bluuebunny/crossref_metadata_2025_split huggingface dataset:
Study on storage technology of corn wax based ice cream
Authors: Zhao Menglan 
Published: August 2024

Abstract
Ice cream is a complex food colloidal system; saturated fat is an essential element given the taste and texture of ice cream (viscosity, hardness). In recent years, research on fat ice cream has focused on adding fat substitutes. Looking for a suitable source of lipid-based fat substitute instead of fat ice cream, developed more conducive to human health, low in saturated / zero trans fatty ice cream products. The study will use linoleic acid-rich soybean and corn oil gel waxes as a fat source for ice cream, make gel-oil-based ice cream, and study changes in its quality during storage. With an incremental storage time index, we can inspect the effects of different storage times on melting rate, hardness, and fat globule diameter changes. The hardness and melt rates show an increasing trend while the fat globule diameter decreases. We found that the quality of ice cream has reduced over time, but it does not affect the sensory evaluation. By analyzing the acidity, peroxidation value, and F.A. composition changes, we found that the acidity and peroxidation values are low, indicating that the shelf-life of ice cream gel is higher due to using better quality fresh oil. The fatty acid composition did not change during storage, and no trans fatty acids were produced.
Optimization study of computational methods in coordinated integrated carrying capacity assessment of multi-voltage hierarchies
Authors: Wang Huibin , Liu Zhaozheng , Li Chunchao , Wang Yuxi , Zhang Gengxi 
Published: August 2024

Abstract
In this paper, we take a two-level distribution grid as the infrastructure of a multilevel distribution grid and study the comprehensive carrying capacity assessment model in depth. The minimum value of the maximum access capacity under each scenario is used to assess the maximum carrying capacity of the distribution network, and the maximum access volume of the multilevel distribution network is taken as the objective function, and the particle swarm algorithm is improved to establish the maximum carrying capacity assessment model. Using the alternating direction multiplier method, a two-level distribution grid carrying capacity distributed optimization model is established, and the multilevel distribution grid access volume problem is transformed into the maximum access volume subproblem at all levels of the distribution grid. Comparing the whale algorithm and particle swarm algorithm, the model in this paper converges at 7465 kW access capacity and about 12 iterations, respectively, and the weak degree is below 0.4 at different distribution network states, which is a good performance in terms of optimization accuracy and weak degree. We conduct simulation experiments with the modified IEEE33 nodes and find that using this paper’s model to participate in optimal scheduling reduces the total operating cost of the distribution network system by more than 6.24% compared to not using it. Finally, we use the model in this paper to evaluate the comprehensive carrying capacity of the distribution network in Ningxia, China.
Machine Learning Diagnosis of Node Failures Based on Wireless Sensor Networks
Authors: Xia Jun , Zhan Dongzhou , Wang Xin 
Published: August 2024

Abstract
Wireless sensors are widely deployed to harsh environments for information monitoring, as the sensor nodes are highly susceptible to various failures, resulting in erroneous monitoring data. Sensor fault diagnosis is the subject of research work in this paper. Sensor faults are categorized based on their causes and mechanisms. Secondly, the wavelet transform, tuned Q wavelet transform, and LSTM-based neural network model are utilized for equipment fault feature extraction and fault diagnosis. The structure of the LSTM neural network, as well as the parameter settings, are completed with an adaptive moment estimation algorithm for the model training, and simulations are carried out for verification. The diagnostic accuracy of the model in this paper is as high as 97%, and the root mean square error converges to 0.02 after 170 times of training, which shows the high accuracy of the model in this paper. The training time is very short, only 1.226s, which shows that the fault diagnosis model in this paper is very efficient and meets the requirements of practical applications, proving the effectiveness of this paper’s model in wireless sensor network node fault diagnosis.
Mechanisms of data mining in analyzing the effects and trends of news dissemination
Authors: Zhang Lihong 
Published: August 2024

Abstract
Data mining techniques can help news organizations and media practitioners extract valuable information from a large amount of unorganized information, such as by analyzing the effect of news dissemination. In data mining, multiple linear regression is a widely used technical model. In this paper, we utilize the classic “cognition-attitude-behavior” analysis framework to construct a regression analysis model of the news communication effect. We solve the positional parameters according to the principle of least squares, ensuring that the regression value and all observations have the minimum residual square. We then solve the system of linear equations using Clem’s law and the Gaussian elimination method. The constructed models are used to analyze the news dissemination effect of Guangzhou’s city image on traditional news platforms and microblog self-media platforms, respectively. It is found that the news videos of “cultural image” and “ecological image” have a significant positive effect on the news dissemination effect. The longer the duration of the news video, the better the dissemination effect. In terms of the influence of event-related online opinion leaders on news dissemination, the number of comments and likes have a significant positive influence, with coefficients of 0.778 and 0.059, respectively, and both are significant at the 1% level. In addition to the number of comments and likes, the influencing factors on the dissemination of related news are the number of fans, whether there is V authentication, and whether there is microblogging membership. After conducting two empirical data mining analyses, we verified the validity of the multiple linear regression model in this paper by analyzing the effect and trend of news dissemination.
Algorithmic Complexity Research on Foreign-related Tourism English Education and Talent Cultivation Models in the Context of Free Trade Port
Authors: Chen Rulin , Hou Peixu , Huang Cheng 
Published: August 2024

Abstract
In today’s booming development of free trade ports, China, as a big country of inbound and outbound tourism, has put forward higher requirements for the talent cultivation mode of foreign-related tourism English. This paper takes the characteristics of foreign-related tourism English as the entry point and establishes the practical teaching system and the four-in-one talent cultivation mode of foreign-related tourism English. The multi-objective optimization model for cultivating foreign tourism English talents is proposed, with the objective function of enhancing the quality of foreign tourism English talents, and the corresponding constraints are set. The multi-objective optimization model is solved using the DQN model, and a strategy gradient algorithm-based model training optimization strategy is proposed. The test conditions of foreign-related tourism English talent cultivation are set, simulation experiments are carried out, and teaching experiments are compared based on the optimal scheme. The training loss obtained by the DQN model after 1700 iterations fluctuates between [0.015,0.019], and when the training period is set to 2 years, the cumulative return of foreign-related tourism English talent cultivation can reach 623.87%, and the maximum retracement is only - 5.457%. The optimal talent cultivation program’s average score is 14.1 points higher than the ordinary version. Foreign-related tourism English needs to be fully integrated with the actual demand for talent, and the faculty and policy guidelines help to enhance the quality of foreign-related tourism English talent training.
A study of innovative models of community governance under digital social policy
Authors: Bai Jie 
Published: August 2024

Abstract
Intelligent communities are based on the Internet, using vehicles, face recognition, surveillance video structuring, and other technologies to integrate the community’s government services, grid-based management, and convenient services. They also design a grid-based intelligent community service management platform to support all kinds of events closely related to residents’ lives and community management. Through relevant questionnaires, statistics, and generalizations, a comprehensive understanding of security management before and after the digital transformation of a community can be obtained. It has been observed after analysis that the detection rate of criminal cases in the public area monitoring range and the community has reached as high as 98.2% and 99.4%, respectively, following the digital transformation. There is a significant positive correlation between the dimensions of institutional remodeling, convenient services, public affairs, community governance performance, and community governance capacity. Residents are highly satisfied with grid-based community governance after digital transformation, with mean scores exceeding 3.0, according to further analysis. This paper provides a theoretical basis for the government, community, and public to promote the application of digital reform in community governance on the ground.
Three-dimensional model construction of power distribution room and its digital twin physical structure research
Authors: Feng Bin , Wang Yu , Mo Liangyuan , Yang Jing , Luo Hui , Wei Zongchun 
Published: August 2024

Abstract
Aiming at the problem of complex internal structure and difficult monitoring of the distribution room, a new monitoring method for the distribution room based on a digital twin is studied. Firstly, a 3D model design method for the distribution room is proposed by combining visualization technology and 3D Max software to complete the modeling. The 3D laser technology is used to scan the entity to get the texture photos of the 3D laser points and the raw data, then a complete model is obtained by modeling the details, and finally, the texture photos are mapped with the model to get the final model. To enhance the model’s accuracy, the optimal minimum spanning tree model optimization method is proposed, and the power distribution room’s three-dimensional model design is now finished. On the basis of the feature extraction of the sensor data of the distribution room, the digital twin technology is used to realize the matching of the information model architecture from the real entity of the distribution room to the virtual model, digital conversion, correlation of the operating data features and real-time monitoring, and then the monitoring method of the distribution room based on the digital twin is obtained. The experimental analysis yields a 3D Max modeling time of 9.98s and a fineness of 90%, which is more suitable for the construction of complex 3D models of distribution rooms than the other two methods. The accuracy of digital twin wireless communication is kept at 98% or above, and the system operation is disturbed to a small extent. It shows that digital twin technology is suitable for monitoring the complex structure inside the distribution room.
Big Data Analysis Methods for Higher Education Physical Education Teaching Interactive Platform and Its Teaching Effectiveness
Authors: Chen Xiao , Feng Jian 
Published: August 2024

Abstract
The use of big data comprehensively serves physical education, so that students can clarify their learning situation and make reasonable changes in physical education teaching. In this paper, firstly, we do an analysis and investigation on the application of big data in physical education teaching in colleges and universities, apply the tree hierarchy algorithm to collect the key data indexes of physical education teaching classrooms, and use the SMDA aggregation algorithm to aggregate and analyze the collected key data. The weight of each index system of teaching evaluation is calculated using the hierarchical analysis evaluation method. The role and application of analytical methods in physical education teaching are discussed in the context of big data. This paper constructs a system for evaluating teaching effects, which includes 5 primary indicators and 20 secondary indicators. The evaluation results of the 10-factor index system in the teaching process are divided into five grades to obtain the distribution intervals of excellent, good, medium, qualified, and poor students’ learning performance. The results of data analysis of the attributes of this paper show that the percentages of Cluster l, Cluster 2, and Cluster 3 are 22%, 66%, and 12% respectively. The weights of teaching ability, method, content, attitude, and effect in the actual teaching process were 20.97, 24.29, 24.08, 3.89, and 6.31, respectively. This paper elaborates on the effects and roles of four aspects of the interactive platform Big Data application in physical education teaching and learning in the context of Big Data analytics methods. Ideas for the use of big data analysis methods in sports teaching in colleges and universities are presented.
The Effect of Information Entropy Analysis in Computer-Assisted English Translation on Improving Translation Naturalness
Authors: Ke Jun 
Published: August 2024

Abstract
This paper borrows the concept of entropy and refers the information entropy to the computer-aided English translation to build up the information entropy assessment and evaluation model and the information entropy-based English translation optimization model. The information entropy operation formula is used to calculate the fuzziness between the original text and the target translated text, and at the same time, the segmentation function is utilized to find the approximation value of the information entropy value obtained in a sufficiently fine segmentation of the translated text. Obtain the rectangular window function of semantic Gaussian marginalization, project the information entropy data, add the semantic correlation factors of words, identify the features of semantic information, and realize the optimization of English translation. Simulation experiments are carried out to verify the performance of the model. The information entropy evaluation and analysis model in this paper can achieve convergence after 45 iterations. In contrast, the word error rate and the cut-off error rate of the English translation optimization model are both lower than 10%, and the feature recognition and classification are higher than 80%. The fuzzy statements in Chinese writer Lao She’s work “Teahouse” are selected to explore the naturalness of translation. The information entropy value of the translation optimization model in this paper is closer to the original text, and the English translation’s naturalness is better than that of the GLR model.
A Predictive Model of English Vocabulary Teaching Effectiveness Based on Bayesian Networks
Authors: Li Liwei 
Published: August 2024

Abstract
Bayesian networks are a class of probabilistic graphical models used to characterize the relationships between variables, and structure learning is a key step in Bayesian network modeling, which is the basis for network parameter learning and probabilistic inference. In this study, we introduce Bayesian networks and propose a model for tracking vocabulary knowledge based on BKT. In order to test the performance of the model, the vocabulary knowledge tracking model, including the Bayesian network model, is compared with other models by combining the learning structure algorithm and students’ learning characteristics, and the accuracy, recall, and mean square error of the model are explored to study the accuracy of the vocabulary knowledge tracking model in predicting students’ vocabulary mastery is close to 0.9, and the precision is in the interval of (0.5-0.6). In teaching, the model that predicts students’ mastery of English vocabulary in different datasets performs better than other models in practice.
Spatial data analysis model construction for landscape vegetation impact evaluation
Authors: Xue Yi 
Published: August 2024

Abstract
The impact assessment of vegetation ecosystems is inevitably combined with vegetation, soil, hydrothermal conditions, and topographic factors. This paper utilizes a combination of remote sensing imaging, monitoring, on-site data collection, and spatial information visualization to provide data information on landscape vegetation ecosystems and builds a GIS database for the process of landscape vegetation ecological analysis. Define landscape vegetation types and analyze landscape vegetation pattern indices. Combining the evolution of landscape vegetation areas with the change in vegetation type levels, the vegetation cover of landscape vegetation in the study area was calculated. Surface temperature inversion model based on Landsat atmospheric correction algorithm to get the surface temperature of the region from 2014 to 2020. Combined with the soil erosion classification and grading standards, the soil erosion model RUSLE was used to derive the soil erosion class. In 2020, the landscape vegetation of Jiuzhaigou had a high coverage of 62.79%, and the mean surface temperature generally showed a trend of increasing and then decreasing. Mild and moderate soil erosion decreases. The synthesis of vegetation cover, surface temperature, and soil erosion can indicate that the landscape vegetation ecological environment of the study area is good and in ecological balance.
The promotion of mobile Internet to the construction of informationization of ideological and political education in colleges and universities
Authors: Zheng Qiao , Li Mingxi 
Published: August 2024

Abstract
This paper explores the teaching path of the civics class in colleges and universities during the mobile Internet era, and uses a questionnaire survey to analyze the reality of current mobile Internet-based civics class instruction. The changes in the teaching of civics and political science classes under the influence of mobile internet are tracked and systematically analyzed in terms of differences. This study focuses on both the general effective education classroom and the effective education classroom in the mobile environment. It utilizes the Nvivo software to investigate the teaching styles of teachers and the interactions between teachers and students in these two learning modes. The results show that nearly 20% of the students are in schools that have not yet conducted mobile Internet civics instruction, and about 24.5% do not have political theory classes on mobile Internet teaching. In the context of mobile Internet, the habit of reading on a cell phone is increasing by 10% annually, and learners are paying the highest attention to public news sources, reaching 86.4%, which creates favorable conditions for teaching mobile Internet civics and politics. An effective education classroom in the mobile environment tends to be open; the ratio of teachers’ words to students’s words is about 2.09%, and teachers are more willing to use media resources, and network means to check students’ knowledge. And the classroom status is at 0%, and the teaching process is more stable.
A Quantitative Study of Dance Teaching and Students’ Aesthetic Ability Development in the Framework of Aesthetic Education
Authors: Zhu Yuan 
Published: August 2024

Abstract
With the deepening of today’s education reform, the development of students’ aesthetic ability is becoming more and more an important part of the education system, and dance teaching, as an indispensable part of the cultivation of aesthetic ability, is receiving more and more attention. This study takes students majoring in preschool education in colleges and universities as the research object, integrates dance teaching in music courses, conducts a questionnaire survey research, and then conducts research on the characteristics of the dance teaching mode under aesthetic education, studies the relationship of the factors between the survey object and the school dance teaching in terms of the one-way analysis of variance (ANOVA), correlation analysis, and multiple regression analysis, and further analyzes the factors influencing the development of the aesthetic ability of the students. After the analysis, it can be concluded that the place of residence has the main influence on the development of students’ aesthetic abilities, despite the individual differences of students. The integration of art courses and dance courses in schools, the degree of attention of dance teachers to students’ aesthetic ability in dance teaching, the development of dance club activities in schools, students’ participation in club activities, and the cultural atmosphere of dance on campus had high correlations with students’ aesthetic ability, with the highest correlation value of 0.412** for art courses. From the multiple regression analysis to explore the development of art courses and students’ aesthetic ability, it can be seen that the school is the main influencing factor in cultivating the development of students’ aesthetic ability towards dance, so the school should improve the content of art and culture courses and focus on the development of students’ aesthetic ability.
Analysis of value shaping education for college students in the view of ideological education in colleges and universities based on deep learning
Authors: Zhuang Huaijun , Shen Ming 
Published: August 2024

Abstract
This paper proposes a values sentiment analysis model based on RoBERTa-BiLSTM-Attention based on the mechanism and path of values process evaluation under sentiment analysis. After extracting and presenting the values and sentiment features data, we build the values dataset of college students, finish the training of the model, and obtain the classification results of values and sentiment. The college students’ value identity model is established to analyze the value shaping of education at the national, social, and individual levels. The correlation coefficients of the influencing factors of college students’ values were analyzed, and the correlation coefficients of the influencing factors were less than 0.75, and the p-value was less than 0.01. The hypotheses were put forward, and the standardized regression coefficient of the “social role model” was 0.2658, which was significantly higher than that of the other indicators, and the standardized regression coefficient of “emotional satisfaction” was 0.2658. The regression coefficient of “emotional satisfaction” is 0.1987, second only to cognitive identity. In view of the existence of the problem of values, the proposed political education intervention guidance strategy, after the political education intervention, 71.3625% of the students think that the values of guidance have a great help, but there are still some shortcomings, compared with this paper puts forward the optimization of the values of guidance recommendations.