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Research Articles
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Synthesis and characterization of cyclopentyl methyl ketazine
- ZHAO Peng, ZHAO Wenzhao, XIA Yangfeng, LIU Long, ZHANG Yanqiang
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2021, 38 (5):
583-589.
DOI: 10.7523/j.issn.2095-6134.2021.05.002
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Abstract (
534 )
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In this paper, a new ketazine compound (C14N2H24) was synthesized from cyclopentyl methyl ketone and hydrazine hydrate. After the separation and purification of the product, the structure of cyclopentyl methyl ketazinewas determined by 1H NMR,13C NMR, and IR spectra. With Gaussian 09 computation, the structure (1E, 2E) of the product was proved to be the most stable molecular configuration. Furthermore, the basic physical and chemical properties of cyclopentyl methyl ketazine under atmospheric pressure were measured, including boiling point (Tb, 238.4℃), melting point (Tm, -38.2℃), density (ρ, 0.910-0.969 g·cm-3), dynamic viscosity (η,2.35-13.17 mPa·s), and specific heat capacity (Cp, 2.97-3.63 J·g-1·℃-1). The thermal expansion coefficient (α, 8.26×10-4-8.75×10-4℃-1) was calculated according to its density.The results show that ρ and η have a positive correlation with temperature while Cp and α have a negative correlation with temperature. The obtained data and correlation formula are very valuable for the industrial application of cyclopentyl methyl ketazine.
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Multi-objective calibration and evaluation of SWAT modela case study in Meichuan River basin
- LI Jing, MA Tianxiao, LU Yanru, SONG Xianfeng, LI Runkui, LIU Junzhi, DUAN Zheng
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2021, 38 (5):
590-600.
DOI: 10.7523/j.issn.2095-6134.2021.05.003
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Abstract (
731 )
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SWAT model calibrated by streamflow data from gauging stations often provides a relatively high accuracy of hydrologic simulation, nevertheless those calibrated model parameters are still with uncertainty, particularly in the area with sparse gauging stations where the compensation between parameters would make SWAT model deeply disturbed by the phenomenon of equifinality. In this paper, a multi-objective calibration method is proposed to calibrate SWAT model and improve modeling quality by using leaf area index (LAI) from remote sensing data. Generally, vegetation has a crucial impact on eco-hydrological process that is also the core component of hydrological process. Therefore, the calibration of vegetation module facilitates to increase the precision of hydrologic model output. In-situ measured streamflow data is usually collected at gauging points, while remote sensed data is a snapshot over a large space. So LAI data may presents much more spatial details in the model other than streamflow data. The test was carried out with streamflow, crop yield yearbook, and MODIS LAI datasets in the Meichuan River basin, and the results showed that the multi-objective method significantly reduced the impact of equifinality on model parameters and improved the simulation accuracy as well as the robustness of the SWAT model because it took full advantages of vegetation remote sensing and concerned the great role of vegetation in hydrological process.
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Spatio-temporal dynamics of snow cover in Amur River basin and its relationship with climate factors
- LU Xiaolin, ZHANG Wanchang, NIU Quanfu, LIU Jinping, CHEN Hao, GAO Huiran
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2021, 38 (5):
601-610.
DOI: 10.7523/j.issn.2095-6134.2021.05.004
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Abstract (
644 )
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As one of the important types of land cover, snow cover has important feedback and adjustment effects on the local hydrological environment and phenological change of vegetation. Based on MOD10A1/MYD10A1 daily snow cover dataset after removing cloud, the spatio-temporal variation of snow cover and the correlation between snow cover area and meteorological factors (temperature and precipitation) was analyzed in the Amur River Basin from 2002 to 2016. The results show that:1) during the study period, the proportion of land surface with increasing snow-cover days (SCDs) was slightly larger than that of decreasing SCDs in Amur River Basin. In terms of temporal variations, the annual snow cover area of the whole basin showed a slightly increasing trend, whereas it was manifested as an increase in winter and summer, a decrease in autumn, and oscillating in spring. 2) The correlations between snow cover area and climate factors vary with season. Snow cover area was negatively correlated with mean air temperature (P<0.01) in March and April or with the highest air temperature (P<0.05) in autumn, while it was positively correlated with precipitation (P<0.01) in February, June, and December. To sum up, the interannual variation of snow cover in Amur River basin over the past 14 years and its correlation with temperature and precipitation showed significant seasonal differences. The results will provide a reference for the researches on climate change, disaster prevention and environmental effects of human activities.
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Geospatial distribution characteristics and key influencing factors of mountain torrents in Guangdong Province, China
- WANG Jun, YU Yan, GONG Qinghua, YUAN Shaoxiong, CHEN Jun
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2021, 38 (5):
611-623.
DOI: 10.7523/j.issn.2095-6134.2021.05.005
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Abstract (
511 )
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According to the data from mountain torrent sites, the geospatial distribution regularity of mountain torrents was first explored. Second, six influencing factors such as relative relief, slope gradient, drainage density, stratigraphy, average annual 24-hour rainfall, and distance to rivers, were chosen to explore the relationship between torrents and these factors. The study area was classified into 179 801 grid cells, and each cell data of six factors was collected using ArcGIS software. Then, the statistical analysis of the quantity distribution and occurrence probability of torrents was carried out. The results showed that both the quantity and density of torrents in the Hanjiang River basin were the largest in Guangdong Province. In terms of administrative division, Meizhou has the largest quantity of torrents while Chaozhou has the highest density. Results also showed that relationships between the occurrence probability of torrents and the relative relief/slope/drainage density were described by y=a1eb1x+a2eb2x with different fitting constants while relationships between the occurrence probability and the stratigraphy/average annual 24-hour rainfall/distance to rivers could be described by y=aebx with different fitting parameters. The study results can provide basis for prevention and control of mountain torrents in Guangdong Province.
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Effects of glacier ablation on surface deformation, stress field, and seismic risk of main faults in Qilian Mountain area
- MENG Qiu, HU Caibo, SHI Yaolin
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2021, 38 (5):
624-631.
DOI: 10.7523/j.issn.2095-6134.2021.05.006
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Abstract (
460 )
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With the continuous development of global climate change, the widespread modern glaciers may further melt or even completely disappear, resulting in the temporal and spatial changes of surface deformation, stress, and fault seismic risk in Qilian Mountains. In this paper, a plane-strain viscoelastic finite element program was developed to calculate the spatial and temporal evolution of surface deformation and ground stress in Qilian Mountains during the 150-year period from 1956 to 2106 under the surface load caused by glacier melting and the continuous tectonic compression. We calculated the normal stress, shear stress, and the change of Coulomb stress on the main faults in Qilian Mountains. The changes of seismic risk on each fault were quantitatively estimated. The surface uplift rate of Qilian Mountains is controlled by the ice rebound. The surface uplift rapidly increase at the beginning and then tends to be stable under the continuous melting of Qilian Mountains glacier. The horizontal stress, vertical stress, and shear stress change obviously under the effects of glacier melting and boundary tectonic loading. The Coulomb stress changes ΔCFS of the DZF, HSF, and HNF continuously increase, and the seismic risk increases in the future. Coulomb stress changes on the YAF and QNF faults are very small, and the seismicity seismic risk changes little. The numerical simulation provides a theoretical reference for understanding the spatial and temporal variation of future earthquake risk in Qilian Mountains under the glacier melting and tectonic loading.
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Statistical characteristics of global earthquake time-celestial body position and its correlation with tidal force
- JI Ce, WU Kai, LUO Lei, WANG Xinyuan
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2021, 38 (5):
632-641.
DOI: 10.7523/j.issn.2095-6134.2021.05.007
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Abstract (
458 )
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Based on a dataset of 550 000 earthquake events gathered from IRIS website, this article studies the periodic changes in the sun-moon-earth, sun-earth, and moon-earth spatial relationship, performs statistical analysis on its impact on global earthquake frequency, and analyzes the relationship between the statistical results and tidal forces. The results demonstrate that:1) Considering the sun-moon-earth space relationship, when the difference between the geocentric ecliptic longitudes of the moon and sun is 90° or 180°, the global earthquake frequency will be greatly elevated at a specific earthquake magnitude and focal depth. 2) Considering the space relationship between the sun and the earth, the frequency of global earthquakes has increased significantly when the earth is passing the Insects Awaken and Grain Rain points in its orbit. When the earth is passing the Vernal Equinox and Qingming points in its orbit, the global earthquake frequency increases significantly on the seventh day of the month in the lunar calendar. This number is 47.6% higher than the natural probability. 3) Considering the space relationship between the moon and the earth, an earthquake tends to be triggered at a location where the longitude is 180° ahead of the sub-lunar point. 4) The analytical results illustrate that some earthquakes are modulated by tidal force. In a specific time period, the interval of maximum tidal force corresponds to the time interval during which the global earthquake frequency increases.
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A moving ship tracking method based on long time interval sequential SAR images
- LIU Yujie, QI Xiangyang
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2021, 38 (5):
642-648.
DOI: 10.7523/j.issn.2095-6134.2021.05.008
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Abstract (
424 )
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Aiming at solving the difficult problem of tracking moving ships, which is caused by their great position variation in long time interval sequential SAR images, a matching tracking method combining track initiation and image feature is proposed. Firstly, the ships are detected from the SAR image to obtain the image slices and extract the ships' image features and spatial position information. Then, ships at different times are correlated to form multiple candidate trajectories according to the constraints of velocity and acceleration. Finally, ship trajectories are screened out based on the minimum difference principle of feature matching to realize moving ship tracking. The effectiveness of the proposed method is verified by simulation experiments and airborne sequential SAR images processing analysis.
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Multiple moving ships detection method based on saliency map fusion for GF-4 satellite remote sensing image
- WANG Xiaohui, HU Yuxin, LÜ Peng
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2021, 38 (5):
649-659.
DOI: 10.7523/j.issn.2095-6134.2021.05.009
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Abstract (
421 )
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The GF-4 satellite is a geostationary-orbit optical remote sensing satellite with the highest resolution in the world. The satellite can incessantly observe the designated area with high temporal resolution, high spatial resolution, and large imaging width. In this paper, a multiple moving ships detection method for GF-4 satellite is proposed. Firstly, the median filtering denoising and non-linear gray-scale stretching are applied to the remote sensing image. Secondly, the saliency map is extracted by the spectral residual (SR) method. Finally, a fusion processing is further performed by adopting the image fusion method based on weighted Dempster-Shafer evidence theory (WDS) to detect ships. Evaluated by the experiment based on real data of GF-4 satellite, it is shown that the proposed method can detect the multiple moving ships accurately and efficiently by the GF-4 satellite image.
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A soft demodulation optimization algorithm of 16APSK signal for DVB-S2X standard
- ZHANG Sha, JIANG Quanjiang, LIANG Guang, YU Jinpei
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2021, 38 (5):
660-665.
DOI: 10.7523/j.issn.2095-6134.2021.05.010
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Abstract (
619 )
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Multiple high-order APSK modulation schemes are added in the DVB-S2X standard on the basis of the DVB-S2 standard, and an 8+8APSK constellation is added based on the original 16APSK. In this paper, characteristics of a 16-APSK constellation are mainly analyzed, and a new soft demodulation optimization algorithm is proposed. Compared with the LLR algorithm and the Max-log-MAP algorithm, the proposed algorithm has the significantly reduced computational complexity. Simulation results of the three algorithms show that the optimization algorithm is small in performance loss and has good practicability in engineering application.
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Heart rate evaluation algorithm based on PE-based MEEMD filter in LFMCW radar
- LIAO Honghai, HE Wei, LIN Shuiyang
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2021, 38 (5):
666-677.
DOI: 10.7523/j.issn.2095-6134.2021.05.011
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Abstract (
397 )
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Aiming to the existing problem that the poor stability and the low accuracy of FFT-based algorithm and Levenberg-Marquardt (LM) fitting algorithm in the heart rate evaluation, this paper proposes an improved heart rate estimation algorithm after analyzing the characteristics of the 77 GHz linear frequency modulated continuous wave (LFMCW) radar.Firstly, the algorithm recognizes the human body through the velocity-distance spectrum and obtains an permutation entropy (PE) interval[0.31,0.44] corresponding to the heartbeat interval of 50-120 beats/min through simulation experiments.Then, this paper proposes a PE heartbeat signal interval screening method to eliminate interference and noise in micro motion signals. Accurate evaluation of heart rate can be realized through peak detection algorithm. Finally, this paper invited 30 volunteers to conduct experiments, and evaluated and compared the algorithm proposed in this paper, FFT algorithm, and LM fitting algorithm from the aspects of stability, accuracy, and estimation error. Experiments show that the comprehensive evaluation indicator of the stability and estimation error of the algorithm proposed in this paper is the best with an accuracy of 98.30%.
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Adaptive neural network for 3D channel amplitude prediction
- YU Wenxin, LI Kai, ZHOU Mingtuo, LI Jian, YANG Yang
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2021, 38 (5):
678-686.
DOI: 10.7523/j.issn.2095-6134.2021.05.012
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Abstract (
365 )
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Aiming at the problem that the computation and time overhead of obtaining channel amplitude is very large when implementing network planning of 5G massive MIMO (multiple-input multiple-output) networks with the traditional system-level simulation methods, this paper proposes a BP (back propagation) network based adaptive neural network to predict the channel amplitude of massive MIMO systems. The adaptive neural network consists of a basic BP sub neural network and a feature-reduced BP sub neural network, which can realize self-adaption to the given training and test set and can quickly and accurately predict the user channel amplitude based on the ray-tracing data. Simulation results show that the proposed adaptive neural network can achieve close accuracy to the traditional system-level simulation methods when obtaining channel amplitude but with significantly reduced time overhead and can obviously reduce the training time, the amount of users with large prediction error and the average prediction error compared with the traditional BP neural network.
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Inter-satellite load balancing routing algorithm for LEO satellite constellation based on regional-traffic-detour
- ZHOU Ya, XIE Zhuochen, LIU Peilong, LIU Huijie
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2021, 38 (5):
687-695.
DOI: 10.7523/j.issn.2095-6134.2021.05.013
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Abstract (
599 )
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The LEO (low earth orbit) satellite communication networks are characterized by non-uniform traffic distribution, unevenly ground station distribution, and time-varying network load. The data transmission between satellites and the nearby ground stations may lead to dynamic funnel-type congestion in the space segment. It will result in the congestion of the feeder link congestion and the worse end-to-end characteristics. In this article, a regional-traffic-detour multipath search load balancing routing algorithm (RMLBR) is proposed. RMLBR calculates the transition probability according to satellite network status and the source-to-destination distance to implement the regional-traffic-detouring. Under the constraint of path delay, the optimal path and alternative path are obtained by the multipath search to alleviate the dynamic funnel-type congestion. The simulation shows that RMLBR can alleviate the funnel-type congestion, reduce the end-to-end delay, the packet loss, and the size of the high flow area compared with TLR(traffic-light based intelligent routing strategy) and ELB (explicit load balancing).
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Multi-resource scheduling algorithm based on EDA simulation software
- WANG Jing, CHEN Lan, ZHANG He, WANG Haiyong
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2021, 38 (5):
696-701.
DOI: 10.7523/j.issn.2095-6134.2021.05.014
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Abstract (
450 )
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In order to improve the resource utilization of electronic design automation(EDA) parallel simulation tasks and ensure fairness, on the basis of dominant resource fairness allocation(DRF), dominant resource fairness allocation algorithm considering license(LDRF) is proposed. On the one hand, the problem of fair scheduling of multiple types of resources is considered, satisfying the diversity of resource requirements of EDA tasks. On the other hand, the license resource scheduling of EDA tool is considered to avoid the reduction of utilization caused by the lack of license for hardware resources. The experimental simulation results show that under the condition of limited license, the CPU resource utilization of LDRF is increased by 60% compared with DRF, and the memory resource utilization rate is increased by 34%.
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Fog computing resource scheduling in intelligent factories
- DAI Zhiming, ZHOU Mingtuo, YANG Yang, LI Jian, LIU Jun
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2021, 38 (5):
702-711.
DOI: 10.7523/j.issn.2095-6134.2021.05.015
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Abstract (
394 )
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With the development of next-generation information technology, many traditional factories have begun to transform into smart factories. How to deal with the massive data in smart factories and improve the production efficiency of the factory is still a serious problem. In this paper, based on the characteristics of smart factories, a fog computing framework for smart factories is proposed, and Kubernetes is used to automate the deployment of containerized smart factory applications.And an improved genetic algorithm based interval division genetic algorithm IDGSA (interval division genetic scheduling arithmetic) is proposed to dispatch and allocate container applications in smart factories. Simulation experiments show that compared with Kubernetes' default scheduling algorithm, IDGSA algorithm can reduce data processing time by 50% and increase the utilization rate of fog computing resources by 60%. Compared with traditional genetic algorithms, it has fewer iterations. In this case, the processing time of the data can be reduced by 7%, and the utilization rate of the fog computing resource can be increased by 9%.
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Single-event upsets fault tolerance of convolutional neural networks based on dropout algorithm
- QIAN Huan, XIE Zhuochen, LIANG Xuwen
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2021, 38 (5):
712-719.
DOI: 10.7523/j.issn.2095-6134.2021.05.016
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Abstract (
406 )
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Space radiation interference especially the single event upset (SEU) effect can make a great impact on the normal and stable operation of the neural network chips, which can lead to the random bit flips of the weight parameters stored in the SRAM, and thus change the values of the neural weight parameters and the accuracy of the neural network chip outputs. In this paper, we analyze the commonly used radiation resistant methods, and try to overcome the problem of hardware consumption, recovery time, and processing speed. After the software simulation of the neural network accuracy with the different ratios of weight parameter errors, we adopt the dropout algorithm to construct the novel network framework to avoid the decline of accuracy. The algorithm can mask the neurons affected by SEU with some probability. The simulation experiment results show that this method can promote the accuracy of the neural network affected by SEU.