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百年期刊
ISSN 1000-0585
CN 11-1848/P
Started in 1982
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, Volume 57 Issue 10
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COMPUTER SCIENCE AND TECHNOLOGY
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Secret key generation strategy based on broadband channel state information
LI Tao, LUAN Fengyu, ZHOU Shidong
Journal of Tsinghua University(Science and Technology). 2017,
57
(10): 1009-1013. DOI: 10.16511/j.cnki.qhdxxb.2017.25.038
Abstract
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The channel information for a large number of frequency points in broadband communication systems can be used as a random source to generate secret keys, thereby, enhancing system security. However, there is a limited number of multipaths in the scattering and there is a correlation between different frequency points. Thus, for the condition that the total transmission power is limited, the power allocation strategy for different frequency points will affect the secret key security. A power allocation model is given with the key generation rate as a measure of the security that maximizes the key generation rate. The model is solved with the Lagrange multiplier method. A suboptimal power allocation method is given to reduce the calculation complexity that compares with the optimal solution with the sequential quadratic programming (SQP) algorithm. Numerical tests show that the security with the suboptimal power allocation strategy is quite close to the security with the SQP algorithm which is considered to be the optimal strategy.
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Hybrid recommendation approach enhanced by deep learning
ZHANG Min, DING Biyuan, MA Weizhi, TAN Yunzhi, LIU Yiqun, MA Shaoping
Journal of Tsinghua University(Science and Technology). 2017,
57
(10): 1014-1021. DOI: 10.16511/j.cnki.qhdxxb.2017.25.039
Abstract
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Collaborative filtering based on matrix factorization has been very successful, while cold-start and data sparseness problems have not been well resolved. Hence, many studies have attempted to include review information into rating predictions. This paper presents a hybrid model that introduces deep learning into recommendation system with collaborative filtering. The algorithm combines a stacked denoising auto encoder (SDAE) with a latent factor model (LFM) to make use of both review and rating information to improve the rating predictions. Evaluations on a large, commonly used Amazon dataset show that this approach significantly improves the rating prediction accuracy in comparison with traditional models, with up to 64.43% better predictions.
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Detect use-after-free vulnerabilities in binaries
HAN Xinhui, WEI Shuang, YE Jiayi, ZHANG Chao, YE Zhiyuan
Journal of Tsinghua University(Science and Technology). 2017,
57
(10): 1022-1029. DOI: 10.16511/j.cnki.qhdxxb.2017.25.040
Abstract
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Use-after-free (UaF) vulnerabilities are one of the most common and risky memory corruption vulnerabilities. However, UaF vulnerabilities are difficult to detect. A UaF vulnerability is triggered if and only if three operations occur on the same memory region, in an order of allocating memory, freeing memory, and using the freed memory. These three operations may be conducted anywhere in the program in any order, so the analysis must track a long execution sequence and search for potential vulnerable event sequences to detect UaF vulnerabilities. This study analyzes the root causes of UaF vulnerabilities, ways to exploit them, the severity of the threat and the challenges in detecting them. A solution is then given based on a static analysis and dynamic symbolic execution to detect UaF vulnerabilities in binaries. Tests show that this solution can detect known vulnerabilities in a benchmark. Thus, this detection system can be used to identify and fix bugs to improve application security.
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Parallel incremental dynamic community detection algorithm based on Spark
WU Bin, XIAO Yan, ZHANG Yunlei
Journal of Tsinghua University(Science and Technology). 2017,
57
(10): 1030-1037. DOI: 10.16511/j.cnki.qhdxxb.2017.25.041
Abstract
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Dynamic community detection is a crucial step in researching network evolution. Nonparallel algorithms cannot efficiently mine community structures with large amounts of data. This paper presents a parallel incremental dynamic community detection algorithm based on Spark (PIDCDS), which maximizes the total permanence of the vertices in the network to discover the community structure. PIDCDS uses parallel computations on GraphX to calculate a specialized permanence as the community partition metric. Only the permanence of the incremental vertices is computed in each step to derive a new community structure. This algorithm is accurate with less computations. PIDCDS has better stability and more accurately detects the community structure than the FacetNet algorithm. PIDCDS performs well and the execution time increases only slowly as the network scale increases. More cores will accelerate PIDCDS to some extent.
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Weighted phone log-likelihood ratio feature for spoken language recognition
ZHANG Jian, XU Jie, BAO Xiuguo, ZHOU Ruohua, YAN Yonghong
Journal of Tsinghua University(Science and Technology). 2017,
57
(10): 1038-1041,1047. DOI: 10.16511/j.cnki.qhdxxb.2017.25.042
Abstract
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The extraction of linguistic discriminative features is one of the fundamental issues in spoken language recognition (SLR). The frame level phone log-likelihood ratio (PLLR) has been recently introduced to improve language recognition. In this paper, the
F
-ratio analysis method is used to analyze the contributions of different SLR feature vector dimensions. Then, a weighted phone log-likelihood ratio (WPLLR) feature is used to more heavily weight those dimensions with high
F
-ratio values. Tests on the National Institute of Standards and Technology (NIST) 2007 dataset for SLR show the effectiveness of this feature, with significant relative improvements in the average cost performance and equal error rate compared with the PLLR feature.
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Global optimization to recognize causal relations between events
LI Peifeng, HUANG Yilong, ZHU Qiaoming
Journal of Tsinghua University(Science and Technology). 2017,
57
(10): 1042-1047. DOI: 10.16511/j.cnki.qhdxxb.2017.25.043
Abstract
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Classifier-based models are widely used to identify causal relations between events. However, these models only consider the relationship between two specified events while ignoring related events. Thus, the results may have many logical contradictions. This paper presents a global optimization approach to recognize causal relations between events using an inference method based on integer linear programming (ILP). This approach introduces various kinds of constraints, i.e., a basic logical relationship, causal signal words, event types and argument information constraints to improve the performance. Tests on an annotated corpus show that this global optimization approach improves the
F
1 score by 5.54% compared with a classifier-based model.
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Cooperative dynamic data possession scheme across a cloud storage environment
CAO Laicheng, HE Wenwen, LIU Yufei, GUO Xian, FENG Tao
Journal of Tsinghua University(Science and Technology). 2017,
57
(10): 1048-1055. DOI: 10.16511/j.cnki.qhdxxb.2017.25.044
Abstract
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User data integrity across cloud storage can be verified by a cooperative dynamic data possession (CDDP) scheme presented here. A layered Hash index is used to aggregate the response messages of the cloud storage service providers into one message with the communications among the cloud service providers, the organizer and a trusted third party used to verify the data possession. Dynamic updates of the user data, such as data modifications, data insertions, and data deletions, only require updating of the index records and the data block tags in the index-Hash table. This scheme reduces the computation times and resists forgery attacks.
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Fast Nash bargaining algorithm for resource scheduling problems with a large number of media streaming channels
LIU Yang, WEI Wei
Journal of Tsinghua University(Science and Technology). 2017,
57
(10): 1056-1062. DOI: 10.16511/j.cnki.qhdxxb.2017.25.045
Abstract
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The servers in large media streaming systems need to handle a large number of requests from all around the world. However, due to the increasing dynamic media content and because existing cloud-based architectures cannot provide enough benefits, the service provider needs to utilize a hybrid architecture composed of a content delivery network with private and cloud data centers to provide sufficient quality of service while reducing costs. This paper describes a general resource scheduling problem for this scenario for a hybrid cloud, which is then transformed into a Nash bargaining problem. A fast Nash bargaining algorithm is given based on a geometrical perspective of the problem. Tests show that the algorithm improves the quality of service and reduces expenses by about 40% compared with a traditional hybrid architecture, so it can effectively handle large amounts of dynamic media content.
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CIVIL ENGINEERING
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Damage evaluation and seismological mechanism of frostquakes
ZHOU Meng, FAN Jiansheng, NIE Jianguo
Journal of Tsinghua University(Science and Technology). 2017,
57
(10): 1063-1069. DOI: 10.16511/j.cnki.qhdxxb.2017.25.046
Abstract
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(2294KB) (
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The frostquake is a new kind of natural hazard. It shares similar phenomena with the precursory events of large destructive earthquakes. This has caused wide panic of the damage that frostquakes may bring about, and hence placed increasing importance on damage evaluation for the frostquake. However, no scientific theory has been developed for mechanism explanation and quantitative damage evaluation of frostquakes in previous studies. An amount of Chinese reports even confound the frostquake with the icequake. In this paper, a series of available frostquake reports in the literature have been reviewed and discussed. Based on this review, the maximum intensity and highest peak ground acceleration (PGA) level of the frostquake is evaluated by adopting the elastic deformation assumption and conservation of energy assumption. The proposed theory predicts that the possibly maximum intensity of the frostquake is VI modified Mercalli intensity and its possibly highest PGA exhibits lower that 10 percent of that of earthquake elcentro-NS, which is a typical tectonic destructive earthquake. It is concluded that the frostquake effect may cause crack opening but no destructive damage in general reinforced concrete civil facilities.
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China's carbon emissions peak path-based on China TIMES model
MA Ding, CHEN Wenying
Journal of Tsinghua University(Science and Technology). 2017,
57
(10): 1070-1075. DOI: 10.16511/j.cnki.qhdxxb.2017.25.047
Abstract
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In this study, an integrated carbon emission peak path model system was built based on China TIMES model, and was used to analyze China's carbon emissions peak and peak path. The results show that China's carbon emissions will maintain rapid growth in the reference scenario between 2010-2050, and give enormous pressure on China's energy security and addressing climate change; in emission peak scenarios, through the development of non-fossil energy and the adoption of energy-conservation and emission-reduction measures, carbon-intensive sectors (power and industry sectors) can achieve early emissions peak and guarantee the overall carbon emissions peak between 10.0-10.8 billion t; power sector and energy-intensive sectors are the main carbon mitigation sectors, the contribution of carbon mitigation are 75% and 15%, respectively. In addition, adopting non-fossil energy and the energy-efficient technologies are main carbon mitigation measures, and the contribution of carbon mitigation are 65% and 15%, respectively.
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The mode and process of BIM-aided construction management
GUO Hongling, PAN Zaiyi
Journal of Tsinghua University(Science and Technology). 2017,
57
(10): 1076-1082. DOI: 10.16511/j.cnki.qhdxxb.2017.25.048
Abstract
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BIM (building information modeling) is a promising approach for improving the efficiency of the construction industry, but it is mainly used in the planning and design of construction projects, with less use during construction. Although some research has been done to promote BIM during construction, most research has focused on the development of BIM methods with little work on the management and organization needed to implement BIM. This paper describes how to efficiently implement BIM during the construction phase by analyzing problems related to traditional construction management approaches. A conceptual framework is given for a BIM-aided construction management platform, which consists of a simulated BIM system and a real-time BIM system to further promote system implementation. This research will benefit application of BIM during the construction phase, as well as a comprehensive information management system.
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Theoretical and empirical research on urban housing investment in China
WU Jing, GUO Wei
Journal of Tsinghua University(Science and Technology). 2017,
57
(10): 1083-1088. DOI: 10.16511/j.cnki.qhdxxb.2017.25.049
Abstract
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The growth rate of housing investment in China has been significantly lower in recent years, so there is great interest in the cause and in future trends. This paper provides both theoretical and empirical analyses of the housing investment trends in urban China, focusing on the well-known indicator of the share of housing investment as a percentage of the total output (SHTO). Theoretical analyses based on the Cobb-Douglas production function and empirical analyses based on panel data from 287 cities between 2002 and 2012 indicate that the so-called "SHTO curve" also works in Chinese cities, which implies that SHTO would first increase with economic development and then decrease after some threshold. Further analyses suggest that the threshold in the SHTO curve is determined by the relative scarcity of land and capital. The results also suggest most of the Chinese cities are approaching, or have even passed, their thresholds in the SHTO curve. The results imply that further declines of the growth rate or even the absolute volume of housing investment in most Chinese cities is inevitable, so China's real estate market needs a new development model.
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AUTOMATION
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Quantum process tomography based on distributed compressed sensing
YUAN Xiaohu, WU Rebin, LI Chunwen
Journal of Tsinghua University(Science and Technology). 2017,
57
(10): 1089-1095. DOI: 10.16511/j.cnki.qhdxxb.2017.25.050
Abstract
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Quantum process tomography (QPT) is one of the foundations of quantum information science research, but the required experimental resources during QPT grow exponentially with the number of qubits. Recently, a compressed sensing QPT (CSQPT) was proposed that significantly reduces the required resources and the post-processing time based on the sparseness of the process matrix. However, the quantum channel analysis needs to simultaneously identify a variety of quantum gates and there are always outliers during the QPT process. This paper describes a distributed compressed sensing quantum process tomography (DCSQPT) method to identify the multi quantum channel tomography while effectively attenuating outliers through collaborative sparse learning. Simulations show that this method is robust to outlier data and accurately reconstructs the process matrix compared to the compressed sensing QPT method while significantly improving the quantum process tomography identification speed.
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ENVIRONMENTAL SCIENCE AND ENGINEERING
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Clustering algorithm for burst detection in water distribution systems
LIU Shuming, WU Yipeng, WANG Xiaoting, LIU Youfei, LI Jiajie
Journal of Tsinghua University(Science and Technology). 2017,
57
(10): 1096-1101. DOI: 10.16511/j.cnki.qhdxxb.2017.25.051
Abstract
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693
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Pipe bursts are a universal problem in water supply systems, which can severely disrupt daily life and urban development. This study correlates flow measurements collected from inlets and outlets of a district metering area (DMA) to quickly identify bursts. The analysis uses a clustering algorithm to detect abnormal flow data i.e., outliers. Then, some outliers are identified as bursts according to the inlet and outlet flow fluctuation characteristics. The results indicate that the number and locations of the inlets and outlets affect the detection performance. The system can accurately detect bursts and insure a low false positive rate when there are a relatively small number of inlets and outlets and the locations are well placed.
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BIOLOGY AND BIOMEDICAL ENGINEERING
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Simulation of the optical stimulation mechanism of cochlear nerves
GUAN Tian, YANG Muqun, WEI Zikun, JIANG Yucheng, WANG Jian
Journal of Tsinghua University(Science and Technology). 2017,
57
(10): 1102-1105. DOI: 10.16511/j.cnki.qhdxxb.2017.25.052
Abstract
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546
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There has been much research in recent years on pulsed laser stimulation to evoke auditory nerve responses. However, the mechanism is not yet fully understood. This paper describes use of the simulation software COMSOL Multiphysics to build a three-dimensional model to study both the photoacoustic and photo-thermal effect induced by the pulsed laser stimulation of the cochlea, combined with in vivo experiments on guinea pigs to analyze the mechanism. The simulations show that pulsed lasers cause a temperature rise, but also trigger a photoacoustic effect with the compound action potentials induced in guinea pigs deafened acutely by drugs. The results demonstrate that the response from optical stimulation is more likely the superposition of photoacoustic and photo-thermal effects.
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AUTOMOTIVE ENGINEERING
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Simulation and experimental demonstration of a seamless two-speed automatic mechanical transmission for electric vehicles
NGUYEN Truong Sinh, SONG Jian, FANG Shengnan, SONG Haijun, TAI Yuzhuo, LI Fei
Journal of Tsinghua University(Science and Technology). 2017,
57
(10): 1106-1113. DOI: 10.16511/j.cnki.qhdxxb.2017.25.053
Abstract
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(3173KB) (
809
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This paper describes a two-speed automatic mechanical transmission (AMT) for an efficient, uninterrupted powertrain for electric vehicles. This paper describes the transmission structure, which consists of a single planetary gear system, a disk friction clutch and a drum brake that allows seamless shifting between two gears. A dynamic model is given for a front drive wheel powertrain system in an electric vehicle in a MATLAB/Simulink environment that is more suitable for real-time simulations for designing the transmission. A real-time dynamic transmission test bench was setup with a hardware-in-the-loop simulation platform. The simulation and test results indicate that the power interrupt during shifting is eliminated and the transmission significantly improves the electric motor efficiency as well as the vehicle dynamics and energy consumption.
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NUCLEAR ENERGY AND NEW ENERGY
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Thermodynamic analysis and optimization of helium turbine cycle of commercial high temperature gas-cooled reactor
QU Xinhe, YANG Xiaoyong, WANG Jie
Journal of Tsinghua University(Science and Technology). 2017,
57
(10): 1114-1120. DOI: 10.16511/j.cnki.qhdxxb.2017.25.054
Abstract
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With gradual increase in reactor outlet temperature, the efficient power conversion technology has become one of developing trends of (very) high temperature gas-cooled reactor. Based on the HTR-10, HTR-10GT and HTR-PM, aiming at a higher reactor outlet temperature (ROT), the paper analyzes, optimizes and designs the thermodynamic parameters of the helium turbine cycle of high temperature gas-cooled reactor. Two proposed operating points are determined by the optimization model combined with the constrints of engineering experience. One of these working points is close to the current engineering experiences, inherited the design experience of the helium compressor and turbine of the HTR-10GT. Its ROT is 850℃, the cycle pressure ratio is 2.47, and the cycle efficiency is 47.60%. Another working point is slightly forward-looking. Its ROT is 900℃, the reactor inlet temperature is 550℃, the cycle pressure ratio is 2.75, and the cycle efficiency is 48.92%. And based on these two working points the HTGR helium cycle parameters have been designed. It would be helpful to develop a closed Brayton cycle coupled with a high temperature reactor in the future.
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