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    25 March 2023, Volume 2023 Issue 2 Previous Issue   
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    Mathematics
    Two-degree trees
    Pu QIAO, Xingzhi ZHAN
    2023, 2023 (2):  1-4.  doi: 10.3969/j.issn.1000-5641.2023.02.001
    Abstract ( 216 )   HTML ( 20 )   PDF (427KB) ( 138 )   Save

    A graph is called a two-degree graph if its vertices have only two distinct degrees. A two-degree tree of order at least three have two degrees, $ 1 $ and $ d $ for some $ d\geqslant 2; $ such a tree is called a $ (1,d) $ -tree. Given a positive integer $ n, $ we determine: (1) the possible values of $ d $ such that there exists a $ (1,d) $ -tree of order $ n; $ (2) the values of $ d $ such that there exists a unique $ (1,d) $ -tree of order $ n $ , and (3) the maximum diameter of two-degree trees of order $ n. $ The results provide a new example showing that the behavior of graphs may sometimes be determined by number theoretic properties.

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    The Hermitian R-antisymmetric solution of an inverse quadratic eigenvalue problem
    Zhiping QI, Lan ZHANG
    2023, 2023 (2):  5-11.  doi: 10.3969/j.issn.1000-5641.2023.02.002
    Abstract ( 143 )   HTML ( 19 )   PDF (484KB) ( 85 )   Save

    In this paper, we consider the inverse problem of quadratic eigenvalue for a Hermitian R-antisymmetric matrix. By using the matrix block method, singular value decomposition, vector straightening, and the Moore-Penrose inverse, we prove the existence of a Hermitian R-antisymmetric solution. In addition, we provide the general expression for a Hermitian R-antisymmetric solution, and discuss the best approximation thereof. Finally, an example is offered to validate the theory.

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    Strongly Gorenstein weak flat modules
    Yanhui SONG, Ting GUO
    2023, 2023 (2):  12-16.  doi: 10.3969/j.issn.1000-5641.2023.02.003
    Abstract ( 171 )   HTML ( 10 )   PDF (499KB) ( 108 )   Save

    In this paper, we introduce the notion of strongly Gorenstein weak flat modules, and we subsequently provide homological characterizations of strongly Gorenstein weak flat modules. It is shown that a Gorenstein weak flat module is a summand of a strongly Gorenstein weak flat module.

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    Complete convergence of weighted sums for extended negatively dependent sequences under sublinear expectation
    Dandan FEI, Zongkui FU
    2023, 2023 (2):  17-25.  doi: 10.3969/j.issn.1000-5641.2023.02.004
    Abstract ( 166 )   HTML ( 10 )   PDF (585KB) ( 96 )   Save

    The complete convergence of sequences of random variables under sublinear expectation was studied. Using the properties of extended negatively dependent (ND) sequences, under the condition that the $ \lambda $ -order Choquet integrals of the random variable are finite, the complete convergence of the weighted sums for extended ND sequences under a sublinear expectation was proved. The results generalize and improve the results of independent sequences in the classical probability space.

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    A class of second-order semilinear singularly perturbed boundary value problems with turning points
    Min ZHAO, Mingkang NI
    2023, 2023 (2):  26-33.  doi: 10.3969/j.issn.1000-5641.2023.02.005
    Abstract ( 154 )   HTML ( 11 )   PDF (1686KB) ( 107 )   Save

    The dynamical behavior of a class of second-order semilinear singularly perturbed Neumann boundary value problems with a turning point are studied. Firstly, we establish sufficient conditions for the exchange of stabilities near the turning point. By correcting the regularized equation of the degenerate problem, the accuracy of the asymptotic solution to the original problem is improved. Secondly, the Nagumo theorem is used to prove the existence of a smooth solution. Finally, a specific example is used to verify the validity of the results.

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    Contrast structure in a singularly perturbed delay reaction-diffusion equation
    Qingzhao GAN, Mingkang NI
    2023, 2023 (2):  34-47.  doi: 10.3969/j.issn.1000-5641.2023.02.006
    Abstract ( 152 )   HTML ( 13 )   PDF (790KB) ( 101 )   Save

    This paper considers a Neumann boundary value problem of a singularly perturbed delay reaction-diffusion equation with a nonlinear reactive term. By using the boundary layer function method, contrast structure theory, and contraction mapping principle, the asymptotic expansion of the solution is constructed, and the existence of a uniformly valid solution is proven. Finally, an example is presented to show the effectiveness of our result.

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    Hypothesis testing for the precision matrix of high-dimensional periodic vector autoregressive model
    Jin ZOU
    2023, 2023 (2):  48-59.  doi: 10.3969/j.issn.1000-5641.2023.02.007
    Abstract ( 147 )   HTML ( 9 )   PDF (1000KB) ( 78 )   Save

    The precision (inverse covariance) matrix generated by the periodic vector autoregressive model is a sparse block tridiagonal matrix. Based on this precision matrix, a new block trace function is proposed for testing the equality of block traces of two precision matrices, the asymptotic behavior under the null hypothesis is investigated. Numerical experiments show that the proposed testing procedure has both appropriate size and good power.

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    Computer Science
    Target-dependent event detection from news
    Tiantian ZHANG, Man LAN
    2023, 2023 (2):  60-72.  doi: 10.3969/j.issn.1000-5641.2023.02.008
    Abstract ( 206 )   HTML ( 14 )   PDF (1822KB) ( 108 )   Save

    In real-world scenarios, various events in the news are not only too nuanced and complex to distinguish, but also involve multiple entities. To address these problems, previous event-centric methods are designed to detect events first and then extract arguments, relying on imperfect performance for event trigger detection; this process, however, is unfit to deal with the sheer volume of news in the real world. Given that the performance of named entity recognition (NER) is satisfactory, we shift our perspective from an event-centric to a target-centric view. This paper proposes a new task: target-dependent event detection (TDED), which aims to extract target entities and detect their corresponding events. We also propose a semantic and syntactic aware approach to support thousands of target entity extractions first and subsequently the detection of dozens of event types; this approach can be applied to data from massive corporations. Experimental results on a real-world Chinese financial dataset demonstrated that our model outperformed previous methods, particularly in complex scenarios.

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    A memory allocation strategy for learned index based on huge pages
    Jialin GUAN, Yan ZHU, Tingliang WU, Yan CHEN, Jingwei ZHANG
    2023, 2023 (2):  73-81.  doi: 10.3969/j.issn.1000-5641.2023.02.009
    Abstract ( 224 )   HTML ( 11 )   PDF (1015KB) ( 85 )   Save

    In the era of big data and with the continuous expansion of data, there are significant challenges with efficient access to data. Hence, designing an efficient index structure is of great significance. ALEX (updatable adaptive learned index) is a learned index that uses a machine learning model to replace the traditional B-tree index structure. Although it offers good time and space performance, it suffers from frequent page faults. In order to solve this problem and further improve the performance of ALEX, a memory pre-allocation strategy based on huge pages is proposed, on the basis of ALEX, that can help reduce the rate of memory page faults and improve the overall performance of ALEX. In the memory allocation phase, the pre-allocation strategy is adopted, and the memory free phase adopts a delayed release strategy. Experiments on the Longitudes dataset show that this strategy offers good performance.

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    A landscape simulation modeling method based on remote sensing images
    Zehua WANG, Yan GAO, Mingang CHEN
    2023, 2023 (2):  82-94.  doi: 10.3969/j.issn.1000-5641.2023.02.010
    Abstract ( 336 )   HTML ( 13 )   PDF (4124KB) ( 129 )   Save

    Traditional virtual terrain modeling commonly uses a procedural generation method based on manual design, which cannot be used for competent simulation modeling tasks that need to restore real environments, such as in military applications. In this paper, we proposed a landscape simulation modeling method based on remote sensing images. The core of our proposed method is a landscape blended texture generation network (LBTG-Net); this method uses a blended texture generator (BTG) to generate landscape blended textures with the supervision of a style discriminator (SD) and multi-stage classification loss. Then, we procedurally build the complete virtual environment based on the blended texture generated by LBTG-Net. Our method has two main features: (1) accurate land-cover classification ability of remote sensing image inputs; and (2) high quality landscape blended texture outputs to guarantee virtual landscape modeling quality. We used multispectral image data from the Sentinel-2 satellite as the experimental dataset. The experimental results showed that our method offered high performance under mainstream land-cover classification evaluating indicators and can accurately reproduce the environmental distribution of input remote sensing images while completing high-quality virtual terrain simulation modeling.

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    Fast establishment of a point cloud model for a lock pin based onhigh overlapping views
    Zhiwei JIN, Chang HUANG, Ruihong ZHU
    2023, 2023 (2):  95-105.  doi: 10.3969/j.issn.1000-5641.2023.02.011
    Abstract ( 179 )   HTML ( 8 )   PDF (2472KB) ( 80 )   Save

    In this paper, we propose a method for fast splicing of three-dimensional point clouds based on the lock pin model on a container terminal using high overlapping views. This experiment first uses an Azure Kinect depth camera to collect scene point clouds, and subsequently preprocesses the point cloud. The target point cloud is thus obtained. For lock pins with slightly different views, the sample consensus initial algorithm (SAC-IA) is used on the basis of the classic iterative closest point (ICP) algorithm to determine the overlapping position relationship of the two point clouds. In the overall splicing process, the relative size of the bounding box area projected by the lock pin in the z-direction of the camera is adopted to estimate the general shape of the lock pin; the relative size of the bounding box area is also used to select an appropriate number of point cloud views with high overlap in order to ensure the accuracy of registration and reduce processing time by comparing the difference between the area of adjacent views. The experimental results show that the proposed method has a lower relative registration error for the lock pin, and can quickly establish a workpiece model suitable for type matching.

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    Research on travel time prediction based on neural network
    Zhaoyang WU, Jiali MAO
    2023, 2023 (2):  106-118.  doi: 10.3969/j.issn.1000-5641.2023.02.012
    Abstract ( 253 )   HTML ( 9 )   PDF (1993KB) ( 250 )   Save

    The popularity of positioning devices has generated a large volume of vehicle driving data, making it possible to use historical data to predict the driving time of vehicles. Vehicle driving data consists of two parts: the sequence of road segments that the vehicle travels through, the departure time, the total length of the path, and other external information. The questions of how to extract sequence features in road segments and how to effectively fuse sequence features with external features become the key issues in predicting the travel time. To solve the aforementioned problems, a transformer-based travel time prediction model is proposed, which consists of two parts: a road segment sequence processing module and a feature fusion module. First, the road segment sequence processing module uses the self-attention mechanism to process the road segment sequence and extract the road segment sequence features. The model can not only fully consider the spatiotemporal correlation of road speeds between each road segment and other road segments, but also ensures the parallel input of data into the model, avoiding the low efficiency problem caused by sequential input of data when using recurrent neural networks. The feature fusion module fuses the road segment sequence features with external information, such as departure time, and obtains the predicted travel time. On this basis, the number of road segments connected by the intersection is determined by the upstream and downstream intersection features of the road segment, and the input model is combined with the road segment characteristics to further improve the prediction accuracy of the driving time. Comparative experiments with mainstream prediction methods on real data sets show that the model improves prediction accuracy and training speed, reflecting the effectiveness of the proposed method.

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    Time series database query optimization for anomaly detection
    Shuai ZHANG, Huiqi HU, Yaoqiang XU, Xuan ZHOU
    2023, 2023 (2):  119-131.  doi: 10.3969/j.issn.1000-5641.2023.02.013
    Abstract ( 314 )   HTML ( 16 )   PDF (2279KB) ( 158 )   Save

    With the development of the Internet of Things, a large number of sensor devices can be connected to a network. Anomaly detection of data generated by these devices is related to the stability of system services. A time series database is a database system optimized for time series data. As an important component of a monitoring system, time series databases are responsible for storing and querying continuous streams of time series data. The current time series database, however, cannot fully utilize system computing resources and cannot meet the latency requirements when coping with queries from multiple data sources. To address these drawbacks, we redesigned the query execution model of a time series database based on the well-known InfluxDB, and we proposed InfluxDB-PP (parallel processing) as a method to address the aforementioned problems. The experimental results show that InfluxDB-PP reduces query latency by about 85.7% compared to InfluxDB for real-time anomaly data query scenarios.

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    Device component state recognition method of power distribution cabinet based on a residual networks
    Yang ZHANG, Yejing LAI, Dingjiang HUANG
    2023, 2023 (2):  132-142.  doi: 10.3969/j.issn.1000-5641.2023.02.014
    Abstract ( 183 )   HTML ( 11 )   PDF (970KB) ( 75 )   Save

    With the continuous development of industrial intelligent inspection technology, the equipment element state recognition system based on digital image processing is widely used. In order to improve the accuracy of power distribution cabinet(PDC) equipment element state recognition in a distribution room, a ResNet(residual networks)-based equipment element state recognition method is proposed. Firstly, the data acquisition system is set up and the data set is constructed. Then, for the PDC image, the preset device component target area is cropped to generate the device component image. For device component images, a ResNet-based component state recognition model was constructed and trained, and the trained model was used to identify component states. Taking the data set for power distribution cabinet equipment element in substation distribution rooms as the research object, a network of single prediction heads is adopted as the component with complex features, and the network of multiple prediction heads is adopted as the component with simple features. Then, the compact and pruning model compression method is used to reduce the number of parameters and the calculation amount under the condition of less accuracy loss. Finally, the architecture design of the inspection system is introduced. A JetSon Nano edge terminal is used as the running hardware of the algorithm module to reduce the communication cost.

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    Fault location algorithm based on Kirchhoff ’s law and a Boolean equation
    Xiaoqiu LU, Yang CAI, Jiajun CHEN, Xi ZHOU, Xueming ZHOU, Yunzhe TANG, Dingjiang HUANG
    2023, 2023 (2):  143-154.  doi: 10.3969/j.issn.1000-5641.2023.02.015
    Abstract ( 203 )   HTML ( 8 )   PDF (1422KB) ( 55 )   Save

    With the continuous development of China’s electric power system, the security and reliability of power supply directly affects regional production output and people’s economic life. As an important part of the power dispatch system, traditional fault locations rely on the cumulative experience and manual judgment of dispatchers. Faced with increasing demands, fault locations that rely solely on the traditional method are likely to result in an increase in misjudgment rates and pose a threat to the stable operation of the power system. This paper proposes a Boolean equation based on Kirchhoff’s law and the grid fault location algorithm to address this challenge. The fault location issue can effectively be converted to Boolean linear mixed programming problems and combined with simulated annealing algorithms. When these genetic algorithms are applied to the idea of a network and realized in the grid for fast positioning of small faults, the scheduling error rate can be reduced and the time difference from fault occurrence to fault isolation and fault processing can be shortened; in turn, this saves human resources and improves scheduling efficiency.

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    Life Sciences
    Textual research on Xishuai grass
    Zhuqing HE, Binjie GE
    2023, 2023 (2):  155-160.  doi: 10.3969/j.issn.1000-5641.2023.02.016
    Abstract ( 341 )   HTML ( 10 )   PDF (1942KB) ( 86 )   Save

    Cricket fighting is a traditional Chinese game that has lasted for more than 1000 years. Before competitions, Xishuai grass (stimulant grass) is commonly used to hit a cricket’s head and antennae to prepare the insects for battle. In “Flora of China” and flora of Chinese provinces, Xishuai grass is referenced as the Chinese common name of Eleusine indica (L.) Gaertn. In “Flora of Beijing” and “Flora of Hebei”, Xishuai grass is referenced as the Chinese common name of the genus Eleusine. In this paper, however, we demonstrate that Xishuai grass should actually be Digitaria spp. Given the mistakes in the above flora references, this paper aims to clarify the correct classification for future reference.

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    Disinfection effect of seven frequently used disinfectants on bacteriophage MS2
    Yu LI, Zhenming GE
    2023, 2023 (2):  161-167.  doi: 10.3969/j.issn.1000-5641.2023.02.017
    Abstract ( 317 )   HTML ( 13 )   PDF (1485KB) ( 222 )   Save

    In this study, the MS2 phages were used as an indicator microorganism to test the function of seven disinfectants with different components: hydrogen peroxide, ethanol, fermented lactic acid disinfectant, iodine disinfectant, quaternary ammonium disinfectant, chlorine-containing disinfectant, and peracetic acid disinfectant. Our results showed that the virus disinfection rate varied notably between the selected disinfectants. The iodine disinfectant exhibited the strongest disinfection effect, followed by the quaternary ammonium salt disinfectant and the peracetic acid disinfectant, while the disinfection effects of hydrogen peroxide, ethanol, and fermentation lactic acid disinfectant were inadequate. The test results provide a reference for the efficient utilization of various disinfectants to eliminate harmful microorganisms in the environment.

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    Chemistry and Chemical Engineering
    Surface-modified aluminum used for hydrogen generation and aqueous contaminant removal
    Yang YANG, Zhenyan DENG, Xiaohan GUO, Genwang MA, Weizhuo GAI
    2023, 2023 (2):  168-182.  doi: 10.3969/j.issn.1000-5641.2023.02.018
    Abstract ( 173 )   HTML ( 13 )   PDF (3313KB) ( 39 )   Save

    Aluminum (Al) used for hydrogen generation and aqueous contaminant removal has been widely studied given its abundance and low redox potential; the reduction ability of Al, moreover, is restricted by the passive surface oxide film on Al particles. In addition to common Al surface treatment methods, such as acid/alkali washing, alloying, and mechanical ball-milling, Al surface modification technology arising in recent years has also been confirmed as an efficient Al activation method given its economical cost and benign manufacturing process. In this study, the merits and disadvantages of surface modification relative to other Al surface treatment methods were highlighted by reviewing existing research on the application of Al surface modification in hydrogen generation and aqueous contaminant removal. In addition, the paper presents an outlook on Al surface modification technology used for hydrogen generation and aqueous contaminant removal to promote the study of related processes.

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