Table of Content

15 December 2024, Volume 9 Issue 12

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Adjoint Polynomials and Unimodality of Stable Set Partitons

Yang Limin, Yang Jiaoyan

2024, 9(12):  1-11.  DOI: 10. 3969 / j. issn. 2096-2266. 2024. 12. 001

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To study the unimodality of stable set partitions, the concept of its adjoint polynomials is proposed and the adjoint polynomials of several graphs are obtained. Using the adjoint polynomials, the unimodality of various graphs is demonstrated, including star graphs, complete products of star graphs, complete q-partite graphs,（ n-2） - regular graphs, complete products of（ n-2） - regular graphs, etc. Furthermore, the number of all possible partitions of stable sets is calculated skillfully. Finally, a generalization of the unimodal theorem is extended, and several classical examples are derived. In addition, a generalization of one form of the Newton inequalities is given, and a series of related inequalities are obtained.



Properties of Firecracker and Firecracker-Like Graphs

Hou Shengzhe

2024, 9(12):  12-17. 

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Firecracker graphs have good symmetry, extensibility and practicality. Their modes are widely used in fields such as electrity and organic chemistry. This paper mainly investigates the adjacency matrix, nullity, matching number and independence number of firecracker graphs. Additionally, the Hosoya index of firecracker-like graphs is provided.



Exact Solution of the（ 3+1）-Dimensional Boussinesq Equation Using the F-Exp Method

Ding Li

2024, 9(12):  18-24. 

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The F-Exp method is utilized to obtain the solitary wave solutions of the （3+1）-dimensional Boussinesq equation. The
waveform diagrams of several typical solutions are obtained by Maple software. This method can also be applied to the solution of other
nonlinear evolution equations.


Uniform Convergence and Algorithm of Lagrange Interpolation Method

Yuan Yuan

2024, 9(12):  25-29. 

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To solve the problem that Lagrange interpolation polynomials do not uniformly converge for any continuous function, the
convergence is improved by the Bernstein-type operator with the one-point correction method and the trigonometric interpolation
polynomial operators and algebraic polynomial operator with the two-point correction method. The one-point correction method is used to construct an algebraic polynomial operator Fn ( f;x)（Bernstein-type operator）, two-point correction method is used to construct trigonometric interpolation polynomial operator Tn ( f; r, x)（ r is a natural number）, and algebraic polynomial operator Gn, R ( f; x)（ R is a natural number）, and a specific program is written in C language to analyze the superiority and inferiority of its approximation effects. The results show that compared with Lagrange interpolation polynomial operators, the Bernstein-type operator, trigonometric interpolation polynomial operator and algebraic polynomial operator optimized by the one-point correction method and the two-point correction method have faster running speed, smaller error values, and closer convergence results to the exact solution.


Relative Granularity Incremental Attribute Reduction Algorithm Based on Relational Matrix

Wang Jihe

2024, 9(12):  30-35. 

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Attribute reduction is an important data processing method in rough set and granular computing theory. In view of the
shortcomings of traditional attribute reduction algorithms in dealing with dynamic data problems and based on relative granularity, the
incremental change mechanism of relative granularity changes is studied using relational matrix when the objects of the decision
information system change. According to this change mechanism, a relative granularity incremental attribute reduction algorithm based on relational matrix is proposed to improve the efficiency of attribute reduction.



Modeling and Simulation Analysis of Regional Climate Complex Hierarchical Network in Yunnan Province

Ma Xin, Wang Caikui, Hu Anshun, Liu Xuan, Fang Lianbiao, Luo Guilan

2024, 9(12):  36-45. 

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To solve the destructive impact of climate change in Yunan Province on human production, life, and the ecological environment and to understand the main influencing factors of climate change in this area, this study uses the complex network theory to abstract meteorological stations into network nodes based on the climate data of 32 meteorological stations in Yunnan Province from
1984 to 2016. The Pearson correlation coefficient is used to determine the connection weight of edges. A single-layer and hierarchical
climate complex network model in Yunnan Province are constructed, and the network characteristic parameters and stability are
analyzed. The research finds that in single-layer networks, the correlation between temperature, pressure, relative humidity, and wind
speed networks are strong, while the correlation between precipitation and sunlight networks is weak. According to the results of
principal component analysis and single-layer network experiments, temperature, pressure, and relative humidity are the main
influencing factors of climate change in Yunnan Province. In the hierarchical network, temperature has a strong negative correlation
with pressure, relative humidity, and precipitation, temperature mainly shows a strong positive correlation with wind speed and
sunlight. There is an inherent correlation between various meteorological elements. Deletion of the three meteorological factors of
temperature, relative humidity and pressure would significantly damage the stability of the entire network. Therefore, it is recommended to protect the climate and environment of Yunnan Province from these three main influencing factors.


Identity Authentication System Based on QR Code and Face Recognition

Feng Dacheng, Zhang Lulu, Li Hui

2024, 9(12):  46-50. 

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To solve the problems of identity information leakage and document forgery in traditional identity authentication methods using manual verification or RFID card, an identity authentication system based on QR code and face recognition is designed.This system adds QR code scanning technology on the basis of face recognition technology. In the registration stage, the system generates a
specific QR code identifier for each individual. In the recognition stage, face scanning and QR code scanning are combined to find the
corresponding face image in the face image database. The performance of the system is verified by conducting face recognition tests of 43 volunteers.The results shows that the recognition rate of the system is above 94.56%. This not only solves the problem of high
manufacturing cost of RFID cards, but also reduces the probability of identity information leakage and documents forgery.


Masks-Wearing Face Recognition System Based on RetinaFace and FaceNet Algorithms

Pei Yi, Liu Guangyu, Lei Yuanbin, Zhang Jilei, Chen Bobo, Zhao Hongyi, Zhao Enming

2024, 9(12):  51-57. 

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During the epidemic outbreak, wearing masks has become an important public epidemic prevention measure. However, masks will lead to a reduction in recognition accuracy and a slowdown in detection speed of image-based face recognition systems. This study designs a masks-wearing face recognition system based on RetinaFace and FaceNet algorithms. First, the RetinaFace algorithm
is used to train the RetinaFace model to realize the face key point positioning function. Secondly, the FaceNet algorithm is used to train
the FaceNet model to extract the face feature vector and build a feature database. Finally, by comparing a Euclidean distance between
the facial feature vector to be recognized and the vectors in the database, the recognition result is output. The experimental results show that the recognition speed of the system after RKNN model conversion exceeds 25 f/s. On the dataset Mask-LFW, when the Euclidean distance threshold between feature vectors is set to 1.01, the ACC is up to 93.78%, and the AUC is 91.03%. The system meets realtime requirements and has high detection accuracy, which can be used in laboratories, company offices, factories and some public places.


Cattle Posture Estimation Based on YOLO Algorithm

Chen Bobo, Lei Yuanbin, Zhang Jilei, Zhao Hongyi, Luo Chuang, Zhao Enming

2024, 9(12):  58-64. 

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Cattle posture estimation plays a crucial role in analyzing cattle behavior and evaluating cattle health. To address the problem that cattle cannot be monitored around the clock and corresponding behavioral information cannot be obtained in a timely manner, the YOLO algorithm is used to study cattle posture and establish a cattle posture estimation model for identifying cattle and extracting their skeleton structure. The test results show that compared with YOLOv7-w6-pose, the YOLOv8n-pose cattle posture estimation model has increased accuracy, recall rate, and mean average accuracy at Loks=0.50（mAP0.50） by 4.7%, 3.0%, and 2.7%,
respectively. The model parameter and computational complexity have decreased by 59.2% and 91.0%, respectively, and the average
detection time per single image has decreased by 5.74 ms. The YOLOv8 cattle posture estimation model has high accuracy and
inference speed, providing a reliable and valuable reference for cattle posture estimation in large-scale animal husbandry.


Comparative Analysis of Swarm Intelligence Optimization Algorithm Based on WSN Network Coverage Optimization Problem

Song Jie, Hu Yongmao, Luo Yanbi

2024, 9(12):  65-73. 

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To address the issue of low coverage rate caused by random deployment method in wireless sensor network（WSN）, this
study compares and analyzes various swarm intelligence optimization algorithms, including particle swarm optimization（ PSO）, artificial bee colony algorithm （ABC）, glowworm swarm optimization （GSO）, grey wolf optimizer （GWO）, ant lion optimization （ALO）, manta ray foraging optimization （MRFO）, sparrow search algorithm （SSA）, artificial rabbits optimization （ARO）, hunter-prey optimization（HPO）, and dung beetle optimizer （DBO） based on WSN network coverage problem. The performance of the algorithms is compared and analyzed through single-objective optimization and multi-objective optimization. The simulation results show that the performance of different algorithms is different under the same conditions and the performance of the algorithms is better as the area of the monitored region increases. Among the above algorithms, GWO, MRFO, ARO and HPO algorithms are more suitable for solving the WSN network coverage problem. Multi-objective optimization based on coverage, movement distance, and connectivity is better than single-objective optimization based on coverage alone in terms of algorithm performance for the WSN network coverage problem.


Practice of the Case Library Construction of Signal Courses for Professional Master's Students  in Dali University 

Liu Guangyu

2024, 9(12):  74-78. 

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Based on the 2022 Yunnan provincial professional graduate course case library construction project "Construction of the teaching case library for signal courses in electronic information programs for professional master's students in Applied Universities", this study reflects and summarizes the construction work around the teaching content of "Modern Signal Processing Technology" course
for the classroom teaching and training of professional master's students in Dali University. Some suggestions are put forward from
several aspects, such as the role of case library construction, the basic principles of construction, the purpose of case teaching, key
knowledge points, the formation of the construction team and the development ideas of the teaching case library, for the reference of
relevant researchers and scholars.


Analysis of Autumn Nocturnal Migratory Birds Diversity in Nanjian Fenghuang Mountain from 2018 to 2022

Cui Maohuan, Shi Guocai, Luo Zengyang, Li Jian, Xu Jiawu, Yuan Yuchuan

2024, 9(12):  79-90. 

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The ringing data of autumn nocturnal migratory birds from 2018 to 2022 at the Nanjian Fenghuang Mountain Bird Banding Station were analyzed. The results are as follows: （1） A total of 8 459 migratory birds of 188 species belonging to 38 families and 11 orders were captured in 5 years. The dominant species were Ficedula albicilla, Ardeola bacchus and Calliope calliope.（ 2） The bird diversity index is 3.931 9, the uniformity index is 0.750 9, the dominance index is 0.038 1, the F index is 17.317 0, the G index is 4.252 5,
and the G-F index is 0.754 4. The diversity of migratory birds is relatively high at the family, genus levels. （3） The highest similarity
index of migratory birds in different years is 0.780 9 and the lowest is 0.710 5.（ 4） There are 15 species of wild birds under national key protection, 4 species of birds listed in Appendix Ⅱ of The Convention on International Trade in Endangered Species of Wild Fauna and Flora, and 14 species of birds listed in The Red List of China's Vertebrates.（ 5） In different areas of Yunnan such as Nanjian Fenghuang Mountain, migratory birds are mainly Passeriformes, which is different from the migratory birds in Pingfengjie of Hunan Province, Jiuwan Mountain and Damao Mountain in Guangxi Province, which are mainly Ciconiiformes waterfowl. （6） The diversity of migratory birds in Nanjian Fenghuang Mountain was higher than that in Dazhong Mountain of Nanhua, Longqingguan of Weishan and Jinshan Yakou of Xinping in neighboring areas. The bird diversity index, uniformity index with the dominance index are significantly negatively correlated, while the G-F index is not highly correlated with the dominance index.


Yielding Ability, Stability and Adaptability of New Maize Varieties in Yunnan Province

Sun Lu, Liu Chaorui, Yao Sidan, Yin Xiaohua, Ye Zhilan

2024, 9(12):  91-98. 

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To objectively and comprehensively analyze the yielding ability, stability and adaptability of new maize varieties in Yunnan
province, a two-year randomized block experiment was conducted on 14 new maize varieties at 12 regional pilot sites in Yunnan
Province from 2019 to 2020. Haihe No.2 was used as the control variety. Variance analysis, coefficient of variation analysis, fitness
analysis, C.S.lin and AMMI methods were used to comprehensively analyze the yielding ability, stability and adaptability of the new
varieties. The results showed that the interaction among varieties, pilot sites, and between varieties and pilot sites reached a highly
significant level. The tested varieties Diyu 403, Diyu 503 and Jinli 66 are relatively ideal varieties with good yielding ability and
stability. Xuanwei is the most ideal pilot sites, with strong variety selectivity, which is conducive to breeding excellent maize varieties.
This study evaluated the production performance of a series of new maize varieties in Yunnan Province, laying a theoretical and
practical foundation for promoting the development of maize industry and the ecological layout of plateau characteristic agriculture in
Yunnan Province.


Correlation between Yield and Agronomic Traits of 29 New Maize Hybrid Varieties in Yunnan Province

Yin Xiaohua, Ma Chenyu, Liu Chaorui, Yao Sidan, Sun Lu, Ye Zhilan

2024, 9(12):  100-106. 

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Using grey relational degree analysis method, 29 new maize hybrid varieties in Yunnan Province were used as experimental
materials to analyze the correlation between agronomic traits such as plant height, ear height, ear length, ear diameter, bald tip length,rows per ear, kernels per row, hundred-grain weight, kernel rate and water content with yield. The results showed that the order of relational degree between yield and each agronomic trait was as follow: ear length＞kernel rate＞plant height＞ear height＞hundredgrain weight＞ear diameter＞rows per ear＞kernels per row＞water content＞bald tip length; the order of correlation between yield and each agronomic trait was as follow: kernel rate＞hundred-grain weight＞ear diameter＞plant height＞ear height＞rows per ear＞ear length＞bald tip length＞kernels per row＞water content. The varieties with the best comprehensive evaluation were Yuanyu 1505, Linxin 11 and Zhuyu 818. In this study, excellent new maize hybrid varieties were screened out, and the primary and secondary
relationship of each agronomic trait on yield was clarified, which could provide a theoretical basis for the selection of high-yield and
high-quality maize hybrid.


The Structural Evolution and Optimization of Railway Logistics Network in China

Zeng Fanlong, , Wang Mengyuan, Sun Huaping, Zhang Yongzheng

2024, 9(12):  107-114. 

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From the perspective of network and based on the gravity model and complex network theory, this paper studies the evolution of the railway logistics network structure in China from 2015 to 2021. The results show that:（ 1） The scale of railway logistics in China and the inter-provincial railway logistics connections are generally strengthened, and basically synchronous development between regions is achieved. Among them the acceleration of railway logistics development in Xinjiang is the most significant.（ 2） The regional development of railway logistics in China is unbalanced and there is a "Matthew Effect". The development speed of railway
logistics in Hainan, Xizang, Shanghai, and Qinghai is seriously lagging behind. （3） The centrality is significantly improved, and the
external radiation capabilites of central provinces in the railway logistics network, such as Shanxi, Nei Mongol, Shaanxi, and Shandong is enhanced.（ 4） The "Small World" characteristic is significant. From 2015 to 2021, the five major communities evolved into three major communities, with Shanxi-Hebei-Nei Mongol, Shandong-Henan-Shaanxi, and Guangdong-Guizhou-Sichuan as the main development axis chains. On this basis, optimization measures for the railway logistics network structure in China are put forward.