bluuebunny/crossref_metadata_2025_split huggingface dataset:
Information Flow and Optimization Model in Counselor-Student Interaction in Higher Education Civics
Authors: Dong Yekai 
Published: October 2024

Abstract
With the continuous development of the information society, the information flow model makes the counselor able to transfer some civic and political knowledge to the students more quickly, while the students can get the latest information more feverishly. This paper, recognizing the impact of information flow on civics education in colleges and universities, introduces an enhanced information flow model. It specifically builds an information flow and optimization model using network information technology and information analysis. The article employs an open Civics class at a university as an empirical research object, delving into the proposed information flow model to examine the real impact of Civics teaching on teacher-student interaction. The analysis of students’ learning of the six Civics objectives reveals an improvement in their overall literacy, as evidenced by the quantitative scores of the pre-test and post-test, which are 3.051 and 3.999, respectively, with a 0.948 difference in value pursuit. The analysis of classroom organizational differences reveals that the experimental group has a behavior management score of M = 5.62, while the control group has a score of M = 4.73. This indicates that the teachers of civics courses in the experimental group are capable of providing clear and forward-looking instruction in behavior management, ensuring that students’ behavior management is in place.
Big Data Analysis and Decision Making Optimization in International Relations Supported by Constructivist Theory
Authors: Wang Xiaorong , Wen Jie 
Published: October 2024

Abstract
With the peaceful end of the Cold War and the deepening development of economic globalization, the traditional international relations theory is in trouble, and constructivism comes into being amidst people’s reflections on neorealism and neoliberalism. This paper proposes an optimization method for decision-making in international relations, guided by the constructivist international relations theory system. Big data is used to analyze the decision-making opinions of experts in international relations processing and to fuse complex relationships, and then the dual-consensus feedback mechanism is used to calculate the comprehensive score of each international relations decision-making scheme to obtain the optimal decision-making scheme in international relations. The analysis finds that the solution obtained using the method proposed in this paper is better than the solution obtained using the JIA method and can provide the optimal decision-making solution for processing international relations. In the simulation case, after optimizing its decision-making in international relations, country T actively engages in economic and trade exchanges with country M and jointly establishes several economic cooperation frameworks. The export trade volume of country T to country M increased by about three times from 2016 to 2023, and the total global trade volume of country T doubled by nearly five times (481.97%). The paper’s impact can be seen in the establishment of relatively stable international relations and the realization of the practice of friendly interaction between state subjects.
Modern methods for solving partial differential equations of parabolic type and their mathematical theoretical foundations
Authors: Wu Changzhong 
Published: October 2024

Abstract
In this paper, the existence problem of weak solutions in partial differential equations is first discussed. Secondly, the parabolic-type partial differential equation (PDE) model with non-chiral terms is used to portray the coupling principle of microwave heating dielectric medium, and the approximate models of TEM and TE10-wave microwave heating are constructed and verified by comparing with the COMSOL model in simulation. An open-loop type iterative learning control algorithm is proposed for the distributed parameter system, and the effectiveness of the control algorithm proposed in this paper is theoretically demonstrated. It is concluded that the TEM and TE10-wave microwave heating approximation models are more successful in describing the microwave heating process than the COMSOL model, and the consistency of the simulation results fully proves the correctness and effectiveness of the proposed model. The paradigm of the system output error decreases with the increase in the number of system runs, and the paradigm of the system output error tends to be close to zero.
Research on the Innovation of Teaching Mode of Orienteering Sports Courses in Colleges and Universities Based on Mobile Intelligent Terminals
Authors: Zheng Zhufei , Lei Wu , Bing Zhou 
Published: October 2024

Abstract
This paper studied motion state recognition algorithms using acceleration signals (ACC). At the same time, research is also being conducted on ECG motion artifact suppression algorithms and respiration rate detection algorithms. Based on this, we designed a mobile intelligent terminal sports app that allows users to view physiological signals and sports status in real time at any time. In college and university orienteering classes, the mobile intelligent terminal movement app is used to teach the sport. The results of comparing the experimental group and the control group in the orienteering course show that the mobile intelligent terminal orienteering teaching makes a significant difference in the men’s physical quality, except for the seated forward body flexion (P<0.05). There were significant differences in the women’s group in terms of 50 m running (P = 0.013) and 800 m (P = 0.042). The experiment improved the dimensions of the Orienteering Campus Short Distance Test, Learning Motivation Indicator, and Emotional Management.
Research on Narrative Landscape Design Strategies for Theme Parks Based on Intangible Cultural Heritage Perspectives
Authors: Zheng Weiqing 
Published: October 2024

Abstract
Intangible cultural heritage is characterized by uniqueness, diversity, locality and ethnicity, and its integration into the narrative landscape design of theme parks is an important way for the inheritance and development of non-heritage culture. The article explores the narrative landscape design techniques used in theme parks and the types of narrative sequences used. Relying on the existing research, the evaluation index system of theme park narrative landscape design is established, the weights of evaluation indexes are solved by the entropy weighting method, and the EWM-TOPSIS model is combined with the TOPSIS method to realize the comprehensive evaluation of narrative landscape design. The satisfaction of narrative landscape design in theme parks in Province Y was analyzed using six theme parks as research objects. The evaluation index for narrative landscape design of theme parks found that aesthetic perceptibility had the most weight at 28.72%, while historical readability had the least weight at 14.27%. The comprehensive evaluation index of the theme park is the highest at 0.314, and the mean values of public satisfaction and importance for the theme park’s narrative intangible cultural heritage landscape design are 3.969 points and 4.049 points, respectively. Narrative landscape design for theme parks that celebrate intangible cultural heritage can help the public experience the charm of intangible cultural heritage.
Application of Hierarchical Analysis of the Efficacy of Digital Resource Integration in Mathematics Teaching and Learning
Authors: Li Ling 
Published: October 2024

Abstract
At present, the construction and application of digital teaching resources is no longer an educational development trend but a normalized teaching tool. The purpose of this paper is to analyze the principle of digital integration of resources for teaching mathematics and develop the FAHP-Entropy model. Determine the weights of the first-level indicators in the hierarchical model constructed in this paper, then determine the weights of the second-level indicators by the entropy method, and use the fuzzy comprehensive evaluation method to carry out a comprehensive evaluation of the established indicators and then get the results. The study found that the total score of the fuzzy comprehensive evaluation of algebraic knowledge points is 83.825 points, and the secondary indicators are all above 75 points, with the highest being that D1 can make students’ analytical problem-solving ability improve significantly, up to 91.21 points. Most of the secondary indicators are in the first and second quadrants, of which A1 and B1 continue to maintain the zone in the first quadrant with high importance and good evaluation results. The fourth quadrant focuses on the improvement area with two secondary indicators, A4 and C1, indicating that A4 media presentation is diversified and C1 media is well-produced and attractive, both of which need to be further improved. The scores of the four first-level indicators in the comprehensive evaluation results of the geometry category are 81.111, 86.061, 82.525, and 82.957, respectively, and the highest among the second-level indicators is D3, with a score of 87.76. A1, A4, and C1 are in the fourth quadrant of the key improvement area, which is an indicator that does not match the importance of the results of the evaluation and is in urgent need of improvement. The Probability Statistics category had a slightly lower overall evaluation score than the Algebra and Geometry category of knowledge points. The total score of the comprehensive evaluation results was 81.898. The four primary indicators have scores of 80.438, 84.01, 79.901, and 83.281. The evaluation results of the A4 and C1 indicators are not aligned with their importance, and the other indicators perform better or have lower importance. This study provides new ideas for the analysis of the effects of digital resource integration.
Research on Optimizing English Translation Teaching Methods for College Students Using Machine Learning Technology
Authors: He Tong 
Published: October 2024

Abstract
With the changes in the market situation for English majors, teaching English translation in colleges and universities is also facing many challenges. This paper proposes an optimization strategy for English translation teaching methods by using machine learning technology to automatically identify English translation errors and extract text summaries. Pearson coefficient and multi-feature fusion technology are used to prejudge the correctness of English translation results, and according to the directed graph of wrong translation results, the automatic identification algorithm of English translation errors is constructed to automatically identify translation errors. The unsupervised machine learning TextRank algorithm is introduced and applied in text summary extraction, and combined with a multi-feature fusion computer system based on similarity relationships, it is improved to enhance the efficiency and quality of text extraction. Inner Mongolia Normal University set up an experimental class and a control class and applied this paper’s technology to practice English translation teaching. After the practice, the total English translation score of students in the experimental class was 85.74, which was 4.41 higher than that of the control group, showing a significant difference (P<0.05). Prior to the practice, the interest and attitude toward English translation rose from 3.42 and 2.43 to 4.32 and 4.75, while the control group’s mean values decelerated slightly. The two dimensions of teaching satisfaction, learning atmosphere, and English translation ability development were also higher than the control class by 0.71 and 0.91, indicating a statistical difference (P<0.05).
Design and optimization of high-precision servo control system in precision positioning technology
Authors: Zhang Xiaowei 
Published: October 2024

Abstract
High-precision control technology, as a general technology in the field of manufacturing and assembly, is widely used in high-end manufacturing equipment such as chip packaging equipment and high-speed CNC machining centers. In this thesis, a permanent magnet synchronous motor is used as the actuator motor of a high-precision servo control system, and vector control strategy and sliding mode observer are adopted to study and realize the servo control of permanent magnet synchronous motor based on sliding mode observer. The current, speed, and position simulation experiments of the high-precision servo control method are also carried out to compare the positioning accuracy before and after the use of the servo control method and to study the performance of the method in precision positioning. The experiments prove the correctness and effectiveness of the SMO-based PMSM high-precision servo control method and the current response speed of the servo control in this paper is fast, and the speed and position estimation errors are maintained within 1.6 r/min and 0.15 rad in steady state condition, and within 20 r/min and 20 rad in the sudden-change condition, which is able to contribute to 11.91% and 19.30% of the machine’s X-axis and Y-axis positioning accuracy improvement. The SMO-based PMSM high-precision servo control method has high steady-state accuracy and immunity to disturbances and can be used for the precision positioning of machine systems.
Practical Exploration of Augmented Reality Technology in Engineering Project Site Management
Authors: Sun Wenbo 
Published: October 2024

Abstract
In recent years, with the rapid development of augmented reality technology, its technical application fields have become more and more extensive. This paper studies the application of augmented reality technology in engineering projects, mainly including target detection technology, feature matching technology, and 3D modeling technology. The article first improves YOLOv5 based on the original YOLOv5 algorithm by integrating the attention mechanism. The SURF algorithm is improved, the FAST-SURF algorithm is adopted for feature extraction and matching of images, and an engineering project simulation system is designed using augmented reality technology. Then, the improved YOLOv5 algorithm was tested for performance, and the experiment concluded that the improved YOLOv5 algorithm has high precision and recall. For experimental analysis of image stabilization based on feature matching, the ORB model and FAST-SURF were used. The experimental results are in line with expectations, and FAST-SURF has a good virtual fusion effect for images. This paper takes the electromechanical engineering project as a case for simulation experiments and uses Monte Carlo method simulation to verify the reliability of the method, for which traditional technology and augmented reality technology were used to predict the project duration of the project engineering. The results show that the project duration prediction cycle based on augmented reality technology is shorter, the project plan is more feasible, and the probability of achieving the project duration with augmented reality technology is stable at about 40.
A study on graph neural network correlation analysis and real-time evaluation for cigarette production quality management
Authors: Gao Yulei , Wu Yongxing , Zhang Sheng , Wang Zhengguang , Li Shuen , Su Yifan 
Published: October 2024

Abstract
The technological era has greatly promoted the informatization of the cigarette production process, making it a hotspot for research on how to use production data for quality management and correlation analysis. The article employs Pearson’s correlation coefficient and the Apriori algorithm to identify the frequent item set and correlation structure associated with the quality management of cigarette production, as well as to identify the key factors that influence this quality management. Then, we combined historical data and prioritized data points with Lajda’s law to split the distribution of events, enabling accurate construction of the item event library and single-point data factor search analysis. Finally, based on the results of correlation and causal analysis, the FDGM model for time series analysis is constructed using a priori knowledge combined with graph neural networks to realize causal learning and real-time prediction and evaluation of cigarette production quality management. The correlation coefficient between the total downtime and the production efficiency after removing the cumulative effect is 0.946, and the enhancement degree of the strong correlation rules is all greater than 1.55. The prediction F1 value of the FDGM model can be up to 0.910, and the importance of cigarette temperature in production quality is the largest at 90.62%. The evaluation score for silk production quality improved from 91.58 to 97.74, with an overall improvement of 6.73%. The combination of graph neural networks and correlation analysis algorithms can effectively detect abnormalities in cigarette production quality management and improve the quality of cigarette production.
Multimedia Delivery and Teaching Innovation of Civic Value in Art Education in the Digital Media Era
Authors: Xiao Lei , Yan Lili 
Published: October 2024

Abstract
The rapid development of information technology and multimedia education in today’s world has led to important changes in the delivery of ideological values in the process of art education. In this paper, according to the form of multimedia presentation of knowledge, a multimedia learning cognitive model is used to study the process of multimedia transmission of Civic and political values. A diverse and efficient recommendation algorithm is proposed, and a recommendation system for Civics and Politics courses is constructed based on the algorithm. The method mines the set of high-efficiency items related to the relationship between courses and categories through a conceptual hierarchical tree and introduces a diversity upper bound function to optimize the mining process. Thus, rules are efficiently generated in the efficiently used generalized itemsets. A collaborative filtering algorithm between users and course types is used to find the neighbors that best match the target users. The results show that the four indicators of this paper’s recommender system are better than other recommender methods. The F-measure of this paper’s system is 0.45, which indicates that this paper’s method can produce the best recommendation effect of the Civics courses. The students in the process of art education can get the Civics course recommendation that is more suitable for them, which improves the efficiency of the Civics value transmission among students.
Red blood cell extended antigen typing in Omani patients with sickle cell disease to enhance daily transfusion practice
Authors: Breiki Amal Salim Al , Kindi Salam Al , Castilho Lilian 
Published: October 2024

Abstract
Many Omani patients with sickle cell disease (SCD) undergo red blood cell (RBC) transfusions that are only matched for ABO and D, making RBC alloimmunization a significant concern in this population. Currently, the integration of molecular assays and hemagglutination testing helps to determine RBC phenotypes and genotypes, facilitating the provision of compatible blood and minimizing additional alloimmunization risks in patients with SCD. Based on this finding, our objective was to use molecular methods to predict the extended antigen profile of Omani patients with SCD across various blood group systems including Rh, Kell, Duffy, Kidd, Colton, Lutheran, Dombrock, Diego, Cartwright, and Scianna. This approach aims to implement RBC matching strategies and enhance daily transfusion practices for these patients. Molecular methods encompassed multiplex polymerase chain reaction for RHD, BeadChip arrays for variants of RHD and RHCE, and ID CORE XT for the primary allelic variants of RBCs. This study enrolled 38 patients with SCD, comprising 34 patients with homozygous HbSS, 1 patient with HbSC, and 3 patients with HbS Oman. The predominant ABO blood group was group O, observed in 44.7 percent of patients, followed by group A in 21.1 percent and group B in 13.2 percent. The most prevalent Rh phenotype predicted from the genotype was D+C+E–c+e+, identified in 34.2 percent of patients. All patient samples were K–, exhibiting the k+ Kp(b+) Js(b+) phenotype, with 81.6 percent demonstrating Fy(a–b–) due to the homozygous FY*02N.01 genotype and 28.9 percent displaying Jk(a+b–). RH variant alleles were detected in five patients (13.2 %), with only one type of RHD variant (RHD*DIIIa) and one type of RHCE variant (RHCE*ceVS.02.01) identified. Alloantibodies were present in 26 patients (68.4%). This study presents the initial comprehensive report of extended RBC antigen profiling in Omani patients with SCD, revealing disparities in the prevalence of RBC phenotypes compared with SCD patients from other regions and countries. Furthermore, our findings underscore a high rate of alloimmunization in these patients, emphasizing the need to implement antigen-matching programs to improve daily transfusion practices.
A challenging case of hemolytic disease of the fetus and newborn (HDFN) due to anti-Ku in a K0 (Kellnull) mother
Authors: Wan Mohd Hasni Siti A. , Ahmad Nor H. , Ganeshan Muniswaran , Yong Soon L. , Tan Pei P. , Wahab Rahimah Abdul , Musa Rozi H. , Muniandi Gunaseelan , Nakulan Ambika , Hassan Afifah 
Published: October 2024

Abstract
Hemolytic disease of the fetus and newborn (HDFN) due to an antibody in the Kell blood group system can be associated with severe fetal anemia. This case report details the challenges of managing a Kellnull mother with anti-Ku that affected her fetus/newborn. A gravida 4 para 3 woman at term underwent an emergency lower caesarean section because of fetal distress. The baby was intubated because of low oxygen saturation. An urgent request for a hematology workup showed severe anemia and erythroblastosis fetalis. Unfortunately, no compatible blood was found, and the baby died. The case was referred to the National Blood Centre, and anti-Ku was confirmed in a sample sent from the mother. When she presented with her fifth pregnancy, meticulous planning was used to manage this pregnancy. Her family screening revealed one brother with a matching phenotype. Three blood donations were planned for the brother—for freezing, for intrauterine transfusion, and for standby during delivery. Serial anti-Ku titrations of maternal samples were performed, and the fetus was monitored for anemia through middle cerebral artery Doppler scans. Although the anti-Ku titers reached as high as 1024, fetal anemia was never diagnosed. The neonate was delivered safely but was diagnosed with severe pathologic jaundice and anemia secondary to HDFN and congenital pneumonia. The baby was transfused with K0 packed red blood cells and later discharged to home.