bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Study of Japanese Vocabulary Recognition Teaching Strategies Based on Deep Belief Networks
Authors: Tang Huiqin , Zhou Bin , Gu Weijie 
Published: August 2024

Abstract
Based on the deep belief network, this paper proposes a teaching strategy for Japanese vocabulary recognition with the main direction of realizing scientific classification of Japanese vocabulary and building a corpus. In order to improve the classification effect of Japanese vocabulary, a Japanese vocabulary classification model based on a deep belief network is constructed, and the TF-IDF and LSI features of the text are used as inputs to obtain the deep-level features and improve the final classification effect. A Japanese vocabulary corpus is constructed through the steps of corpus collection, database design, and corpus production, and a Markov number labeling model based on a deep belief network is constructed to transform the problem of sentence tense processing into the problem of labeling tense trees and propose a DBN-based method for translating the tense of the corpus. The teaching practice of Japanese vocabulary recognition was conducted with 100 first-year students at the College of Japanese Language at Dalian University of Foreign Languages as research subjects. The experimental class scored slightly higher than the control class in all six Japanese vocabulary tests, and the mean values of vocabulary utilization ability and vocabulary comprehension ability were higher than those of the control class by 2.94 and 1.06, respectively, which showed a significant difference (P<0.05). The experimental class also scored higher than the control class in all dimensions of Japanese vocabulary learning ability, showing significant differences (P<0.05).
A quantitative study of the relationship between attachment styles and psychological resilience in the context of social anxiety among college students
Authors: Wang Qinchao 
Published: August 2024

Abstract
The purpose of this paper is to reveal the effects of attachment style quality and psychological resilience on college students’ social anxiety so as to provide new ideas for subsequent research on social anxiety. The study polled 450 college students using the Intimate Relationship Experience Scale, the Adolescent Psychological Resilience Scale, and the Interaction Anxiety Scale. It then used statistical analysis to find out how attachment styles and psychological resilience are related in college students. It also looked at how attachment styles and psychological resilience affect social anxiety in college students. According to the findings, there was a significant difference in demographic variables and a significant correlation between attachment style and psychological resilience among college students. The mediating effect of psychological resilience between attachment style and social anxiety was 25.47% of the total effect, and psychological resilience mediated the effect of attachment style on social anxiety among college students.
Human Resource Management Optimization Strategies for Diverse Work Environments Based on Artificial Intelligence
Authors: Wu Min 
Published: August 2024

Abstract
Under the diversified work environment, the relationship between employees and enterprises has ushered in new and significant changes. How to adapt to changes, form a new human resource management model, and improve management performance is an urgent issue. In this paper, we constructed an employee turnover pre-analysis measurement model based on XGBoost artificial intelligence, iterated many times during training, generated a weak classifier in each iteration, trained on the basis of the residuals of the previous classifier, and finally combined all the weak classifiers in a weighted way, reduced the bias to improve the accuracy of the final classifier through continuous iteration, and completed the construction of the model. The historical data of employees in six branches of enterprise W are imported into the model for analysis, and the F1 values are all above 0.85, and the AUCs are all higher than 0.7, with good prediction performance. The top three important employee turnover influencing characteristics and their weights are overtime work 0.647, monthly income 0.618, and interpersonal relationship 0.579. Accordingly, human resource management optimization strategies are designed and applied in Enterprise W to implement human resource management reform. After the reform, the average monthly separation rate has been reduced from 2.23% to 0.19%, and the average number of monthly separations has been reduced to only 7, which is 91.86% lower than during the pre-reform period. This study proposes feasible paths for modern information technology and artificial intelligence-enabled human resource management, and optimization of human resource management in a diverse work environment.
Analysis of the Dynamic Relationship between Transgressive Innovation Behavior and Team Network Structure in High-Tech Firms
Authors: Xu Xingqiang , Youngwook KO 
Published: August 2024

Abstract
The current market economy has stepped into the stage of high-quality development led by innovation. How to effectively improve the innovation capacity of enterprises has become a widespread concern in the academic community. The article first analyzes the formation factors and consequences of transgressive innovation behavior and then combs through the dynamic collaboration and system performance generation in multi-team network structures. Based on the network centrality of social network analysis, two models based on sub-team type and team structure balance are constructed by combining structural balance theory. Regression analysis was conducted for Model 1 to clarify the effects of transgressive innovation behavior on network centrality and subteam type, and social network analysis was used to investigate the influencing factors of team structure balance in Model 2. Network centrality increases by 0.121 percentage points when the subteam type variable increases by 1 percentage point. The regression coefficient of subteam type on network centrality decreases from 0.138 to 0.114 after adding the variable of team members’ transgressive innovation behavior to Model 1. When the number of subteams is 3 and 4, the team network structure can reach a strong balance state at this time, while more than 5 will cause the growth of negative team relationships because of the transgressive innovation behaviors of team members, which will affect the balance of the team network structure. Therefore, there is a dynamic relationship between the transgressive innovative behavior of high-tech enterprises and the team network structure, and it is necessary to set up a reasonable multi-team structure in order to effectively ensure that the performance of high-tech enterprises can be improved.
Study on the transformation model of old neighborhoods oriented towards sustainable community economic development
Authors: Yang Shuyang , Ren Chongbao , Sun Xialing 
Published: August 2024

Abstract
Urban renewal now dominates the strategic stage of urbanization, shifting from the previous focus on “whether there is” to the pursuit of “good.” In the context of urban renewal, the transformation of old neighborhoods should be carried out reasonably. In this regard, this study focuses on exploring design ideas for the transformation of old neighborhoods in the context of sustainable community economic development, with the aim of proposing a set of comprehensive transformation programs. Then, based on the three perspectives of residents, community, and city, the evaluation indexes for the transformation of old neighborhoods are selected from two perspectives of input-output, and the transformation efficiency evaluation model is constructed by combining the model of DEA-BCC and the model of DEA-Malmquist index. Finally, taking 19 old neighborhoods in QD city as samples, we analyze the citizens’ satisfaction with the transformation effect of the neighborhoods, analyze the efficiency of the transformation investment in the old neighborhoods from the two perspectives of comprehensive efficiency value and scale efficiency value, and analyze the problems and the direction of improvement of the transformation of the old neighborhoods from the redundancy of the slack variables. The results show that the average investment efficiency of the old neighborhood transformation is 0.9185, and the pure technical efficiency and scale efficiency are 0.9239 and 0.9651, respectively.
Construction and Application of University English Knowledge Mapping Supported by the Concept of Outcome-Oriented Education
Authors: Gong Lin 
Published: August 2024

Abstract
The outcome-oriented e-education concept is one of the current international advanced education concepts, and its generation and development fit with the development of information technology and the social demand for the quality of talent cultivation. In this paper, a knowledge mapping system for university English courses based on the concept of outcome-orientated education is investigated to enable the integration of university English course knowledge and its visualization in the form of web pages. Knowledge points, concepts, definitions, and other information about the university English subject are extracted, and various data sources, which contain structured, semi-structured, and unstructured data, are collected, integrated, and extracted in the form of English knowledge triads. The system testing results indicate that, in comparison to the traditional DistMult method, this paper’s method enhances the classification accuracy of the three English course datasets by 0.93%, 1.68%, and 0.85%, respectively. The experimental results validate the effectiveness and superiority of the system. Meanwhile, the questionnaire survey found that the system can effectively help learners improve their confidence, interest, and initiative in learning, enhance their learning effectiveness, improve their learning efficiency, and provide them with high-quality learning resources that have good application value.
Research on Fault Detection and Localization Techniques for Distribution Networks Based on Edge Clustering
Authors: Lin Xiongfeng , Zhang Tuo , Li Shengyun , Qiu Junqi , Zhang Lihang , Su Lisha , Bai Yiming , Liang Jiehua 
Published: August 2024

Abstract
With the intelligent transformation of the power grid, the number and type of various terminals, sensors, and new types of loads in the distribution network increase, and the huge amount of information and noise information accessing the power grid brings great challenges for fault detection and localization. In this paper, we propose to combine wavelet transform and LSTM unit to form a novel neural network basic unit TFM and examine the fault detection and localization capability of TFM by combining them with a typical example system, IEEE33. Spectral clustering and the K-Means algorithm are utilized to cluster the edge nodes, and the number of nodes in the three partitions after partition correction is 11, 10, and 12 nodes in order. The data shows that the TFM system performs the fault diagnosis task with better test accuracy than LSTM in every dimension, and its accuracy improvement for fault localization is the largest, at 5.39%. Introducing two reconfiguration scenarios for three edge node partitioning models and retrograde fault localization detection, compared with the no reconfiguration scenario, their localization accuracies all produce different degrees of decline, but always not less than 80%. The localization accuracy of the MⅡ model is still not less than 98% in the fault resistance range of 500~1000Ω, which proves that the TFM system can effectively extract high-resistance fault features.
Semantic Network Analysis and Optimization Path Research on Medical English Terminology
Authors: Wang Dan , Yao Zhuang 
Published: August 2024

Abstract
Specialized terms are often longer words in medical English, and how to improve the effective memorization of specialized terms has become a research hotspot in medical English learning. The article proposes a method for creating a semantic network model for medical English terms using CRFs and the ATT-BiLSTM model. Firstly, on the basis of combing the characteristics and methods of medical English terminology composition, the CRF model is introduced to recognize the named entities of medical English terms and combined with the Viterbi decoding algorithm to obtain the lexical annotation result sequence of medical English terms. Secondly, an entity-relationship extraction model for medical English terms is established by combining the attention mechanism with the BiLSTM model, and ELMo vectors are added to improve the extraction efficiency of medical English terms. Finally, a semantic network model of medical English terms was constructed based on the Neo4j database by combining the named entity recognition and entity relationship extraction model, and the semantic network analysis was carried out by the semantic similarity algorithm based on information content. The results show that the CRFs model only needs a 14.2MB training corpus to co-represent the contextual information of medical English terms, and its F1 value is maximally improved by 10.22% on average after adding ELMo vectors to the ATT-BiLSTM model. The mean semantic similarity of medical English terms in the semantic network model is 1.391, and the result of the semantic similarity assessment is 0.803. Relying on the semantic network model can help learners understand the differences between medical English terms, find more similar terms to elucidate the standard terminology, and improve learners’ comprehension of medical English terms.
Analysis and Optimization of the Effectiveness of College Physical Education Courses Based on Fuzzy Cognitive Evaluation
Authors: Zhang Chunmiao 
Published: August 2024

Abstract
Cognitive diagnostic theory can provide a comprehensive and detailed objective evaluation of individual macro learning ability, thus providing an effective reference for targeted teaching and learning. In this paper, a fuzzy cognitive diagnostic model is used to evaluate the degree of mastery of a college student on the physical education course, calculate the probability of mastery of each attribute, and statistically analyze the degree of mastery of the attributes of the individual as well as the class as a whole. Then, a learning effect evaluation standard is constructed to evaluate the learning effects of the physical education course for all students. The empirical results show that the mean value of the evaluation of the students’ cognition of physical education in School X is 0.6587, and the average probability of mastery of physical education emotion is 0.6021, both of which have reached the degree of good mastery. The average probability of mastering sports operations was 0.5909, which indicates that university students have an average level of mastery in all sports skills through the physical education program. The outcome is in line with the current situation, which can serve as a reference for teachers to make targeted teaching decisions. The study has both theoretical value and practical significance in promoting the development of wisdom education.
Modern Transformation of Ancient Chinese Philosophical Thought in Ideological And Political Education in Colleges and Universities Based on Multiple Learning Styles Adaptation
Authors: Deng Haiman , Shao Jianxun , Li Tao 
Published: August 2024

Abstract
Ancient Chinese philosophical thinking, as an important part of Chinese civilization, has influenced thousands of years of Chinese history and also had a profound impact on the Ideological and Political Education in modern colleges and universities. Based on the philosophical nature of Ideological and Political Education, the article analyzes the learning styles of different categories and establishes a blended-tiered teaching model for Ideological and Political Education with the aid of digital technology. Based on students’ online Ideological and Political education learning behavior data, a Bayesian discriminant analysis algorithm is used to identify students’ learning styles. Then, the GRU neural network model is introduced to define the diagnosis of the knowledge level of Ideological and Political Education, and the Ideological and Political Knowledge Level Diagnosis Model is established. An example analysis was conducted to assess the learning style, cognitive level, and relevance of Ideological and Political Education. The study shows that when carrying out the identification of students’ learning styles, the Bayesian discrimination improves by 10.98% compared with the results of the style clustering algorithm, and the average absolute error of the diagnosis of students’ Civics knowledge level minimizes only 0.128. The scores for various learning styles are highly variable, and the extreme differences are all over 24 points. The standardized regression coefficients of learning interest in Ideological and Political courses and literacy learning styles are between 0.072 and 0.163, with a very significant correlation. Incorporating ancient Chinese philosophical ideas into ideological and political education is conducive to satisfying students’ multiple learning styles and also contributes to modernizing and preserving ancient philosophical ideas.
An Exploration of the Integration of Marx’s Philosophical Thought and Modern Ethical Decision-Making Models for Artificial Intelligence
Authors: Liu Jianning 
Published: August 2024

Abstract
Artificial Intelligence is involved in more and more fields, and the debate of whether human beings will be replaced by it is more and more intense. This paper explores the paradigm of ethical decision-making of artificial intelligence from the perspective of Marx’s philosophical thought. Based on the basic elements of ethical decision-making, three decision-making methods are proposed to complete the judgment of decision-making consequences, and the calculation formula for the consequences of these methods is derived. Using the Bayesian learning method, a utility-maximizing agent effect function is constructed to implement the moral embedding policy. Measure the ethical fairness of decision-making algorithms based on statistical fairness orientation to propose fair decision-making methods. Through the example analysis, the practical application effect of the model is analyzed from two perspectives: public policy implementation and education. More than 40% of the users are more satisfied with the public policy implementation made by AI, and they are relatively satisfied with the implementation of AI governance policy at this stage, but there is still room for improvement. There is a difference in the cognition of students of education-related majors and computer science majors on the ethics of identity intelligence, and education majors pay more attention to the educational level and social virtue issues, such as educational sovereignty, educational purpose, educational value, educational evaluation, educational fairness, as well as the development of students, and integrity issues.
A Study on Synergistic Improvement of Physical Fitness and Skills of Basketball Players Based on Big Data
Authors: Cai Ning , Zhang Jungang , Li Jinpeng , Luo Jian , Yu Ao 
Published: August 2024

Abstract
This paper proposes a strategy for synergistic improvement of physical fitness and skills of basketball players with the content of big data analysis of decision-making of physical fitness training programs and estimation of the human posture of basketball players. The data related to physical training and testing are processed using neural network methods, and a priori algorithms with continuous attributes discretize the data to realize data fragmentation and prevent data distortion caused by intrinsic correlation so as to build up a technical and methodological platform for physical training programs. At the same time, the basketball action posture estimation algorithm based on multi-scale spatiotemporal correlation features is proposed, and the human body temporal sequence feature capture module based on Transformer is constructed to improve the accuracy of basketball action posture estimation to meet the needs of skill training. The men’s basketball team of Shandong Agricultural University in China was used as a research object to carry out basketball physical fitness and skill training practices. The experimental group’s basketball players’ performance in barbell bench press and weighted squat was 11.06kg and 10.05kg more than that of the control group. Their performance in 3/4-court sprint running, and return running. Restriction-area footwork was 0.52s, 2.16s, and 1.97s faster than that of the control group, with significant differences in basketball skills, such as 14-meter round-trip straight-line dribbling around the pole and 30-second in situ spotting of two-handed chest pass (the first time in the experimental group). Basketball skills showed significant differences (P<0.05).
Research on the Path of Cost Control and Economic Benefit Enhancement in Construction Engineering Projects
Authors: Chen Liang , Tang Yu 
Published: August 2024

Abstract
The increasingly competitive market situation in the construction industry requires that construction enterprises strengthen the cost control of construction projects in order to improve the economic efficiency of enterprises. This paper is based on the improved genetic algorithm to realize the optimization of the cost control strategy of the construction project and effectively overcome the problems of weak cost control consciousness and high material procurement cost in the previous cost control. A construction company is selected as the object for the case study, and the genetic algorithm is used to calculate and analyze the cost control of the construction company. The return on investment, net present value, and internal rate of return are used as indicators to measure the economic benefits before and after optimizing cost control strategies. The improved genetic algorithm calculates that among the cost control factors of the construction company, procurement management, and field operation have a high probability of being selected in the genetic calculation, and the final project cost is 36.7849 million yuan through the genetic algorithm, which achieves the goal of project cost control. At the same time, this paper finds that cost control has a significant positive effect on the improvement of economic efficiency, and the economic efficiency of this construction company before and after the optimization of the cost control strategy is significantly improved.