bluuebunny/crossref_metadata_2025 huggingface dataset:
Practical Research on Talent Cultivation Mode of First-class Professionals in Environmental Design under the Background of Artificial Intelligence
Authors: Chen Huijie , Wu Pengjun , Wei Xuefei
Published: November 2024

Starting from the basic principles of talent cultivation mode, this paper proposes a reform strategy to optimize the talent cultivation mode of environmental design with the help of intelligent technology in order to improve the quality of talent cultivation and achieve the “first-class” level for the current talent cultivation mode of environmental design majors. The necessity of an intelligent database in environmental design teaching is analyzed, and the improved TF-IDF algorithm and automatic classification algorithm of resources are proposed to improve the search for teaching resources for environmental design majors. Then, based on the query, the teaching resource recommendation model (UBM) is proposed. An algorithmic comparison between the improved TF-IDF method and the UBM model is carried out to verify the effectiveness of the improved algorithmic model. Combining the traditional talent training model results with the intelligent technology-assisted talent training model results for independent samples of the T-value test. T-value test results show that the F-value is 0.317, the Sig-value is 0.782>0.05, and the significance corresponding to the ANOVA t-test value is 0.009<0.05. It indicates that there is a significant difference in the final examination results for environmental design in the classes of the experimental and control groups. It means that after one semester of intelligent technology-assisted teaching practice, the professional performance of environmental design students improves, which contributes to the cultivation of first-class professional talents. The use of an intelligent database can be one of the effective ways of cultivating talent.
Analysis of Chinese-English Differences in “Degree Adverb + Noun” Constructions in the Perspective of Constructive Grammar Based on Pattern Recognition Technique
Authors: Chen Lvfang
Published: November 2024

The “degree adverb + noun” constructions in modern languages are widely used in people’s oral communication with novel forms, rich connotations, economy, humor, and fun. We select representative literary works from English and Chinese in the 20th century as the research corpus, and use regular expressions to count the results of the corpus search for English-Chinese “degree adverb + noun”. The distance-based pattern recognition algorithm figures out how close the feature vectors are to each other and finds constructions that match the pattern “degree adverb + noun” by combining the principle of proximity selection. We analyze the processed “degree adverb + noun” constructions for differences between English and Chinese, based on the retrieval and recognition results. At the same time, the cognitive state and teaching strategies of second language learners of “degree adverb + noun” are further investigated based on the analysis results. The distance-based pattern recognition algorithm in this paper can recognize “degree adverb + noun” constructions with an accuracy of more than 90%, which is about 3.5 times higher than that of the pattern recognition method based on the TFIDF algorithm. Through the analysis, this paper finds that there are differences between English and Chinese languages in terms of noun collocation, semantic basis and realization process, syntactic components, and pragmatic functions of “degree adverb + noun” constructions.
Research on the Integration Strategy of Artistic Elements and Technology in the Design of Intelligent Elderly Environments
Authors: Cheng Yin
Published: November 2024

In the face of the increasingly large aging group and the severe aging situation, attaching importance to the intelligent transformation of the aging environment and the integration of intelligent technology can make the existing traditional aging mode and other profound changes. This paper utilizes Maslow’s pyramid of needs hierarchy theory as a support, analyzes the elements of the elderly’s needs, and combines these elements to design an intelligent senior living environment. Then, the intelligent voice control and sensing systems are integrated with the lighting control system to realize lighting changes according to the needs of the elderly and create an artistic and intelligent senior living environment. The questionnaire was utilized to measure the satisfaction of the elderly with the intelligent aging environment. The results of the questionnaire data processing show that the elderly show high satisfaction with the intelligent aging environment at the instinctive, behavioral, and reflective levels. In addition, there is a significant difference in the satisfaction of the elderly of different ages with the intelligent aging environment at the instinctive level (P=0.003<0.05), and the younger elderly are more satisfied with the intelligent aging environment that integrates artistic elements and scientific and technological design. This paper designs intelligent senior living environments integrating science and technology, art and needs, which provide effective methods and research perspectives for senior living practice, and has certain social significance for design innovation to promote the formation of a friendly aging society.
Endangerment Evaluation and Inheritance Protection Path of Hainan Marine Intangible Cultural Heritage Based on Modern Information Technology
Authors: Deng Qiongfei
Published: November 2024

Hainan’s marine intangible cultural heritage, with its unique value, occupies an important position in global cultural diversity, but it is currently facing an endangered situation. This paper utilizes the Delphi method to select the initial indicators for the evaluation of the endangerment of Hainan’s marine intangible cultural heritage, then applies the hierarchical analysis method to determine the weights of the indicators at each level and evaluates the endangerment of Hainan’s marine intangible cultural heritage based on the fuzzy comprehensive evaluation method. Then, according to the current situation and evaluation results of Hainan marine intangible cultural heritage, the digital inheritance and protection path of Hainan marine intangible cultural heritage is designed by using modern technology as a means. Among the specific indicators of the endangerment evaluation index system of Hainan marine intangible cultural heritage, the economic benefit has the largest weight, which is as high as 0.104. It shows that the economic benefit of preserving and preserving Hainan marine intangible cultural heritage needs to be improved. In the endangerment evaluation of Hainan’s marine intangible cultural heritage, for example, the overall evaluation value is 3.525, and its endangerment status is between generally endangered and relatively endangered. Among them, the evaluation values of social and cultural factors are higher, favoring comparatively endangered, indicating that more consideration should be given to the inheritance and protection of A Hainan marine intangible cultural heritage from both social and cultural aspects.
Research on the Development Status and Countermeasures of New Cooperative Economic Organizations in Rural Areas in the Information Age
Authors: Geng Fangmei , Sun Yanyan
Published: November 2024

The article borrows game theory to analyze the development dilemma of new rural cooperative economic organizations. A rural cooperative economic organization that is based on game theory is proposed by describing the new rural cooperative economic organization and game theory. According to the subject of interest, the basic assumptions of the model are determined, and the game theory model for rural cooperative economic organizations is constructed by combining the basic assumptions and relevant variables, and the evolutionary stabilization strategy solution process is given at the same time. The development status of new rural cooperative economic organizations in the context of information technology is evaluated using the model mentioned above. When E
2 = 0.18, the probability of both parties choosing {cooperation, cooperative} strategy will increase to 82.3%. And E
2 = 0.82 will reduce the probability of forming complete cooperation to 71.5% through the introduction of cost and benefit distribution, supervision and punishment mechanisms to achieve a win-win situation for the community of interest, but there is still the probability of the two sides cooperating to choose the optimal strategy will become smaller, revealing that the current development of the rural cooperative economic organization has problems and shortcomings. In order to improve the development of cooperative economic organizations in rural areas, relevant strategies are proposed.
An empirical study on the data integration model in the comprehensive development of ideological education and student management in colleges and universities based on the concept of three-pronged parenting
Authors: Guo Lingfei
Published: November 2024

In this paper, a smart campus analysis model based on multi-source data fusion technology is constructed with the study of college students’ behavior as the starting point. The K-means algorithm is utilized to mine the campus data of real college students from multiple sources, and through the fusion of multi-source data, a real, intelligent, multi-level student portrait is portrayed in the three dimensions of consumption, academics, and socialization, so as to provide a rational decision-making basis for the comprehensive development of the ideological and political education and student management of the university with the “three-whole-education” approach. The results show that multi-source data fusion technology can significantly reduce the storage space required for data. University X has a low borrowing interest for Civics and Political Science books. Sports are loved by 70% of students, but half of them don’t exercise regularly. Outside spending is a habit among some students, and 20% of them may exhibit abnormal behavior. These individual behavioral characteristics will have a significant impact on the performance of Civics.
Application of Big Data Visualization Technology in Quality Assessment of English Translation of Ancient Books
Authors: He Yanan
Published: November 2024

The development and application of machine translation cannot be separated from the evaluation of its quality. Correct evaluation is a correct lead to its development direction, and the translation direction respected by mainstream evaluation can be said to be the development direction of machine translation in research. In this paper, the Transformer model of the multi-head attention mechanism is constructed, and the optimization and improvement schemes in both model architecture and training data are proposed for the mBERT and XLM models to form the XLM-R model. Based on the predictor-evaluator QE model and the pre-trained model-evaluator QE two models, the XLM-R translation quality assessment baseline is proposed. A CLS pooling method is proposed for the baseline system, which ensures similarity at a finer-grained subword level. Meanwhile, the subword similarity scoring index is embodied using a simple splicing method, taking into account the global semantic quality. Simulation experiments are set up to evaluate the quality of translation tasks at the sentence and system levels, respectively. There was a 7.92% improvement in the Pearson correlation coefficient of the model with similarity characterization when compared to the one without the model in the sentence-level QE task development set, which was 0.0379 higher. The model’s translation fluency also showed an increasing trend in the interval of 0.15 to 0.5 with the growth of the manual score, indicating that the model proposed in this paper is effective in baseline system evaluation.
Using Natural Language Processing Techniques to Study the Development Dynamics of the Subei Mongolian Language and Its Shaping of the Chinese National Community Consciousness
Authors: Bao Dongmei
Published: November 2024

Language and society are a pair of covariance; language reflects the changes in society, and the changes in society have an important impact on the language. The urbanization process in the Subei area is reflected in the current Mongolian language use situation. This paper explores the intrinsic connection between language and the Chinese national community, in which the emotional identity of Mongolian script is one of the factors affecting the development of Mongolian language in Subei. Mongolian emotions are represented semantically using the SOFT self-attention mechanism. The computation of emotion word weights and distributions is carried out sequentially to enhance the emotion word tokens that semantic rules represent. Through the mining of emotion prior knowledge, new emotion words are found from the Mongolian emotion corpus with the help of emotion seed words, and a set of candidate emotion words is constructed. The emotion words that were mined in Mongolia are merged into emotion sentences, and then they are emotionally masked. An empirical survey is designed to visit and examine the local Mongolian residents in Subei using random sampling. The psychological distance of Mongolians towards intermarriage is the lowest among the subject ethnic groups, with a mean value of 1.7585. The development of the Mongolian language in Subei is a map of the progress of the Chinese nation’s consciousness and contributes to the formation of a sense of community among its people.
Research on the Protection and Inheritance Strategy of Folk Dance Art in the Digital Era
Authors: Li Da
Published: November 2024

The digital protection and development of folk dance art play a crucial role in bridging the gap between science and the humanities, enabling the integration of science, technology, and the humanities. The article initially employs an optical motion capture system to gather data on the movements of folk dance art. Subsequently, it merges this data to create a digital archive of folk dance art and explores the specific applications of this digital archive. To eliminate abnormal data from the motion capture process, this paper introduces the Kalman filtering algorithm, which preprocesses the folk dance action data. The PAFs algorithm then extracts the key points of the human skeleton from the folk dance action. Then, the coordinates of folk dance action features are changed by Euler angles to extract the corresponding action features and combined with the feature vectors of the action sequence to realize the gesture matching of folk dance actions. The KANO model and regression analysis exploration are the primary means of data analysis for the development of folk dance art inheritance. Using the PAF algorithm to extract the human skeleton key points of folk dance art, the average precision rate is 82.52%, the convenience of the audience’s demand for the digital experience of folk dance art has the highest better value of 0.712, and the regression coefficient of closeness to life is the largest at 0.283. Folk culture should inform the digital preservation and inheritance of folk dance art, expanding its dissemination and fostering its digital development.
The Integration of Virtual Reality Technology in Chinese Language and Literature Classroom Teaching and Its Teaching Effects
Authors: Li Xue
Published: November 2024

Virtual reality technology has the potential to be applied to enhance the presentation effect and student participation in the Chinese language and literature classroom. After analyzing the applications of this technology in the teaching of Chinese language and literature, a virtual scenario teaching program is created in this paper. A virtual reality-based scenario teaching system is constructed by the program and integrated with traditional teaching methods. A teaching case combining VR technology was designed with “Tianjingsha-Autumn Thoughts” as an example, and a teaching experiment study was conducted based on the case. The results show that the outstanding rate of poetry achievement in the experimental class increased by 50%, the average score increased by 9.41 points, and the scores of the survey results in the four dimensions of learning interest, learning participation, system satisfaction, and knowledge mastery were all around 3.5 points. Virtual reality technology in the teaching program has a positive effect on students’ better mastery of traditional poetry and enhanced learning interest.
Research on the innovation path of “one axis and two wheels” course ideology and politics of mechanical majors under the support of cloud computing
Authors: Li Yanfang
Published: November 2024

“Curriculum Civics” is a reform measure of human education put forward under the fundamental pursuit and urgent demand for human education in colleges and universities in the development of the country and society, and it is an important hand for colleges and universities to realize the fundamental task of establishing morality and educating people. This paper focuses on the problems that exist in the education and teaching of Civics and Politics in college and university mechanical courses, takes the core qualities of mechanical disciplines as the “axis” and takes the national courses and school-based courses as the “two-wheel drive” to build the “one-axis-two-wheels The curriculum system of “one axis and two wheels” is constructed with the national curriculum and school-based curriculum as the “two-wheel drive”. Based on the whole perspective learning theory and ARCS motivation model, combined with the “one axis and two wheels” curriculum system, the innovative model of Civic and Political Teaching for Mechanical Professional Courses is constructed. The teaching experiment method was utilized to implement the teaching design that included Civics elements in the experimental class. Analyzing the data of the control class and the experimental class, the conclusion shows that the ideological and political literacy of the experimental class (4.7119±0.9943) is significantly greater than that of the control class (4.1696±0.8406), and at the same time, the end-of-course averages of the “Fundamentals of Mechanical” course of the experimental class and the control class are 85.25 and 76.41, respectively, which are also significantly different (P<0.05). It indicates that the teaching mode of Civics and Politics of Mechanical Specialty Course can improve the students’ Civics and Politics level, indirectly contribute to the improvement of their grades in the specialty courses, so that the students can realize the moral and technical skills and cultivation.
Intelligent Optimization Method and Network Security Analysis for Power System Active Control
Authors: Ding Chaojie , Li Lanqing , Zhou Nan , Gu Dongjian
Published: November 2024

Optimizing the active control of the power system and improving the stability of the system in the face of cyber-attacks are necessary to secure the power supply and achieve energy saving and emission reduction. The article proposes an improved granular computing method applied to power system active control, which includes chaotic initialization, dynamic parameter adjustment, and a fast search strategy. And also provides two strategies for defense against FDIA and DDoS attacks. The minimum cost of the IGrC algorithm in 5, 10 and 30 unit systems are 43115.67$, 1017569.51$ and 10170321$, and it has good convergence and robustness. The F1 value of the vertical and horizontal prediction algorithm used is more than 90% in all environments, and the optimal marginal cost of this paper’s algorithm is 44.8357 regardless of whether or not it is facing DDoS attacks. Therefore, the active control optimization method and attack defense strategy proposed in this paper have practical application effects.
Advances in computer AI-assisted multimodal data fusion techniques
Authors: Fan Pan , Wu Qiang
Published: November 2024

Through the integration of multimodal data fusion technology and computer AI technology, people’s needs for intelligent life can be better met. This paper introduces the alignment and perception algorithm for multimodal data fusion, which is based on combining the multimodal data fusion model. Taking the air pollutant concentration prediction as an example, the time series of air pollutant concentration is obtained through the LSTM model for concentration prediction, and the attention mechanism is introduced to establish the numerical prediction model of air pollution. Different stations are also selected to acquire weather image data, and the TS-Conv-LSTM multimodal spatio-temporal fusion model of air quality images is constructed by utilizing the Conv-LSTM cell as an encoder, and then the TransConv-LSTM cell, which integrates the anti-convolution and the long-short-term memory network cell, as a decoder. The Gaussian regression model was then used to combine numerical prediction and image prediction models, thus achieving the multimodal synergistic prediction of air pollutant concentrations. The RMSE of the ATT-LSTM model on the dataset was reduced to 8.03 compared to the comparison model, and the predictive fit to the image dataset was above 0.75 for all R² values. The lowest MAE value obtained by the multimodal collaborative prediction model is only 3.815, and the highest R² value is up to 0.985. Introducing deep learning techniques into multimodal data fusion helps to explore the value of massive data more deeply and obtain more comprehensive and reliable information about it.
Behavioral Pattern Identification of E-commerce Consumers’ Purchase Intention in Big Data Environment
Authors: Gao Feng , Peng Caigen
Published: November 2024

Predicting user purchase behavior using shopping history data on e-commerce platforms helps to improve user experience and marketing effect. Our paper uses the time-sliding window method to construct features that mine users’ interest preferences in different periods based on the real interaction records between users and products in e-commerce scenarios. Then, a model for predicting user purchase behavior based on CNN-LSTM is proposed. By automatically extracting and selecting user attributes, product attributes, and user behavioral features, the model is used to predict user purchasing behavior. An online retail platform implements precision marketing using this model. The results show that the calculated values of the marketing effect in the Attention Stage, Interest Stage and Active Participation Stage are between [0.8-1.0], and the effect of Precision Marketing is “Excellent”. The calculated value of the marketing effect in the action stage and repeat purchase stage is between [0.6-0.8], and the effect of precision marketing is “good”. After the implementation of precision marketing, the operating income of e-commerce platform A is increasing, while the operating expense ratio remains stable. This paper’s model can effectively improve consumers’ purchase intention, as evidenced by its findings.
A study on the relationship between physical education teaching strategies and students’ physical fitness based on big data analysis
Authors: Guo Qiang , Liu Yamei , Guo Li
Published: November 2024

Physical education occupies a very important position in university programs. Cultivating students’ physical fitness and comprehensive ability is the important significance of the existence and development of university sports. In this paper, after collecting and processing data related to students’ physical fitness tests, the K-means clustering algorithm is improved to cluster and analyze the physical fitness data of different students. Then, the FP-growth algorithm based on association rules mines the relationship between the physical fitness indicators of different groups of students, obtains the optimization strategy of physical education teaching, and introduces the logistic regression model to analyze the correlation relationship between the physical education teaching strategy based on big data optimization and students’ physical fitness. The results showed that whether the 20m round-trip running (students’ speed) was qualified or not was positively correlated with the frequency of application of physical education teaching strategies (sometimes used, not used, or occasionally used) (OR values of 1.49 and 2.12, respectively, with p-values less than 0.05) and that it was conducive to promoting the normal development of college students’ physique and physical fitness through the application of physical education teaching strategies.
An Advanced Approach to Optimizing Teaching Strategies Using Game Theory in English Curriculum Ideology and Politics
Authors: Hu Zhihong
Published: November 2024

Ideology and politics education is both an innovative practice of professional talent training reform in colleges and universities and a realistic response to the cultivation of high-quality and high-level talents in the society of the new era. This paper creates an evolutionary game model that represents the ideology and politics of the English curriculum for teachers and students. Based on the evolutionary stability strategy, we put forward the game hypothesis, use the replication dynamic equation to construct the evolutionary game model for the optimization of the English course, and describe the model stability test principle and calculation process. Our exploration of the English course is based on game theory using the data simulation method. The cost directly impacts the likelihood of teachers’ ideologies and political education as well as students’ ability to take a serious attitude. When both sides of the benefit exceed 75, both sides of the evolutionary stability strategy adopt serious attitudes, leading to an increase in the speed of choosing a serious attitude. This increase is also reflected in the results of the overall game analysis, which determines the teaching strategy for the English curriculum’s ideology and politics. The complete interpretation of game theory regarding the English course optimization effect is necessary to enhance the level of ideological and political education in colleges and universities.
Personalized Recommendation Mechanism of College English Writing Teaching Content Based on OBE Concept in Big Data Environment
Authors: Huang Xuemei , Tan Haoliang
Published: November 2024

With the rapid development of education information technology today, more and more educators are beginning to consider how to implement more personalized education and better align teaching to students’ abilities. This paper explores personalized recommendations for college English writing instruction, utilizing the concept of Personalized Behavior Education (OBE). This paper first analyzed English-related data from 200 college students, including vocabulary, grammar, reading, and speaking abilities. Cluster analysis is used to classify the abilities of different groups in English writing. Collaborative filtering recommendation modeling is used to recommend writing methods for college students that are appropriate for them individually. This paper revealed that the first group of students utilizes 14% and 26% more quotations and advanced vocabulary, respectively, compared to the fifth group. Simulation experiments reveal that setting parameter 1 to 0.6 and parameter 2 to 0.2 results in a lower and more stable MAE value, thereby lessening its influence on the recommendation algorithm. Furthermore, the performance test results demonstrate that the precision value of this paper’s scheme surpasses that of the traditional CF algorithm by a range of 0.088 to 0.14, and the recall value of this paper’s algorithm surpasses that of the traditional CF method, with a maximum difference of 0.11. In addition, the actual accuracy of this paper’s personalized recommender system is 6.2% higher than the expected one, and it takes only 1s to provide the user with a personalized recommender’s response time. In summary, the experiments above reflect the high efficiency of this paper’s recommender system and the high acceptance of students.
Research on College Counselors’ Ability to Guide College Students’ Employment and Entrepreneurship Based on Analysis of Big Data Technology
Authors: Lei Yonghan
Published: November 2024

Employment is the basis of people’s livelihood, and in the face of the severe employment problems of college students, the guidance role and ability of college counselors are becoming more and more prominent. Based on the current situation of college students’ employment and entrepreneurship and the responsibilities of college counselors in this area, the author uses multiple linear regression analysis to explore the ability of college counselors to guide college students’ employment and entrepreneurship. After conducting factor analysis, descriptive statistical analysis, correlation analysis and regression analysis on the employment and entrepreneurship ability of college counselors through the example study, the influencing factors of the employment and entrepreneurship counseling ability of college counselors are identified. The four public factors extracted through principal component analysis have a total explained variance of over 98%. The mean and median of the overall employment and entrepreneurship counseling competence of the college counselors surveyed in this study were slightly greater than 4. Among the eight secondary indicators, the highest score was Q5 Entrepreneurship Policy Propaganda (4.28), while the lowest score was Q7 Innovation and Entrepreneurship Competition Guidance (3.67). The mean value of overall employment and entrepreneurship guidance competence is 4.13. There is a significant correlation between the employment and entrepreneurship guidance competence of college counselors and each sub-dimension. The correlation coefficients of overall employment and entrepreneurship guidance competence (EGA) with employment guidance competence (EGA1), entrepreneurship guidance competence (EGA2), internship guidance (Q2), and career planning and counseling (Q3) were 0.964, 0.902, 0.924, and 0.928, respectively. Counselors with more than 10 years of work experience were more skilled in career guidance than counselors with less than 5 years of experience.
Functional framework construction of blockchain technology in the information management of college students’ ideological and political education in colleges and universities
Authors: Li Lin
Published: November 2024

Currently, ideological and political education faces three major pain points: mismatch of information supply and demand, obstacles to resource sharing, and lack of trust between the subject and object of education. Based on this, this study applies blockchain technology to the informatization management of college students’ ideological and political education in colleges and universities and designs the functional framework and main functional modules of the informatization management platform of college and university ideological and political education. Teachers and students of a regional university are selected as the research samples, and after analyzing the application of the platform by teachers and students of the university, we construct the evaluation indexes of the platform’s system structure and system function and use the DBN model to evaluate the application effect of the platform. The results show that after the use of the Civic and Political Education Informatization Management Platform, the sample teachers and students have a better knowledge and use of it, and 65.8% of the teachers and students have a higher frequency of use. The ideological and political education informatization management platform obtains a better application effect, with evaluation scores of 75.3 and 85.7 for its system structure and system functions, and it obtains excellent performance in the quality and organization of teaching resources, the construction and sharing of high-quality teaching resources, and the improvement of management efficiency. The organic combination of blockchain technology and ideological and political education in colleges and universities can improve the level of ideological and political education and promote innovation and optimization of the education model.
Research on thermal error compensation strategy of CNC machine tools based on full working area modeling
Authors: Pei Xinglin
Published: November 2024

Traditional manufacturing equipment is developing in the direction of precision, intelligence and integration, and the precision requirements of CNC machine tools are getting higher and higher. Compensating and controlling the thermal error of the machine tool is an important part of improving machining accuracy. This paper uses a cuckoo search algorithm to optimize the BP neural network to get the CSBP neural network model and inputs the temperature value of the CNC machine tool into the CSBP model to get the thermal error prediction results. Combined with the thermal error values of each measurement point on the CNC machine table, the B-spline function is used to fit the thermal error prediction model for the entire working area. Finally, the thermal error compensation system of the CNC machine tool has been established. Simulation and empirical studies show that the fitting and prediction accuracy of the model in this paper are better, and the maximum error value of the prediction is reduced by 20.27% compared to the LSTM model. After the application of the thermal compensation system in this paper, the thermal error of the CNC machine tool is greatly reduced, and most of the offset caused by the thermal deformation of the machine tool is eliminated through compensation. In this paper, the design of a thermal error compensation system based on full work area modeling can effectively reduce the thermal error of CNC machine tools, which can be applied to the actual machining process of machine tools to improve the machining accuracy of CNC machine tools.
Intelligent Reconstruction and Effectiveness Evaluation of Nursing Workflow for Future Hospitals
Authors: Su Miao , Wang Dongmei
Published: November 2024

In this paper, the overall structure of the intelligent nursing system is designed in detail to realize the reconstruction of each process of nursing work by the intelligent nursing system. The data of nursing medical record documents of a tertiary hospital were collected as the basis of analysis, and statistical methods were used to compare and analyze the writing of medical records before and after the intelligent reconstruction of nursing workflow. Analysis of variance (ANOVA) and independent paired t-test were chosen to understand the clinical measurement differences between the intelligent nursing system and the traditional technology, and a self-designed questionnaire was used to explore the nurses’ intention to use the intelligent nursing system from their point of view. The results showed that the intelligent nursing system significantly reduced writing time (P≤0.001) and improved medical record writing ability compared with manual methods. The time efficiency of measuring physical sign data was improved by intelligent nursing systems by 74.16% and 69.8% respectively. Nurses’ knowledge of the intelligent nursing system was as high as 63.64%, and functionally, nurses’ intention to use the intelligent nursing system accounted for 85.29%, which was at a medium-high level.
Educational gamification: motivation and engagement strategies
Authors: Ma Junyuan
Published: November 2024

Gamified learning creates authentic situations for students to solve tasks, provides students with active learning opportunities, and is an effective way to cultivate problem-solving ability, critical thinking, creativity, etc. In this paper, we conduct an in-depth study of gamified learning and learning behavior modeling technology, choose the Hidden Markov Model as the technical support of the study, adopt the Bayesian Information Criterion to select the optimal number of hidden states of the model, and combine the K-means algorithm with the model optimization in model parameter estimation, which to a certain extent improves the speed of convergence in the process of learning behavior modeling. The game elements and learning activity elements have been integrated and migrated, and proposed gamified learning activity elements. Activity theory and self-determination theory were used to design a gamified learning activity process for the educational field. The game-based learning activity process was continuously revised and optimized by iterating the process with actual teaching cases. Subsequently, we merged qualitative and quantitative research to examine students’ gamified learning and the changes in their learning effects. The results showed that gamified learning produced significant facilitation (p<0.001) in all four dimensions of mind-flow experience, intrinsic motivation, knowledge retention, and transfer performance, with effect values of 1.05, 1.65, 1.00, and 1.08, respectively. This indicates that the gamified learning model can enable students to stimulate and maintain good motivation for learning, and further demonstrates that the process of designing gamified learning activities has effectiveness.
Research on the optimization of interior design visual elements and art design innovation method under the deep convolutional network framework
Authors: Miao Cuijie
Published: November 2024

As data science and computer science continue to advance, the application of deep learning methods to address technological innovation and optimize interior design has emerged as a significant area of research. In this paper, we propose a VR matching algorithm that utilizes deep convolutional networks to match the appropriate visual elements of the room layout, thereby realizing a panoramic scheme for interior design. A method of automatic extraction of features and labels of room layout based on a convolutional neural network is designed, trained, and tested with the help of a convolutional deep confidence network, and the labeled room layout feature map is classified using the Softmax classifier. A fast retrieval algorithm is being investigated with input in the form of images and combining text and content. Firstly, we input the room layout feature image, extract the feature vector using a convolutional neural network model, and then calculate the similarity between the feature vector in the visual element decorative design drawing and the feature vector of the input room layout image. The maximum similarity is selected as the visual element design scheme of the feature, and then the picture of the panoramic scheme is realized in order to let the designer get the customer’s feedback on the design effect in a more timely manner. The classification models developed in this paper achieve an accuracy rate exceeding 90%, effectively fulfilling the task of classifying images of room layout features. The user’s satisfaction with the interior design methodology experience projects proposed in this paper is also all higher than 70%, and the feedback from both designers and users is very good, which shows the excellent effect of deep convolutional networks in the optimization of interior design visual elements.
Quantitative Analysis and Modeling of Student Innovation Capability in Higher Education Management in an Innovative and Entrepreneurial Environment
Authors: Miao Yuee
Published: November 2024

Colleges and universities often focus on cultivating talent, a practice that directly contributes to the lack of creativity among their students. In light of this, this paper aims to promote education reform and enhance students’ capacity for innovation. This paper constructs the evaluation index system and model of innovation ability of students in colleges and universities to promote the cultivation of innovative talents. Based on the AHP model to determine the index weight of each evaluation factor, with the help of gray correlation to analyze the relationship of each evaluation index, the decision matrix is established, and the gray comprehensive judgment model is constructed. We establish the evaluation sample matrix by using the whitened weight function to determine the evaluation gray class. We then calculate the gray evaluation coefficients, weight vectors, and weight matrices to arrive at a comprehensive evaluation of innovative ability. This paper employs the Hebei University of Technology in China as its research site and applies its methodology to evaluate the innovation capacity of its students. The comprehensive evaluation value of the students’ innovative abilities is only 6.67, placing them at the medium level. The maximum relative error between the evaluation mean value of each specific index at the index level and the expert evaluation result is 1.84%. In terms of the satisfaction of the evaluation method, the satisfaction mean value of this paper’s method exceeds that of the expert evaluation method in the dimensions of the evaluation concept, the evaluation subject, the evaluation method, the evaluation indexes, the evaluation procedure, and the application of the evaluation result, which are respectively 0.14, 1.25, 1.43, 0.7, 1.45, and 0.49.
Research on the Innovative Expression of Folk Art under Intelligent Technology Support
Authors: Wan Yuanyuan
Published: November 2024

Chinese folk art is a valuable cultural treasure of China, and in the context of digitalization and the information revolution, the growth of productivity has laid a solid foundation for the advancement of folk art display modes. Therefore, this paper combines three-dimensional modeling, human-computer interaction technology, and augmented reality technology to design a digital folk art display system. It aims to create an innovative display system with interactive features, thereby enhancing the inheritance and development of folk art. This paper employed a quantitative testing method to test the folk art display system, focusing on cultural identity and psychological experience. The data results show that the students’ overall cultural identity after using the folk art digital display system proposed in this paper is 88.15%.
Mathematical and Intellectual Innovation in Higher Education Talent Training Models
Authors: Wu Chunhua
Published: November 2024

The economy and society have entered a highly transformative digital age. Digital Intelligence promotes the change of social and economic forms and promotes the integration and innovation of technology, economy and society. In this paper, we formulate the goal of training talents with digital intelligence thinking and the model of training talents with digital intelligence thinking, and propose a strategy for implementing talent training. Using big data technology (cloud computing resource scheduling method, virtual scene dynamic splicing technology) to assist in the implementation of teaching strategies. Conduct simulation experiments to analyze the performance of the cloud resource scheduling algorithm proposed in this paper on different numbers of virtual machines. Evaluate the effect of virtual scene splicing technology on image alignment. Discuss the influences factors from the three aspects of cultivation objectives, curriculum arrangement, and scientific research training in light of the satisfaction of the implementation of the mathematical and intellectual talent cultivation model. The cultivation objectives for numerical intelligence ability are viewed by 40.61% of the students as average, and 13.75% of them feel completely satisfied. Only 4.31% of the students agreed on scientific research and innovation. It can be seen that most of the students did not carry out any interdisciplinary research in depth. It shows that the implementation of the strategy for cultivating mathematical and intellectual talents still needs improvement and strengthening.
Analysis of Internet Communication Effect and Influencing Factors of Traditional Music
Authors: Xiong Ying
Published: November 2024

This paper digs out the corresponding influencing factors by defining the traditional music communication effect. For research purposes, the questionnaire is analyzed to analyze the impact of traditional music communication from an Internet perspective. Two distribution methods, online and offline, are used to collect research data. The data are analyzed based on the Pearson correlation coefficient and multiple regression model, after testing the reliability of the questionnaire. The music form scored the highest, with a mean of 20.70 and a standard deviation of 12.09, and it had the greatest influence on the traditional music dissemination process. There is a significant positive correlation between music content, music form, creator, communicator, audience, and communication media and traditional music communication effect, P<0.05, and the explanatory power of the independent variable to the dependent variable is 68.8%, which leads to the regression equation of the factors influencing the communication effect of traditional music in the Internet perspective. This study provides a new understanding of the Internet communication effect of traditional music, allowing it to be comprehensively improved.
Research on Multidimensional Data Analysis and Predictive Modeling for International Political Stability Assessment
Authors: Xu Yupu
Published: November 2024

International political stability has been a hot issue of global concern. Starting from the factors influencing international political stability, the study constructs a prediction model based on the CNN neural network and takes some international countries as the case study objects to predict the political stability of each country. The system of political stability influencing factor indicators is constructed. 13 influencing factor indicators are selected and divided into three categories, and the warning intervals of early warning indicators are determined. The study trained and validated the CNN neural network model, and the results showed that the mean square error of the prediction model was 1.862 × 108, the average accuracy of the model was 1.53%, and the relative error of each year was within ±4%, which reached the set model accuracy, and thus the prediction model proposed in this paper can be highly accurate. Subsequently, 44 countries along the route were selected to carry out political stability prediction research using the early warning model, and finally, the political stability of some countries was investigated according to the stability interval level classification method, and the results showed that the political stability of Syria, Iran, and many other countries had a high-risk phenomenon.