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Table of Content

    25 March 2024, Volume 2024 Issue 2 Previous Issue   
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    Mathematics
    Ergodicity for a class of pure-jump population systems
    Zhenzhong ZHANG, Yeqin CHEN, Huiyuan LIU, Xinping LI, Xin ZHAO
    2024, 2024 (2):  1-13.  doi: 10.3969/j.issn.1000-5641.2024.02.001
    Abstract ( 101 )   HTML ( 20 )   PDF (716KB) ( 153 )   Save

    To characterize the effects of stochastic environment and major mutation factors on populations, we consider a class facultative population system based on Markov chains and pure-jump stable processes. First of all, the existence and uniqueness of a global positive solution of the proposed model is discussed. Then, sufficient conditions for ergodicity are specified. Finally, conditions for positive recurrence of the model are presented.

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    ${\rm{E}} $ -total coloring of cycles and paths which are vertex-distinguished by multiple sets
    Xiang’en CHEN, Jing CAO
    2024, 2024 (2):  14-22.  doi: 10.3969/j.issn.1000-5641.2024.02.002
    Abstract ( 55 )   HTML ( 8 )   PDF (1116KB) ( 40 )   Save

    An ${\rm{E}} $ -total coloring of a graph $G $ is an assignment of several colors to all vertices and edges of $G $ such that no two adjacent vertices receive the same color and no edge receive the same color as one of its endpoints. If $f $ is an ${\rm{E}} $ -total coloring of a graph $G $, the multiple color set of a vertex $x $ of $G $ under $f $ is the multiple set composed of colors of $x $ and the edges incident with $x $. If any two distinct vertices of $G $ have distinct multiple color sets under an ${\rm{E}} $ -total coloring $f $ of a graph $G $, then $f $ is called an ${\rm{E}} $ -total coloring of $G $ vertex-distinguished by multiple sets. An ${\rm{E}} $ -total chromatic number of $G $ vertex-distinguished by multiple sets is the minimum number of the colors required in an ${\rm{E}} $ -total coloring of $G $ vertex-distinguished by multiple sets. The ${\rm{E}} $ -total colorings of cycles and paths vertex-distinguished by multiple sets are discussed by use of the method of contradiction and the construction of concrete coloring. The optimal${\rm{E}} $ -total colorings of cycles and paths vertex-distinguished by multiple sets are given and the ${\rm{E}} $ -total chromatic numbers of cycles and paths vertex-distinguished by multiple sets are determined in this paper.

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    Several classes of sign pattern matrices that allow algebraic positivity
    Yan TIAN, Yang JIAO, Haoran YU
    2024, 2024 (2):  23-29.  doi: 10.3969/j.issn.1000-5641.2024.02.003
    Abstract ( 35 )   HTML ( 2 )   PDF (641KB) ( 42 )   Save

    Tridiagonal sign pattern matrices and paw form sign pattern matrices were analyzed with respect to their potential for ensuring algebraic positivity. The necessary conditions allowing algebraic positivity of the two classes of sign pattern matrices were given using combinatorial matrix theory and graph theory. Finally, the equivalent conditions that would ensure algebraic positivity of tridiagonal sign pattern matrices and paw form sign pattern matrices of order $n $ were determined.

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    On *r-clean rings
    Jian QIN, Zhiling YING, Hua ZHOU
    2024, 2024 (2):  30-32.  doi: 10.3969/j.issn.1000-5641.2024.02.004
    Abstract ( 44 )   HTML ( 4 )   PDF (447KB) ( 52 )   Save

    An involution ring is called a *r-clean ring if every element is the sum of a projection and a *-regular element. Some extensions of *r-clean rings are discussed, and a characterization of the element in a *-abelian *r-clean ring is given.

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    Forced oscillation of fractional damped partial differential equation solutions with impulsive delays
    Wenxian LIN
    2024, 2024 (2):  33-41.  doi: 10.3969/j.issn.1000-5641.2024.02.005
    Abstract ( 37 )   HTML ( 3 )   PDF (538KB) ( 48 )   Save

    In this paper, some sufficient conditions for forced oscillation of impulsive multi-delay fractional partial differential equation solutions with damping term are established by using the method of differential inequalities under Robin and Dirichlet boundary conditions, an example is given to verify the validity of the main results.

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    Computer Science
    Research and design of data synchronization schemes of postgraduate information systems based on microservice
    Huiling TAO, Yilin MA, Ye WANG, Qiwen DONG
    2024, 2024 (2):  42-52.  doi: 10.3969/j.issn.1000-5641.2024.02.006
    Abstract ( 62 )   HTML ( 7 )   PDF (1018KB) ( 73 )   Save

    With the popularization of university information system applications and the increase in their usage frequency, teachers and students have higher requirements for data consistency, accuracy, timeliness, and completeness. The original data synchronization scheme using extensible markup language (XML) for data synchronization has the disadvantages of low synchronization efficiency and difficulty of expansion. The open-source tool, DataX, can complete data synchronization between various heterogeneous databases without damaging the source database. This study used DataX to improve the original data synchronization scheme and proposed different data synchronization schemes for various business requirements and application scenarios in the foundation of university postgraduate information system construction. At the same time, in view of the shortcomings of DataX in which only one read can do one write during the start-up and execution, the method where one read can do multiple writes was designed. The comparison experiment shows that the optimized scheme can improve data synchronization efficiency, has better scalability, and can meet the data synchronization requirements of universities.

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    Collaborative stranger review-based recommendation
    Luping FENG, Liye SHI, Wen WU, Jun ZHENG, Wenxin HU, Wei ZHENG
    2024, 2024 (2):  53-64.  doi: 10.3969/j.issn.1000-5641.2024.02.007
    Abstract ( 48 )   HTML ( 7 )   PDF (6769KB) ( 43 )   Save

    Review-based recommendations are mainly based on the exploitation of textual information that reflects the characteristics of items and user preferences. However, most existing approaches overlook the influence of information from hidden strangers on the selection of reviews for the target user. However, information from strangers can more accurately measure the relative feelings of the user and provide a complement to the target user’s expression, leading to more refined user modeling. Recently, several studies have attempted to incorporate similar information from strangers but ignore the use of information regarding other strangers. In this study, we proposed a stranger collaborative review-based recommendation model to make effective use of information from strangers by improving accurate modeling and enriching user modeling. Specifically, for capturing potential user preferences elaborately, we first designed a collaborative stranger attention module considering the textual similarities and preference interactions between the target user and the hidden strangers implied by the reviews. We then developed a collaborative gating module to dynamically integrate information from strangers at the preference level based on the characteristics of the target user-item pair, effectively filtering preferences of strangers and enriching target user modeling. Finally, we applied a latent factor model to accomplish the recommendation task. Experimental results have demonstrated the superiority of our model compared to state-of-the-art methods on real-world datasets from various sources.

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    Dual-path network with multilevel interaction for one-stage visual grounding
    Yue WANG, Jiabo YE, Xin LIN
    2024, 2024 (2):  65-75.  doi: 10.3969/j.issn.1000-5641.2024.02.008
    Abstract ( 41 )   HTML ( 3 )   PDF (1515KB) ( 37 )   Save

    This study explores the multimodal understanding and reasoning for one-stage visual grounding. Existing one-stage methods extract visual feature maps and textual features separately, and then, multimodal reasoning is performed to predict the bounding box of the referred object. These methods suffer from the following two weaknesses: Firstly, the pre-trained visual feature extractors introduce text-unrelated visual signals into the visual features that hinder multimodal interaction. Secondly, the reasoning process followed in these two methods lacks visual guidance for language modeling. It is clear from these shortcomings that the reasoning ability of existing one-stage methods is limited. We propose a low-level interaction to extract text-related visual feature maps, and a high-level interaction to incorporate visual features in guiding the language modeling and further performing multistep reasoning on visual features. Based on the proposed interactions, we present a novel network architecture called the dual-path multilevel interaction network (DPMIN). Furthermore, experiments on five commonly used visual grounding datasets are conducted. The results demonstrate the superior performance of the proposed method and its real-time applicability.

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    Parallel block-based stochastic computing with adapted quantization
    Yongzhuo ZHANG, Qingfeng ZHUGE, Edwin Hsing-Mean SHA, Yuhong SONG
    2024, 2024 (2):  76-85.  doi: 10.3969/j.issn.1000-5641.2024.02.009
    Abstract ( 37 )   HTML ( 4 )   PDF (1107KB) ( 25 )   Save

    The demands of deep neural network models for computation and storage make them unsuitable for deployment on embedded devices with limited area and power. To solve this issue, stochastic computing reduces the storage and computational complexity of neural networks by representing data as a stochastic sequence, followed by arithmetic operations such as addition and multiplication through basic logic operation units. However, short stochastic sequences may cause discretization errors when converting network weights from floating point numbers to the stochastic sequence, which can reduce the inference accuracy of stochastic computing network models. Longer stochastic sequences can improve the representation range of stochastic sequences and alleviate this problem, but they also result in longer computational latency and higher energy consumption. We propose a design for a differentiable quantization function based on the Fourier transform. The function improves the matching of the model to stochastic sequences during the network’s training process, reducing the discretization error during data conversion. This ensures the accuracy of stochastic computational neural networks with short stochastic sequences. Additionally, we present an adder designed to enhance the accuracy of the operation unit and parallelize computations by chunking inputs, thereby reducing latency. Experimental results demonstrate a 20% improvement in model inference accuracy compared to other methods, as well as a 50% reduction in computational latency.

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    Multi-view and multi-pose lock pin point cloud model reconstruction based on turntable
    Xin LU, Chang HUANG, Zhiwei JIN
    2024, 2024 (2):  86-96.  doi: 10.3969/j.issn.1000-5641.2024.02.010
    Abstract ( 45 )   HTML ( 3 )   PDF (3511KB) ( 20 )   Save

    The surface structure of a container lock pin is complex, making it difficult to establish a point cloud model with a high surface feature integrity. Therefore, a multi-view and multi-attitude point cloud model reconstruction algorithm based on a turntable was proposed to restore the complete surface features of the locking pin. Considering that sensors at a fixed height are paired with rotating turntables in most scenarios, the collected surface features are usually somewhat missing. Initially, the algorithm uses the parameter calibration results of the turntable to realize the multi-view three-dimensional point cloud stitching, and establishes a fixed attitude point cloud model. Then, through the proposed improved spherical projection algorithm, the positioning of the locking pin on the turntable is selected to establish a point cloud model under another posture. Finally, the point cloud model with multiple attitudes is integrated to improve its surface characteristics. Experimental results show that the proposed algorithm can build a lock-pin point cloud model with high surface feature integrity.

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    Infrared small-target detection method based on double-layer local energy factor
    Lingxiao TANG, Chang HUANG
    2024, 2024 (2):  97-107.  doi: 10.3969/j.issn.1000-5641.2024.02.011
    Abstract ( 50 )   HTML ( 5 )   PDF (1822KB) ( 33 )   Save

    Infrared small-target detection has always been an important technology in infrared tracking systems. The current infrared approaches for small-target detection in complex backgrounds are prone to generating false alarms and exhibit sluggish detection speeds from the perspective of the human visual system. Using the multiscale local contrast measure using a local energy factor (MLCM-LEF) method, an infrared small-target detection method based on a double-layer local energy factor is proposed. The target detection was performed from the perspectives of the local energy difference and local brightness difference. The double-layer local energy factor was used to describe the difference between the small target and the background from the energy perspective, and the weighted luminance difference factor was used to detect the target from the brightness angle. The infrared small target was extracted by a two-dimensional Gaussian fusion of the processing results of the two approaches. Finally, the image mean and standard deviation were used for adaptive threshold segmentation to extract the small infrared target. In experimental tests on public datasets, this method improved the performance in suppressing background compared with the MLCM-LEF algorithm, DLEF (double-layer local energy factor) reduced the detection of a single frame time by one-third.

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    Group contrastive learning for weakly-supervised 3D point cloud semantic segmentation
    Zhihong ZHENG, Haichuan SONG
    2024, 2024 (2):  108-118.  doi: 10.3969/j.issn.1000-5641.2024.02.012
    Abstract ( 75 )   HTML ( 7 )   PDF (1305KB) ( 57 )   Save

    Three-dimensional point cloud semantic segmentation is an essential task for 3D visual perception and has been widely used in autonomous driving, augmented reality, and robotics. However, most methods work under a fully-supervised setting, which heavily relies on fully annotated datasets. Many weakly-supervised methods have utilized the pseudo-labeling method to retrain the model and reduce the labeling time consumption. However, the previous methods have failed to address the conformation bias induced by false pseudo labels. In this study, we proposed a novel weakly-supervised 3D point cloud semantic segmentation method based on group contrastive learning, constructing contrast between positive and negative sample groups selected from pseudo labels. The pseudo labels will compete with each other within the group contrastive learning, reducing the gradient contribution of falsely predicted pseudo labels. Results on three large-scale datasets show that our method outperforms state-of-the-art weakly-supervised methods with minimal labeling annotations and even surpasses the performance of some classic fully-supervised methods.

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    Hidden layer Fourier convolution for non-stationary texture synthesis
    Xinxin HE, Haichuan SONG
    2024, 2024 (2):  119-130.  doi: 10.3969/j.issn.1000-5641.2024.02.013
    Abstract ( 44 )   HTML ( 2 )   PDF (5109KB) ( 34 )   Save

    The remarkable achievements of deep learning in computer vision have led to significant development in example-based texture synthesis. The texture synthesis model using neural networks mainly includes local components, such as convolution and up/down sampling, which is unsuitable for capturing irregular structural attributes in non-stationary textures. Inspired by the frequency and space domain duality, a non-stationary texture synthesis method based on hidden layer Fourier convolution is proposed in this study. The proposed method uses the generative adversarial network as the basic architecture, performs feature splitting along the channel in the hidden layer, and builds a local branch in the image domain and a global branch in the frequency domain to consider visual perception and structural information. Experimental results show that this method can handle structurally challenging non-stationary texture exemplars. Compared with state-of-the-art methods, the method yielded better results in the learning and expansion of large-scale structures.

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    An image caption generation algorithm based on decoupling commonsense association
    Jiawei LIU, Xin LIN
    2024, 2024 (2):  131-142.  doi: 10.3969/j.issn.1000-5641.2024.02.014
    Abstract ( 36 )   HTML ( 3 )   PDF (1781KB) ( 25 )   Save

    The image caption generation algorithm based on decoupling commonsense association aims to eliminate the interference of commonsense association between various types of entities on the model reasoning, and improve the fluency and accuracy of the generated description. Aiming at the relationship sentences in the current image description that conform to common sense but do not conform to the image content, the algorithm first uses a novel training method to improve the attention of the relationship detection model to the real relationship in the image and improve the accuracy of relationship reasoning. Then, a relation-aware entity interaction method was used to carry out targeted information interaction for entities with relationships, and the relationship information was strengthened. The experimental results show that the proposed algorithm can correct some commonsense false relationships, generate more accurate image captions, and obtain better experimental results on various evaluation indicators.

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    Skinning in character animation based on implicit surface
    Sijing RAO, Ying XIN, Junjun PAN
    2024, 2024 (2):  143-156.  doi: 10.3969/j.issn.1000-5641.2024.02.015
    Abstract ( 42 )   HTML ( 5 )   PDF (1376KB) ( 49 )   Save

    This paper presents a method for skinning in character animation, utilizing implicit surfaces, which is designed to deform animated models with skeleton and associated skinning weights.This method reconstructs the mesh around a given skeleton with the Hermite radial basis function and Poisson-disk sampling on surfaces.This process transforms the character’s volume into a set of localized 3D scalar fields and preserves the original mesh properties.Field functions are then constructed and employed to refine the results obtained from the geometric skinning technique.The implicit method, combined with two types of combination operators, generates realistic skin deformations around the human skeleton model finally.The method does not cause candy twist and joint swelling problems, and can handle skin collision and muscle protrusions.Due to its post-processing feature, this method is very suitable for animation generation in standard production pipeline.

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