bluuebunny/crossref_metadata_2025 huggingface dataset:
PERANCANGAN MEJA SLIDER PALET PAVING BLOK MENGGUNAKAN METODE ERGONOMIC FUNCTION DEPLOYMENT (EFD) DI PT. DIAN NUSWANTORO REKAYASA TEKNOLOGI
Authors: Aji Chandra Wahyu , Wijaya Dewa Kusuma
Published: January 2024

Dikarenakan banyaknya minat pengguna dalam penggunaan paving membuat produksi paving membludak dan banyak pesanan menyebabkan produsen atau karyawan pembuat paving menjadi kwalahan dikarenakan masih manualnya pengangkut paving yang keluar dari mesin produksi ke tempat penjemuran paving, dengan kira kira sekali produksi ± 100kg/pallet dan sehari bisa menghasilkan 20-25 pallet secara terus menerus dengan diangkat menggunakan tangan oleh 2-3 orang penggangkat. Hal ini sangat berbahaya dan dapat menyebabkan cidera jika terus – menerus dilakukan dan proses produksi juga akan menjadi lebih lama.Pada permasalahan tersebut dibutuhkan meja Slide yang dapat digunakan untuk mempermudah pekerja pembuat paving untuk menggangkat pallet.

Analisa indeks postur tubuh pekerja di PT Direct menggunakan Loading on the Upper Body Assessment (LUBA). Kemudian dilakukan perancangan alat bantu kerja meja menggunakan metode Ergonomic Function Deployment (EFD). Alat Bantu Kerja Meja Slider yang dirancang sangat efisien, karena proses penjemuran menjadi lebih cepat dengan perbandingan waktu penjemuran 1 jam mendapatkan selisih dari yang sebelum menggunakan alat 24 pallet dan setelah menggunakan jadi 60 pallet selama 1 jam jadi efisiensi sebesar 60%.
Analisis Paparan Panas Terhadap Beban Mental Pekerja Bagian Produksi Dengan Metode National Aeronatics And Space Administration Task Load Index (NASA TLX)
Authors: Asri Vikha Indira , Huda Mahabib Miftahul , Sokhibi Akh.
Published: January 2024

Lingkungan kerja yang baik dapat mempengaruhi kinerja pekerja. Salah satu yang mempengaruhi kinerja adalah suhu ruangan yang harus sesuai dengan Nialai Ambang Batas (NAB) sebesar 18–28℃. Suhu ruang produksi pada toko roti Gembong Gedhe melebihi NAB yaitu sebesar 29,3℃. Oleh karena itu perlu di lakukan analisis pengaruh paparan temperature terhadap beban mental pekerja

Metode yang di lakukan dalam menyelesaikan permasalahan pada toko roti Gembong Gedhe yaitu dengan menggunakan metode NASA-TLX. Dengan harapan dapat analisis beban mental pekerja dari paparan panas dengan menggunakan software surfer 11. Berdasarkan hasil analisis data dengan uji Chie-square di dapatkan nilai p-value 0,0594 pada variabel KW, nilai p-value 0,997 pada vaiabel P, dan nilai p-value 0,997 pada variabel TU. Sehingga terdapat variabel Kebutuhan Waktu (KW),Performansi (P), dan Tingkat Usaha (TU) berpengaruh terhadap beban kerja mental.

Kata kunci: Beban Kerja Mental, Software Surfer 11, NASA-TLX
Dental health status assessment of TNI-AL bintara officers using DMFT index and Chief of Naval Staff Regulation: a descriptive study
Authors: Arifin Kanisa Mirena , Irmaleny Irmaleny , Sitam Suhardjo , Setiawan Krisnadi
Published: January 2024

ABSTRACTIntroduction: Military personnel belong to a high-risk group for the development of various pathological conditions in the oral cavity. Based on research, the experience of dental caries in the army population of several other countries was relatively high. The purpose of this study was to describe the assessment of the dental health status of Bintara Officer (the NCO) the Indonesian National Military-Naval Force (TNI-AL) using caries experience index. Methods: The descriptive method was used with primary data collection through the caries experience index (DMF-T) examination and assessment of the dental health status of the TNI-AL. A purposive sampling technique with a total of 40 members with inclusion criteria, ranked Bintara Officer, 10 years of service, male or female, was used. Exclusion criteria were those serving outside the city or abroad and not signing an informed consent form. The data was collected and analyzed descriptively using Microsoft Excel. Results: DMF-T index value was 3.7, included in the Stakes I category, which had a maximum number of DMF of 10 teeth: 25.0% in the very low category, 17.5% in the low category, 27.5% in the moderate category, 17.5% in the high category, and 12.5% in the very high category. The dental health status of the TNI-AL were 95.0% in the Stakes I category, 2.5% in the Stakes II category, 2.5% in the Stakes III category, and there were no subjects in the Stakes IV category. Conclusion: Assessment of the dental health status of bintara officer Indonesian National Military-Naval Force using DMFT index value was in the moderate category, and based on Perkasal the majority was included in the Stakes I category.KEYWORDS : Caries, DMF-T index, dentistry, TNI-AL dental health status
Analysis of the completeness of specific nutritional interventions as an effort to prevent stunting: an observational study
Authors: Setianingsih Triseu , Hussain Nervana
Published: January 2024

ABSTRACT Introduction: Handling stunting through nutritional interventions is classified into two categories: specific nutrition interventions and sensitive nutrition intervention. Specific nutrition interventions referring to causal factors directly related to nutrition, aimed at pregnant women and breastfeeding mothers, are the responsibility of the health sector, contributing 30%. The completeness of specific nutritional interventions for breastfeeding mothers according to standards are more challenging. The purpose of this study is to analyze several factors that influence the completeness of specific nutritional interventions in breastfeeding mothers to create prediction models. Methods: This was a quantitative study with a cross sectional design. The population was all breastfeeding mothers with a total of 193 nursing mothers. Samples of 128 people were taken using a simple random sampling technique. Data analysis using univariate analysis, bivariate analysis with Chi square analysis and Multivariate analysis with logistic regression analysis. Result: In bivariate analysis there were 8 influencing variables. The Mother’s education with p=0.006, Mother’s knowledge with p=0.001, Mother’s Attitudes with p=0.001, Mother’s Job with a p=0.001, Parity with p=0.001, Husband's Support with p=0.001, Health Workers’ Support with p=0.001, Village Officials’ Support with p=0.001. The most influential variable was the health workers’ support variable with OR=20.56. Through multivariate analysis, a predictive model of achieving completeness of specific nutritional interventions is produced so that it can be used as a preventive effort in overcoming these problems. Conclusion: The completeness of specific nutritional interventions for breastfeeding mothers has not been achieved according to the government's target, it is necessary to intervene on the factors that influence it which include mother’s knowledge, mother’s attitude, husband’s support, health workers’ support and village apparatus’ support.Keyword : Stunting, nutritional support, specific intervention
Cadmium selenium quantum dot based nanosensor with femto molar level sensitivity for the detection of the pesticide endosulfan
Authors: Nair Lakshmi V , Nair Resmi V , Jayasree Ramapurath S
Published: January 2024

Endosulfan (6,7,8,9,10,10-Hexachloro-1,5,5a,6,9,9a-hexahydro-6,9-methano-2,4,3-benzodioxathiepine-3-oxide) is an off-patent insecticide used in agricultural farms. Its usage as a pesticide has become highly controversial over the last few decades. This is due to its reported hazardous nature to health and side effects like growth retardation, hydrocephalus, and undesired changes in the male and female hormones leading to complications in sexual maturity. Endosulfan is the main culprit among all pesticide poisoning incidents around the world. Though the usage of this dreaded pesticide is banned by most countries, the high stability of this molecule to withstand degradation for a long period poses a threat to mankind even today. So, it has become highly essential to detect the presence of this poisonous pesticide in the drinking water and milk around these places. It is also advisable to check the presence of this toxic material in the blood of the population living in and around these places so that an early and appropriate management strategy can be adopted. With this aim, we have developed a sensor for endosulfan that displayed high selectivity and sensitivity among all other common analytes in water and biological samples, with a wide linear concentration range (2 fM to 2 mM), a low detection limit (2 fM), and rapid response. A citrate-functionalized cadmium-selenium quantum dot was used for this purpose, which showed a concentration-dependent fluorescence enhancement, enabling easy and sensitive sensing. This sensor was utilized to detect endosulfan in different sources of water, human blood serum, and milk samples with good recoveries. It is also noted that the quantum dot forms a stable complex with endosulfan and is easy to separate from the contaminated source, paving the way for purifying the contaminated water. More detailed tests and validation of the sensor are needed to confirm these observations.
Effects of Humic Acid and Bromide on Trihalomethane Formation during Water Disinfection with Chlorine
Authors: VELİOĞLU Yakup Sedat , AKDOĞAN Rukiye , BALOĞLU Zehra
Published: January 2024

Chlorination is one of the most important methods used in water disinfection. Chlorine reacts with natural organic substances in water and causes the formation of disinfection byproducts that might cause health problems. The predominant by-product of chlorination is trihalomethanes. Humic substances, which make up the majority of natural organic substances, are the primary precursors of trihalomethanes. In this study, the effect of different doses of chlorine on the formation of chloroform, bromodichloromethane, dibromochloromethane and bromoform in the presence of natural organic matter and bromide in drinking water was evaluated. Artificial raw water samples prepared with the addition of 2, 3 and 5 mg/L humic acid representing natural organic matter were subjected to chlorination at doses of 1, 2 and 3 mg/L and analysed on the 0th, 3rd and 7th day. The only trihalomethane formed was chloroform with a concentration of 20.52-131.13 μg/L. Increased humic acid and chlorine levels resulted in increased chloroform content. Free chlorine in the water caused chloroform formation to continue even on the 7th day. Accordingly, the amount of chloroform formed increased with the contact time. While the chlorine dose was constant, increased humic acid resulted in decreased free chlorine. To evaluate the effect of bromide on trihalomethane formation, 200 μg/L bromide was added to 2 mg/L humic acid containing water, and 1 mg/L and 2 mg/L chlorination was applied. At the end of the chlorination process in bromide-free waters, only 23.46-41.90 μg/L of chloroform was formed. In the presence of bromide, chloroform, bromodichloromethane, dibromochloromethane and bromoform were formed and the total trihalomethane level increased to 50.03-85.59 μg/L. While the ratio of brominated trihalomethane increased, the amount of chlorinated species decreased.
Improving the timeliness of college English teaching model based on multilevel fuzzy evaluation
Authors: Pang Bingliang , Li Zaimin , Liu Bing
Published: January 2024

In order to meet the changing educational needs, this paper collects the factors related to the teaching mode through the method of multilevel fuzzy evaluation and establishes a multilevel fuzzy evaluation system including the factors of teaching methods, textbook selection, learning resources and so on. To obtain quantitative satisfaction results, fuzzy numbers are employed to calculate the satisfaction evaluation of teaching programs. Establish a judgment matrix using triangular fuzzy numbers and hierarchical analysis to assign weights to different indicators. The evaluation results of each factor are synthesized to obtain the evaluation results for the timeliness of the English teaching method. The results show that although there is not much difference in the basic level of English between the experimental class and the control class, the experimental class, after using the method of this paper, has a measure of qualitative data higher than the standardized metric of 71.195, and the academic grade reaches a full score of 10. It is further verified that by using the method based on multilevel fuzzy evaluation, universities can optimize their teaching mode in a more targeted way to adapt to the increasingly changing educational environment.
Innovation and Practice of Public Security Police Training Curriculum and Education System in the Age of Information Technology with Police Professional Competence as the Core
Authors: Yang Zhiguo
Published: January 2024

This paper constructs an educational innovation system for training courses based on information technology with the core of police professional ability. Firstly, using the vector space model, each document of the training course knowledge point establishes the weight information. Then, using the triangular dissection algorithm, the police combat training virtual reality scene is constructed, achieving two modes of display: a three-dimensional view window and a two-dimensional planar map. Finally, through the discrete point topology relationship, the scene image becomes more realistic and clear during the process of realizing dynamic simulation. The results show that in the police training innovation system constructed in this paper in the professional knowledgeability test, the number of people who passed the score is more than 300. The special course training had a pass rate that exceeded 80%. The research of this paper is of great significance to the reasonable construction of the police’s business knowledge structure and vocational ability structure and to improve the overall combat effectiveness of public security organs.
Study on the Cluster of Coastal Cities in China under the Influence of Storm Surges
Authors: Zhu Li , Cui Shibai , Luo Tianyu
Published: January 2024

Coastal areas are the most developed areas in China’s economic society, but they are vulnerable to storm surges. The characteristics of coastal cities under the influence of storm surges can be targeted to adjust social and economic activities and promote sustainable development. Combining characteristics of 52 coastal cities and based on the indicator system method and data cluster analysis, this study explores the different indicators and future development strategies of 5 clusters of cities when facing storm surges, aiming to fill the research gap in this area. The indicators related to the economy, population, and environment of coastal cities were selected, and the characteristics and frequency of regional storm surges were considered. At the same time, the K-means clustering method and DBSCAN were used to select the most suitable clustering method. The clustering results of coastal cities caused by storm surge disasters were analyzed, and a series of specific strategies and suggestions were proposed. According to the research findings, the K-means clustering method is more appropriate for this study. A total of 52 cities are clustered into five categories, of which the number of the fourth category is the largest, and the number of the fifth category is the least. The findings can be used to scientifically determine and guide subsequent analyses related to the disaster-bearing abilities of different types of coastal cities in the face of storm surges, thereby greatly enhancing and strengthening refined storm surge disaster defense efforts.
Statistical method for clustering high-dimensional data based on fuzzy mathematical modeling
Authors: Wang Changhui
Published: January 2024

In this paper, firstly, the fuzzy mathematical model and its types and algorithms of fuzzy numbers are studied. Then, the concept of fuzzy mathematics is added to cluster analysis, and fuzzy cluster analysis is carried out on samples or objects after data standardization and the construction of a similarity matrix. Then, the fuzzy C-mean FCM algorithm is proposed, and the FCM algorithm is improved by introducing the point density of data objects, the maximum minimum distance method of point density sampling, and the reduction of computation to improve the statistical function of clustering high-dimensional data. Finally, the algorithm of this paper is compared with other algorithms by AC, PR, RE, convergence speed, running time, DBI index and other indexes in order to analyze the advantages of the FCM algorithm in high dimensional data clustering statistics. The results show that the F value of the FCM algorithm in the Zoo dataset reaches 0.976, which improves 61% compared to FKM and nearly 12.6% compared to the IIFKM0 algorithm, with the best clustering effect. The DBI index of the FCM algorithm is the lowest in the four datasets, which is basically stabilized in the range of 0.5-0.6. This is better than other algorithms.
Design of Online Intelligent Detection System for Power Quality and Fault Identification in Distribution Networks
Authors: He Wanru , He Chunhong , Zhang Zongjie , Ren Bin
Published: January 2024

This paper lays the foundation for the subsequent analysis of power quality in distribution networks by briefly describing the indicators of power quality. Utilizing the zero sequence voltage mutation detection fault of a small current routing algorithm, the instantaneous values of voltage and current of each phase of the three-phase circuit are quickly calculated based on the electrical parameters of instantaneous reactive power and the online intelligent detection system is established. The effectiveness and feasibility of the designed detection system and detection algorithm in detecting electrical energy parameters have been verified through experiments. The results show that the error of voltage measurement is within 0.0003-0.002, the frequency error of the system is up to 0.0117%, the measurement error of three-phase unbalance is distributed between 0.001 and 0.1, and the error of negative sequence and zero sequence is between ±0.003, which meet the system design requirements. It shows that the use of online intelligent detection systems can improve the quality of distribution network operation and fault identification accuracy, improve power quality, and effectively improve the reliability of power supply.
Vocational Education and Industry Integration and Symbiosis of Subjects and Digital Drivers
Authors: Guo Yi
Published: January 2024

Under the new round of scientific and technological revolution and industrial change, the integration of vocational education and industry is an important direction of educational development. In this paper, the structure of the learning path network of higher vocational professional courses is analyzed, and through the analysis of the elements of learning behaviors, the learning behaviors are mined by adopting sequence relations, and the behavioral structure model is established. The assessment of the learning path under the integration of industry and education courses was finished using uncertainty association coefficients and time association coefficients. After building the learning path network for vocational education, the subjective characteristics of students under vocational education were detected using isolated point analysis. The detection results show that the correlation coefficient between the first pair of typical variables is 0.488. The Wilks statistical test results for typical correlation coefficients show that the p-value of the first typical correlation coefficient is 0.098, which is less than 10%. The correlation study of the environment of integration of education and industry and the effect of integration can be simplified to study only the relationship between the first pair of typical variables. By analyzing the main characteristics, the main body for vocational education and industry integration is clarified, which creates a digital-driven impetus for the integration of industry and education.
Analysis of Challenges and Countermeasures for Higher Education Management in the Era of Big Data
Authors: Chen Feng
Published: January 2024

This paper analyzes the factors affecting the efficiency value of human resource management in higher education by using the Tobit regression model, puts forward the hypotheses of the influencing factors, constructs a model of the factors affecting the efficiency of human resource utilization in higher education, and derives the specific correlation coefficients of the influencing factors. After examining the correlation between each dimension of teacher management culture in higher education and teachers’ organizational commitment and its dimensions using Pearson’s product-difference correlation method, the correlation between educational management and teachers’ teaching commitment is verified through the quantitative measurement of correlation analysis and linear regression analysis. Based on the decision tree algorithm and multiple linear regression method to predict the resource allocation of teachers’ positions, we constructed a model of human resource optimization and allocation strategy for college teachers and carried out the actual analysis of the utilization rate of resources for teachers’ positions and teachers’ schedules by genetic algorithm. Analysis obtained shows that selecting different population sizes for test results in teacher positions and teacher scheduling programs results in higher algorithm efficiency for populations between 30-50. When the value of the population is taken in the range of 30-50, the average time of the experiment is 60380.4ms-153199.2ms.
Analysis of the effectiveness of virtual reality technology integration in landscape design
Authors: Li Fubin , Zhao Xia
Published: January 2024

In this paper, we first studied the 3D visual immersion technology of virtual reality, explored the stereoscopic display and multi-channel stereoscopic display method of virtual reality, and corrected the nonlinear distortion by grating alignment and deformation correction. After that, the model’s lighting technology is examined, and the model’s lighting coefficient is analyzed and calculated. Then, the advantages of landscape design based on virtual reality technology in terms of subjective evaluation, human perception, and promotion of work efficiency were analyzed by comparing traditional landscape design with virtual reality landscape design. The results show that the Sig value of the environmental adaptability of the two spatial designs is 0.037, which is less than 0.05, and there is a significant difference between the two in terms of subjective ratings. People’s attention was enhanced by 7%-10% in the virtual design scene, and the induced brain frequency was 8%-10% higher than that of the traditional landscape design, indicating that the virtual landscape design was more effective.
Research on the Design of Digital Teaching Resource Management and Sharing Platform in Colleges and Universities Based on Cloud Storage
Authors: Wang Yajie
Published: January 2024

In this paper, after analyzing the structural system of the digital resource sharing model in colleges and universities, a shared storage model based on cloud storage is designed, and a digital teaching resource management and sharing platform for colleges and universities based on cloud storage is constructed on this basis. In order to realize accurate sharing, the sharing behaviors of teaching resources are symbolically illustrated, double behavior aggregation is performed, and a multidimensional preference personalized recommendation algorithm, i.e., DB-CGAT model, is designed to construct the personalized sharing module of teaching resources that integrates the behavioral graph. In addition, three types of experiments are conducted on the personalized sharing module of the platform to test its sharing performance and overall performance. The results show that the accuracy of this model is reduced by 0.04 compared with the traditional algorithm; the 90 percent time of login transaction is 2.44, and the time of query transaction is 1.46, which is all up to the standard value. All the action actions are green, and the number of clicks and throughputs in 5~30ss are around 120. Universities can benefit from the digital teaching resource management and sharing platform designed in this paper, which can improve teaching efficiency.
A Study on the Development of Professional Training in Physical Education in Colleges and Universities under Information Technology
Authors: Zhang Zhihua , Li Songmei
Published: January 2024

The deep integration of technology and college sports professional training can effectively stimulate the enthusiasm of students for sports training and, to a certain extent, reduce the danger of professional training. This paper first introduces the virtual reality technology under information technology to build a virtual sports training framework, and through virtual sports training, can effectively realize the immersive training of participants. Secondly, we use LiDAR to obtain point cloud data for the virtual scene of college sports professional training and reconstruct the virtual scene using the Poisson surface 3D reconstruction algorithm. Based on the OpenPose human posture estimation algorithm, the training movements of students in the virtual scene are identified, which helps coaches to better formulate standardized training movements. Finally, to verify the effectiveness of the method given in this paper in college physical education training, a series of quantitative analyses was carried out. The results show that the training loss of the Poisson surface 3D reconstruction algorithm is about 0.087 after 180 rounds of iteration, the verification accuracy is about 87.62%, and the training loss of the OpenPose algorithm is about 0.04% when the number of iterations reaches about 130 times. After using VR technology to carry out professional training in sports, the score of students in the experimental group in terms of active learning interest is 4.487±0.324 points, which is about 1 point higher than that of the control group. Virtual reality technology can effectively promote the innovation and reform of sports professional training in colleges and universities, enhance the student’s interest in learning sports training, and provide a guarantee for improving students’ physical quality.
Research on Grading and Evolution of International Trade Development Quality of City Clusters Based on Logit-ISM Modeling
Authors: Ye Baiqian
Published: January 2024

In order to further accelerate the realization of high-quality development of international trade and enhance the discourse power in international trade activities, this paper explores the grading and evolution of the quality of international trade development of city clusters. After analyzing the DEA static model and DEA-Malmquist dynamic evaluation model, combined with the entropy value method, the entropy value-DEA model is constructed to measure the comprehensive evaluation of the quality of international trade development of the city cluster, and the results are comprehensively analyzed. In addition, combined with the Logit-ISM model to analyze the factors affecting the development quality of international trade of city cluster and explore the grading and evolution of the development quality of international trade of city cluster from two perspectives of global statistics and global spatial trend. The results show that the fluctuation of the trade structure score is smaller than the trade scale, with an average growth rate of 0.165, and the trade competitiveness score basically stays in a state of growth except for 2008 and 2009, with an average annual growth rate of 0.972. The urban agglomerations in the eastern region account for a total of 0.38 of the city agglomerations in the city agglomerations synthesis, and the number of prefectural-level cities included is 106, which accounts for a total of 0.52 of the number of prefectural-level cities included in the city agglomerations. The quality of international trade development in city clusters in the eastern and northeastern regions stands out as the most significant. Based on the research in this paper, we advocate for the balanced development of the quality rating and evolution of each city cluster in international trade development.
Research and Practice of Digital Training Model Based on Artificial Intelligence Technology
Authors: Duan Haipeng
Published: January 2024

There are fatal defects in both the simulation practical training model and the actual combat practical training model. This paper firstly takes artificial intelligence technology as the basis for the construction of digital wisdom training classrooms and constructs the artificial intelligence digital wisdom training model. Secondly, it combines multi-factor reasoning and integrated clustering ideas to portray the vocational ability portrait of the learner group in the model and realizes the recommendation of students’ personalized training teaching resources with the learner’s portrait. Finally, the effectiveness is verified through the application practice of the digital training model for AI in higher vocational colleges. The results show that the use of multi-factor reasoning and integrated clustering can realize the accurate portrayal of the learner portrait of the digital intelligent training students and the difference between the loss value of the training and validation of the personalized recommendation model based on the learner portrait is about 0.01, and the average time consumed is about 1.05s. The digital training model supported by artificial intelligence technology can help students establish higher-order scientific thinking, promote students’ mastery of skills, and fully compensate for the shortcomings of the existing practical training model.
A Study of Minority Culture Outreach Translation Based on Cognitive Mapping Construction
Authors: Jin Ling
Published: January 2024

In this paper, we first construct a cognitive neural network and use the knowledge representation learning technique for knowledge complementation and relation extraction to semantically match head-tail entity pairs with relations and accurately model the semantic relationships between entities and relations. Then, the vectors of each entity are mapped onto the hyperplane of a given relation by the cognitive mapping translation model, and vector translation operations are performed on the hyperplane. Finally, this paper’s translation model is compared with other models to compare the semantic representation translation, task processing function, and model complexity of each model so as to verify the superiority of this paper’s model for minority culture outreach translation. The results show that this paper’s method increases 3.4 and 1.2 BLEU values on average in the four translation tasks compared to the Imagination model and VAG model, respectively. When the number of iterations is 40, the MRR value of this paper’s model is 0.345, which is at least 0.1-0.5 more than the other models, thus indicating that this paper’s model has a better performance in outreach translation.
The Construction of Online Interactive Teaching Mode of Cross-border E-commerce English in Colleges and Universities under the Background of Internet
Authors: Zhang Qian
Published: January 2024

In this paper, we first constructed an online interactive English teaching model through the interaction hierarchy tower model and adopted a data-driven social cognitive network analysis approach to explore the evolutionary dynamics of cross-border e-commerce English learning communities in higher education and their potential correlation with the development of participants’ interaction patterns. Then, the online synchronous and asynchronous interaction patterns of learners are compared and integrated by extracting the characteristics of online interactive teaching learners. Finally, an instructional design for an online English for Cross-border E-commerce course was used to explore the differences and associations between online interactive teaching modes. The results show that in the teaching experiment, students have 39 nodes in the synchronous interaction network (SMN) and 34 nodes in the asynchronous interaction network (UMN), and the degree centrality and eigenvector centrality Rank=4.07 and 3.15 of the SMN are also significantly higher than those of the three interaction networks. The SMN interaction model is found to be the most efficient in the online interaction teaching process. This study helps to improve the dynamic regulation and precise guidance of the online learning process for cross-border e-commerce English, which ultimately enhances the quality of online teaching.
Analysis of the effect of music therapy on psychological anxiety relief based on artificial intelligence recognition
Authors: Xin Lei
Published: January 2024

In order to improve the accuracy and reliability of EEG emotion recognition and avoid the problems of poor decomposition effect and long time consumption caused by manual parameter selection, this paper constructs an EEG emotion recognition model based on optimized variational modal decomposition. Aiming at the modal aliasing problem existing in traditional decomposition methods, the KH algorithm is used to search for the optimal penalty factor and the number of decomposition layers of the VMD, and KH-VMD decomposition is performed on the EEG signals in the DEAP dataset. The time-domain, frequency-domain, and nonlinear features of IMFs under different time windows are extracted, respectively, and the Catboost classifier completes the construction of the EEG emotion recognition model and emotion classification. Considering the two conditions of the complexity of the network structure of the KH-VMD model and the average classification accuracy of different brain regions in different music environments, the WEE features of the target EEG can constitute the optimal classification network by taking the WEE features of the target EEG as the input of the KH-VMD classification model. At this time, the average classification accuracy that can be obtained with differentiated brain regions and differentiated music environments is 0.8314 and 0.8204. After 8 weeks of music therapy, the experimental group’s low anxiety scores of pleasure and arousal on the Negative Picture SAM scale were 3.11 and 3.2, which were significantly lower than those of the control group’s low-anxiety subjects. The experimental group with high anxiety had anxiety scores and sleep quality scores that were 5.23 and 3.01 points lower than before the intervention. Therefore, music therapy can effectively alleviate psychological anxiety and enhance sleep quality.
The construction of rural e-commerce and logistics synergistic development model based on the coupling model
Authors: Mi Jing , Meng Que
Published: January 2024

By connecting the consumption and demand of the city and the countryside through the use of e-commerce platforms and logistics as an intermediary bridge, this study creates a model for the synergistic growth of rural e-commerce and logistics. A multi-dimensional index system is created by combining the actual state of rural e-commerce and logistics, using Shaanxi Province as an example. The degree of coordination between logistics and e-commerce can be ascertained by applying the coupling coordination model. Determine the weights of the indicators to solve for the level of coordinated development, the degree of linked coordination, the degree of rural e-commerce and logistics coupling, and the coordination level of each year using the entropy value technique. Together with the gray correlation degree, we will examine the crucial elements of optimizing the logistics chain for rural e-commerce. According to the study, rural e-commerce and logistics have a coupling coordination degree of 0.0913 in 2010 and 0.6347 in 2019. The degree of coupling coordination between the two is increasing, indicating a major coordination degree in 2019.
A personalized recommendation algorithm for online teaching resources of vocal music based on graph neural network
Authors: Wang Lina
Published: January 2024

In the development process of education informatization, realizing personalized learning is the urgent demand of learners. In this paper, we construct an online teaching resources recommendation algorithm (VGNN) based on a graph neural network (GNN). The project-based collaborative filtering algorithm is used to find highly similar teaching resource materials using Pearson’s correlation coefficient in order to personalize the recommendation of online teaching resources. The personalized recommendation algorithm for online teaching resources was tested and analyzed using the online teaching course Fundamentals of Vocal Music Theory as a case study. The results show that the course “Fundamentals of Vocal Music Theory” is divided into 4 clusters with clear boundary contours under the graph neural network algorithm, and the number of knowledge points in the 4 clusters is 2308, 655, 513, and 97, respectively. After learning the personalized recommended content from the 4 clusters of knowledge points, the average rate of loss of points for each of them decreases by about 0.3. The algorithm effectively solves the accurate classification of vocal knowledge and implements personalized recommendations for educational resources.
Research on the Influence of Socialist Core Value System Construction on College Students’ Ideological and Political Education in the Context of Deep Learning
Authors: Zhang Rongwei
Published: January 2024

In this paper, the word-level N-gram language model applicable to Chinese word segmentation in ideological and political education is obtained through large-scale corpus training, and the Chinese word segmentation path in ideological and political education is calculated according to the conditional probability formula. On the basis of the deep learning algorithm, the Chinese participle algorithm is optimized by introducing word frequency deviation and sorted word frequency deviation indexes, and the cut score with the largest value of the participle indexes is taken as the final participle result output. Starting from the current situation, we determine the evaluation indexes of ideological and political education. Meanwhile, we complete the research design of the impact of the socialist core value system and use the SPSS22.0 and Origin2019 statistical software to carry out the research and analysis of ideological and political education. The results show that the index values of the Chinese word separation algorithm based on the 4-gram language model have also been improved by 1.15%, which means that there exists the possibility of practical application of the model in Chinese word separation in ideological and political education. The college students’ identification with the socialist core values at the national, social and personal levels are all at a high level, with values of 4.28±0.82, 4.32±0.75 and 4.61±0.62 respectively. This study improves students’ ideological-political literacy and provides references to their healthy growth.
A Whole-Segment Carbon Measurement Approach for Energy Systems Incorporating Knowledge Mapping Techniques
Authors: Li Qiang , Liu Juanyu , Zhang Laidong , Li Xinyue , Luo Junting , Wang Sijue , Han Shuwang
Published: January 2024

As the current carbon measurement method makes it difficult to reflect the time-space variability of carbon emission factors, it leads to the inability to clarify the carbon emission responsibility of grid-side losses. In this paper, starting from the internal power system, based on the power system carbon emission flow analysis theory and knowledge graph technology, a trend-tracking analytical algorithm based on the node conductivity matrix operation is proposed to solve the complex power allocation relationship between each generating unit and each node load, and between each generating unit and the line network loss. On the basis of this algorithm, the carbon flow tracking model of the whole power system is established according to the conversion relationship between the current and the carbon flow, and the analytical expressions of the carbon emission distribution among the power generation side, the load side and the line loss are obtained by combining with matrix operation, so as to measure the carbon emission measurement results of the whole power system and to provide data references for the responsibility sharing of carbon emission. Finally, simulation verification is carried out based on the actual system operation and load data for C city. The total amount of carbon emissions from electricity consumption is 98.8 million tCO2 when C city is used as the minimum spatial scale, while the total amount of carbon emissions from electricity consumption is 67.9 million tCO2, 14.0 million tCO2, 16.9 million tCO2, and the total amount of the three regions is 98.8 million tCO2, which is consistent with that calculated when C city is used as the minimum spatial scale. The calculation results are consistent in real-time. The carbon measurement method proposed in this paper can obtain higher spatial resolution carbon measurement results for electricity consumption.
Exploration of Interdisciplinary Teaching Innovation Mode for Environmental Design Majors Based on Information Integration Technology
Authors: Xia Xing , Zhou Yangxiaoxiao , Fu Gang
Published: January 2024

This paper constructs an interdisciplinary, innovative teaching model for environmental design majors based on information fusion technology. Based on sensors to collect students’ expression characteristics, interest characteristics, attention characteristics and other information, and three-dimensional modeling of students’ state, the trajectory multimodal data generated from students’ interactions with the teaching facilities in the process of learning are correlated with the externally manifested learning activities and the implicit learning characteristics. Subsequently, the extracted data was merged and analyzed, and feedback was provided to enhance teaching effectiveness. The results show that the information fusion model has a recall rate of more than 0.9, a checking accuracy rate of 0.87-0.93, and a student behavior recognition rate of 85%-91%, which are all better than other models. After using the innovative teaching method, the coefficient of student feedback evaluation increased from 0.4 to 0.88, which indicates the effectiveness of this paper’s model in student behavior identification and feedback.
Research on the Construction Problems of Innovation and Entrepreneurship Education Programs in Higher Vocational Colleges and Universities under the Background of Digital Technology Era
Authors: Xu Yanwei
Published: January 2024

Entrepreneurship and innovative education have emerged as a new paradigm for the development of higher vocational abilities in the modern era, leaping into the global trend and tendency of higher education’s change and growth. The objective of this study is to explore the current state of innovation and entrepreneurship course construction in higher vocational schools. Specifically, we extracted students’ behavioral characteristics using the short-term behavioral sequence of attention and used the SVM model to predict the classification of innovation and business ownership education courses in higher professional colleges. Data mining was used to combine background information from the digital technology era to construct these courses in higher vocational schools. Furthermore, a multivariate linear regression model based on students’ comprehensive ability to innovate and entrepreneurship is established after the problems associated with curriculum construction are analyzed in order to investigate the relationship and impact between curriculum construction and students’ ability to innovate and entrepreneurship. The findings indicate that there is a general lack of an entrepreneurial culture in schools, a poor cultural heritage of entrepreneurship, a gender difference of 6.1, a lack of faculty strength, and a lack of funding, to the tune of 5.2 and 4.4, respectively, and the comprehensive ability of innovation and entrepreneurship of students = 0.30+0.25*curriculum structure+0.54*curriculum implementation+ 0.15*curriculum evaluation. Higher vocational institutions looking to enhance the way their courses on innovation and entrepreneurship are constructed can use the results of this study to guide their research.
Design of cultural and creative experience products in scenic spots based on CORE model
Authors: Dai Ying , Zhang Shusen
Published: January 2024

Under the background of “cultural and tourism integration”, scenic cultural and creative experience products are an important means to enhance the communication power of scenic spots and generate income. In this paper, the CORE model is used as the design concept, and the CORE design process for scenic cultural and creative products is constructed. The plain Bayesian classification algorithm is used to extract review feedback from the product, and the vectorization of the extracted reviews is achieved using the FastText model. The vectorized reviews are input into the logistic regression classification model to obtain sentiment classification results. A fused sentiment feature vector is constructed by combining Apirior and a sentiment dictionary aimed at separating sentiment vector classification. Finally, the experience effect of cultural and creative products is explored as an example of X scenic spot, and the optimization strategy of product design is explored. The attribute feature of X Scenic Spot’s cultural and creative experience product, “color” embraces four emotional attributes, and the corresponding adaptations are 4.77, 5.42, 5.40, and 5.38, respectively. The SDs of the emotional attributes of the existing product are The SDs of the emotional attributes of the existing products are 1.141, 1.025, and 0.184, respectively, and the differences between the product descriptions and the users’ opinions on the perceptual attributes are large, which provides the evaluation correlation in the CORE model. Under the guidance of the CORE model, four aspects of cultural and creative marketing, scenic area IP, consumer needs and product experience dimensions are proposed.
Practical Research on Curriculum Development in Chinese Traditional Culture Universities with an Information Technology Background—Taking Wood Engraving Picture as an Example
Authors: Guo Yadong
Published: January 2024

In today’s rapid development of information technology, integrating woodblock prints into campus curriculum development is an effective path to cultivating students’ cultural confidence. This paper takes the specific inspiration of woodblock New Year’s paintings for campus curriculum development as the entry point, and designs the implementation process of woodblock New Year’s paintings school-based curriculum. The stylistic features and color characteristics of woodblock prints are crucial for teachers to develop their teaching curriculum. In this paper, two-dimensional stylized images combined with an elliptic Fourier algorithm are used to preprocess and optimize the images of woodblock prints. The color features of woodblock annual paintings are extracted by the Mean shift algorithm based on pixel expression, which can be used to develop a school-based curriculum for teachers. In order to verify the effectiveness of the above method in extracting the shape and color features of woodblock annual paintings, this paper designs relevant experiments to carry out the verification analysis. The results show that the styling optimization based on the elliptic Fourier method has a stable output rate of about 0.92 after more than 300 iterations, and the recognized woodblock New Year’s painting styling image has the best clarity, up to about 0.211. The color feature matching method based on pixel expression increases with the number of feature matching points, and its final time consumption is approximately 32.5 seconds. The full combination of science and technology can combine the traditional excellent culture with curriculum development, providing a new path to revitalize the traditional culture as well as innovative curriculum teaching.