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百年期刊
ISSN 1000-0585
CN 11-1848/P
Started in 1982
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Table of Content
, Volume 56 Issue 7
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AUTO MATION
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Fast entire-flight-phase trajectory predictions
ZOU Xiang, CHENG Peng, CHENG Nong
Journal of Tsinghua University(Science and Technology). 2016,
56
(7): 685-691. DOI: 10.16511/j.cnki.qhdxxb.2016.21.038
Abstract
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This paper presents a fast flight 4-D trajectory projection approach for air traffic management based on a navigation database and flight plans. The system predicts the 4-D trajectory of the entire flight phase from the departure runway to the arrival runway for civilian flights. The approach uses a mass point model to speed up the projections, designs transitions between two inexactly defined legs that ensures continuity, conforms to the speed and altitude constraints of terminal procedures to guarantee the fidelity of the generated trajectories, and uses geometric calculations based on the WGS-84 geodesic system to improve the accuracy. Tests of routes from the Beijing Capital airport to the Shanghai Hongqiao airport show the efficiency of this approach.
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ELECTRONIC ENGINEERING
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Resource optimization with large-scale channel state information for spectrum sharing systems
ZHAO Juntao, FENG Wei, ZHAO Ming, WANG Jing
Journal of Tsinghua University(Science and Technology). 2016,
56
(7): 692-695. DOI: 10.16511/j.cnki.qhdxxb.2016.21.028
Abstract
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In a distributed antenna-based spectrum sharing system (DSSS), both the channel allocation and the antenna selection are important issues for enhancing system performance. The system overhead can be controlled by a joint channel allocation and antenna selection scheme presented here that is based on only the large-scale channel state information. Particularly, the sum rate of the secondary users (SUs) is used as the optimization objective to formulate the optimization problem. The integer programming problem is transformed into a linear programming problem through variable relaxation to reduce the complexity. Simulations show that the system sum rate is significantly improved using only the large-scale channel state information. In practical applications where the system overhead is strictly limited, this scheme offers an effective way to balance the system overhead and performance gain.
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Optimizing power consumption in distributed antenna systems with large-scale CSIT
WANG Jing, WANG Yanmin, FENG Wei, XIAO Limin, ZHOU Shidong
Journal of Tsinghua University(Science and Technology). 2016,
56
(7): 696-699,706. DOI: 10.16511/j.cnki.qhdxxb.2016.21.039
Abstract
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The power consumption in distributed antenna systems (DAS) is reduced for green mobile communications by optimizing the total power consumption in downlink DAS with only large-scale channel state information at the transmitter (CSIT) using a practical power consumption model including both the transmission power and the circuit power. The scheme combines transmit antenna selection and power allocation, decomposes the original problem into a series of sub-problems, each of which can be solved by efficient algorithms. The result is a low-complexity joint ordering selection and power allocation algorithm. Simulations show that the total power consumption is reduced considerably by this algorithm while satisfying the ergodic capacity requirements of the users. Thus, this scheme provides practical performance enhancement for DAS with low system overhead.
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CHEMISTRY AND CHEMICAL ENGINEERING
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Simultaneous optimization of the feed location and thermodynamic feed conditions for a distillation column based on column grand composite curves
LIU Xuegang, ZHANG Bingjian, CHEN Qinglin
Journal of Tsinghua University(Science and Technology). 2016,
56
(7): 700-706. DOI: 10.16511/j.cnki.qhdxxb.2016.24.020
Abstract
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The study used the column grand composite curve (CGCC) method to simultaneously optimize the feed location and feed conditions for a distillation column to reduce the total utility costs. The CGCC method based on the near-minimum thermodynamic condition (PNMTC) can be decomposed into two theoretical curves for the overall rectifying and overall stripping curves. The intersection point
O
of the two theoretical curves is not only the ideal feed point, but also the partitioning point for the amount of feed preheating. The total cost of the cold and hot utilities is used as the objective function to optimize the feed preheating and to identify the intersection point location
O
. The optimal feed location in the distillation column is then found using the enthalpy difference, Δ
H
n
, def
, between the intersection point and the actual feed point. The feed location and the feed conditions are then optimized using the CGCC curves. A benzene and toluene column was used to evaluate the accuracy of this graphic method. The maximum savings for the cold and hot utilities is about 1.24 RMB/h. The feed preheating is 1.98 MW and the enthalpy difference, Δ
H
n
, def
, is 0.038 MW. The optimal feed location is the 21
th
stage. The CGCC results compare well with Aspen Plus results with differences only 1%-3%.
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Temperature control of an acrylonitrile polymerization kettle using multiple models with second level adaptation
WANG Zhenlei, MAO Fuxing, WANG Xin
Journal of Tsinghua University(Science and Technology). 2016,
56
(7): 707-716. DOI: 10.16511/j.cnki.qhdxxb.2016.24.023
Abstract
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A generalized predictive control method was developed from multiple models with second level adaptation for temperature control the acrylonitrile polymerization process which has long time delays and large parameter uncertainties. Several adaptive models are designed for the system parameter ranges with the parameters estimated by a recursive least squares algorithm. Then, the model weights are calculated based on the parameter estimates and the prediction error of each model. Then, the parameter estimates are used as the true values of the parameters to determine the control action via the generalized predictive control algorithm. Simulation results show that this method enables a system with unknown parameters to quickly converge to the true value. The system performance of the system and the tracking accuracy of the ideal temperature are significantly improved compared with conventional multiple model adaptive control.
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Optimization of a hydrogen network with consideration of the energy consumption for purification
LIU Guilian, WANG Yingjia
Journal of Tsinghua University(Science and Technology). 2016,
56
(7): 717-722. DOI: 10.16511/j.cnki.qhdxxb.2016.24.019
Abstract
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Increasing stringent environmental regulations and the increased processing of inferior crude oils require that refineries reduce fresh hydrogen consumption. This can be achieved by purification of the hydrogen. However, the energy consumption for purification must be considered in the system. The study balances both factors to determine the optimal purification feed flow rate (PFFR). The pinch concept is used to relate the hydrogen utility savings (HUS) and the purification feed flow rate. The cost versus PFFR diagram includes the pressure swing adsorption (PSA) cost with an HUS cost versus PFFR line and a purification cost versus PFFR line to identify the optimal PFFR and the limiting PFFR. The hydrogen network of a petrochemical enterprise is optimized using this method with the results showing that the limiting PFFR is 4.8 mol/s, the optimal PFFR is 60.74 mol/s , and the annual cost can be decreased by 2.41×10
6
US$/a.
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Naphtha characterization based on a molecular-type homologous series vector representation
MEI Hua, DU Yupeng, WANG Zhenlei, QIAN Feng
Journal of Tsinghua University(Science and Technology). 2016,
56
(7): 723-727. DOI: 10.16511/j.cnki.qhdxxb.2016.24.022
Abstract
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A novel homologous series vector representation method was developed for naphtha in which each homologous molecule of naphtha is defined as a state variable and all these variables are then used to construct a high dimension vector space. Thus, any variation of naphtha as one point in this vector space can be blended linearly by a group of independent naphthas named Basis Oils. These basis oils are obtained using the non-negative matrix factorization (NMF) method with the components data matrix of a huge number of naphtha samples factorized into a characteristic matrix with a lower dimension and its coefficient matrix. In a case study, a naphtha model containing 21 groups of naphtha bases was extracted from 59 groups of naphtha samples with a maximum representation error of less than 2.5 percent of the original data.
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Optimization of a shell-and-tube heat exchanger based on a genetic simulated annealing algorithm
XIAO Wu, WANG Kaifeng, JIANG Xiaobin, HE Gaohong
Journal of Tsinghua University(Science and Technology). 2016,
56
(7): 728-734. DOI: 10.16511/j.cnki.qhdxxb.2016.24.021
Abstract
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A mathematical model was developed to optimize the design of a shell-and-tube heat exchanger based on design data obtained by using the Bell-Delaware method to describe the pressure drop and heat transfer on the shell-side. The design variables were the tube diameter, the tube length, and other geometric parameters with the Tubular Exchanger Manufacturers Association (TEMA) standard taken as the reference for the constraints and the minimum total heat exchanger cost as the objective. The solution used the genetic simulated annealing algorithm (GA-SA). This method more effectively balances the heat exchanger area cost and pumping cost than previous methods by searching for the global optimal solution for the main geometric heat exchanger parameters with the minimum total cost. With the margin requirement for heat exchanger designs for specific industrial projects, these results are close to those given by commercial HTRI software, which indicates that this heat exchanger design method is reliable. This method guarantees the economic optimum without an empirical method to optimize the design variables in the heat exchanger design which is a major weakness of HTRI software packages.
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Coordinated optimization of hydrogen networks with purification reuse coupled with a shortcut model of the pressure swing adsorption
DENG Chun, ZHOU Yeyang, JIANG Wei, FENG Xiao
Journal of Tsinghua University(Science and Technology). 2016,
56
(7): 735-742. DOI: 10.16511/j.cnki.qhdxxb.2016.24.018
Abstract
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Pressure swing adsorption (PSA) is used to purify hydrogen streams with the upgraded streams reused by hydroprocessing units to increase the hydrogen supply in refineries. This study used a PSA shortcut model to construct a hydrogen network design with purification reuse. The mathematical model used the minimum hydrogen utility as the objective function with the commercial optimization software GAMS (general algebraic modeling system) to solve the problem with DICOPT (discrete and continuous optimizer) as the solver. The results of a case study show that the PSA device has the optimal inlet hydrogen purity. As the adsorption and desorption pressure ratio increases and the adsorbent selectivity decreases, the PSA hydrogen recovery increases and the hydrogen utility decreases. The hydrogen network optimization shows that designers should not blindly increase the PSA inlet hydrogen purity to enhance the hydrogen recovery.
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CIVIL ENGINEERING
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Optimal traffic sensor layout model considering traffic big data
SUN Zhiyuan, LU Huapu
Journal of Tsinghua University(Science and Technology). 2016,
56
(7): 743-750. DOI: 10.16511/j.cnki.qhdxxb.2016.24.025
Abstract
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An optimal traffic sensor layout model was developed to improve the accuracy, reliability and economy of urban traffic information collection. The traffic sensor layout was optimized in light of big data traffic information with the system optimized with consideration of the system cost, multi-source data sharing, data demand, fault conditions, road infrastructure, and different types of sensors. The impact of these influential factors was taken into account in a multi-objective programming model that included system cost minimization, traffic flow intercept maximization, path coverage minimization, and an origin-destination(OD) coverage constraint. The model was solved by the tolerant lexicographic method based on a genetic algorithm. A case study shows that the model provides multi-objective optimization, reflects the influence of multi-source data sharing and fault conditions, satisfies the origin-destination coverage constraint, and provides the optimal traffic sensor layout.
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BIOLOGY AND BIOMEDICAL ENGINEERING
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In vitro hyperthermia based on a multi-mode detection chip with impedance sensing
XIE Xinwu, LIU Weiran, LIU Ran
Journal of Tsinghua University(Science and Technology). 2016,
56
(7): 751-758. DOI: 10.16511/j.cnki.qhdxxb.2016.21.040
Abstract
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Hyperthermia is a useful method for cancer treatment after surgery, chemotherapy and radiotherapy for numerous types of cancers. However, the mechanism is not yet fully understood and some in vitro results cannot be repeated in clinical applications; thus, further research is needed. In this study, a lab-on-a-chip device and a corresponding detection system was constructed to study in vitro hyperthermia. The device incorporated electric cell-substrate impedance sensing (ECIS), morphological imaging, and fluorescence observation during and after cells were thermally treated in situ with automatic on-chip temperature control. The temperature control was tested in an incubator. The cell culture and impedance sensing were also validated. Then, cancer cells were treated and monitored by the system for two hyperthermia conditions. The impedance curve with rectangle hyperthermia control of 41℃ for 2 h shows a "V" shape change during the 41℃ treatment with the cells quickly shrinking and re-adhering without any obvious viability changes in the fluorescent labeling images. However, two hyperthermia pulses at 55℃ for 2 min caused cell impedance "L" shape changes and killed most of the cells. These results demonstrate that this device with un-labeled and labeled methods is a useful tool for in vitro research on thermal therapy.
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NUCLEAR AND NEW ENERGY ENGINEERING
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Static droplet phase transformation model for variable pressure conditions
ZHAO Fulong, BO Hanliang, LIU Qianfeng
Journal of Tsinghua University(Science and Technology). 2016,
56
(7): 759-764,771. DOI: 10.16511/j.cnki.qhdxxb.2016.21.041
Abstract
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The steam-water separator is a very important part of steam generators. The steam separator removes small droplets carried by the vapor stream to provide saturated vapor to the steam turbine. The steam-water separator performance then greatly impacts the safety and economy of the nuclear power station. As droplets move through the separator, the pressure decreases due to the flow resistance and structure variation, which may break the liquid-vapor equilibrium, cause the droplets to evaporate and influence the steam-water separator performance. This paper gives a hydrodynamic-kinetic model of static droplet phase transformations when the pressure varies based on physical and mechanist models of droplet evaporation. The model predictions are independent of the time step and the results agree well with existing data with relative errors less than ±5%. This model provides a theoretical reference for further studies of droplet phase transformations to improve the separation performance of steam separators.
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COMPUTER SCIENCE AND TECHNOLOGY
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S transform feature for pathological speech
LI Haifeng, FANG Chunying, MA Lin, ZHANG Mancai, SUN Jiayin
Journal of Tsinghua University(Science and Technology). 2016,
56
(7): 765-771. DOI: 10.16511/j.cnki.qhdxxb.2016.21.042
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Pathological speech is difficult to analyze because it is non-stationary and mutative. The study combines the S transform, which has good time-frequency resolution and time-frequency positioning capability with the human auditory Mel characteristics to calculate Mel S-transform cepstrum coefficients (MSCC) which highlight vocal organ pathological lesions. The MSCC are compared with the classical Mel frequency cepstrum coefficients (MFCC) and the common acoustic characteristics in the NCSC corpus to show that the MSCC are more able to portray the dynamics and to quickly identify pathological speech information. In addition, the MSCC also give classification performance based on the F-Score method with the particle swarm optimization algorithm for feature selection. Therefore, the MSCC provide accurate analyses of pathological speech characteristics for clinical diagnosis.
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SVD-based DNN pruning and retraining
XING Anhao, ZHANG Pengyuan, PAN Jielin, YAN Yonghong
Journal of Tsinghua University(Science and Technology). 2016,
56
(7): 772-776. DOI: 10.16511/j.cnki.qhdxxb.2016.21.043
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Deep neural networks (DNN) have many parameters, which restricts the use of DNN in scenarios with limited computing resources or when speed is a priority. Some researchers have proposed to prune the DNN using singular value decomposition (SVD). However, this method lacks adaptivity as it prunes the same number of singular values in all the hidden DNN layers. A singular rate pruning factor (SRPF) based DNN pruning method is given here. This method first separately calculates the SRPFs for each hidden layer based on the data with every layer then pruned using different pruning factors. This method makes full use of the distribution traits of the singular values in each hidden layer. This method is more adaptive than pruning a fixed portion of singular values with experiments showing that a DNN pruned with this method performs better. A retraining method is also given which adapts to the pruned DNN.
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Program security verification based on abstract invariants
ZHANG Yan, QIAN Junyan, LI Zhoujun, MA Dianfu
Journal of Tsinghua University(Science and Technology). 2016,
56
(7): 777-784. DOI: 10.16511/j.cnki.qhdxxb.2016.21.036
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Program security verification is a difficult issue with program invariants used for program security verification. Verification of whether a program has the correct temporal nature is converted into a problem solved at a fixed point. However, directly constructing an algorithm to solve the fixed point problem is very difficult. This paper presents a class of invariant construction methods based on an abstract interpretation framework to solve the structure method. Firstly, the Tableau method is used to construct the figure of the temporal formula based on the traditional invariant structure rules, with forward or backward state transitions to improve the invariant validation rules. Secondly, this paper presents an abstract state transition system based on an abstract interpretation framework and gives the abstract invariants validation rules. Finally, the fixed point theorem of abstract invariants is used with the forward or reverse transformations to solve the approximate fixed point in an automatic validation method based on abstract invariants of the program. Approximate widening and narrowing operations based on the abstract fixed point invariant verification algorithm accelerate the convergence.
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Query authentications based on a fixed grid partitioning quad-tree index in LBS big data
NING Bo, PEI Xiaoxia, LI Yuju, PEI Xinyu
Journal of Tsinghua University(Science and Technology). 2016,
56
(7): 785-792. DOI: 10.16511/j.cnki.qhdxxb.2016.21.044
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When publishing data from location-based services (LBS), the data owner authorizes a third party publisher to be responsible for forwarding the appropriate result to the mobile clients. However, the service provider in the LBS big data may be susceptible to attacks which may lead to garbled or incorrect query results that can have commercial interest. This paper describes a quad-tree indexing structure based on a fixed grid partitioning mechanism for spatial range query authentication that partitions and indexes the spatial data. The position of an object in the LBS big data changes with time, so the data requires a dynamic index structure that can deal with many update operations. The spatial index structure presented here to update the price has low overhead, is convenient for data management systems, shortens the retrieval time for range queries, and uses a quad-tree index for high query efficiencies. The system ensures the authenticity, completeness and correctness of the query results. Tests show that this method is effective.
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Matrix factorization based social recommender model
YAN Surong, FENG Xiaoqing, LIAO Yixing
Journal of Tsinghua University(Science and Technology). 2016,
56
(7): 793-800. DOI: 10.16511/j.cnki.qhdxxb.2016.21.045
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This study describes an improved matrix factorization based social recommender model that uses tailored relationship networks of users as a solution for the sparsity, cold-start and scalability problems in big datasets. The social influence of the relationship networks is targeted as an extra user-item specific bias for the matrix factorization with the uniformity of relationship networks modeled as dynamic social regularization terms in the matrix factorization. A boosting-shrinking algorithm is used for the relationship networks for better prediction accuracy and scalability where the relationships of each user are tailored to generate personalized relationship networks according to the user-specific data density of the user-item rating matrix and the correlation matrix. Tests on unbalanced datasets with different sparsity levels show that this model significantly improves the prediction accuracy for sparse datasets, effectively addresses the cold-start problem, and has better scalability compared to other state-of-the-art matrix factorization based social recommendation models.
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