bluuebunny/crossref_metadata_2025 huggingface dataset:
Research on the Integration and Innovative Expression Methods of Visual Elements of Popular Music in Multimedia Era
Authors: Ma Xiaohong
Published: October 2024

Visual art and music art are two typical media, and the progress of multimedia technology has prompted the cross-border integration between them. This paper tries to visualize the visual translation of music acoustic information and emotional experiences through audiovisual mapping design. The extraction and analysis of musical and visual elements in the music visual mapping model are summarized and analyzed. Combined with the visual expression method, a mapping pattern framework that can be reused in music visualization design is proposed, and two types of mapping patterns are classified on top of it. Based on the four basic attributes of pitch, chord, tone, and timbre of popular music, corresponding visual elements are designed. Finally, the impact of the two mapping modes on the functional and aesthetic effects of music visualization is experimentally demonstrated and evaluated, and it is found that the mean value of the scaling index of the original HCR sequence of the pop music clip is close to 0.864, while the mean value of the disturbed sequence is 0.504, which is a referable evaluation result for determining the appropriate mapping type when designing music visualization.
Research on the Evaluation of the Effectiveness of Industry-Teaching Integration Construction of Higher Vocational Excellence Courses--Based on Network DEA Model Analysis
Authors: Chen Chen , Song Peisen
Published: October 2024

The integration of industry and education is an important model for building high-level higher vocational colleges and universities, and it is also a necessary way to promote the modernization and development of higher vocational education. Based on Hall’s three-dimensional structural model, this paper explores the specific process of the construction of industry-teaching integration of high-level, high-quality courses and evaluates the effectiveness of the construction of industry-teaching integration of high-level, high-quality courses using the network SBM-DEA model. The evaluation index system was first constructed according to the questionnaire survey method, Delphi method, and hierarchical analysis method, and then the indexes were screened and applied to the empirical analysis of the effectiveness of the construction of industry-teaching fusion of higher vocational boutique courses. The average overall operational efficiency of the industry-teaching fusion of boutique courses at 45 higher vocational colleges and universities is 0.547, which is the average level. However, the efficiency of the two phases still has some differences between the average efficiency value of the resource construction phase and the outcome output phase. The correlation coefficient between the efficiency of the outcome output stage and the overall operational efficiency is 0.885, which is highly correlated. Most institutions pay more attention to the operation of the outcome output stage. The R² of the fit between pure technical efficiency and comprehensive efficiency is 0.731, and the R² of the fit between scale efficiency and comprehensive efficiency is 0.264, indicating that pure technical efficiency is the dominant factor affecting the comprehensive efficiency of institutions. In the two stages of resource construction and output of results, the output side shows insufficient output, while the input side shows input redundancy, indicating that the input resources are not effectively utilized. This paper provides a direction of action to strengthen the deep integration of industry and education in higher vocational boutique courses and to promote complementary resources and a benign interaction between schools and enterprises.
Data-driven innovation and implementation effectiveness of tourism marketing strategies in the digital era
Authors: Cui Lili
Published: October 2024

Tourism marketing strategy is the top priority for all tourist attractions and tourism-related enterprises, and how innovative tourism marketing strategy in the digital era has become the key to improving the competitiveness of attractions and enterprises. This paper uses data mining technology as a basis to study feasible solutions for innovative tourism marketing strategies for scenic spots and enterprises under data-driven. A formalized label representation is used to construct an extended user portrait conceptual model by clustering the tourists’ contextual information using K-means. Tourism marketing targets users based on similarity calculation results, and association rules are used to mine the alignment association rules between tourists’ contextual features and attractions. Combined with the big data framework system Hadoop technology, we have built a tourism marketing platform that is used to analyze the tourism preferences of different tourists and formulate effective tourism marketing strategies. This paper, based on the data-driven tourism marketing strategy, can significantly improve scenic spot traffic. After marketing the Biluo Tower scenic spot in October, the average value of the traffic is up to 20,384 people, compared with the pre-marketing increase of 56.71%. At the same time, the marketing strategy significantly improves the satisfaction of tourists, and after the implementation of the marketing strategy, the satisfaction of tourists in the scenic area generally improves to more than 0.975.
Research on Dynamic Capture and Pattern Recognition Technology of Pitching Technology in Baseball Sports
Authors: Li Haike
Published: October 2024

This paper proposes a baseball pitching action recognition algorithm based on a spatiotemporal graph convolutional neural network and constructs an error action correction algorithm on this basis. The dynamic skeleton model ST-GCN is used to combine the positional information of human movement with the temporal dynamic information. The action contour sequence is extracted to determine the funding for the erroneous action. Finally, the machine learning method is used to realize the adaptive corrective analysis of the erroneous action. Example analysis shows that the action correction algorithm proposed in this paper improves the recognition accuracy by 20.78%, 16.67%, and 9.11%, 9.73% in the two datasets, and the pitching accuracy of the experimental group is 12.5% higher than that of the control group, and the standardized degree score of the pitching technical action is 1.1 points higher than that of the control group. Therefore, the practical effectiveness of the pitching action identification and correction method in this paper has been effectively verified.
Research on the Integration of Virtual Reality Technology and Teaching Scene Innovation in Civic and Political Education Management in Colleges and Universities
Authors: Wu Xiaobing
Published: October 2024

The generation and development of virtual reality technology provides new and powerful tools for the management of ideological education in colleges and universities. This paper focuses on exploring the utility of using virtual reality technology in college civic education. By selecting and deploying appropriate virtual reality display devices and development environments, we provide sufficient hardware and software support for the application of virtual reality technology to the ideology and politics classroom in colleges and universities. The browser/server 3-tier architecture model is introduced to develop this paper’s interactive teaching system based on virtual reality technology and integrate it with Civics classroom teaching. Students in the Civics classroom of University A are selected as the research subjects, and the eye movement index experiment is designed, which shows that the subjects’ attention time ratio and first-time attention time when using VR panorama learning are significantly improved compared with that of using static picture learning. The Civics classroom can easily accept this paper’s VR interactive teaching system, as demonstrated by the questionnaire results of the experimental group in two courses in teaching practice. At the same time, the mean values of the experimental group’s mind-flow experience and quiz scores using this paper’s system were 19.76% and 16.30% higher than those of the control group, and the degree of learning engagement was improved by as much as 78.556%, which effectively demonstrates the value and role of this paper’s VR interactive teaching system applied in the Civics classroom.
Research on the application of neural networks in macroeconomic forecasting and strategic management decision-making
Authors: Xue Qianqian
Published: October 2024

Traditional macroeconomic forecasting models have some limitations in utilizing large-scale variables, screening appropriate variables, and forecasting accuracy. Based on the theories of economic fluctuation and New Keynes, this paper uses monetary policy, investment behavior, and consumption behavior as predictors of macroeconomic fluctuation. Then, it explores the principles and steps of the BP network applied to forecasting, the design of BP neural network structure, the selection of training algorithm and training parameters, and finally establishes a reasonable BP network structure model. Finally, using the prediction of GDP growth rate as an example, an empirical comparative analysis of model prediction accuracy is carried out. The empirical results of the model in the training set and the test set show that the structure of the BP neural network model is 3-48-1, and the model obtains the optimal learning error (6.207×10−5) at 500 iterations. In the experimental set, the root-mean-square prediction error between the output predicted value and the actual value is less than ±0.2 . The model accurately predicts the GDP growth rate, which can provide a theoretical basis for proposing macroeconomic strategic management decisions.
A Study of Computer-Assisted Communicative Competence Training Methods in Cross-Cultural English Teaching
Authors: Yang Chunli
Published: October 2024

With the advancement of globalization, China is implementing the “Belt and Road Initiative”, a major strategic initiative to open up to the outside world, which means that it needs to cultivate talents with cross-cultural communication skills. In this paper, we design a computer-assisted model for cross-cultural English teaching implementation that is based on the objectives of cross-cultural teaching. A questionnaire was designed to collect data on the effect of students’ communicative competence training in cross-cultural English teaching, and t-tests and correlation tests were used to analyze the impact of the computer-assisted English teaching mode on students’ communicative competence training. The results of the study show that there is a significant difference between the dimensions of intercultural communicative competence of the experimental group of students applying the computer-assisted teaching mode and the control group under traditional teaching at the end of the teaching experiment (P<0.05). At the same time, it was found that there was a positive correlation between the effect of communicative competence training and the factors in the teaching mode (r>0), indicating that computer-assisted English language teaching can improve students’ intercultural communicative competence. This paper puts forward the optimization suggestions of communicative competence training from the aspects of teaching object and teaching design in order to improve teachers’ professional teaching ability and students’ intercultural communicative competence.
An Empirical Study of the BOPPPS Pedagogy in a Computer Networks Course and Strategies for Curriculum Reform
Authors: Yuan Lihui , Kong Ling , Liu Fenghua
Published: October 2024

In the context of modern education, it is essential for the sustainable development of the computer discipline to continuously explore the general process of course teaching and the strategy of class reform through the practice of new teaching methods. This paper discusses the practical application of the BOPPPS model teaching method in computer network courses and the strategy for class reform. The BOPPPS teaching model creates six teaching sessions in the Computer Networks course, which include an introduction, learning objectives, pre-test, participatory learning, post-test, and summary. Finally, we used student performance analysis and student questionnaires to understand the teaching effect of this teaching model. The study’s findings revealed that the average score of the case study questions in the experimental class was 3.32 points higher than that of the control class after adopting the BOPPPS teaching mode. During the learning process, both 33.5% and 39.5% of students expressed their ability to clarify and recognize learning objectives and think independently.
Cost-Benefit Modeling of Smart Contracts Applied to the Accounting and Auditing Field
Authors: Zheng Wei
Published: October 2024

Blockchain technology is increasingly pervasive in social production and life, and its influence on the accounting and auditing industry is undeniable. The article extensively researches blockchain technology and smart contracts, and it constructs a blockchain-based cloud data auditing model. Combining it with the evolutionary game model completes the construction of the blockchain-based cloud data auditing system. The running cost of the auditing model is analyzed in terms of communication and computation overhead, smart contract cost, time cost, etc., and how it affects the strategies of auditing clients and auditors is studied from the aspects of cost and benefit, respectively. In this paper, the audit model’s average communication overhead and computation overhead are 9.86 KB and 0.82 seconds, respectively. The cost of the smart contract model is relatively low and shows a steady trend. The average query time of this paper’s auditing model is 0.78ms, and none of the validation times on the validator exceeds 5ms, while the average validation times on the blockchain and cloud servers are 11.01ms and 534.35ms, respectively. The auditing client and the auditor tend to adopt the blockchain technology strategy when the cost reduces, or the benefit increases, with a probability of adoption approaching 1 after numerous games.
Stylistic Analysis of Chinese Language Literature Based on Text Mining Techniques
Authors: Shuai Xiaomin
Published: October 2024

Chinese literary style highlights the distinctive features of different Chinese language literary works, which is of enormous significance to the research in the field of Chinese language literature. In this paper, we use web crawler technology to construct a dataset of 183 Chinese-language literary works obtained from online reading websites, and we use statistical-based segmentation methods, de-duplication, and other methods to preprocess the text data. The conditional cooccurrence matrix represents the acquired texts, and the BRET-AE model extracts text features. Appropriate classifiers are selected for different literary style analysis tasks. This paper selects seven literary works by Mo Yan and Jia Pingwa for empirical analysis of the Chinese language literary style. While Jia Pingwa’s word formation rate is higher than that of Mo Yan’s. Are selected for empirical analysis of Chinese language literary style. The average word length of all of Mo Yan’s works is 1.5115, and the average word length of Jia Pingwa’s 7 works is 1.3995. In addition, the average sentence length of Mo Yan’s works exceeds that of Jia Pingwa’s works, while the word formation rate of Jia Pingwa’s works is higher than that of Mo Yan’s works. Eventually, the clustering degree analysis reveals that Mo Yan’s Red Red Sorghum Family has the lowest clustering degree, while Wine Country has the highest clustering degree, highlighting the literary style transformation of Mo Yan’s works.
Computer simulation and optimization of building models for photovoltaicphotothermal integration
Authors: Wang Yike , Hao Zhanguo
Published: October 2024

Photovoltaic solar thermal integration is a new idea for buildings to fully utilize clean energy for energy saving and emission reduction. The digital modeling of photovoltaic solar thermal integration in buildings is finished by creating the energy balance equation of the energy supply system and the physical model of the main equipment. The objective function is established and the constraints are set to achieve optimization of the operation model through planning and solving problems. The TRNSYS simulation platform carries the integrated operation model and optimization scheme, and the optimization effect is simulated and validated. The results of computer simulation effect analysis show that the RMS of the parameters is 2.74%, 11.71%, 8.55%, and 2.47%, respectively, and the simulated and experimental values are consistent. The average system thermal efficiency and average water tank thermal efficiency of the optimized scheme are better than those of the PV/T-FPC system, and the cumulative cost savings in the whole life cycle after replacing the proposed scheme in Beijing and other five cities are 8432 yuan, 5937 yuan, 3513 yuan, 31744 yuan, 34893 yuan, and 31877 yuan, respectively, and the optimization effect is significant.
Research on the Strategy of Educational Management and Resource Optimization Based on Big Data Technology in the Mode of Industry-Education Integration
Authors: Xie Ligao
Published: October 2024

In order to build an education information platform to support “industry-education dialogue” and at the same time serve the teaching and research of industry-education integration. In this paper, we use big data technology to construct a system of education management and resource optimization, supporting education construction in the context of industrial transformation and upgrading. For larger-scale WSNs, an energy-efficient data collection algorithm based on non-uniform clustering is proposed. To deal with large-scale optimization problems, a hybrid algorithm of genetic algorithms and particle optimization hierarchical collaboration is introduced. Then, the algorithm is applied to cluster WSNs, an adaptation function is constructed with the goal of equalizing energy consumption, and a data collection algorithm based on non-uniform clustering is proposed. The Apriori algorithm, which is based on the interest degree model, is used to mine the course evaluation data for the system design in the university industry-teaching fusion model. This system design does both course evaluation and resource optimization. The system’s total evaluation score is high, at 90.84 points. It also improves the efficiency of cooperation between the education industry and schools. It proves that the system’s design is effective and high-level and has a positive effect on teaching management and resource optimization in education.
Research on transparent management of economic transactions using blockchain technology
Authors: Xue Qianqian
Published: October 2024

The data asset trading market is gradually emerging with the development of the digital economy, making the development of a safe and effective data asset trading management system an important research direction. This paper uses blockchain technology to create a transparent management system for economic transactions. A PHRP algorithm is proposed to guarantee the security of the transaction, addressing the privacy protection issue involved in the transaction process. The PHRP algorithm calculates the actual transaction amount by encrypting both the input and output amounts, utilizing the additive homomorphic property. It also ensures the undeniability and integrity of the transaction by encrypting and committing random numbers. The relevant test results show that the transaction privacy protection scheme based on the PHRP algorithm can better meet the requirements of the economic transaction management system. Users’ satisfaction with the system constructed in this paper in terms of perceived usefulness and perceived ease of use scored high on average, 4.23 and 4.17, respectively, and expressed average for security, for which this paper proposes relevant improvement strategies.
Prediction of job-seeking intention of college students based on group intelligence algorithm and its guidance for career planning
Authors: Yu Guoshi , Lin Lin
Published: October 2024

The increasingly large employment group has brought great employment pressure to society. Therefore, predicting the job-seeking intentions of college graduates and providing personalized career planning has become feasible methods to solve the structural contradiction of college employment. This paper proposes a better support vector machine model that utilizes the gray wolf optimization algorithm in the group intelligence algorithm, with the aim of establishing a prediction scheme for the job-seeking intentions of college graduates using this model. The collected data are pre-processed by cleaning, integrating, converting, and other pre-processing work to form a standardized dataset to prepare for the subsequent experiments. Finally, the prediction scheme of the job-seeking intention of college graduates is designed and developed based on the GWO-SVM optimization model, and the actual application of the prediction model is analyzed as a case study based on the real data of graduates from a college. The study shows that when the number of input features is 9, the average value of the comprehensive score of this prediction model is 0.5703, the standard deviation is 0.0278, the optimal learning rate of the model is 0.165, the F1 value is stable above 0.6, and the optimal F1 value is 0.856, which proves that this prediction model has a good prediction effect. This study has certain guiding significance in helping college students establish reasonable job-hunting intentions, proposing personalized career planning for students, and promoting high employability.
The Integration Mechanism of Optimization Model Design of Scholarship System and Civic and Political Education under the Strategy of Financial Aid and Parenting in Colleges and Universities
Authors: Li Xinlei , Zhang Xue
Published: October 2024

The selection of college grants is affected by many factors, but some of the influencing factors cannot be quantitatively judged at present. In order to be more fair and reasonable to the students in need of financial assistance for the review and evaluation, this paper introduces the fuzzy comprehensive evaluation method into the process to establish a fuzzy hierarchical analysis based on the college national scholarship evaluation model, the article finally through a specific example of the application of this paper based on the fuzzy comprehensive evaluation of the optimization model of the bursary system. The affiliation degree of the fuzzy comprehensive evaluation-based scholarship system constructed in this paper is (0.536,0.323,0.130,0.014), and the article concludes that Zhang’s moral education status is very good, and he is qualified to receive the scholarship.
Study on the effect of biomass charcoal-biogas application technology on soil carbon and nitrogen fractions and soil microbiological properties based on biomass charcoal-biogas application technology
Authors: Zhang Shuchang , Zhang Yuanxin , Zhai Yong , Liu Zhongqiao , Zhang Xiaotian
Published: October 2024

The application of biogas and biomass charcoal to terrestrial crops and vegetables can promote their growth. The effects of the combined application of the two on soil carbon and nitrogen fractions and soil microbiological properties are not well-studied. Therefore, in this experiment, the red and yellow soil of Hangzhou City, Zhejiang Province, was used as the research object, and two factors, biomass charcoal and biogas, were set up to investigate the soil changes under the conditions of biomass charcoal-biogas application. One-way ANOVA and correlation analysis examined the differences in soil and crop radish under biomass charcoal-biogas application technology. The experimental results showed that the 2% application of hog manure charcoal at 350°C and 100% N amount of replacement of biosolids dosing treatments were the most effective, which could increase the content of organic matter, soluble organic carbon, etc., as well as the content of nitrogen in the soil, and improve the activity of soil enzymes. The enhancement of radish yield was greater with the application of swine manure charcoal with biogas than with the single application of both, and the maximum radish yield was achieved with the 100% N amount substitution of biogas with the application of swine manure charcoal at 2%-350°C treatment. The heavy metal contents in radish were below the limit values after 9 months of application of both biogas and biomass charcoal, which did not affect the edible safety of radish.
Research on the Path of Teaching Reform of Chemistry Major in Agricultural and Forestry Colleges and Universities by Integrating Curriculum Civics in the Network Information Age
Authors: Chu Mingjie
Published: October 2024

In the information age, the ideological and political education of college students has become an important task of higher education. Based on the Word2vec model and the improved TF-IDF algorithm, this paper constructs a text analysis method to analyze the distribution of ideological and political elements in chemistry textbooks taught in colleges and universities. Taking the text of chemistry teaching materials of an agricultural and forestry university as an example, the constructed model is used to mine the distribution of the ideological and political elements and the integration of the ideological and political elements in the chemistry teaching materials of colleges and universities is counted. On this basis, a teaching reform path for integrating Civics and Politics in chemistry courses is proposed, and it is being applied to the freshman class of chemistry majors at an agricultural and forestry university. The effectiveness of integrating Civics into the chemistry program was assessed by comparing the chemistry scores and Civics literacy levels of sample students before and after the teaching practice. 74.3% of the students had a high degree of acceptance of the integration of civics into the chemistry curriculum. The chemistry grades and the level of Civic and Political Literacy of the students in the classes with teaching reform were significantly improved, and the overall scores were 4.26 points and 5.7% higher than those of the control classes respectively. The pedagogical reform path of the curriculum Civics integrated into Chemistry has a significant effect on students’ civics literacy level.
Research on Intelligent Strategies and Challenges of Intangible Cultural Heritage Inheritance in the Age of Digital Economy
Authors: Wu Jiaming , Xu Yuhui , naranbilik
Published: October 2024

The intelligent construction and protection of intangible cultural heritage resources is an innovative approach to inheritance and development that fosters the survival of these resources, as well as an effective arrangement for the joint development of high-quality cultural and intangible cultural heritage resources. In this paper, we design a resource library based on 3D reconstruction, which we then implement online to create an intangible cultural heritage landscape. In addition, based on the characteristics of volume video technology, the innovative experience of building intangible cultural heritage is applied. Through an in-depth inquiry, this paper presents strategies for promoting body diversity, creating engaging communication content, disseminating the technology in detail, and developing a communication strategy for the intangible cultural heritage concept.
Research on Management Innovation in Colleges and Universities Based on the Concept of Knowledge Management
Authors: Zhang Ye
Published: October 2024

In the era of the knowledge economy, colleges and universities, as knowledge-intensive units, urgently need to seek a new management model that meets the requirements of the times, supports the high quality of teaching, and helps colleges and universities to realize sustainable development. Based on this demand, this paper focuses on the concept of knowledge management to innovate the existing management mode and takes the construction of a knowledge-sharing system, the establishment of a knowledge innovation incentive mechanism, the development of organizational learning, and the creation of knowledge alliance as the specific implementation strategies. Using the multi-level gray correlation evaluation method and fuzzy comprehensive evaluation method, we evaluate the actual effects of the knowledge management strategy of colleges and universities in this paper. The multi-level gray correlation evaluation method is used to assess the knowledge management level of 60 colleges and universities, and the results of their scoring order are compared with the reference order. The order-preserving test parameter δ=0.0446<0.1 indicates that the basic trend of this paper’s sorting is consistent with the reference sorting, which verifies the practicality of the knowledge management evaluation system for colleges and universities constructed in this paper. Taking the university H, which implements the knowledge management strategy of this paper as an example, the five levels of the evaluation set V={excellent, good, medium, poor, very poor} are assigned a value of 5~1 respectively, and the final evaluation score of university H is 3.9394, and its knowledge management level tends to be excellent. This paper’s knowledge management strategy has a positive implementation effect and can be a valuable reference for knowledge management innovation in colleges and universities.
Exploring the Communication Path of Civic Education in Cyberspace Using Data Mining Technology
Authors: Li Sha
Published: October 2024

A recommendation algorithm is a specific application of data mining technology, which is an important means to expand the dissemination of Civics education in cyberspace. The elbow method is employed in this paper to determine the best number of clusters to cluster the Civics course evaluation dataset and finish preprocessing large-scale data. Aiming at the problem of different importance of rating bias between items, the traditional Slope One algorithm is optimized by comprehensively considering the relationship between the number of common ratings and the similarity between items and the prediction results. The optimized Slope One algorithm is used to perform one round of prediction and fill the scoring matrix to solve the data sparsity problem and improve prediction accuracy and stability. The optimized algorithm reduces by 8.56% compared to the user-based collaborative filtering algorithm, 5.83% compared to the item-based collaborative filtering algorithm, and 5.25% compared to the content-based recommendation algorithm, with a significant improvement in accuracy, recall, and F1 value. The four hypothesis validations indicate that the diversity, personalization, and accuracy of resource recommendations all have positive effects on the dissemination effect of civic education. The recommendation algorithm’s dissemination effect score in this paper is 3.781, which is significantly superior to the dissemination effect of Civic Education.
Artificial Intelligence Application and Environmental Protection Strategies in Rural Ecotourism Resource Development
Authors: Sang Qingqing , Hu Yu
Published: October 2024

This paper constructs a GIS database from the aspects of data input, storage and processing. Then, it applies a BP neural network learning algorithm to categorize rural ecotourism resources and evaluate their development potential. Finally, it presents four aspects of the challenges of AI technology in rural ecotourism resource development. The rate of discrimination when rural types are divided into two types is overall higher than that when they are divided into three types, and their correct rates are all more than 86%. The best-developed villages among the rural ecotourism resources in %%A are villages J, C, and E, with total development values of 6.5647, 6.5225, and 6.4919, respectively. Villages A (5.5384), G (5.3031), and I (5.5586) are the next best-developed areas, with total development potentials ranging between 5 and 6. The rest of the 4 villages with total development value <5 are under-optimal development villages. Scientific tourism development and planning are essential for the development of rural tourism resources and environmental protection.
Construction and Evaluation of a Machine Learning-Based Conversation Model for English Spoken Tourism Conversation
Authors: Wei Tao
Published: October 2024

The development of language macromodeling has led to the widespread adoption of spoken English conversation systems in various industries. Similarly, it has had an impact on the tourism industry, where the involvement of machine learning has taken a big step forward. The purpose of this paper is to explore the use of machine learning methods in spoken dialog systems to construct a dialog model that is suitable for the tourism industry. Speech, map image, and tourism information text data are collected first, which form the database of the dialog model through processing, storage, and application. A bag-of-words model and word vectors represent the text, while speech activity and an English conversation system construct the speech and intention recognition model. On the test set, the best speech recognition rate using double-threshold endpoint detection is up to 98.73%, and the corresponding sentence recognition rate is also up to 93.67%. This paper’s model achieves the highest intention recognition accuracy, scoring 0.943 and 0.955 on the CCKS2018 and SMP2018 datasets, respectively. This paper proposes a machine-learning conversation model that provides technical support for conversational AI development in the tourism industry.
A Study on the Methods of Improving Writing Skills by Bayesian Classifier in English Teaching and Learning
Authors: Zhang Suqin
Published: October 2024

Teachers have been researching how to effectively improve the English writing ability of contemporary college students. The article utilizes web crawler technology to establish an English writing knowledge database and preprocesses the data through a word division algorithm, lexical annotation, and word form reduction. The article employs Bayesian classification algorithms to model the English writing style of students. The English writing grammar error correction model was constructed based on the BiGRU model, combined with the BERT pre-training task, fused with the attention mechanism. The English writing knowledge database was used to analyze the data for the model mentioned above. The sentence length of English written text fluctuates between -0.095 and 0.436, and the Bayesian classification model’s AUC value is 0.814. The grammar error correction model for English writing text has a GLEU value of 63.24, with an automatic scoring mean of 26.69, which is only 0.35 higher than manual scoring and a scoring error of only 1.29%. Through the English writing text style and grammar error correction model, teachers can optimize the English writing teaching mode and help students improve their English writing abilities.
A Study of Computer-Assisted Automatic Translation Techniques and Practices for English Vocational Terminology
Authors: Zeng Yanming
Published: October 2024

This paper mainly carries out a more in-depth study on the design and planning of computer-assisted translation models based on translation memory and demonstrates the new computer-assisted translation model formed in this way. The TMX specification model, combined with the actual needs, summarizes the corresponding terminology data model, introduces and summarizes the word splitting, similarity, and alignment techniques of the computer-assisted translation model, and verifies the effectiveness of the model through practical application. The study shows that the average code length of computer-aided translation is about 0.1~0.3 lower than that of human translation in specialized fields, and its performance and efficiency are better than that of human translation. The efficiency of computer-aided translation software in extracting terminology positively correlates with an increase in frequency. Computer-assisted translation plays a significant role in the professional field and provides empirical support for subsequent related research.
Research on Digital Teaching Resources Development and Personalized Teaching in Sensor Courses
Authors: Hou Yan , Li Zongrui , Wei Jianghua
Published: October 2024

In the era of rapid development of computer technology and education technology, personalized teaching can provide learners with learning content that meets their needs and achieves the teaching purpose of “tailor-made teaching”. In this paper, the MOB method is used to reorganize and describe digital teaching resources after the coding process so as to achieve the development and management of digital teaching resources in sensor courses. Then, the hybrid differential evolution algorithm is used to cluster similar learning resources and learners in the learning process, and the recommendation of personalized digital teaching resources in sensor courses for students is realized through the operations of mutation and selection. Based on this, a personalized teaching model is constructed for teaching sensor courses. After testing, the personalized teaching model was found to be able to accurately analyze the learners’ knowledge of each knowledge point, and its accuracy is much better than the benchmark model. The empirical analysis shows that after applying the personalized teaching model to assist teaching, the average score of students’ sensor course test scores increased from 65.26 to 90.22 (P<0.01), and their learning attitudes were also significantly improved. This paper can provide teachers and administrators with some new ideas about optimizing classroom teaching practices and provide references for implementing and promoting classroom teaching reform in schools.
Prediction and optimization of individual skill development patterns in physical education based on big data analysis
Authors: Chai Meng , Ye Mingliang
Published: October 2024

This paper proposes a data-based gray preprocessing neural network optimization model based on the principle of the BP neural network model and its optimization method. SPSS statistical software was used for statistical analysis to compare the student physical education test data of S college students from 2019 to 2023. The GA-BP optimization prediction model is applied to generate and process the raw data of 5-year sports tests to find the law of systematic changes and generate the data sequence with strong regularity so as to predict the condition of the future development trend of things. The results show that the measured and actual numbers have a high rate of conformity, and the maximum error is 0.67%, which is high accuracy. The overall speed and strength of boys and girls in sports is on the rise. The overall endurance level of boys is increasing while the overall endurance level of girls is decreasing. In the future, endurance training should be strengthened as a way to improve the continuing trend of low endurance quality among students.
Research on machine learning based processing strategies for large-scale datasets
Authors: Yang Longfei , Zheng Kai , Xiao Hui , Yang Zhiqiang , Li Shufang , Fan Lei
Published: October 2024

In this paper, we first mine the interconnections between data in large-scale datasets through association rule models in machine learning and then perform T -time K-Means clustering on the mined datasets to realize large-scale data integration. On this basis, a classification prediction model based on an enhanced ChebNet model is proposed, which combines the efficient feature extraction capability of graph convolutional neural network and the accurate prediction advantage of big data analysis to effectively realize the processing of large-scale data sets. Taking the tobacco production monitoring data as an example, the model performs well in predicting the correlation of cigarette sensory indexes, especially when the sliding window size is 30 and the prediction jump step is 1. The model performance reaches the optimal, which provides strong support for the quality control of cigarette production, and is capable of processing large-scale datasets of tobacco production.
Real-time processing and optimization strategies for IoT data streams
Authors: Yang Longfei , Wang Xiaoming , Liu Zhuwen , Liu Yang , Fan Lei
Published: October 2024

With the development of industrial IoT and the arrival of smart manufacturing, the field of edge computing has gained more and more attention. However, traditional industrial computing scenarios relying on industrial clouds make data latency a greater challenge. In this paper, for the contradiction between edge devices and task resource allocation encountered in edge computing scenarios in smart manufacturing, we propose an industrial internet task scheduling model for smart manufacturing and introduce a scheduling node state matrix to realize the state management of each scheduling subtask. Aiming at the problem of multiple tasks seizing resources in a complex, intelligent manufacturing environment, the study combines the caching mechanism to realize the task offloading computational processing of order scheduling, in which the caching mechanism is used to solve the problem of computational resource limitations at the edge. It is found through simulation that when the computational task factor ξk
=2 is larger, more offloading power is allowed to be transmitted to the edge ser ver for computation. For computational tasks with smaller task factor ξk
, the device tends to allocate more computational rate to that computational task. Eventually the data queue length will be continuously reduced and the data queue is concentrated in the interval of very small values, this result verifies that the task scheduling algorithm is able to perform task scheduling efficiently and reduce the latency.
Muzyka metalowa w żywiole akademii. Wokół pracy "Żywioły i ideologie w narracjach muzyki metalowej" (red. Jakub Kosek, Wydawnictwo Naukowe UP, Kraków 2022, ss. 259)
Authors: Kominek Patryk
Published: October 2024

Recenzja monografii "Żywioły i ideologie w narracjach muzyki metalowej" (red. Jakub Kosek, Wydawnictwo Naukowe UP, Kraków 2022, ss. 259).
Neuromarketingowy wgląd w kompetencje cyfrowe: refleksja teoretyczna na temat wykorzystania neuromarketingu do targetowania treści i kampanii przeznaczonych dla różnych grup demograficznych
Authors: Darázs Tamás
Published: October 2024

Niniejszy artykuł przedstawia wpływ neuromarketingu na analizę zachowań konsumenckich i na reklamę. Dzięki integracji neuronauki z badaniami konsumenckimi otwierają się nowe możliwości badania wewnętrznych procesów umysłowych, które wpływają na decyzje konsumentów. Neuromarketing to dziedzina komercyjnej komunikacji marketingowej, która stosuje neuropsychologię do badań rynkowych, badając sensoryczno-motoryczne, poznawcze i afektywne reakcje konsumentów na bodźce marketingowe. Autor koncentruje się na ważnych aspektach neuromarketingu, w tym na potencjalnych korzyściach dla marketerów i na narzędziach neuronauki konsumenckiej. Omawia też znaczenie reklamy i emocjonalne reakcje konsumentów na nią. Badania pokazują, że reklamy wywołujące pozytywne emocje mają większy wpływ na zapamiętywanie i pozytywne postrzeganie marki. Inne badania koncentrują się na związku między lojalnością wobec marki a aktywnością mózgu – pokazano, że lojalni klienci wykazują większą aktywność w obszarach mózgu związanych z emocjami i pamięcią. Artykuł kończy się omówieniem konkretnych zastosowań neuromarketingu na Wydziale Komunikacji w Mediach Masowych Uniwersytetu Świętych Cyryla i Metodego w Trnawie. Działający na wydziale Neurolab pozwala mierzyć reakcje na różne treści oraz identyfikować skuteczne i nieskuteczne elementy reklam. Ponadto w artykule przedstawiono przykłady badań nad zastosowaniami neuromarketingu, w tym analizę postów na Facebooku Policji Republiki Słowackiej oraz postrzeganie reklamy telewizyjnej przez markę COOP Jednota Slovakia.
Sprawozdanie z ogólnopolskiej konferencji naukowej pt. „Kompetencje cyfrowe w edukacji 4.0 wobec wyzwań cyfrowego społeczeństwa wiedzy oraz sztucznej inteligencji. Praktyki edukacyjne, metody badania i pomiaru, narzędzia i instytucje”, 21–22 marca 2024, tryb zdalny, Uniwersytet Komisji Edukacji Narodowej w Krakowie
Authors: Ryrych Tomasz
Published: October 2024

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Sprawozdanie z VII edycji ogólnopolskiej konferencji naukowej z krajowego cyklu Metal Music Studies pt. „Praktyki i (re)prezentacje w kulturze muzyki metalowej”, 12 kwietnia 2024 r., Uniwersytet Komisji Edukacji Narodowej w Krakowie
Authors: Karbownik Karolina
Published: October 2024

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Lata 60.: audiosfera bigbitu
Authors: Pęczak Mirosław
Published: October 2024

Na początku lat 60. z powodów politycznych nazwa „big beat” („bigbit”) zastąpiła termin „rock’n’roll” jako określenie polskiej muzyki młodzieżowej. Chodziło o to, by złagodzić niechęć partyjnych decydentów do twórczości inspirowanej anglosaską kulturą popularną. Polska wersja rock’n’rolla rozwijała się zatem pod presją ideologiczną, ale także w kontekście przemian technologicznych istotnych dla specyfiki muzycznej audiosfery (pejzażu dźwiękowego). Duże znaczenie miał tu rozwój fonografii i (politycznie limitowana) obecność muzyki rockowej w mediach. Jej atrakcyjność warunkowana była także modą i zapleczem subkulturowym.
Sytuacja zdrowotna seniorów krajów bałtyckich na tle Europy
Authors: Brambert Patryk , Kiniorska Iwona
Published: October 2024

Celem opracowania była ocena sytuacji zdrowotnej populacji seniorów Litwy, Łotwy i Estonii na tle Europy. W analizie wykorzystano dane ilościowe pochodzące z Eurostatu. Przyjęto obiektywny podział Europy wynikający z geograficznego położenia państw, w którym badane kraje należą do Europy Północnej. Charakterystyka rozpatrywanego zjawiska została przeprowadzona w oparciu o podstawowe miary demograficzne i starzenia się ludności, a zwłaszcza wybrane wskaźniki opisujące uwarunkowania zdrowotne seniorów. W pracy wykorzystano nieczęsto stosowaną w badaniach demograficznych, zaawansowaną statystycznie metodę samoorganizujących się sieci neuronowych Kohonena. Wyznaczono dzięki niej cztery typy uwarunkowań zdrowotnych ludności senioralnej państw europejskich i określono położenie krajów bałtyckich w tych zbiorach, odpowiednio dla stanu z lat 2008 i 2021. Wskazanie poszczególnych skupień pozwoliło m.in. stwierdzić, że kraje bałtyckie miały najbardziej zbliżoną ocenianą sytuację zdrowotną osób starszych do krajów Europy Wschodniej. W obu porównywanych latach ich sytuację określono jako złą, najgorszą względem pozostałych skupień państw Europy. Zrealizowane badania mogą stanowić modelowe podejście przy określaniu kształtowania się uwarunkowań zdrowotnych i ich wzajemnych relacji, które dotyczą seniorów oraz innych grup wiekowych ludności.