters and these characters contains rich internal information. The semantic of a word is closely related to the semantic of its composing characters. Therefore, this paper take Chinese for example and present two model to collaborative learn word and character representation. In order to solve the phenomenon of homonymy and polysemy, multiple-prototype character embeddings and an word selection method are proposed. We evaluate the proposed models on similarity tasks and analogy tasks. The results demonstrates the proposed models outperform other baseline models.

Physics

Extracting and Modeling of Median-plane Spectral Characteristics

CHENG Hong DENG Huilong XU Shanshan GAO Yaoli WEI Sui

2018, 46(8):  130-133,150.  doi:10.3969/j.issn.1000-565X.2018.08.018

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Head-related transfer functions (HRTFs) reflect the transmission process from sound sources to human ears, and therefore vary with sound source position, individual, and frequency. Aiming to obtain statistically independent information encoded in HRTFs, an extracting and modeling method of median-plane spectral characteristics was proposed on the basis of independent component analyses (ICA). Calculation results indicate that the mean of median-plane spectral distortion gradually decreases with increasing expansion order, and a weighted combination of the preceding six orders components represents the main part of median-plane spectral characteristics. Moreover, a subjective discrimination experiment was carried out. Corresponding results show that no auditory degradation is perceived when the proposed ICA-based median-plane spectral model is used in the elevation range from 45° to ?45°.

Impact of Nonvisual Biological Effects with the Description of the Equivalent Illuminance for LED Lights#br#

2018, 46(8):  134-141.  doi:10.3969/j.issn.1000-565X.2018.08.019

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This paper introduces and applies the concept of equivalent illumination to describe the light sources. Three kinds of white light with different color temperatures and three kinds of color light were selected, using the spectral power distribution and the spectral response curves to calculate respectively five kinds of photoreceptor cells corresponding biological rhythm factor, and calculate the corresponding equivalent illuminance, it is convenient to describe the influence of five photoreceptors on the photobiological effects. The physiological monitoring of blood pressure and heart rate was carried out in six kinds of light environment. The rate of change of physiological data before and after illumination was combined with the theoretical calculation to quantitatively describe the photobiological effect of light source on human body. The results showed that the higher the equivalent illuminance of the third type photoreceptor cells, the higher the change rate of physiological parameters, that is, the corresponding light source can produce stronger stimulation. The correlation coefficients of heart rate change and rhythm factor were all higher than 0.90, and the correlation coefficient of systolic blood pressure and rhythm factor were all higher than 0.88, they have good correlation. Therefore, the rate of heart rate change and systolic blood pressure rate of change can be combined with the biological rhythms reflect the light source of non-visual biological effects intensity.

Phase Retrieval Technology under Multi-angle Tilt Light Modulation

ZHONG Xiaoli LIU Xuejie

2018, 46(8):  142-150.  doi:10.3969/j.issn.1000-565X.2018.08.020

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The non-interferometric phase retrieval technique based on the transport of intensity equation (TIE) is employed to calculate the missing phase information from the intensity measurement. However, since the limiting effect of the lens aperture is existed in the actual imaging system, a certain effect on the resolution of the recovery phase is under consideration. In this paper, the concept of tilted illumination is introduced into the phase retrieval based on the TIE, the modulation function is loaded on the spatially modulated light (SLM), and the plane wave accompanies with various different wave vectors oblique impinging onto an object, then the pass band of the lens aperture cover the frequency spaces with different parts. Summing the fields covered by these shifted passbands yields, and obtain a synthesized field with an enlargened passband, which improve the imaging ability of the system in the field of high frequencies. At the same time, the multi-angle tilt light modulation system based on 4f and single lens is constructed, and the better phase results are obtained by the measured intensity images combined with the TIE. The experimental results show that the proposed method can improve the resolution of recovery phase without compromising the numerical error of the recovery results.