Reviewerly/exHarmony huggingface dataset:
Exploring Innovative Strategies for Teaching English to College Students Based on Data Mining Theory

Abstract This paper suggests a J2EE framework-based online intelligent diagnostic assessment scheme. The system has the capabilities of teaching, diagnosis, testing, and feedback as auxiliary teaching software through the automated alteration of subjective and objective questions and the individualized design of diagnostic results. Combined with the characteristics of English composition, the research focuses on the use of the shortest editing distance, cosine vector space, regular matching and other techniques to automate the composition correction and diagnosis, which not only realizes the final scoring of subjective questions but also the diagnostic report can provide students with personalized comments, precisely give the strengths and weaknesses in terms of knowledge points, as well as the analysis chart of knowledge points, scores and ability values of previous exams. In this paper, when evaluating the system with teacher ratings, the overall mistake rate for class essays was 9.0% when the similarity criterion S=0.2 was employed. For individuals and classes passing the test, the error was within 10%, and the score difference was within 2 points. Finally, the common errors of students in English writing were detected, with grammar errors accounting for 58.2%, vocabulary errors for 26.7%, and essay errors for 15.1%. Therefore, this system can make a good contribution to the teaching reform of English and achieve a real reduction of the burden for teachers and students.
The Origin and Significance of Research on Music Education Reform and Talent Cultivation Based on Evaluation Index

Abstract In order to explore the origin and significance of music education reform and talent cultivation in the new era, this paper constructs a new music curriculum evaluation model based on SVM. Firstly, we explore the path of music education reform and the goal of music talent cultivation by taking the trend of Internet of everything as the origin of the proposed “high-quality courses” for music in universities. Then, we analyzed that the recognition accuracy of SVM is significantly better than most machine learning methods in solving high-dimensional small sample data, so we established a new music curriculum teaching evaluation model on this basis. The average score of each index of the new course teaching effect is 74, and the evaluation grade is better, obtained by establishing the evaluation system of the new music course of SVM. In the evaluation index, the CVI indexes were all kept in the range of 0.82 to 0.98, which was higher than the standard 0.78 of the CVI index, and the Kappa value of each evaluation index was higher than 0.86. The attendance rate in college teaching rose from 78% to 100%, the ability to master music knowledge rose from 67% to 93%, the ability to apply knowledge rose from 76% to 92%, and the average score on weekly tests rose from 86 to 96. Finally, it is concluded that the Internet-based music education reform approach can promote the development of music education careers and cultivate the important means of all-around talents.
Research on the innovative development model of ideological and political education based on big data and self-media environment

Abstract This paper aims to explore the innovative development model of ideological and political education. By establishing a Civic and Political Science teaching platform, two functions of classroom interaction and online dual-teacher interaction are designed under nine ideological and political teaching modules. The VR technology and system framework are analyzed, and the corresponding MDP algorithm is constructed. The algorithm model was used to analyze the percentage of students’ favorite Civics classrooms and the acceptance level of VR teaching classrooms. The result data show that only 27.5% of students like Civics class, 51.53% of students maintain a neutral attitude towards Civics class again emotionally, and 16.36% of students do not like Civics class. 70.1% of students prefer the means of communication of Internet platform tools. 16.58% of students prefer the means of communication of newspapers and magazines, 50.2% of students prefer the means of video communication, and 35.26% of students prefer the means of video communication. 35.26% of students prefer book communication. This paper provides reference data and models for the development of ideological and political education innovation.
Research on the construction and reform path of online and offline hybrid English teaching model based on time series

Abstract With the widespread use of blended English teaching, the teaching model has become increasingly rigid and needs to be reformed. This paper proposes an analytical model of student learning behavior under blended English teaching based on big spatiotemporal data and constructs a structure of offline and online student learning behavior. The DWT-FCM clustering method for learning behaviors is constructed by using a similar distance based on time series instead of Euclidean distance in the traditional fuzzy C-mean algorithm. The maximum information coefficient was used to analyze the correlation between learning behaviors and grades based on MI. the DWT-FCM algorithm divided learning behaviors into five clusters, where the discussion number of cluster 0 reached an average of 45.2, which was 3.2 times higher than that of cluster 1. Cluster 4 has an average number of task completions of only 1.88, which will skip almost the entire course taken. The correlations of the number of task completion, course video progress, and assignment evaluation scores are all highly correlated, with correlation coefficients reaching 0.884 and 0.825, respectively. This study suggests the influence of learning characteristics on English performance in a blended teaching model, which can effectively guide the reform of the blended English teaching model.
Exploring a hybrid online and offline English teaching model based on model hierarchy analysis

Abstract This article examines a hybrid online and offline teaching strategy for English that is based on the “Internet+” environment in order to create a positive learning environment for the language. First off, the essay supports the reform of the English teaching model and explains the relevance of the new online and offline hybrid teaching model for English based on the idea of “Internet+.” The secondary indicators and weights of the quality evaluation are derived to assess the online and offline hybrid English teaching modes, and the quality evaluation system for the hybrid English teaching mode is built based on AHP and fuzzy evaluation. Finally, through the evaluation of competency and final assessment, the student’s attendance rate increased by about 5%, and the overall final grade increased by 8%. Compared to the prior semester, there were 8 more students who received outstanding marks, and there were 4 fewer who received poor grades. In terms of teaching ability, the students were very satisfied with over 60%, and the overall satisfaction level was over 99%. Students’ English learning ability also improved at a high level, with more than 55% of teachers being very satisfied. It proves that blended teaching can improve English teaching ability and stimulate students’ interest in learning.
Study on the optimization of the cultivation path of finance professionals in universities in the digital era

Abstract The rapid development of big data technology is bound to affect the development direction of finance majors in colleges and universities and put forward new challenges to the cultivation of talents. This paper first analyzes the data mining concept, process as well as methods and selects the clustering analysis method, K-means algorithm, and NMF algorithm of big data technology. Secondly, data pre-processing is carried out for students’ learning behavior, learning evaluation, and professional ability data, which makes the subsequent data mining results more reliable. Finally, the judgment matrix is constructed for the training of college finance professionals, and the consistency test of the matrix is carried out to form the absolute indexes of the primary indexes and the relative weight values of the secondary indexes, and the absolute weights of the secondary indexes are obtained through calculation, which finally forms the weights about the student learning behavior, learning evaluation and professional competence evaluation indexes. The learning percentages of student learning clusters are: 16.1%, 19.3%, 30.1%, 34.4%. The innovation and collaboration ability of finance students has been improved, and the deep processing feedback ability of financial knowledge content has been strengthened. Thus, the wide application of big data technology provides a new path for the training of finance professionals in colleges and universities.
Research on high quality development system of vocational education based on improved particle swarm optimization algorithm

Abstract This paper first investigates the implementation process of the particle swarm algorithm by introducing the weight factor ω to make the algorithm population iterative, using the particles to perform a local search and make them stay near the optimal solution of the algorithm to find the best. Then, we discuss the improvement of the particle swarm optimization algorithm by adding inertia weight ω and shrinkage factor to improve the performance of the algorithm and analyze the convergence of the optimization algorithm to determine the convergence conditions and the state of the system. Finally, the improved particle swarm algorithm was used to evaluate the development status of vocational education, analyze its problems, and propose countermeasures for high-quality development. In terms of problems, 68% believe that there is a misalignment in management. 69% believe that the internal management system of the school is not perfect. 66% believe that the school does not have enough funds for the cultivation of talents. As for the learning atmosphere, 294 people think the learning atmosphere is weak, and 487 people think the learning atmosphere is average. The study of this paper is important for the development and optimization of vocational education.
Exploring the Construction and Practice of College English Blended Teaching Model Based on Fuzzy Comprehensive Teaching Evaluation Model

Abstract In order to explore a new English teaching mode, this paper constructs a hybrid teaching model of English in colleges and universities combined with multimedia to respond to the call for reform and innovation of teaching mode. Firstly, through analyzing three hybrid modes of teaching: complementary mode, flipped mode and cooperative mode, a multimedia-based hybrid English teaching model is constructed in combination with current multimedia technology. Secondly, the fuzzy comprehensive teaching evaluation model based on EWM-AHP-DEMATEL and the teaching quality and learning quality evaluation index system of the hybrid English teaching mode in the multimedia context were constructed. Then in the teaching evaluation system, it was found that the satisfaction of teaching materials construction after the improvement was only 85%. There is still a lot of room for improvement, but overall, all have more than 5% satisfaction improvement. In the learning evaluation system, the number of outstanding students in English class participation, English accompanying test, innovation challenge, and English practice all increased by more than 5, and the number of those needing efforts decreased by more than 3. The overall grade improved by about 12% compared to the previous semester. Finally, the conclusion found that this new teaching model can improve teaching ability and students’ English learning ability and is worth implementing in colleges and universities.
Design and application of an online teaching platform for public sports tennis in colleges and universities based on discrete choice regression model

Abstract At present, online teaching is becoming an increasingly popular teaching activity, and while it is gaining more and more popularity, its quality issues are becoming more and more prominent. This paper firstly analyzes the discrete regression model, and after comparing the logit model under random utility selection and its three derivative models, this paper selects the most widely used hybrid logit model to evaluate and analyze the online teaching platform of university public sports tennis with the MNL model of the maximum likelihood method for error analysis. Secondly, the overall architecture of the online teaching platform system is proposed, and the online teaching platform student satisfaction is studied and analyzed. Finally, based on the hybrid logit model, the AIC, BIC, and log-likelihood value indexes of the online teaching platform for college public education tennis are analyzed for the goodness of fit. The results of the study showed that students were more concerned about three aspects of the online teaching platform: operational difficulty, course comprehensiveness, and learning efficiency, which were 65%, 69%, and 74%, respectively. The AIC and BIC indicators of the hybrid logit model were 4753.656 and 4901.321, which were 192.142 and 117.848 lower than those of the conditional logit model, respectively, indicating that the model fits well and provides a better evaluation and analysis of the platform.
The Impact of Retention Policies on Employees Satisfaction in UFONE – Karachi

Purpose: The purpose of conducting this research is to know whether retention policies enhance or declines the committed employee satisfaction in UFONE – Karachi. It is important to realize that the preferences of employees may vary from person to person and from situation to situation. Methodology: This study is quantitative as well as qualitative in nature and a close-ended questionnaire is used as a research tool to gather data and SPSS is used for data analysis. Employee satisfaction is dependent whereas retention policies and procedures are independent variables in this study. Subjects were randomly selected to know the effect of retention policies on the employee. This research focuses on the impact of retention policies on job satisfaction and the scope of research was UFONE Company - Karachi. 342 out of 400 employees accepted the importance of retention polices and said that it is important for employee’s satisfaction. Findings: The majority of the employees are satisfied with the retention policies, however dissatisfied employees were also there who were unhappy with the retention policies of the UFONE. Conclusion: There is a need in UFONE to revisit their employee retention policies and adopt quantifiable measures to improve and benefit their employees.
The Urgency of the Role and Concept of Digital Literacy in Education in the Disruption Era (21st Century)

In addition to entering the era of globalization with the start of the AEC (Asian Economic Community) and the incessant life of the 21st century, the world is currently experiencing super- fast changes marked by a new era or referred to as the era of the industrial revolution 4.0. This high competence is of course a special concern for education as the main guard for competency development. One of the most important components in this field is of course educators. An educator in this era is required to be able to make digital natives (children who know technology from birth) as human beings who will not lose and make mistakes in taking steps and in utilizing existing technology, bearing in mind that in addition to great benefits, technology is quite a threat to the development of students. Educators must be able to select and filter technology and insert value into their learning with digital literacy. So, of course this is of particular concern so that educators have this digital literacy competence. Strengthening literacy, numeracy and technological adaptation are important efforts to improve the quality of human resources in the Digital Age and the Disruption Era. Indonesia is very far behind other countries in terms of this capability. The government as well as related parties (Schools, Universities, Education Quality Assurance Institutions, and Parents) must participate in strengthening literacy, numeracy, and technology adaptation for students and educators in Indonesia. One of the activities is integrating literacy, numeracy and technology activities in learning either at school or at home.
Beyond the Accident Republic: Making Life and Safety with Disaster Memorials in Korea

In the same manner that disasters are political, so too are disaster memorials. Following the 2014 Sewol Ferry Disaster, the bereaved families worked quickly to establish institutions for self-protection, protest, investigation, and memorialization. This article contends that Sewol Ferry “memorial work” is a multi-faceted endeavor, involving several discrete types of expertise and action, including community education and outreach, urban spatial site advocacy, and scientific/forensic analysis. To make sense of this memorial work, we recount foundational memorialization efforts following the Sampoong Department Store collapse (1995) and the Daegu Subway Fire (2003) in which survivors and bereaved families pioneered memorial work techniques. Secondly, we track the evolving struggles over 4.16 memorialization in An-san, the hometown of the 250 students of Danwon High School who died in the disaster, culminating in the site and design selection process of the 4.16 Life and Safety Park. Finally, memorialization efforts recounted in this article have unfolded against the backdrop of multiple scientific/forensic investigations into the causes of the ship’s sinking and the recovery of human remains and victims’ belongings. In the slow disaster of the Sewol Ferry, memorialization is not the final stage, indeed in some crucial ways it may just be the beginning.
An Interactive Teaching Mode based on Artificial Intelligence Teaching

With the continuous development of artificial intelligence, its impact on people's lives is becoming increasingly significant. Countries, universities, and students have increased their emphasis on learning artificial intelligence knowledge. This article designs and proposes a teaching mode called mo-tutor, which achieves the goal of learning artificial intelligence (AI)knowledge through video playback, segmented speech explanations, picture and text sketching, and online coding. This mode effectively coordinates the AI knowledge system and reduces the barrier for students to learn AI.
An Access Control Scheme Based on Blockchain and Ciphertext Policy-Attribute Based Encryption

Ciphertext policy-attribute-based encryption (CP-ABE), which provides fine-grained access control and ensures data confidentiality, is widely used in data sharing. However, traditional CP-ABE schemes often choose to outsource data to untrusted third-party cloud service providers for storage or to verify users' access rights through third parties, which increases the risk of privacy leakage and also suffers from the problem of opaque permission verification. This paper proposes an access control scheme based on blockchain and CP-ABE, which is based on multiple authorization centers and supports policy updating. In addition, blockchain technology's distributed, decentralized, and tamper-proof features are utilized to solve the trust crisis problem in the data-sharing process. Security analysis and performance evaluation show that the proposed scheme improves the computational efficiency by 18%, 26%, and 68% compared to previous references. The proposed scheme also satisfies the indistinguishability under chosen-plaintext attack (IND-CPA).
ImbGAFS: GA Feature Selection for AUC in Bird Strike Prediction

Several studies discuss airplane failure prediction due to bird strikes. However, these studies need to analyze further the imbalance in their dataset. Our research aim is to create an airplane failure prediction by bird strike using a machine learning method optimized using GA feature selection. GA feature selection uses AUC maximization as the objective function to tackle imbalance problems in the bird strike dataset. First, we obtained the airplane bird strike dataset from Kaggle. We carry out preprocessing on the dataset.We then compared and chose one of four stateof-the-art machine learning methods: SVM, MLP, logistic regression, and random forest. The selection process involves oversampling methods, synthetic minority oversampling technique (SMOTE), and optimum threshold selection, which involves geometric mean (g- mean) and area under curve (AUC) values. Finally, we optimize airplane failure prediction by performing AUC maximization using GA feature selection. Our test results show that random forest is the best machinelearning method in airplane failure prediction compared to SVM, logistic regression, and MLP. SMOTE can increase random forest AUC from 0.845 to 0.878. Finally, the random forest model from ImbGAFS is better than the conventional method without feature selection. The increase in the AUC value is from 0.878 to 0.889. Then, after carrying out optimal threshold selection, ImbGAFS+random forest also has better sensitivity, specificity, and g-mean than conventional methods. The increase is from 0.7737, 0.8350, and 0.8037 to 0.8033, 0.8301, and 0.8166, respectively.
Digital Transformation in Public Management Functions for Public Information Disclosure

This research emphasizes the conditioning of resources in the context of public management to create the openness of public information during digital transformation. A literature study from various databases related to managing resources in public management is analyzed. The intended resources include the latest technology used to protect data and privacy when discussing information disclosure in Indonesia. Digital transformation has led public management to improve and accelerate technological acceleration in the context of data analytics and create the openness of information for the public by government administrators. The strategy used to address this digital transformation in public management encompasses a comprehensive plan, including strong data protection policies, investment in technology infrastructure, and training for public employees. Thus, pieces of technology and performance management, open government, and human resource capacity development Public information disclosure results in transparency and accountability, information disclosure, and improving public services. Moreover, integrating technology into the public information ecosystem provides great potential for increasing openness, participation, and better public services.
The application of red music culture resources in the education of ecological civilization concept in colleges and universities under the background of multimedia

Abstract This paper uses a user-based collaborative filtering algorithm to predict the ratings of items by target users and to recommend items that target users have not interacted with. The red music and cultural resources were ranked according to their values, and the Bartholomew coefficient was introduced to calculate the similarity of items from the perspective of a probability distribution, and the content recommendation algorithm was used to construct a model of ecological civilization education concept. It is found that more than 50% of undergraduate college students pay regular attention to ecological environment information, and 30.56% of them will actively learn ecological civilization knowledge, which is not thorough and comprehensive enough for ecological civilization concept establishment and cultivation. It is suggested that universities should integrate red music culture into ecological civilization education to create an ecological civilization cultivation atmosphere.