bluuebunny/crossref_metadata_2025_split huggingface dataset:
Research on the problems and countermeasures of environmental design of rural residential areas based on deep learning model
Authors: Wei Xuemin , Cai Yonghai , Zhang Xia 
Published: September 2023

Abstract
This paper first starts by analyzing the environmental design problems of rural settlements and constructs an evaluation system of environmental design indicators of rural settlements based on the AHP-TOPSIS-POE model. Then the index weights are calculated by using the hierarchical analysis method, the priority ranking of index weights is realized by the TOPSIS method, and the feedback analysis of index evaluation is carried out based on POE theory. Finally, the validity of this paper’s index system is verified and analyzed with the example of a new rural construction and several rural residential area environmental design schemes. The results show that humanistic respect, square space and landscape greenery have weights of 0.5819, 0.5434 and 0.4463, respectively, in the environmental design of rural residential areas, and the index system can rank the advantages and disadvantages of environmental design solutions, and then provide effective environmental design solutions to improve villagers’ happiness.
A study of user data privacy protection algorithms in the context of metaverse based on emotional AI IoT
Authors: Shi Lusheng , Zhu Huibo 
Published: September 2023

Abstract
In the context of the metaverse, user data privacy protection has become an important issue. In this paper, firstly, a user data privacy leakage risk assessment scheme is designed by attribute sensitivity calculation, attribute similarity calculation, and attribute association calculation. Then a data privacy protection algorithm based on differential privacy is proposed, and the differential privacy data protection algorithm and implementation mechanism are described. Finally, the performance of the differential privacy protection algorithm is evaluated by analyzing the learning performance and protection performance of the algorithm. The results show that the learning performance of the differential privacy protection model decreases with increasing τ when q = 0 The larger q is, the better the protection performance of the model is, and the optimal τ value also shows a trend to the right. This study provides an effective method for user data privacy protection under the metaverse and offers new ideas for research in related fields.
Research on the influence of physical games in the process of preschool children’s psychological development
Authors: Hua Zhenghong 
Published: September 2023

Abstract
This paper takes preschool children as the research object, combines the knowledge of psychology education, and improves the LSTM to bi-directional LSTM combining the benefits of LSTM’s temporal characteristics with CNN’s local features while also taking contextual semantics into account to produce a C-BiL model that performs better and can be used to study how sports games affect children’s psychology. Three layers make up the entire C-BiL model: the first layer produces word vectors using CNN and Bi-LSTM; the second layer produces sentence vectors using CNN and Bi-LSTM; and the third layer produces output using Softmax. There was a significant improvement in all psychological indicators of children after 3 months of performing sports games. Among them, the total score of social skills increased from 36.01±4.95 to 41.08±1.37, and the total score of psychological resilience increased from 35.75±5.70 to 44.13±2.37 Therefore, sports games can promote children’s cognitive development, build good self-concept and self-confidence, help children’s intellectual development, and cultivate children’s resilience and positive spirit.
Research on network data transmission and compression based on compression-aware model
Authors: Mao Zhijian , Chen Xiaozhong 
Published: September 2023

Abstract
This paper first analyzes the theory of compressive sensing for wireless sensors and constructs a mathematical model of compressive sensing. Secondly, the sparse representation and observation of the signal in the compressed sensing technique are analyzed to provide the theoretical basis for the new model of P-tensor product compressed sensing based on the digital signature encryption algorithm in the later paper. Finally, the recovery performance of the model and the encryption effect is analyzed by simulation experiments. The results show that when the CR is 0.8, the PSNR values of the Lena image, Peppers image and Cameraman image are 37.608dB, 37.32884dB and 37.3428dB, respectively. 512×512 network data fragment has the shortest encryption time of 2.0156s. This shows that the compression-aware model can guarantee network data transmission security and guarantee compression quality.
The integration of English teaching and ideological and political education based on cognitive mapping constructs
Authors: Zhang Jiao 
Published: September 2023

Abstract
This paper combines the fuzzy cognitive diagnostic model and the four-parameter Logistics model to analyze students’ cognitive states of ideology, politics and English education. Following that, a design method based on fuzzy cognitive mapping is proposed based on cognitive diagnosis theory and educational goal classification theory, and the construction process of learners’ fuzzy cognitive mapping is specified from three perspectives: course knowledge mapping construction, learners’ cognitive level diagnosis, and cognitive mapping visualization. Finally, a personalized learning platform with a learning style tendency test, quantitative assessment of cognitive level, accurate construction of the cognitive map, dynamic pushing of learning paths, and similar recommendation of learning peers was constructed. The results showed that in the study of the impact of the teaching model incorporating Civics on the comprehensive level of English, a significant t=3.43 at 0.01 level, p=0.0018 was presented between the experimental group and the reference group, and the mean value of the experimental group exceeded that of the reference group by 13.23.
Planning Research on Electrically Coupled Integrated Energy System Based on ARIMA-LSTM Model
Authors: Xiang Wenle , Zhou Lixing 
Published: September 2023

Abstract
This paper firstly establishes the mathematical models of electric networks, natural gas networks and electrically coupled equipment, respectively, and models them comprehensively to form the basic architecture of an electrically coupled integrated energy system. Based on this, an integrated energy system planning model based on the ARIMA-LSTM model is proposed, and the objective function is optimized. Among them, the ARIMA model is used to fix the order of the objective function, and the LSTM model is used to train the backpropagation of the error of the objective function. Finally, the effectiveness of electrical cost planning and CO2 emission planning is verified by simulation experiments under two scenarios. The results show that scenario 1 saves $79,799.8 in electricity cost and reduces 11,612 t of CO2 emissions compared with scenario 2, which is not configured with an electrically coupled integrated energy system. The research in this paper provides new ideas and methods for the planning of electrically coupled integrated energy systems, which have certain academic value and application prospects.
Research on the teaching model of physical education in colleges and universities based on semi-supervised radial basis function neural network
Authors: Li Yawei 
Published: September 2023

Abstract
With the development of the modern sports concept, physical education mode in colleges and universities needs to adapt to the requirements of the new era. In this paper, we studied the feasibility and comparative advantages of exercise prescription physical education, collected physical fitness test data of college students, completed the cluster analysis of student physical test data based on the k-medoids algorithm, used semi-supervised RBF neural network to learn each cluster, and generated an exercise prescription for each class of students. In the comparative teaching, the performance of students in the experimental class improved in standing long jump and 50 m, and the changes were statistically significant with p-values less than 0.05. While the indicators in the control class improved slightly before and after the experiment, the p-values were greater than 0.05, and there was no significant difference.
Research on the mechanism of teaching culture in Civics course based on deep learning model
Authors: Rong Qinyu 
Published: September 2023

Abstract
This paper uses convolutional neural networks to construct a deep learning-based teaching mechanism for question-and-answer on civic culture. The one-hot representation and the distributed representation of words in the distributed expression form of natural language are analyzed. Word2Vec, a word embedding training tool, is used to generate word embedding representations, and CNN is applied to store and classify word semantics so as to generate semantic matrices. The attention mechanism is combined to simplify the model processing steps and reduce the complexity of operations. The deep learning hierarchical semantic extraction model is tested by loss function and relative similarity to judge the accuracy and performance of the model’s operation. The results showed that the mean composite score of the experimental group was 5.2 points higher than that of the control group, and the t-test results P=0.003<0.05 indicated that there was a significant difference between the overall assessment scores of the two groups, and the teaching of Civic Culture Quiz was beneficial to the improvement of students’ performance.
The construction of a teacher training system for artificial intelligence professionals in universities oriented to RNN models
Authors: Li Lintao 
Published: September 2023

Abstract
In this paper, a custom recurrent neural network is constructed based on RNN. The internal structure of the GRU recurrent neural is mainly analyzed, and the activation function is used to ensure the smooth flow of information in the backward propagation of the neural network. By analyzing the recurrent neural in the processing sequence as well as correlation data, the time-based backpropagation algorithm is constructed. Take advantage of Highway connection in backward propagation to improve the computational speed of the improved recurrent neural network. The moving average method is used to deal with abnormal data and combined with the SGD algorithm to avoid the problem of using all training samples in one iteration so as to establish the optimal model of teacher training time series. The results show that: 48% of the training target factors account for teacher training mainly focused on professional knowledge and 35% on practical ability.
Column generation algorithm based on recursive matrix for optimal development strategy of physical education teaching in colleges and universities
Authors: Liu Yang 
Published: September 2023

Abstract
In this paper, in the process of solving the mathematical model of sports facility optimization, the integer linear programming issue of choosing a sports facility is solved using a branch delimitation approach paired with a recursive matrix-based column-generating method. As part of the process of creating a scientific evaluation system for physical education, a hierarchical gray correlation-based evaluation model for the quality of physical education in colleges and universities is built by combining the hierarchical analysis weight-solving method and the solution method of the gray correlation degree. After the analysis, 81.1% of the teachers and students were satisfied after physical education facilities were optimized with the physical education teaching facilities. The gray correlation coefficient of physical education hardware facilities and software is 0.7, and the gray correlation coefficient of physical education effect is 0.18.
A Model for Integrating and Reconstructing Music Curriculum for Higher Education Based on Deep Learning
Authors: Shi Lei 
Published: September 2023

Abstract
In this paper, firstly, the problem is modeled by a formal description of the problem of resource fragmentation in music courses for teachers, and the problem is simplified based on regional division. Secondly, an FFD-basic migration matching algorithm is proposed, and the migration matching of teaching resource nodes is realized by the least resource maximum flow model tuning. Then the measurement model of the music teaching ability of teachers was constructed, and the teaching ability measurement scale was designed. Finally, the effectiveness of the curriculum integration and reconstruction model was proved through empirical effect and analysis. The results show that the training speed is effectively increased by about 0.25 with the deep learning based model of curriculum integration and reconstruction for teachers in music. This paper provides a new solution for the integration of teaching resources in the field of music education for teachers, which has important theoretical and practical significance.
Design and implementation of fine-grained realistic 3D virtual simulation experiment
Authors: Zhang Haiyan , Shi Lei , Wang Junzhi , Cao Mei 
Published: September 2023

Abstract
Based on the virtual simulation platform, this paper firstly builds a five-in-one comprehensive, realistic 3D virtual platform with teaching method orientation, experiment method frontier, course thinking daily, team building refinement, and assessment and evaluation comprehensiveness. Then the establishment of the UAV nonlinear mathematical model, the bit attitude calibration of the UAV model, the virtual simulation of the motion of the UAV model, and the construction of the UAV flight sky realistic model based on the UAV corner control of virtual reality technology, and also the analysis of the UAV formation keeping control research based on 3D virtual simulation. The results show that the UAV takes off from a random initial position, so the initial error is large, and then the formation holding error is less than 0.1m when flying in a straight line, and the formation error is less than 1.79 when coordinating a turn. When flying in formation for the 40s, the ground sends a formation spreading command to perform a reconnaissance mission, and this study has a catalytic effect on the development of UAV aerial photography virtual simulation.
Analysis of the Economics of Talent Mobility Based on Logistic Model
Authors: Sun Liping 
Published: September 2023

Abstract
This paper analyzes the relationship between talent introduction policy and talent mobility based on a logistic breakpoint regression model. The logit function and likelihood function are analyzed to determine the probability values between the relationship of things. The variable selection is achieved by adding penalty terms in estimating the regression parameters. Focused on the analysis of the MM algorithm to select the optimal control function and iterative solution to separate the parameters in the optimization problem. The processing effect of breakpoint analysis is studied, and breakpoint regression is classified and used to optimize the objective function to the minimum using local linear regression. The feasibility of the breakpoint analysis method is demonstrated by analyzing the use of breakpoint regression in different fields. The results surface: the probability of implementing a talent introduction policy for individuals on one side of the breakpoint is 0, while the probability on the other side of the breakpoint is 1, which meets the condition of exact breakpoint regression. The most talent policies are mainly concentrated in the third and fourth tier cities, accounting for 49%, followed by the second tier cities, with 39% of talent introduction policies.
Resource distribution of online and offline interactive teaching mode based on feature fusion network
Authors: Wu Wencong 
Published: September 2023

Abstract
This paper combines the text similarity calculation of co-occurring words, text similarity calculation of semantic similarity, text similarity calculation of cosine similarity, and text similarity calculation based on a language network and joins the feature fusion network to construct a multi-feature fusion text similarity calculation method, so as to realize the resource distribution of interactive teaching mode. Through the design of functional modules, database design, and framework design of the system, JavaEE technology is used to realize the system design and complete the online and offline interactive teaching. After testing, the distribution of teaching resources under this algorithm does not change as the number of users increases, and the range fluctuates between (0,25). The system can run stably when multiple classrooms and users are online at the same time, and the system resource consumption is around 95%, all in a reasonable range.
Research on the Optimization Pathways of University Education and Teaching Reform based on OBE Concepts
Authors: Huang Jingjing 
Published: September 2023

Abstract
This paper proposes to introduce OBE theory in the curriculum map so as to build a curriculum master map based on the concept of engineering education accreditation-oriented and professional training objectives. In order to provide personalized services to students in the curriculum map, this paper applies the user-based collaborative filtering recommendation algorithm to the curriculum map and uses a similarity calculation based on Barclay’s coefficient improved similarity (BCCF) to finally implement the curriculum recommendation algorithm. The results show that the AUC of the recommendation algorithm constructed in this paper reaches 0.867. After the teaching reform, the mean values of students in the course reform class are 0.68, 0.61, and 1.31 higher than those in the non-course reform class at the level, of course, affect perception, teacher teaching, and student learning. Therefore, the OBE-based teaching method in this paper can develop personalized learning paths for students, which helps students learn better and plan the overall learning paths and make the most of educational resources.
An Innovative Discussion on Ideological and Political Education for College Students Based on Digital Mining
Authors: Hu Dan , Xue Jing , Shi Guoyong 
Published: September 2023

Abstract
In this paper, a self-organized data mining model for college students’ ideological and political education is constructed. Firstly, a suitable input-output association set is specified to build the model, and then one or more are selected as the outer criterion to filter the model. The models of each layer are evaluated by the outer criterion, and the optimal complexity model is established by finding the model structure and the law of system operation through the selection of different models. Then unknown correlations between factors of ideological and political education were mined from the data samples, and the system variables were predicted and analyzed. Finally, the model is applied to analyze the effect of ideological education and the influencing factors of College A. The p-value of the degree of matching between education level and professional level is 0.456, and the education level will have a significant influence on ideological and political education. The research in this paper is important for the development of ideology and politics in colleges and universities.
Optimization Study on Carbon Trading and Constructive Repetitive Project Scheduling in the Context of Internet Era
Authors: Zhou Lin , Guo Xinyu , Wang Hao 
Published: September 2023

Abstract
This paper constructs a carbon trading market trade-off problem model based on the time-constrained relationship of process families in RSM. By analyzing the repetitive construction project processes, linear, block, and strip processes are refined. The time-constrained relationship between process families in the RSM is studied, and the expression formula is derived. Process continuity and resource continuity in repetitive construction projects are analyzed to reduce the time required to complete a unit of work. The process duration of the project is determined by optimizing the amount of new resources and human resources used. The results show that when the length of the carbon emission interval is at (0.5, 2]t, when the length of the carbon emission interval is small, the role of RSM process time carbon trading price is larger.
Research on the layout of coal resource project development in China based on multi-objective optimization algorithm in the context of infrastructure construction
Authors: Yang Xiuyu , Zhao Liang , Huo Dong 
Published: September 2023

Abstract
In this paper, the multi-objective optimization algorithm is first used to construct a multi-objective dynamic optimization model algorithm for enterprise coal resource development in the context of infrastructure construction, to implement optimization of multiple objectives of coal enterprises based on variable descriptions, objective functions, and constraints, and also to study the extent and utilization of coal resource exploration and development. Then the coal development example based on a multi-objective optimization algorithm is analyzed, and the effectiveness of this scheme is verified by analyzing the relationship between coal mining volume and recovery rate. The results show that the coal mining volume and coal mining speed are both increasing and then decreasing in the process of advancing the working face from 200m to 500m, and the coal mining volume gradually increases with the coal mining in the working face hollow area, and the retrieval speed is consistent with the changing trend of coal mining, which indicates that this study has reference value for safe and efficient mining and efficient resource recovery in coal mines.
A Study on the Teaching Practice of Multimodal Data Analysis in International Chinese Language Education for International Students in China
Authors: Zhang Song 
Published: September 2023

Abstract
In this paper, an improved semantic learning model under multimodal data fusion is proposed to model both image attention features and problem attention features using a network architecture of collaborative attention learning, which can effectively reduce irrelevant feature interference and extract more distinguishable features for image and problem representations. In addition, to address the high dimensionality as well as complex computational problems in the multimodal data fusion process, multimodal bilinear decomposition methods are utilized in order to achieve a more effective fusion of visual features in images and text features in questions to capture more complex interactions between multiple models. Compared with TF-IDF and TextRank, the accuracy rate of the model in this paper is 9.7% and 12.1% higher than them, respectively. The F=16.15, p<.05, for the first group of scores and the second group of scores for international students in Chinese language classes playing listening materials in a combination of audio, video, and Chinese characters. The F=8.527, p<.05, for the second group of scores and the third group of scores.