Industry-education integration education is increasingly important in promoting regional economic growth. Taking the private economic development of Wenzhou City as the background, this paper analyzes the development level of industry-education integration in Wenzhou City in depth at the geographical level by applying the perspective of industrial association. The study reveals the correlation between the development of the city’s industry-education consortium and the regional private economy industry and its economic effect characteristics. The relationship between the innovative practice of industry-education consortium and the development of private economy was quantitatively measured using the dominant correlation model’s absolute correlation and correlation order methods. The analysis results show that the economic driving effect of the industry-education consortium is characterized by apparent temporal sequence, and verifies its effectiveness in promoting economic output and facilitating industrial upgrading. It is found that the correlation between the municipal industry-education consortium and Wenzhou private economy is generally higher than 0.6, and the value of the correlation coefficient of the driving force is between 0.6 and 0.9, indicating that the innovation of the industry-education consortium has a significant driving effect on the development of Wenzhou private economy. This study provides valuable references and insights for further deepening the development strategy of regional industry-education integration and promoting regional economic development.
{"title":"Research on the Innovation and Practice of Municipal Industry-Education Consortium Based on the Advantageous Correlation Degree Method under the Development of Wenzhou Private Economy","authors":"Mengyi Yi","doi":"10.2478/amns-2024-0388","DOIUrl":"https://doi.org/10.2478/amns-2024-0388","url":null,"abstract":"\u0000 Industry-education integration education is increasingly important in promoting regional economic growth. Taking the private economic development of Wenzhou City as the background, this paper analyzes the development level of industry-education integration in Wenzhou City in depth at the geographical level by applying the perspective of industrial association. The study reveals the correlation between the development of the city’s industry-education consortium and the regional private economy industry and its economic effect characteristics. The relationship between the innovative practice of industry-education consortium and the development of private economy was quantitatively measured using the dominant correlation model’s absolute correlation and correlation order methods. The analysis results show that the economic driving effect of the industry-education consortium is characterized by apparent temporal sequence, and verifies its effectiveness in promoting economic output and facilitating industrial upgrading. It is found that the correlation between the municipal industry-education consortium and Wenzhou private economy is generally higher than 0.6, and the value of the correlation coefficient of the driving force is between 0.6 and 0.9, indicating that the innovation of the industry-education consortium has a significant driving effect on the development of Wenzhou private economy. This study provides valuable references and insights for further deepening the development strategy of regional industry-education integration and promoting regional economic development.","PeriodicalId":52342,"journal":{"name":"Applied Mathematics and Nonlinear Sciences","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140523698","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper discusses the artistic characteristics and innovative applications of ink animation in the era of artificial intelligence, mainly including the preprocessing of ink works, the Extraction of stylistic feature analysis, the internal haloing technique, and the simulation technique of ink painting features. The research methods include image segmentation, object contour and internal separation, and the application of ink stylization techniques. The results show that the improved CIE1976L*a*b* color space transformation and the “kernel-free” region growing method have successfully realized the efficient processing and stylistic feature extraction of ink works. The experiments use the gray scale co-production matrix for texture characterization, and the results show that the extracted stylistic features have a high degree of consistency with the traditional artistic features of ink animation. In addition, the practical expression of terrain ink style is realized by 3D ink rendering technology, which demonstrates the innovative application of ink animation in modern technology.
{"title":"Artistic Characteristics and Innovative Application of Ink Animation in Animation Scenes in the Age of Artificial Intelligence","authors":"Qiaohong Hu","doi":"10.2478/amns-2024-0591","DOIUrl":"https://doi.org/10.2478/amns-2024-0591","url":null,"abstract":"\u0000 This paper discusses the artistic characteristics and innovative applications of ink animation in the era of artificial intelligence, mainly including the preprocessing of ink works, the Extraction of stylistic feature analysis, the internal haloing technique, and the simulation technique of ink painting features. The research methods include image segmentation, object contour and internal separation, and the application of ink stylization techniques. The results show that the improved CIE1976L*a*b* color space transformation and the “kernel-free” region growing method have successfully realized the efficient processing and stylistic feature extraction of ink works. The experiments use the gray scale co-production matrix for texture characterization, and the results show that the extracted stylistic features have a high degree of consistency with the traditional artistic features of ink animation. In addition, the practical expression of terrain ink style is realized by 3D ink rendering technology, which demonstrates the innovative application of ink animation in modern technology.","PeriodicalId":52342,"journal":{"name":"Applied Mathematics and Nonlinear Sciences","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140523548","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The rise of the intelligent teaching model, relying on artificial intelligence and digital information technology, provides students with personalized and autonomous learning pathways. The model encourages students to learn independently and develop personally by integrating online and offline learning resources, enhancing their innovation and practical skills. Educational innovation has focused on exploring how to effectively incorporate competent teaching resources to improve teaching efficiency and students’ physical education skills. This study designed a new smart teaching mode for physical training science using blended learning theory and artificial intelligence technology. The differences in students’ physical education performance, participation, and satisfaction between the traditional and intelligent teaching modes were analyzed by comparison. The students who used innovative teaching methods in the study were better than those who used conventional teaching methods in 100-meter sprint and basketball shooting accuracy, with an average improvement rate of 15%. According to the study, the intelligent teaching mode can effectively enhance students’ physical education learning efficiency and mastery of movement skills, paving the way for a new development direction in college physical education.
{"title":"The Construction of Wisdom Teaching Mode of Physical Education and Training in Colleges and Universities in the Internet Era","authors":"Yahui Qian","doi":"10.2478/amns-2024-0777","DOIUrl":"https://doi.org/10.2478/amns-2024-0777","url":null,"abstract":"\u0000 The rise of the intelligent teaching model, relying on artificial intelligence and digital information technology, provides students with personalized and autonomous learning pathways. The model encourages students to learn independently and develop personally by integrating online and offline learning resources, enhancing their innovation and practical skills. Educational innovation has focused on exploring how to effectively incorporate competent teaching resources to improve teaching efficiency and students’ physical education skills. This study designed a new smart teaching mode for physical training science using blended learning theory and artificial intelligence technology. The differences in students’ physical education performance, participation, and satisfaction between the traditional and intelligent teaching modes were analyzed by comparison. The students who used innovative teaching methods in the study were better than those who used conventional teaching methods in 100-meter sprint and basketball shooting accuracy, with an average improvement rate of 15%. According to the study, the intelligent teaching mode can effectively enhance students’ physical education learning efficiency and mastery of movement skills, paving the way for a new development direction in college physical education.","PeriodicalId":52342,"journal":{"name":"Applied Mathematics and Nonlinear Sciences","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140523564","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Piano talent cultivation mostly focuses on repetitive training only, and lacks a clear cultivation program for theoretical knowledge and skill points. In this paper, we adopt the curriculum knowledge graph to extract the knowledge point subgraph of piano learning and provide an initialized knowledge graph structure for the learning path under the cultivation scheme. A multi-objective optimization model of the path containing constraints such as the difficulty and mastery of knowledge points is set, and the relevant parameters of the model are defined and calculated to establish a multi-optimization objective function. A solution method that uses constant differential error approximation is proposed as a means of approaching the Pareto optimal solution. To develop the LSPIA algorithm with reciprocal weights, the adjustment vectors are modified using a least squares asymptotic iterative approximation with minimum squares values. Following the discovery of the most suitable route, a teaching experiment was carried out. The results show that the posttest P-value of the total creative thinking score of the experimental and control classes is 0.022 less than 0.05, which indicates that there is a significant difference between the creative thinking of the students in the two classes in terms of affective characteristics. The experimental group achieved a mean score of 122.69 on the post-test, which was a significant improvement from the mean score on the pre-test. An innovative approach to cultivating piano playing talents involves optimizing learning paths.
钢琴人才培养大多只注重重复性训练，缺乏明确的理论知识和技能点的培养方案。本文采用课程知识图谱提取钢琴学习的知识点子图谱，为培养方案下的学习路径提供初始化的知识图谱结构。设定包含知识点难度和掌握程度等约束条件的路径多目标优化模型，定义并计算模型的相关参数，建立多优化目标函数。提出了一种利用常微分误差逼近的求解方法，作为接近帕累托最优解的一种手段。为了开发具有互惠权重的 LSPIA 算法，使用最小二乘法渐进迭代近似最小二乘法值来修改调整向量。在找到最合适的路径后，进行了教学实验。结果显示，实验班与对照班创造性思维总分的后测 P 值小于 0.05，均为 0.022，说明两班学生的创造性思维在情感特征方面存在显著差异。实验组在后测的平均分达到了 122.69 分，比前测的平均分有了明显的提高。培养钢琴演奏人才的创新方法包括优化学习路径。
{"title":"Construction of Piano Performing Arts Talent Cultivation and Creative Thinking Based on the Constant Differential Error Approximation Method","authors":"Xiao Yang, Yanyan Lu","doi":"10.2478/amns-2024-0252","DOIUrl":"https://doi.org/10.2478/amns-2024-0252","url":null,"abstract":"\u0000 Piano talent cultivation mostly focuses on repetitive training only, and lacks a clear cultivation program for theoretical knowledge and skill points. In this paper, we adopt the curriculum knowledge graph to extract the knowledge point subgraph of piano learning and provide an initialized knowledge graph structure for the learning path under the cultivation scheme. A multi-objective optimization model of the path containing constraints such as the difficulty and mastery of knowledge points is set, and the relevant parameters of the model are defined and calculated to establish a multi-optimization objective function. A solution method that uses constant differential error approximation is proposed as a means of approaching the Pareto optimal solution. To develop the LSPIA algorithm with reciprocal weights, the adjustment vectors are modified using a least squares asymptotic iterative approximation with minimum squares values. Following the discovery of the most suitable route, a teaching experiment was carried out. The results show that the posttest P-value of the total creative thinking score of the experimental and control classes is 0.022 less than 0.05, which indicates that there is a significant difference between the creative thinking of the students in the two classes in terms of affective characteristics. The experimental group achieved a mean score of 122.69 on the post-test, which was a significant improvement from the mean score on the pre-test. An innovative approach to cultivating piano playing talents involves optimizing learning paths.","PeriodicalId":52342,"journal":{"name":"Applied Mathematics and Nonlinear Sciences","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140518385","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this paper, in the process of digitization of stylistic features in English translation teaching, the simulated stylistic features in English translation teaching activities are quantified and pre-emphasized to obtain the decoder of stylistic features of English translation with higher precision, and the stylistic features recognition algorithm in English translation teaching is designed, and the results of the stylistic features recognition in English translation teaching can be obtained by substituting the initial data into the recognition algorithm. Based on stylistic feature recognition, combined with the post-particle swarm optimization algorithm and artificial neural network to construct the stylistic feature analysis model in English translation teaching, and use the method of statistical analysis to analyze the differences of stylistic features in English translation teaching. The results show that the rank means value of auxiliary is the highest, reaching 209.81, the lowest is a preposition (145.17), and the conjunction and adverb are 154.17 and 157.45 respectively, which indicates that auxiliary has the strongest variability of features in the translation of English novels, and this study enables students to have a comprehensive and in-depth understanding of the text, to grasp the stylistic features of the text, and to improve the students’ comprehensive English language ability and translation level.
{"title":"Differential Analysis of Stylistic Features in English Translation Teaching Based on Semantic Contrastive Analysis","authors":"Rong Yan","doi":"10.2478/amns-2024-0085","DOIUrl":"https://doi.org/10.2478/amns-2024-0085","url":null,"abstract":"\u0000 In this paper, in the process of digitization of stylistic features in English translation teaching, the simulated stylistic features in English translation teaching activities are quantified and pre-emphasized to obtain the decoder of stylistic features of English translation with higher precision, and the stylistic features recognition algorithm in English translation teaching is designed, and the results of the stylistic features recognition in English translation teaching can be obtained by substituting the initial data into the recognition algorithm. Based on stylistic feature recognition, combined with the post-particle swarm optimization algorithm and artificial neural network to construct the stylistic feature analysis model in English translation teaching, and use the method of statistical analysis to analyze the differences of stylistic features in English translation teaching. The results show that the rank means value of auxiliary is the highest, reaching 209.81, the lowest is a preposition (145.17), and the conjunction and adverb are 154.17 and 157.45 respectively, which indicates that auxiliary has the strongest variability of features in the translation of English novels, and this study enables students to have a comprehensive and in-depth understanding of the text, to grasp the stylistic features of the text, and to improve the students’ comprehensive English language ability and translation level.","PeriodicalId":52342,"journal":{"name":"Applied Mathematics and Nonlinear Sciences","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140515674","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
With the deepening of economic globalization, interregional connectivity is increasing, making regional economic linkages a hot topic in economics. This study draws on the principles of operations research to classify the urban spatial financial interaction structure into four primary forms: isolated scatter, line, circle, column and network. Through the social network analysis method, the economic structure of urban space is analyzed from the three dimensions of network density, network centrality and cohesive subgroups. At the same time, the distribution of the potential hierarchy of intercity economic links is explored in detail using the gravity model. The empirical Analysis of the 26 city clusters in the Yangtze River Delta reveals that the spatial correlation of the industrial circulation level among these cities is 0.331, and the mean value of the empirical distribution reaches 0.4338, which significantly indicates that the industrial circulation level is positively correlated with the regional economic development. This study provides a valuable reference for the formulation of regional development strategies and shows a unique innovation in enriching the content of economic linkage theory.
{"title":"Efficiency Improvement of Urban Spatial Economic Interaction and Regional Economic Development in the Context of Industrial Circulation","authors":"Huanxia Hao, Ziyi Jiang, Chengbing He","doi":"10.2478/amns-2024-0428","DOIUrl":"https://doi.org/10.2478/amns-2024-0428","url":null,"abstract":"\u0000 With the deepening of economic globalization, interregional connectivity is increasing, making regional economic linkages a hot topic in economics. This study draws on the principles of operations research to classify the urban spatial financial interaction structure into four primary forms: isolated scatter, line, circle, column and network. Through the social network analysis method, the economic structure of urban space is analyzed from the three dimensions of network density, network centrality and cohesive subgroups. At the same time, the distribution of the potential hierarchy of intercity economic links is explored in detail using the gravity model. The empirical Analysis of the 26 city clusters in the Yangtze River Delta reveals that the spatial correlation of the industrial circulation level among these cities is 0.331, and the mean value of the empirical distribution reaches 0.4338, which significantly indicates that the industrial circulation level is positively correlated with the regional economic development. This study provides a valuable reference for the formulation of regional development strategies and shows a unique innovation in enriching the content of economic linkage theory.","PeriodicalId":52342,"journal":{"name":"Applied Mathematics and Nonlinear Sciences","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140518156","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This study explores the mining and application of digital health elements in higher education student management and education, refining student user profiles through data mining techniques and applying them to student management and education to improve the accuracy and effectiveness of education management. The basic process of data mining, including data cleaning, integration, selection, transformation, mining, pattern evaluation and knowledge representation, was first carried out in the study. Then, a clustering recommendation algorithm based on user characteristics was designed to construct a clustering model of user interest preferences by calculating the distance between user attributes and filling the rating matrix using rating time and item type. Then, the study constructed a student user profiling system and analyzed techniques such as fuzzy C-mean clustering, association rule algorithm and user-based collaborative filtering. The study results show that applying digital health elements in student management and education helps identify potential association patterns of students’ mental health problems. For example, in the W vocational school case study, the association rule algorithm found that the sense of learning stress and compulsion were the most frequent combinations of psychological problems among students, with support levels of 0.7451 and 0.6518, respectively. In addition, the study evaluated the effects of educational management interventions on the mental health of higher vocational students, and found that, after adopting student user profiles for educational management interventions, the experimental class students’ mental health scores for each variable were 0.602 to 1.113 points higher than those of the control class, which significantly improved the students’ psychological quality.
本研究探索数字健康要素在高校学生管理和教育中的挖掘与应用，通过数据挖掘技术提炼学生用户画像，并应用于学生管理和教育中，提高教育管理的准确性和有效性。研究首先进行了数据挖掘的基本流程，包括数据清洗、整合、选择、转换、挖掘、模式评估和知识表示。然后，设计了基于用户特征的聚类推荐算法，通过计算用户属性间的距离，利用评分时间和项目类型填充评分矩阵，构建用户兴趣偏好聚类模型。然后，研究构建了一个学生用户特征分析系统，并分析了模糊C均值聚类、关联规则算法和基于用户的协同过滤等技术。研究结果表明，在学生管理和教育中应用数字健康元素有助于识别学生心理健康问题的潜在关联模式。例如，在 W 职业学校案例研究中，关联规则算法发现学习压力感和强迫感是学生中最常见的心理问题组合，支持度分别为 0.7451 和 0.6518。此外，该研究还评价了教育管理干预对高职学生心理健康的影响，发现采用学生用户档案进行教育管理干预后，实验班学生的心理健康各变量得分比对照班高0.602分至1.113分，学生的心理素质明显提高。
{"title":"Mining and Application of Digital Health Elements in Higher Education Student Management and Education","authors":"Haibo Yu","doi":"10.2478/amns-2024-0599","DOIUrl":"https://doi.org/10.2478/amns-2024-0599","url":null,"abstract":"\u0000 This study explores the mining and application of digital health elements in higher education student management and education, refining student user profiles through data mining techniques and applying them to student management and education to improve the accuracy and effectiveness of education management. The basic process of data mining, including data cleaning, integration, selection, transformation, mining, pattern evaluation and knowledge representation, was first carried out in the study. Then, a clustering recommendation algorithm based on user characteristics was designed to construct a clustering model of user interest preferences by calculating the distance between user attributes and filling the rating matrix using rating time and item type. Then, the study constructed a student user profiling system and analyzed techniques such as fuzzy C-mean clustering, association rule algorithm and user-based collaborative filtering. The study results show that applying digital health elements in student management and education helps identify potential association patterns of students’ mental health problems. For example, in the W vocational school case study, the association rule algorithm found that the sense of learning stress and compulsion were the most frequent combinations of psychological problems among students, with support levels of 0.7451 and 0.6518, respectively. In addition, the study evaluated the effects of educational management interventions on the mental health of higher vocational students, and found that, after adopting student user profiles for educational management interventions, the experimental class students’ mental health scores for each variable were 0.602 to 1.113 points higher than those of the control class, which significantly improved the students’ psychological quality.","PeriodicalId":52342,"journal":{"name":"Applied Mathematics and Nonlinear Sciences","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140518181","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Di Yang, Ming Ji, Yuntong Lv, Mengyu Li, Xuezhe Gao
Facing the problem of power system data loss, this paper proposes a power system data recovery method based on a generative adversarial network. The power system clustering method utilizes aggregated hierarchical clustering and takes into consideration the similarity between different power system data. To transform the power system data recovery problem into a data generation problem, an improved GAN network data analysis method is proposed that utilizes LSTM as a generator and discriminator. Through experimental tests, the LSTM-GAN method is tested with the LSTM method, interpolation method and low-rank method to compare its effect on lost data recovery under different signals of power system data static and dynamic and four fault scenarios. The results show that the root-mean-square errors of the LSTM-GAN method for recovering data under static-dynamic fluctuations are less than 1.2%, and the difference between the errors under 55% and 15% missing data conditions is only 0.77%, with the highest data recovery error of 2.32% in the power system fault scenarios. Therefore, the GAN-based power system data recovery method can effectively realize the recovery of lost data.
面对电力系统数据丢失的问题，本文提出了一种基于生成式对抗网络的电力系统数据恢复方法。电力系统聚类方法利用聚合分层聚类，并考虑了不同电力系统数据之间的相似性。为了将电力系统数据恢复问题转化为数据生成问题，提出了一种改进的 GAN 网络数据分析方法，利用 LSTM 作为生成器和判别器。通过实验测试，将 LSTM-GAN 方法与 LSTM 方法、插值方法和低秩方法进行比较，以比较其在不同信号的电力系统数据静态和动态以及四种故障场景下对丢失数据恢复的效果。结果表明，LSTM-GAN 方法在静态-动态波动条件下恢复数据的均方根误差小于 1.2%，55% 和 15% 丢失数据条件下的误差仅相差 0.77%，其中电力系统故障场景下的数据恢复误差最大，为 2.32%。因此，基于 GAN 的电力系统数据恢复方法可以有效实现丢失数据的恢复。
{"title":"Generative Adversarial Network-based Data Recovery Method for Power Systems","authors":"Di Yang, Ming Ji, Yuntong Lv, Mengyu Li, Xuezhe Gao","doi":"10.2478/amns-2024-0173","DOIUrl":"https://doi.org/10.2478/amns-2024-0173","url":null,"abstract":"\u0000 Facing the problem of power system data loss, this paper proposes a power system data recovery method based on a generative adversarial network. The power system clustering method utilizes aggregated hierarchical clustering and takes into consideration the similarity between different power system data. To transform the power system data recovery problem into a data generation problem, an improved GAN network data analysis method is proposed that utilizes LSTM as a generator and discriminator. Through experimental tests, the LSTM-GAN method is tested with the LSTM method, interpolation method and low-rank method to compare its effect on lost data recovery under different signals of power system data static and dynamic and four fault scenarios. The results show that the root-mean-square errors of the LSTM-GAN method for recovering data under static-dynamic fluctuations are less than 1.2%, and the difference between the errors under 55% and 15% missing data conditions is only 0.77%, with the highest data recovery error of 2.32% in the power system fault scenarios. Therefore, the GAN-based power system data recovery method can effectively realize the recovery of lost data.","PeriodicalId":52342,"journal":{"name":"Applied Mathematics and Nonlinear Sciences","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140516827","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
While discussing the importance of office reception work, this article emphasizes the key role of fine management in improving work efficiency and service quality. Against the background of the artificial intelligence era, the article successfully constructs a framework for an office reception work management system by utilizing cutting-edge React and Express technologies. The system not only carries out meticulous module design based on functional requirements, but also proposes a personalized recommendation algorithm integrating clustering and collaborative filtering by optimizing the Similarity of user characteristics and item attributes for joint filtering recommendation to achieve more humanized reception services. To verify the system's effectiveness, this study conducted an application analysis using University Q as a case study. The analysis results show that from 2008 to 2022, the indices of reception preparation, knowledge of reception work, staffing, business skills of reception staff, work attitude and work detail control have been significantly improved, with an increase ranging from 32.0761 to 37.1677, indicating that the management level of office reception work is constantly optimized and shows a rapid growth. This innovative office reception work management system not only realizes refined management, but also comprehensively improves the service efficiency and comprehensive management level, which provides a valuable reference for the management of similar work.
{"title":"The Practice of Refined Management of Office Reception Work in the Era of Artificial Intelligence","authors":"Yuefang Zhang","doi":"10.2478/amns-2024-0406","DOIUrl":"https://doi.org/10.2478/amns-2024-0406","url":null,"abstract":"\u0000 While discussing the importance of office reception work, this article emphasizes the key role of fine management in improving work efficiency and service quality. Against the background of the artificial intelligence era, the article successfully constructs a framework for an office reception work management system by utilizing cutting-edge React and Express technologies. The system not only carries out meticulous module design based on functional requirements, but also proposes a personalized recommendation algorithm integrating clustering and collaborative filtering by optimizing the Similarity of user characteristics and item attributes for joint filtering recommendation to achieve more humanized reception services. To verify the system's effectiveness, this study conducted an application analysis using University Q as a case study. The analysis results show that from 2008 to 2022, the indices of reception preparation, knowledge of reception work, staffing, business skills of reception staff, work attitude and work detail control have been significantly improved, with an increase ranging from 32.0761 to 37.1677, indicating that the management level of office reception work is constantly optimized and shows a rapid growth. This innovative office reception work management system not only realizes refined management, but also comprehensively improves the service efficiency and comprehensive management level, which provides a valuable reference for the management of similar work.","PeriodicalId":52342,"journal":{"name":"Applied Mathematics and Nonlinear Sciences","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140521738","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Blockchain technology, with its decentralization, traceability, and immutability, offers promising solutions across various sectors, including education. This study explores the application of blockchain in enhancing the security and personalization of educational resource sharing within university physical education (PE). We ensure secure resource sharing by developing a blockchain-based model for PE resource distribution and refining the consensus algorithm. Our research involved a 10-week experiment with 80 university students, measuring changes in psychological factors (e.g., anxiety, depression) and physiological parameters (e.g., lung capacity). Results indicated a notable improvement in students’ psychological well-being, with anxiety and depression levels dropping by an average of 15%, and a significant enhancement in physiological health, evidenced by an average increase in lung capacity of 2.11±1.00 ml/kg. These findings underscore the potential of blockchain technology to elevate university PE teaching practices and positively impact student health, highlighting its significant applicability and future potential in educational contexts.
{"title":"Analysis of the psychological and physiological conditions of blockchain technology in college physical education","authors":"Gang Cheng","doi":"10.2478/amns-2024-0831","DOIUrl":"https://doi.org/10.2478/amns-2024-0831","url":null,"abstract":"\u0000 Blockchain technology, with its decentralization, traceability, and immutability, offers promising solutions across various sectors, including education. This study explores the application of blockchain in enhancing the security and personalization of educational resource sharing within university physical education (PE). We ensure secure resource sharing by developing a blockchain-based model for PE resource distribution and refining the consensus algorithm. Our research involved a 10-week experiment with 80 university students, measuring changes in psychological factors (e.g., anxiety, depression) and physiological parameters (e.g., lung capacity). Results indicated a notable improvement in students’ psychological well-being, with anxiety and depression levels dropping by an average of 15%, and a significant enhancement in physiological health, evidenced by an average increase in lung capacity of 2.11±1.00 ml/kg. These findings underscore the potential of blockchain technology to elevate university PE teaching practices and positively impact student health, highlighting its significant applicability and future potential in educational contexts.","PeriodicalId":52342,"journal":{"name":"Applied Mathematics and Nonlinear Sciences","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140525599","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：