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Research Articles
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Variable selection method for high-dimensional survival error-in-variable data
- ZHANG Jiarui, WU Yaohua
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2023, 40 (1):
12-20.
DOI: 10.7523/j.ucas.2021.0016
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Abstract (
479 )
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Analysis with censored survival data plays an important role in high-dimensional sparse modeling. Much theoretical and applied work is based on clean data. However, we often face corrupted data with missing data or error-in-variable data and as a result analysis on error-in-variable data is more useful. While in the known literature, relatively few work has been done on high-dimensional survival data variable selecting with measurement error. In this situation, we propose a new method to select variables in high-dimensional additive hazards model with error-in-variable data, which combines the pseudoscore function and the nearest positive semi-definite projection. Our numerical studies and real data analysis show that the method has good performance and can select the nonzero coefficients successfully.
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Numerical simulation of forced convection driven by high-frequency traveling magnetic field for low conductivity liquids
- GUO Shengrong, NA Xianzhao, LIU Runcong, LI Yong, ZHANG Xiangping, DONG Haifeng, DAI Xiaotian, GONG Xiufang, WANG Xiaodong
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2023, 40 (1):
21-28.
DOI: 10.7523/j.ucas.2021.0029
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Abstract (
276 )
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High frequency traveling magnetic field generated by two sets of coil can be applied as a new driving method for low conductivity liquid, therefore study on its mechanism is of great significance. In this paper, a numerical model is established to study the effects of current, frequency, phase difference， and coil distance on the flow field and temperature field of the low conductivity liquid being driven, so as to obtain the optimal electrical parameters configuration and coil structure for the driving task. The simulation results show that the average velocity and temperature of the fluid are linearly correlated with the magnitude and frequency of the current. The average velocity is maximized when the phase difference between the coils is near 90o. Depend on the coil distance, the flow field is either two vortices or a single large circulation. Particle image velocimetry (PIV) is also used to measure the flow field distribution of NaCl solution driven by high frequency traveling magnetic field, which verifies the feasibility and effectiveness of the driving method.
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Trend analysis of ecohydrology research of Yellow River Basin
- LI Tong, CUI Lizhen, YANG Yaqian, SONG Xiufang, TANG Li, CUI Xiaoyong, HAO Yanbin, WANG Yanfen
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2023, 40 (1):
29-38.
DOI: 10.7523/j.ucas.2022.025
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Abstract (
630 )
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The Yellow River Basin is a critical economic corridor for the implementation of the Belt and Road initiative. Maintaining the ecological health of the Yellow River is important for both the national social-economic development and ecological security. However, due to human activities and climate change, the Yellow River Basin has experienced ecological crises, such as degradation of vegetation in the upper reaches, sharp reduction of water and sand in the middle reaches, water shortage in the lower reaches, and retreat of the estuarine delta. This has seriously restricted the high-quality development of the Yellow River Basin and the process of ecological civilization in China. This study uses 5 190 related literature and 145 781 references in the Web of Science (WOS) database during 1990-2020 as the research sample. By scientometric and visual knowledge network methods, it analyzes the literature output pattern, keyword co-occurrence network, and future development of hydrology research in Yellow River Basin. Specifically, it quantifies and visualizes the current status, main institutions, academic journals, high-producing authors, and hot themes of the research at a multi-dimensional and deep level. Thus, this study aims at facilitating relevant researchers to get a panorama view, so as to focus the directions of ecohydrological research of the Yellow River Basin.
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Atmospheric VOCs and their contribution to O3 and SOA formation in summer of Huairou District, Beijing City
- ZHOU Bi, HU Jun, QI Yixuan, ZHANG Lijia, HUO Peng, ZHANG Yuanxun, ZHANG Yang, WANG Shulan
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2023, 40 (1):
39-49.
DOI: 10.7523/j.ucas.2021.0025
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Abstract (
456 )
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In order to study the pollution characteristics and sources of volatile organic compounds (VOCs) and their environmental impact, 99 VOCs in Huairou District of Beijing were monitored online in summer 2016. During the observation period, the average concentration of VOCs was 20.02×10-9, among which alkanes accounted for the highest proportion of 38.48%, followed by oxygenated volatile organic compounds (OVOCs) (28.28%), halogenated hydrocarbons (12.89%), and halogenated hydrocarbons, aromatic hydrocarbons, olefins and alkynes and acetonitrile for a smaller percentage. The average hourly ozone formation potential of the initial VOCs was 157.03μg·m-3 and the major contributors were OVOCs, while alkenes and aromatics, aromatics were the major contributors to secondary organic aerosol formation potential. Seven sources were identified by the PMF model, including background and combustion sources, industrial sources, diesel vehicle emissions, gasoline vehicle emissions oil and gas volatilization, natural sources, and organic solvent use. The results from backward trajectory show that, in addition to local emissions, Hebei, Henan， and Shandong provinces have major contributions to Beijing VOCs pollution, while Tianjin City, Liaoning Province, and Inner Mongolia Autonomous Region also have some contributions.
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Research on geographical factors of location of beacon towers of the Great Wall of Han Dynasty: a case study of Yumen City
- SUN Ruiqi, LUO Lei, WANG Xinyuan, YAO Ya, HUANG Wenjiang, DONG Yingying, LIAN Yi
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2023, 40 (1):
50-58.
DOI: 10.7523/j.ucas.2021.0030
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Abstract (
401 )
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The Great Wall of Han Dynasty is the most important ancient defense system in the desert region of Northwest China with beacon towers standing in great numbers. In the Han dynasty with limited economic conditions and arid areas with adverse natural conditions, how spatial location of beacon towers played a role in agriculture and military is of great significance for understanding the past human-land relationship. However, current domestic researches are mostly qualitative from the perspective of history and archaeology which is difficult to restore the spatial cognition and technology in the ancient environment without quantitative results. Taking Yumen City, Gansu Province as an example, this paper introduced spatial analysis and statistical methods including point pattern analysis, spatial correlation test, Monte Carlo simulation to quantitatively test the sensitivity of factors that probably affect the spatial distribution of beacon sites. Two types of factors, natural environmental and human settlement, were tested, which further summarized the law of spatial layout of beacon towers. Results indicated that the elevation showed sensitivity in the range of 1250-1500m, while the nearest distance to water showed sensitivity in the range of 0-1535m. The slope factor was sensitive between 2.5°-8°, and the aspect was sensitive in the range of 70° southeast to 60° southwest. The city sites were also sensitive predictors within a radius of about 2-20km centered on themselves. Analysis of the results indicated that the beacon towers along the Great Wall optimized the cost and utility of the military intelligence transmission between the front and the rear city barrier while guaranteeing the visibility of the front line. Additionally, the environment for human settlements at the site was considered by choosing oases with flat terrain and sufficient water sources, confirming its auxiliary functions such as farming and transportation, which comprehensively reflected the advanced geospatial cognition and technology in the Han Dynasty.
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Coupling analysis of energy efficiency and structural upgrade of manufacturing in Jiangsu Province
- JIN Tingting, DUAN Xuejun, ZOU Hui
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2023, 40 (1):
59-68.
DOI: 10.7523/j.ucas.2021.0023
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Abstract (
260 )
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The adjustment of regional industrial structure is an important way to improve energy efficiency. This paper evaluates the energy efficiency and structure up-grade index of manufacturing industry in prefecture-level cities of Jiangsu Province from 2006 to 2016 by constructing energy efficiency index, using up-grade index and coupling degree model. In addition, it calculates the coupling degree between energy efficiency and structure up-grade index, and divides the coupling types. Moreover, the structural characteristics of manufacturing industry in different coupling areas are analyzed. As a result, it shows that: 1)The energy efficiency is high in the east and low in the west and differentiated between the north and the south as a whole. In addition, the areas with high energy efficiency are mainly distributed in Nantong, Yancheng, and Suqian. At the same time, the areas with low energy efficiency are distributed in Huai’an, Lianyungang, and Xuzhou. 2)The bipolar pattern of manufacturing structure up-grade index in Nanjing-Suzhou is significant, and the overall level of the southern region is higher than that of the northern region. 3)The manufacturing energy efficiency and industrial structure in the study area are at the primary coupling coordination level as a whole, while Nantong and Yancheng are highly coupled areas. 4)Three kinds of coupling areas are divided according to the coupling relationship between energy efficiency and structural advanced degree of manufacturing industry in each city. The result shows that low energy efficiency-low manufacturing advanced degree region has a relatively large proportion of low added value and high energy consumption manufacturing sector, which is the key area to optimize the industrial structure and improve the efficiency of energy resources.
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Spatial equity of healthcare resource in Xinjiang
- FU Runde, ZHANG Xinhuan, YANG Degang
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2023, 40 (1):
69-78.
DOI: 10.7523/j.ucas.2021.0001
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Abstract (
512 )
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The spatial equity of medical and healthcare resource help to improve social equity, increase residents’ happiness, and achieve the goal of “equal access to public services”. Based on OpenStreetMap dataset and Python scripts, extending accessibility calculation method to a large area, this study explored the spatial equity characteristics and influencing factors of medical and healthcare resource of Xinjiang Uygur Autonomous Region. The results indicate that: 1) From a demographic perspective, the equity of medical resource allocation in Xinjiang tends to be further improved; 2) On basic medical services, only 38.5% settlements-distance costs of nearest medical institutions are within 5km, and 20.1% beyond 10km. And there are significant differences in the equity of medical resource allocation in both cities and counties. The spatial allocation of basic medical services in some regions needs to be further optimized, especially in some border counties; 3) Even, some settlements have no medical institutions within 120km, having a shortage of basic medical services. And, there is significant spatial imbalance between rural area and city area; 4) Average distance costs of nearest tertiary A-level hospital of all settlements is 70.05km. Access to tertiary A-level hospital medical services has a large gap between different areas; 5) At present, the spatial equality of Xinjiang is mainly influenced by the construction of professional medical team and regional economic development.
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VLBI polarization study of compact radio sources 0400+258
- LI Yuhang, ZHANG Haiyan, CHEN Rurong, CHEN Tianlu
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2023, 40 (1):
79-83.
DOI: 10.7523/j.ucas.2022.001
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Abstract (
285 )
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Using the very long baseline array, we perform the double-band polarization observations of the compact radio source 0400+258 at 5 GHz and 8 GHz. We present its mas-resolution total intensity maps and, for the first time, its polarization maps at 5 GHz and 8 GHz frequency bands. The source 0400+258 displays one-sided core-jet structure, and the polarization emission is firmly detected in a region near the core. Besides, by fitting the polarization maps at four frequencies, the mas-scale rotation measure of the source is obtained for the first time. After removing the rotation measure, the intrinsic magnetic field of the source is acquired, which demonstrates that the magnetic field direction is roughly parallel to the direction of the jet.
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A new method of moving target velocity measurement and location based on FrFT
- SHEN Xiaotian, ZHENG Mingjie
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2023, 40 (1):
84-92.
DOI: 10.7523/j.ucas.2021.0017
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Abstract (
425 )
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In traditional, the way to measure the velocity of moving targets using FrFT(fractional Fourier transform) is based on 2D searching. The FrFT is calculated by traversing all angles and the optimal solution is the peak value of 2D plane. The method needs to trade off computational accuracy and computational complexity. In this paper, a new method of velocity measurement and location for moving targets is proposed. Firstly, the FrFT of two different angles and their projection are calculated. Then, the optimal rotation angle for moving target is calculated by using geometric relationship in the time-frequency plane. Finally, the FrFT under the optimal rotation angle is calculated, and velocity and position parameters of moving target are calculated. Moreover, static cluster can be suppressed if two angles for FrFT are symmetric about π. In general, the proposed method is faster and more accurate than the traditional method. The effectiveness and superiority of the method are verified by simulation and real data experiments.
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Unmanned aerial vehicle image face recognition based on improved YOLOv3 and Facenet
- GAO Jinfeng, CHEN Yu, WEI Yongming, LI Jiannan
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2023, 40 (1):
93-100.
DOI: 10.7523/j.ucas.2021.0019
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Abstract (
1019 )
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High precision face recognition based on unmanned aerial vehicle (UAV) images plays an important role in emergency rescue, suspect tracking, and other scenes. Deep learning convolutional neural network is widely used in the field of target detection and recognition because of its high accuracy and less human interference, which can be well applied to UAV image face recognition tasks. This paper explores the use of convolution networks for high-precision face recognition in UAV application scenarios, uses the improved YOLOv3(you only look once) for face detection of UAV images, and inputs the prediction boxes into the classic Facenet network to determine the target identity. Through experiments, this paper compares the detection effect of the improved YOLOv3, the original YOLOv3, and the MTCNN (multi-task convolutional neural network), and also compares the face recognition effect of the three models combined with Facenet. The experimental results show that: 1) compared with the original YOLOv3, the improved YOLOv3 improves the accuracy and recall rate, reduces the number of model parameters; besides, the phenomenon of missing and wrong detection of the improved YOLOv3 for UAV image is less than that of the original YOLOv3; moreover, the AP (average precision) of improved YOLOv3 is 9.49% higher than that of MTCNN, and the detection speed is about 3 times of MTCNN; 2) compared with the original YOLOv3+Facenet and MTCNN+Facenet, the improved YOLOv3+Facenet has stronger ability to distinguish faces and higher accuracy, and has stronger robustness to occlusion and blur.
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Satellite imaging planning method based on improved cuckoo search
- LI Xiaomu, TIAN Miaomiao, MA Guangbin, LIN Youming, CHENG Bo
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2023, 40 (1):
101-108.
DOI: 10.7523/j.ucas.2021.0014
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Abstract (
365 )
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This paper proposes a satellite mission planning method of multi-satellite regional targets based on improved cuckoo search(ICS) in order to maximize the use of satellite resources. Firstly, the regional target is decomposed into strips based on a single satellite transit activity. Secondly, the satellite attitude constraints, sensor usage constraints, transit time constraints, cloud cover and illumination constraints during imaging, etc. are considered to establish a constraint satisfaction model, for which coding and updating strategies are designed. Finally, an improved cuckoo search algorithm, with nonlinear inertia weight, is used to solve the constraint satisfaction model. The results of the experiment show that compared with genetic algorithm (GA), the proposed algorithm in this paper has better convergence, higher target completion rate and stronger stability, which proves the effectiveness of the method proposed in this paper.
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Satellite data receiving system fault location based on GAN sequence
- WANG Zhengsheng, LI Yalin, ZHANG Hongqun
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2023, 40 (1):
109-118.
DOI: 10.7523/j.ucas.2021.0009
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Abstract (
450 )
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Existing satellite data receiving system fault location methods suffer from the difficulty in obtaining expert knowledge. A generative adversarial network (GAN) sequence method called GANseq is proposed in this paper. According to the feature of fault propagation, the receiving system was first divided into M signal processing unit (SPU) to form a SPU sequence ranked by signal processing order (SPO). The fault location issue then was decomposed into ranked M anomaly detection sub-problems, where the mth sub-problem was the detection of the top m SPUs’ joint state. State parameters GANomaly-based detector was employed in each sub-problem, forming a GAN sequence. The detection results of this sequence on all sub-problems were analyzed to locate fault SPU. The experiment result from practical receiving system shows that GANseq can not only achieve fault location from data-driven perspective, but also reduce fault alarm rate and enhance accuracy level of fault location.
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SSA-based WSN clustering routing algorithm for power transmission and substation scenarios
- LIU Tiankai, LIU Hong, ZHENG Min, TAN Chong
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2023, 40 (1):
119-127.
DOI: 10.7523/j.ucas.2021.0024
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Abstract (
290 )
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In view of the large number of sensors and the lack of networking capability on some power transmission and substation scenarios, a solution for using the relay nodes with high computing power to collect sensor information and networking is proposed. According to this solution, a clustering routing protocol algorithm (LEACH-WGR-SSA) that rotates the root node of the relay nodes -wireless gateway is proposed. The sparrow search algorithm is used to optimize cluster head election, which considers the remaining energy of nodes, the number of adjacent and location information for the election of the wireless gateway and cluster heads and joins the Levy flight strategy to avoid the algorithm falling into the local optimum. Simulation results shows that when 50% of the nodes die, the number of network survival rounds of LEACH-WGR-SSA is increased by 121.6%, 64.1%, and 6.5% compared with LEACH, LEACH-WGR, and LEACH-WGR-PSO, which balances energy consumption, prolongs the network life and improves optimization accuracy.
Brief Reports
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Compressed sensing GNSS signal acquisition algorithm based on singular value decomposition
- DENG Lele, ZHOU Fangming, ZHAO Lulu, LIANG Guang, YU Jinpei
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2023, 40 (1):
128-134.
DOI: 10.7523/j.ucas.2021.0031
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Abstract (
395 )
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Signal acquisition is the key step of GNSS (global navigation satellite system) signal reception, and its search process is computationally expensive. Compressed sensing can reduce the amount of computation, but it has a certain impact on the acquisition performance. In order to improve the performance of compressed sensing acquisition algorithm, based on the sparsity of GNSS signal, a Gaussian measurement matrix based on singular value decomposition is constructed. Compared with the traditional Gaussian measurement matrix, the constructed measurement matrix has better performance of non-correlation and reconstruction. Simulation results show that compared with the traditional Gaussian compressed sensing acquisition algorithm, the acquisition probability of the improved algorithm is significantly improved in the case of lower signal-to-noise ratio.
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Three dimensional MIMO wireless channel prediction based on phase space reconstruction
- FENG Xinyu, LI Kai, REN Tianfeng, LI Hanhui, YANG Yang, ZHOU Mingtuo
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2023, 40 (1):
135-143.
DOI: 10.7523/j.ucas.2021.0032
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Abstract (
259 )
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The fifth generation (5G) wireless communication network uses multiple input multiple output (MIMO) technology, which requires a lot of air interface resource estimation and feedback MIMO channel. Besides optimizing pilot, estimation and feedback design, channel fading prediction is also an effective way to save air interface resources. In this paper, phase space reconstruction method is used to study the phase space reconstruction parameters related to three-dimensional channel model, and a small sample online learning method based on empirical knowledge is proposed to predict MIMO channel coefficients and channel capacity. It is found that the wireless channel data is chaotic, and the phase space delay time and embedding dimension obey a certain distribution, so it can be set as the prior parameters of real-time prediction. Experimental results show that the prediction efficiency of the proposed method is about six times higher than that of the traditional ARMA method, and the minimum average error of channel capacity is 5.91%. Finally, the effectiveness of the phase space reconstruction method is verified by the measured data of an urban area, and the minimum average error of channel capacity prediction is 0.91%.
