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ISSN 1000-0585
CN 11-1848/P
Started in 1982
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  • Table of Content
      , Volume 57 Issue 1 Previous Issue    Next Issue
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    COMPUTER SCIENCE AND TECHNOLOGY
    Uyghur morphological segmentation with bidirectional GRU neural networks
    ABUDUKELIMU Halidanmu, CHENG Yong, LIU Yang, SUN Maosong
    Journal of Tsinghua University(Science and Technology). 2017, 57 (1): 1-6.   DOI: 10.16511/j.cnki.qhdxxb.2017.21.001
    Abstract   PDF (1041KB) ( 985 )
    Information processing of low-resource, morphologically-rich languages such as Uyghur is critical for addressing the language barrier problem faced by the One Belt and One Road (B&R) program in China. In such languages, individual words encode rich grammatical and semantic information by concatenating morphemes to a root form, which leads to severe data sparsity for language processing. This paper introduces an approach for Uyghur morphological segmentation which divides Uyghur words into sequences of morphemes based on bidirectional gated recurrent unit (GRU) neural networks. The bidirectional GRU exploits the bidirectional context to resolve ambiguities and model long-distance dependencies using the gating mechanism. Tests show that this approach significantly outperforms conditional random fields and unidirectional GRUs. This approach is language-independent and can be applied to all morphologically-rich languages.
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    Hierarchical calibration algorithm using isolated large targets on an HFGW radar antenna array
    XU Zhaohui, WU Jianping, FENG Zhenghe
    Journal of Tsinghua University(Science and Technology). 2017, 57 (1): 7-11.   DOI: 10.16511/j.cnki.qhdxxb.2017.21.002
    Abstract   PDF (1038KB) ( 659 )
    High frequency ground wave(HFGW) radar antenna arrays always have amplitude-phase errors; thus, when the antenna pattern is changed, the clutter cancellation algorithm must be recalibrated. The existing calibration methods include using an auxiliary source, building an array model for parameter estimation, and using the noise or clutter as a calibration source. However, the first method is expensive, the second has poor real-time performance, and the third cannot calibrate the phase error. This paper presents a hierarchical calibration algorithm using isolated large targets. The array is divided into several subarrays with a high SNR target which is unique in the spatial and Doppler domains as the calibration source. Then, the errors in each subarray are calibrated using the improved noise subspace fitting method or the phase difference calibration method to get a uniform error vector by integrated each subarray error vector to calibrate the entire array's amplitude and phase errors. The calibration significantly reduces the amplitude error, phase error and the sidelobe of the antenna pattern. Both theoretical results and tests show that this calibration method greatly improves the accuracy and real-time response than the traditional algorithm.
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    Intra-domain routing protocol OSPF+ for integrated terrestrial and space networks
    XU Mingwei, XIA Anqing, YANG Yuan, WANG Yuliang, SANG Meng
    Journal of Tsinghua University(Science and Technology). 2017, 57 (1): 12-17.   DOI: 10.16511/j.cnki.qhdxxb.2017.21.003
    Abstract   PDF (1233KB) ( 1472 )
    Constructing an integrated terrestrial and space network is one of the key projects in China. Heterogeneous networks can be efficiently integrated using the IP protocol family in space networks to leverage the advantages of the Internet. However, traditional routing techniques cannot be used directly due to the special characteristics of space networks. This paper describes an extended traditional intra-domain routing protocol based on OSPF for network communications in space. The protocol uses topology predictions based on the regular motion of satellites and extends the neighbor state machine to optimize the synchronization of link-state databases to achieve efficient, stable dynamic self-adaptive routing. Simulations show that this protocol has a convergence time of less than 1 second and greater than 98% stability.
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    Spoken term detection based on DTW
    HOU Jingyong, XIE Lei, YANG Peng, XIAO Xiong, LEUNG Cheung-Chi, XU Haihua, WANG Lei, LV Hang, MA Bin, CHNG EngSiong, LI Haizhou
    Journal of Tsinghua University(Science and Technology). 2017, 57 (1): 18-23.   DOI: 10.16511/j.cnki.qhdxxb.2017.21.004
    Abstract   PDF (1189KB) ( 1354 )
    Spoken term detection (STD) for low resource languages has drawn much interest. A partial matching strategy based on phoneme boundaries is presented here to solve the fuzzy matching problem in query-by-example spoken term detection with dynamic time warping. A variety of features were used to validate the strategy on the QUESST 2014 dataset. Tests show that this strategy is not only quite effective for fuzzy match tasks T2 and T3 but also effective for the exact match task T1. This strategy has significantly improved performance in fusion tests.
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    Node security model for wireless sensor networks based on a reputation system and data noise point detection technique
    FU Junsong, LIU Yun
    Journal of Tsinghua University(Science and Technology). 2017, 57 (1): 24-27.   DOI: 10.16511/j.cnki.qhdxxb.2017.21.005
    Abstract   PDF (1030KB) ( 658 )
    The increased number of wireless sensor networks requires security for the sensor nodes. Since traditional information security systems based on cryptography cannot serve the complex safety issues threatening sensor nodes, the reputation system has been introduced into wireless sensor networks to periodically evaluate security nodes and assign reputation values. However, the reputation system cannot always distinguish some abnormal behavior in the sensor nodes, such as the monitoring data accuracy. As a result, some nodes can avoid monitoring by the reputation system which will affect user decisions. This paper presents a wireless sensor network node security model combining the reputation system with data noise detection. The reputation system provides the node reputations to the data noise detection model to more effectively detect data noise. The data noise detection model then feeds information back to the reputation system which accelerates the convergence rate of the reputation system. Simulations show that this node security model can simultaneously detect network and data attacks better than the traditional credit system model with a higher convergence rate.
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    Score regulation based on GMM token ratio similarity for speaker recognition
    YANG Yingchun, DENG Licai
    Journal of Tsinghua University(Science and Technology). 2017, 57 (1): 28-32.   DOI: 10.16511/j.cnki.qhdxxb.2017.21.006
    Abstract   PDF (993KB) ( 710 )
    A GMM token ratio similarity based score regulation approach for speaker recognition is presented in this paper to judge the reliability of a test score based on the GMM token ratio similarity. In the GMM-UBM (universal background model) method, the GMM token which is the index of the UBM component giving the highest score is saved for each frame to form a vector called the GMM token ratio (GTR) of an utterance during the training and testing phases. In the test phase, the test utterance GTR is compared to the training utterance GTR to compute the similarity for a target speaker. When the similarity is less than a threshold, the original likelihood score is regulated by multiplying by a penalty factor as the final score of this test utterance. Tests on MASC show that this method improves the speaker recognition performance.
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    PDF file vulnerability detection
    WEN Weiping, WANG Yongjian, MENG Zheng
    Journal of Tsinghua University(Science and Technology). 2017, 57 (1): 33-38,43.   DOI: 10.16511/j.cnki.qhdxxb.2017.21.007
    Abstract   PDF (1492KB) ( 993 )
    Recent years have seen more network attacks on business organizations and government agencies. Advanced persistent threat (APT) attacks are one key example. Malicious PDF files are an important carrier for APT attacks, which complete the attack process by executing malicious code embedded in the file. The security vulnerabilities in PDF files and the key codes in PDF vulnerabilities (such as the ROP chain) are detected to block the propagation path of the PDF malicious code at the root to better deal with the diverse malicious PDF codes. This paper introduces the principle and analysis method for identifying PDF file format vulnerabilities. The vulnerability detection rules are defined with a PDF vulnerability detection method combined with a PDF vulnerability analysis based on rule matching. Next this paper describes the principles of the ROP method and analyzes the ROP chain detection method. Finally, this paper compares this vulnerability detection system with Symantec and BitDefender. The results show that this system more effectively detects vulnerabilities than similar products.
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    Behavior measurement scheme for the wireless sensor network nodes
    ZHOU Caiqiu, YANG Yuwang, WANG Yongjian
    Journal of Tsinghua University(Science and Technology). 2017, 57 (1): 39-43.   DOI: 10.16511/j.cnki.qhdxxb.2017.21.008
    Abstract   PDF (1081KB) ( 706 )
    The development of electronic information systems has led to many more wireless sensor networks. However, traditional security systems cannot be directly applied to wireless sensor networks, so the sensor nodes are vulnerable to malicious attacks. This paper presents a node behavior measurement mechanism for wireless sensor networks using different metric mechanisms for different computing nodes with real-time measurements and active control features. Simulations show that this method monitors the energy consumption of the wireless sensor nodes to identify malicious nodes while better adaptability to the environment to make the sensor network run smoothly when some nodes attack.
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    Android malware detection based on the system power consumption
    YANG Hongyu, TANG Ruiwen
    Journal of Tsinghua University(Science and Technology). 2017, 57 (1): 44-49.   DOI: 10.16511/j.cnki.qhdxxb.2017.21.009
    Abstract   PDF (1417KB) ( 608 )
    The power consumption sequential waveform of an Android application while running is similar to the acoustic signal. This paper presents a malware detection algorithm based on the Mel frequency cepstral coefficients (MFCC). The algorithm calculates the MFCC of the power consumption sequential waveform and constructs a Gaussian mixture model (GMM) from the MFCC distribution. Then, the GMM is used to analyze power consumption to identify malicious software through the application classification process. Tests show that the application software functionality and power consumption are closely related and that the software-based power consumption information analysis can accurately detect mobile terminal malware.
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    Security analysis of industrial control network protocols based on Peach
    YI Shengwei, ZHANG Chongbin, XIE Feng, XIONG Qi, XIANG Chong, LIANG Lulu
    Journal of Tsinghua University(Science and Technology). 2017, 57 (1): 50-54.   DOI: 10.16511/j.cnki.qhdxxb.2017.21.010
    Abstract   PDF (1217KB) ( 1614 )
    Fuzzing tests are important for discovery of unknown vulnerabilities and risks. A security analysis method was developed for industrial control networks using the Peach fuzzing framework. The system uses the mutation strategy by fabricating abnormal network packets, sending these packets to the target and then executing tests. The tests monitor the status of the industrial control network protocols. The system then identifies exceptions in the industrial control network protocols. Modbus TCP, a widely used industrial control network protocol is analyzed as an example using a fuzzy Modbus TCP protocol. The results show that this method can effectively identify vulnerabilities in industrial control network protocols.
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    AEROSPACE AND ENGINEERING MECHANICS
    TDRSS traffic model based on time and spatial characteristics
    WANG Lei, KUANG Linling, HUANG Huiming
    Journal of Tsinghua University(Science and Technology). 2017, 57 (1): 55-60,66.   DOI: 10.16511/j.cnki.qhdxxb.2017.21.011
    Abstract   PDF (1100KB) ( 516 )
    Analysis and modeling of the traffic characteristics in tracking and data relay satellite systems (TDRSS) are the key to improving the system scheduling performance. A parametric model was developed to unify the system multi-type traffic representation based on a scheduling principle and actual TDRSS operating data. The system can describe the traffic time and spatial characteristics. The antenna pointing angle is used as the mission's space related variable to improve the time sequence constraint of consecutive missions and the time and spatial accuracies that are rarely considered in conventional traffic models. The model validity is verified through analysis of NASA TDRSS traffic data and numerical simulations. The results show that the average scheduling success rate is 10.65% better than the conventional model, while the average antenna resource consumption is reduced by 12.85%, which effectively improves the TDRSS efficiency.
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    ELECTRONIC ENGINEERING
    Timing tracking methods in millimeter-wave wireless communications
    NIU Yong, FENG Ziqi, LI Yong, JIN Depeng, SU Li
    Journal of Tsinghua University(Science and Technology). 2017, 57 (1): 61-66.   DOI: 10.16511/j.cnki.qhdxxb.2017.21.012
    Abstract   PDF (1173KB) ( 999 )
    The timing tracking of millimeter-wave wireless communications is very challenging since the analog to digital converters (ADCs) cannot provide high oversampling on the received signals and the multi-path channel causes tracking problems. Two timing tracking schemes based on twice over-sampled data and the waveform of the correlation values using Farrow interpolation are described in this paper for multi-path channels. The first scheme compensates for the timing error before channel equalization while the other compensates afterwards. Simulations show that with a timing error of 20×10-6 and a bit error rate (BER) of 10-5, the difference in the signal-to-noise ratios (SNRs) between these two systems and a system with no timing error is about 2.5 dB less than with the Rummler channel. Thus, both schemes provide good timing tracking for multi-path channels.
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    Energy efficient coordinated transmission scheme for multi-cell distributed antenna systems
    WANG Jing, WANG Yanmin, FENG Wei, XIAO Limin, ZHOU Shidong
    Journal of Tsinghua University(Science and Technology). 2017, 57 (1): 67-71.   DOI: 10.16511/j.cnki.qhdxxb.2017.21.013
    Abstract   PDF (1014KB) ( 568 )
    The energy efficiency of coordinated transmissions in multi-cell distributed antenna systems (DAS) was analyzed with a focus on the antenna element correlation within each distributed antenna cluster to maximize the system energy efficiency through inter-cell coordinated optimization of the input covariance matrices. The system uses only the slowly varying channel statistics including the large-scale channel state information at the transmitter and the transmit antenna element correlation characteristics. The optimization problem is non-convex and, therefore, is hard to solve. The method of successive Taylor expansions was used to recast the problem into a succession of quasi-convex fractional optimization sub-problems, which were then further converted to tractable equivalent convex forms via the fractional programming approach. An iterative scheme was then used to address the original optimization problem. Simulations show that this scheme provides improved system energy efficiencies compared to existing schemes.
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    Image salient region detection based on boundary expansion
    LIU Jie, WANG Shengjin
    Journal of Tsinghua University(Science and Technology). 2017, 57 (1): 72-78.   DOI: 10.16511/j.cnki.qhdxxb.2017.21.014
    Abstract   PDF (1890KB) ( 645 )
    Background priors have been shown to improve salient region detection. Typically, image boundary patches are assumed to be the background and the saliency of other patches is defined by their difference from the boundaries. A greater difference indicates a more salient patch. However, when the background is cluttered, or the foreground overlaps the image boundary, using only boundary patches to indicate the background may lead to a saliency map with strong noise and compromise the detection accuracy. To address this problem, the boundary patches are first expanded here into the image interior to contain as much background as possible. Then, the rest of the patches are used as foreground queries with the saliency of each patch measured by a two-stage ranking algorithm. Tests on three large public datasets demonstrate the superiority of this method over five other algorithms.
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    Overlapping speech detection using high-level information features
    MA Yong, BAO Changchun
    Journal of Tsinghua University(Science and Technology). 2017, 57 (1): 79-83.   DOI: 10.16511/j.cnki.qhdxxb.2017.21.015
    Abstract   PDF (1217KB) ( 701 )
    Overlapping speech is one of the main factors influencing the performance of speaker segmentation. This paper presents an overlapping speech detection method using a high-level information feature to improve the speaker segmentation results. A linguistic high-level information feature of the speech is extracted using the universal background model (UBM). Then, a hidden Markov model (HMM) is trained using the Mel frequency cepstral coefficients (MFCC) and the high-level information to detect overlapping speech. The result is then used for the speaker segmentation of the pre-processed speech. Tests on a dataset generated from the TIMIT database show that the error ratio for overlapping speech detection is significantly lower than the reference method using just the MFCC feature. The speaker segmentation is also significantly improved.
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    Single-channel speech separation with non-negative matrix factorization and factorial conditional random fields
    LI Xu, TU Ming, WU Chao, GUO Yanmeng, NA Yueyue, FU Qiang, YAN Yonghong
    Journal of Tsinghua University(Science and Technology). 2017, 57 (1): 84-88.   DOI: 10.16511/j.cnki.qhdxxb.2017.21.016
    Abstract   PDF (1055KB) ( 705 )
    Non-negative matrix factorization (NMF) has been extensively used for single channel speech separation. However, a typical issue with the standard NMF based methods is that they assume the independency of each time frame of the speech signal and, thus, cannot model the temporal continuity of the speech signal. This paper presents an algorithm for single-channel speech separation based on NMF and the factorial conditional random field (FCRF) method. A model is developed by combining NMF with the k-means clustering method. This model can concurrently describe the spectral structure and the temporal continuity of the speech signal. Then, the model is used to train the FCRF model, which is used to separate the mixed speech signal. Tests show that this algorithm consistently improves the separation performance compared with the active-set Newton algorithm, an NMF based approach that dose not consider the temporal dynamics of the speech signal.
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    ELECTRICAL ENGINEERING
    Analyses of permanent magnet DC motor stator vibrations
    CAO Haixiang, SHEN Jingwen, WANG Shanming, MU Jianan, YANG Zhanlu, HONG Jianfeng
    Journal of Tsinghua University(Science and Technology). 2017, 57 (1): 89-94,99.   DOI: 10.16511/j.cnki.qhdxxb.2017.21.017
    Abstract   PDF (1506KB) ( 1050 )
    Stator vibrations in permanent magnet DC motors have distinct characteristics which are also useful for analyzing other types of motors. The magnetic fields and the electromagnetic forces in permanent magnet DC motors were analyzed to characterize the physical mechanisms driving the vibrations. The order of the slot-frequency electromagnetic exciting force is not equal to the spatial order of the stator slot-frequency vibration shape. Accurate analyses of the vibrations inputs the magnetic field and electromagnetic force distributions calculated by finite element simulations into a structural finite element simulation to predict the stator vibrations. Experiments must have enough sensors to obtain the vibration mode shape. The predictions agree well with data from DC motor tests.
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    AUTO MATION
    Improved pitch extraction algorithm for speech processing
    CHEN Xiao, XU Bo
    Journal of Tsinghua University(Science and Technology). 2017, 57 (1): 95-99.   DOI: 10.16511/j.cnki.qhdxxb.2017.21.018
    Abstract   PDF (992KB) ( 764 )
    This paper presents an improved pitch extraction algorithm based on an auto-correlation function for speech processing. The original auto-correlation function algorithm is optimized by increasing the weights of the right pitch values by the texture feature, enlarging the search space by using more candidate pitch values, and restricting the search path to reliable pitch values. These three measures control the weight and proportion of the right pitch values in the search space and then optimize the search space. The algorithm was evaluated on the Keele and FDA databases. The results show that the voiced error is reduced by 28.74% and the pitch tract error is reduced by 5.53% relative to the original algorithm. Thus, this algorithm is more suitable for speech processing.
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    Modeling and empirical analyses of parking space choices based on individual preferences
    LIANG Wei, HU Jianming, ZHANG Yi, ZHANG Zuo, WANG Ziwei
    Journal of Tsinghua University(Science and Technology). 2017, 57 (1): 100-106.   DOI: 10.16511/j.cnki.qhdxxb.2017.21.019
    Abstract   PDF (1864KB) ( 812 )
    A parking space choice model based on personal preferences was developed for large parking lots to analyze the utility of parking spaces in shopping mall parking lots. The driver's behaviorial characteristics when parking are analyzed based on personal preferences which are assigned into three groups (inherence, skill and affordability) using a multinomial Logit model to analyze the impacts of the preferences on parking choices. A parking choice utility model with multiple variants based on personal preferences was then used to study driver behavior in the parking lot of the Beijing IKEA store. The results show that skill preferences have the most significant impact on the parking space choice. This model can accurately evaluate driver behavior when choosing the parking spaces.
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    Experimental modeling of micro turbine engine propulsion systems
    LI Yingjie, LI Huanyu, WU Linfeng, LI Chunwen
    Journal of Tsinghua University(Science and Technology). 2017, 57 (1): 107-112.   DOI: 10.16511/j.cnki.qhdxxb.2017.21.020
    Abstract   PDF (4742KB) ( 818 )
    The development of advanced fighters requires test flights on sub-scaled demonstrators. A sub-scaled fighter usually uses a micro turbine engine as the propulsion system which requires a mathematical model of the engine. Data from ground tests of a micro turbine engine was correlated to develop a signal-rotational speed model and a rotational speed-thrust model using the Wiener models along with the least square method. The models were validated to lay the foundation for further research on the control of the micro turbine engine and control methods for the sub-scale demonstrator.
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