bluuebunny/crossref_metadata_2025 huggingface dataset:
Internalisasi Nilai Siri’ Na Pacce dalam Transaksi Jual Beli pada Pedagang sebagai Formulasi Nilai Tambah Syariah untuk Mewujudkan Kesejahteraan pada Pedagang di Pasar Tradisional Gowa
Authors: Marunta Ristiyanti Ahmadul , Abdullah M. Wahyuddin , K Amiruddin
Published: September 2023

Penelitian ini bertujuan untuk menginternalisasikan nilai-nilai siri’ na pacce dalam transaksi jual beli yang secara sadar atau tidak sadar telah tertanam dalam aktivitas bisnis masyarakat Bugis Makassar. Oleh karena itu penelitian ini dianggap penting untuk mengembangkan konsep nilai tambah syariah dengan kearifan lokal. Jenis penelitian yang digunakan adalah penelitian kualitatif yaitu metode yang akan menghasilkan data deskriptif yang berupa kata-kata tertulis atau lisan. Dalam penelitian ini penulis menggunakan paradigma interpretif untuk mengungkap dan memaknai internalisasi nilai siri’ na pacce dalam transaksi jual beli sebagai formulasi nilai tambah syariah untuk mewujudkan kesejahteraan (studi pada pedagang di Pasar Tradisional Gowa). Temuan dalam penelitian ini adalah secara filosofis kearifan lokal Bugis Makassar tercermin dalam wujud transaksi jual beli. Adanya nilai tambah ekonomi yang memiliki formulasi nilai material dan bentuk nilai tambahnya adalah uang. Nilai tambah mental yang memiliki formulasi nilai kejujuran, nilai keridhaan (suka sama suka), nilai keadilan, nilai kepercayaan dan bentuk nilai tambahnya adalah rasa altuiristik, senang dan persaudaraan. Kemudian nilai tambah spiritual yang memiliki formulasi nilai untuk tidak mendurhakai Allah dan bentuk nilai tambahnya adalah rasa ikhlas dan rasa kehadiran Tuhan. Formulasi nilai tambah syariah ini menjadi dasar dalam perwujudan nilai falāh. Implikasi pada peneltian ini adalah adanya perwujudan kesadaran bagi para pedagang Bugis Makassar untuk selalu memelihara nilai kearifan lokal siri’ na pacce dalam menjalankan segala tindakannya sehingga dapat mencapai tujuan kesejahteraan hidup didunia maupun diakhirat (falāh).
DETECTION OF SQL INJECTION VULNERABILITY IN CODEIGNITER FRAMEWORK USING STATIC ANALYSIS
Authors: Fahmi Al Azhar Muhammad , Harwahyu Ruki
Published: September 2023

SQL Injection attacks are still one type of attack that often occurs in web-based applications. The causes and ways to prevent SQL Injection have been widely explained in various sources. Unfortunately, until now, SQL Injection vulnerabilities are still often found in multiple applications. Web-based application frameworks that already have functions to protect against attacks are often not used optimally. This is inseparable from the role of programmers, who often forget the rules for writing program code to prevent SQL Injection attacks. We conducted this research to detect SQL Injection vulnerabilities in source code using a case study of the PHP CodeIgniter framework. We compared this research with static analysis tools like RIPS, Synopsys Coverity, and Sonarqube. The tool we have developed can detect SQL Injection vulnerabilities that cannot be detected by the two tools with an accuracy of 88.8%. The results of our research can provide suggestions for programmers so that they can improve the code they write.
Kinetics of phenol hydroxylation reaction of open mesoporous TS-1 with high backbone titanium content
Authors: Wang Shuai , Yang Zhenyuan , Xu Lei , Wang Na , Mu Shenglong , Jiao Yilai
Published: September 2023

High skeletal titanium content, open mesoporous TS-1 titanosilica molecular sieves with more accessible active centres exhibit higher catalytic activity, target product selectivity and resistance to coking deactivation in green catalytic oxidation reactions using hydrogen peroxide as oxidant. In this paper, TS-1 titania-silica molecular sieves without anatase, with the highest theoretical skeletal titanium content (2.0 wt%) and open mesopores (mesopore volume 0.71 cm3/g) were synthesised based on the ageing dry gel limited domain conversion method invented in previous research work. The intrinsic kinetics of the catalytic reaction of phenol with hydrogen peroxide for direct hydroxylation of benzenes was investigated. The effects of stirring rate, phenol concentration, hydrogen peroxide concentration, catalyst dosage and reaction temperature on the initial conversion rate of phenol were investigated, and the experimental data were fitted with a power function equation to obtain the intrinsic kinetic equation of the catalyst

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\left( {{\rm{r}} = 2.98 \times {{10}^6}\,\exp \,\left( { - {{56.43 \times {{10}^3}} \over {RT}}} \right){c^{1.07}}\left( {{\rm{Phenol}}} \right){c^{0.10}}\left( {{{\rm{H}}_2}{{\rm{O}}_2}} \right)} \right)

. Under the condition of eliminating the effect of internal and external diffusion, the reaction was 1.07 and 0.10 for phenol and hydrogen peroxide, respectively, with a reaction activation energy of 56.43 kJ/mol. This study provides a theoretical basis for the reactor and process design of hydroxylation of phenol to benzenediol based on this new catalyst.
Construction of a coupled evaluation index system of rural habitat environment and rural tourism in China based on multi-objective optimization algorithm
Authors: Liu Xiaojing
Published: September 2023

This paper presents a coupled evaluation of rural habitat environment as well as rural tourism in China based on a multi-objective optimization algorithm. Firstly, the ANN model is used as the three objective evaluation function values of CVBEC, LCC and LCCO2 as the dependent variables, and the NSGA-II algorithm is introduced as the optimization algorithm for the multi-objective optimization of rural architectural design. Secondly, based on the ANN-NSGA-II algorithm, an improvement strategy is proposed for the rural building environment algorithm, and the multi-objective discrete particle swarm algorithm with a dominant ranking number is applied to rural tourism route planning. Then the coupled evaluation system of rural habitat environment and rural tourism is constructed by first and second-level indicators. Finally, the coordination degree and spatial autocorrelation analysis of the multi-system coupling relationship are conducted for the coupling evaluation system. The study shows that the coordinated development degree P value increased from 0.02 in 2017 to 0.83 in 2022, Moran’s I index of living environment and ecological environment system is greater than 0, and the Z value is greater than 1.63.
The current situation and measures for the protection of marine intangible cultural heritage in Hainan in the context of big data
Authors: Deng Qiongfei
Published: September 2023

In order to construct a knowledge graph of Hainan marine intangible cultural heritage, this paper designs the graph database by setting the annotation system and semantic structure of the intangible heritage metadata. For the named entity recognition of the knowledge graph, a model combining long and short-term memory neural networks and Bi-Lstm-CRF with conditional random field is established. The recognized entities are processed based on the Bert pre-training model, and the semantic relations are extracted by combining the cluster search method. Compared with other models, the accuracy rate of the Bs-Spert model for the extraction of semantic relations of the Hainan marine NRM dataset is improved by 0.64%, 0.85% and 0.98% compared with GCNRE, Match Blank and MTDS, respectively. Meanwhile, other metrics of the Bs-Spert model also performed well, with a recall rate of 82.26% and an F1-value of 74.01%. By constructing a knowledge map based on the graph database, we can analyze the current situation of Hainan’s marine NRM more comprehensively and thus propose corresponding countermeasures.
An analysis of the applicability of integrating Confucian moral education ideas into the Civic Education of college students under the perspective of cultural communication
Authors: Yi Mingrong
Published: September 2023

This paper firstly constructs the mutual mechanism between the characteristics of Confucian moral education thought, and college students’ Civic Education and the influence mechanism of college students’ psychological characteristics on the integration of Confucian moral education thought. Then a logistic regression model of the integration of Confucian moral education into Civic Education was established, and data collection, pre-processing, missing data processing and parameter estimation steps were carried out. Finally, the results of the application of Confucian moral education thought in Civic Education were analyzed, including the analysis of the factors influencing the integration effect and the analysis of the results of psycho-social cognitive factors on the optimization of moral education strategies. The results show that the interaction coefficients of the three regression models of the exposure to Confucian moral education ideas and the effect of ideological and political education dissemination among college students are 0.7325, 0.4817, and 0.3885, respectively, and the coefficients of the interaction terms are all significant at the level of 0.05. The research in this paper has some reference value for promoting the development of moral education and the transmission of cultural values.
Research on the construction of professional clusters in newly built undergraduate colleges facing cultural and creative industries under the background of integration of industry and education
Authors: Hao Jing
Published: September 2023

Firstly, according to the actual situation of some new undergraduate colleges and universities upgraded from teacher training colleges, whose science and technology disciplines are relatively weak but humanities disciplines have an excellent history of nearly one hundred years, the humanities disciplines with strong creativity, such as education, art and media, are closely related through the construction of cultural and creative industry professional clusters. Secondly, based on the clustering algorithm, we classify and quantify the professional relationships of undergraduate institutions, which need to satisfy the assignment rules and perform algebraic operations on the relationship matrix to realize the classification of professional relationships. Then we searched the Chinese literature with “professional cluster” as the keyword to obtain the initial data, and used the clustering algorithm to visualize and analyze the research on professional cluster construction in undergraduate colleges and universities. The results show that when the default values of α1/α0 = 3 and γ[0,1] = 0.6 are used, the seven keywords with the highest emergence intensity are: architecture cluster, transformation development, undergraduate, professional faculty, school, undergraduate school, and big data, and the keyword clustering reflects the research hotspots of professional clusters, which can promote the construction of professional clusters.
Analysis of the Current Situation and Countermeasures of Cross-border Communication of Chinese Medicine Culture in the Context of Big Data
Authors: Yan Qiying , Zhou Yanqiu , Yin Li
Published: September 2023

This paper firstly analyzes the problems of poor effect and translation recognition effect of cross-border communication of Chinese medicine culture. And countermeasures are proposed according to the current situation, and the LDA text model is introduced. Secondly, the LDA model is improved, the method of changing the rate according to the number of topic transfers is applied, and the topic distribution is updated according to the number. Then the functional and holistic framework of the platform is structured to build a cross-border communication platform for TCM culture. Finally, the recognition rate of the improved TD-LDA model is analyzed experimentally, and the recognition rate is improved from 67% to 84% when the number of test sets is below 1000. For the reliability test analysis of the TCM culture platform communication effect, the standard path coefficient SRW from ZYX to TEA is 0.642, t=12.763, p<0.001. The study indicates that the precision of TCM culture platform communication has a positive effect on the cognitive efficacy of TCM communication.
Research on the construction of the evaluation index system of teacher morality in universities under the background of big data
Authors: Li Shengwei
Published: September 2023

This paper constructs the evaluation index system of university teachers’ ethics from the hierarchical structure diagram of the evaluation system. In order to reduce the subjective feelings of the evaluators, a genetic algorithm is introduced to optimize the consistency test of the weights of the hierarchical analysis method. Taking ten colleges and universities in GD province as examples, the GAOHP-AHP model was used to calculate the index weights and then obtain the comprehensive evaluation scores of teacher ethics and teacher morality of each college and university. The results showed that the evaluation scores of ten universities were 3.975, 3.946, 4.075, and 4.078 for love for work, teaching and education, rigorous learning, and being a teacher, respectively. The overall evaluation scores of teacher Q in school 1 increased by 7.13% and 12%, respectively, compared with the other two teachers. This shows that the evaluation index system of teacher morality and teacher style in universities can effectively evaluate the teacher morale and teacher style quality of teachers.
An Empirical Analysis of Internet financing and local economic growth Based on Big Data
Authors: Chen Feifei
Published: September 2023

Internet finance, a byproduct of the close coupling of Internet technology with the financial sector, has contributed significantly to the growth of local economies. This essay first examines the relationship between regional economic growth and online financing. Second, the constraint mechanism between Internet finance and local economic growth is examined using the efficacy function of the coupling degree evaluation model. The consistency of the spillover impact of the Internet finance cluster on the economic growth of the region and the surrounding areas is examined using the spatial effect decomposition. In 2021, the Moran indices of W1, W2, and W3 were 0.418, 0.123, and 0.341, respectively. The correlation between Internet financing and local economic growth is strengthened, while the influence factor of economic and geographical distance is reduced.
Research on the path of integrating Yan’an spirit into the ideological and political education of contemporary college students based on NDK-means algorithm
Authors: Luo Gangfeng , He Rui , Hou Jiale , Wu Wen
Published: September 2023

In this paper, the ideological and political education path is designed according to the spirit of Yan’an. In order to verify the feasibility of the path, as well as to make the student evaluation more effective and objective, the article combines the K-means algorithm and proposes a K-means algorithm based on neighborhood spatial density optimization (NDK-means). The algorithm assists in solving the problem of grading the reliability of student assessment and realizes the labeling of student assessment reliability data. Then, based on the student assessment reliability characteristics and data labeling results, a BP neural network prediction algorithm (CSA-BP) based on crow search improvement is proposed to model the student assessment reliability. The results show that the percentages of freshmen to seniors who are satisfied with the Civic Education proposed in this paper are 85.9%, 82.26%, 76.75%, and 72.45%, respectively, in terms of grade level. Students from urban, rural, and rural areas, in terms of their place of origin, all feel satisfied with the current teaching of Civics and Political Science at 80% or more.
Study of gut microbial homeostasis and targeted therapy for hepatocellular carcinoma based on eigenvalue-fitting superiority algorithm
Authors: Xu Hao , Wu Liying , Liu Bin , Yuan Guojia , Liu Xiaoguang , Chen Nianping
Published: September 2023

In this paper, firstly, we propose the eigenvalue-based goodness-of-fit algorithm to evaluate intestinal microorganisms and liver cancer, based on the basic principle of one-sided right-tailed fitting criterion, using the covariance matrix of the signal can capture the correlation between signal samples, and the maximum-minimum eigenvalue-based goodness-of-fit detection algorithm can be obtained. Secondly, based on the eigenvalue goodness-of-fit algorithm, a training set and a test set were tested using the full-dimensional clinical data set of enrolled cases to construct a prediction model for the risk of metastatic recurrence after HCC surgery and to select evaluation indexes for the prediction model. Then, to further clarify the diagnostic role of lgEr/lgFp on hepatocellular carcinoma, its intestinal microorganism lgEr/lgFp was analyzed with the diagnostic role of AFP on hepatocellular carcinoma. The results showed that for lgEr/lgFp ratio, the analysis was compared between the high AFP cirrhosis group and liver cancer group and the low AFP liver cancer group and cirrhosis group, and it was found that there was a highly significant difference P<0.01. This study emphasizes the influence of intestinal homeostasis on the development of liver cancer, and establishes the link between intestinal homeostasis and the development of liver cancer.
Data Analysis of Linguistic Landscape in the Context of “Internationalization +” Urban Construction
Authors: Kong Hui
Published: September 2023

With the rapid development of internationalization and urban construction, the urban linguistic landscape has become an area of great interest. The purpose of this paper is to explore the data analysis method of urban visual linguistic landscape based on line-of-sight orientation and to optimize the design of urban linguistic landscape based on an improved genetic algorithm. The basic visual analysis unit and the viewable area analysis unit of the linguistic landscape are proposed to quantify the visual characteristic indexes and the optimal view distance of the linguistic landscape. At the same time, the viewable spatial point set analysis unit is used to obtain the view accessibility of the language landscape. Finally, the linguistic landscape optimization model was evaluated and analyzed for application effects. The results show that through the optimized design of 10 linguistic spots in H City National Forest Park, the average score of each spot evaluation is 3.48, and the full score ratio is 63.18%. The urban language landscape optimization model proposed in this paper can effectively improve the aesthetics and visual sensitivity of the urban language landscape.
Seismic performance assessment of typical vertical light industrial building structures based on IDA method
Authors: Dai Hongtao , Sun Hongshuo
Published: September 2023

The seismic response of a typical vertical light industrial building structure is complex, and once damage occurs, it will cause great disasters and losses, so it is very important to evaluate the seismic performance of vertical light industrial building structures. This paper firstly analyzes the IDA principle and determines the ground shaking strength index and structural damage index based on the IDA curve. Secondly, the structural vulnerability curve and the model are derived based on typical vertical light industrial structures, and the structural characteristics of typical vertical light industrial buildings are analyzed. Finally, the seismic performance of the building structure is evaluated and analyzed based on the IDA method, and the seismic vulnerability analysis is carried out for vertical light industrial buildings with different concrete structures. The PA values of CFST structures in four limit states are 0.81g, 0.21g, 0.34g and 0.47g, which are slightly higher than those of RC structures and have better seismic performance.
Fatigue life prediction of power transmission towers based on nonlinear finite element analysis
Authors: Wang Quan , Li Zhengfa , Wang Fan , Li Han
Published: September 2023

In this paper, firstly, the fatigue damage of transmission towers is analyzed from the fatigue load and fatigue damage, and the S-N curve of transmission towers is used to obtain the fatigue damage accumulation. Secondly, the finite element model of the transmission tower is constructed by using the finite element software ANSYS, and the way of its load calculation, as well as the remaining life estimation, is given. Finally, an example analysis was carried out using a transmission tower in the GZ area, and its fatigue life was calculated for it. The results show that when the average wind speed is 15m/s, the maximum wind load time at 40m height is 128N, and the minimum wind load time is −131N. The minimum value of the remaining life of the transmission tower in the GZ area is 64.532, which shows that the fatigue life of the transmission tower can be predicted by using nonlinear finite element analysis.
A study of innovative strategies for teaching English to college students based on tiered probit
Authors: Xie Lili
Published: September 2023

This paper analyzes the current situation of university English teaching and constructs a trinity of EGP+ESP+EIC multiple teaching innovation systems for university English based on the principles of English teaching innovation. In order to analyze this innovative teaching system of English, a stratified statistical model and a spatial autoregressive model are combined, and four ordinal stratified spatial autoregressive Probit models are innovatively constructed to model data where the dependent variable is ordinal, and there is a spatial dependency situation with a stratified structure. The analysis shows that in the process of continuous innovation of English teaching mode, the number of people who are dissatisfied with English teaching decreases by 30%, the number of people who are very satisfied increases by 35%, and the number of people who are very satisfied accounts for 42.5% of the total number of people and 90% of the total number of people who are satisfied in the final stage of innovation of English teaching in university. The English teaching innovation strategy for university students based on this study is feasible.
Research on the application of data mining technology in music therapy in the age of information technology
Authors: Jiang Haichao
Published: September 2023

The wide application of digital mining technology will certainly promote the development of music therapy. In this paper, we first analyze the development of music therapy and clarify the classification of orchestration. Secondly, for the time period model of mining data technology, the mathematical method of the ARMA model and the ARIMA model is investigated. Finally, the music therapy effect of guzheng performance training is predicted based on the ARIMA time series. In accordance with the playing sloped of guzheng clips from Gaojia opera, the relationship between the total number of subjects and the amount of music therapy sessions was examined, as well as the correlation among the number of active behaviors, self-expression, positive emotional expressions, and negative feelings of the subject children. The attentional concentration time showed a highly significant correlation with the number of times under music therapy, i.e., P<0.02, while the number of active behaviors and self-expression showed a significant correlation, i.e., P<0.04.
Design and development of personalized education information management system based on artificial intelligence
Authors: Yi Jie
Published: September 2023

In order to combine artificial intelligence and personalized education, this paper uses semantic similarity to evaluate the similarity between personalized education models and resource information and gives a semantic similarity calculation between word lists. It is used to measure the semantic similarity between user models and texts and between texts, and a recommendation algorithm based on semantic analysis is constructed. Based on this, the needs of personalized education are analyzed, and the personalized education information management system is designed using the MVC framework with a B/S structure. After system testing, we obtained that the MSE value of the review data volume threshold set to 2 was 0.94 on the student information set, 0.86 on the teacher information set, 0.76 on the course information set, 0.74 on the score information set, and 0.81 on the administrative information set.
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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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.