Reviewerly/exHarmony huggingface dataset:
Mainstream Big Data Parallel Computing System Performance Optimization

In recent years, with the widespread application of the Internet and information technology in people's production and life, the amount of data generated by all walks of life every day has shown a geometric and explosive growth trend, and the real-time nature of data analysis has become increasingly high.Therefore, big data parallel computing is widely used.The main purpose of this paper is to analyze and research the performance optimization of parallel computing systems based on mainstream big data.This paper mainly analyzes the design requirements and elastic resource scheduling strategy of the big data parallel computing system, introduces the framework and module design and the main functional modules, and preprocesses the data.The experimental results show that as the parallelism of Shuffle increases, the running time of Task decreases.This is because as the degree of parallelism increases, the amount of data processed by a single task decreases and the processing speed becomes faster.However, the proportion of shuffle data read I/O waiting time is the smallest only when the shuffle parallelism is 800, which is optimal.
Evaluation System for College Students' Innovation and Entrepreneurship Potential Based on Computer Technology

Many colleges and universities now offer innovation and entrepreneurship courses to help students learn innovation and entrepreneurship knowledge, but the teaching results of innovation and entrepreneurship courses are not good.Today's college graduates have a low success rate in innovation and entrepreneurship.Based on computer technology, this paper constructs an innovation and entrepreneurship potential evaluation system that can improve the success rate of college students' innovation and entrepreneurship.This paper uses the three-tier system architecture to build the overall structure of the system, and uses the Bayesian algorithm to allocate university resources to help college students continue to innovate and start businesses.This system can evaluate the innovation and entrepreneurship ability of college students, help colleges and universities to support college students' innovation and entrepreneurship, and improve the success rate of college graduates' innovation and entrepreneurship.
Design and Application of Computerized Adaptive Algorithm in Differentiated Teaching of Higher Vocational English

In recent years, the diversification of higher vocational enrollment has led to significant differences in students.With great differences in foreign language foundation, uneven quality, the imbalance of English teaching increased.The blended teaching mode is an important change in the way of learning in the information age, adopting the teaching mode of "online" + "offline", but students' differences have not received enough attention.Using computer adaptive algorithm technology to build a reasonable test model, and accurately push appropriate test questions to students with a difficulty appropriate to their ability level, it can quickly diagnose students' current learning level, so as to provide teachers with targeted differentiated teaching and provide strong support for students' independent learning.This paper discusses what the advantages of computerized adaptive algorithm on differentiated teaching are, how to carry out differentiated instructional design and implementation with the help of the computerized adaptive algorithm, what the effects are in the differentiated instruction supported by the computerized adaptive algorithm.In order to obtain rich data, quantitative and qualitative methods were used.Through actual research and practice, this project explores the use of computer adaptive algorithms in differentiated teaching, which can change the current situation that higher vocational English teaching has not fully realized students' differentiated learning.
Research on College English Teaching in the Context of Big Data Technology

In the era of big data, it has become a general trend to optimize and innovate college English teaching.Therefore, it is a feasible approach to build a new college English teaching system platform based on big data technology.Based on this, in order to meet the needs of teachers, students and teaching administrators in the new era, this paper explores the design and construction of a college English teaching platform model based on big data technology.Through architecture design, database design, cloud platform construction, the integration of cloud computing technology and other methods has realized the design of this platform model.The actual test results show that the performance of the system has reached the expected requirements, which shows that the designed college English teaching platform model based on big data technology has achieved initial success.
An Analysis of College Students' Satisfaction with Online Courses-Data Processing Based on SPSS

The development of Internet technology has changed the way college students learn, making more and more college students choose online courses.This research is based on domestic and foreign scholars' research on college students' satisfaction with online courses, with reference to several representative literatures in China.The author of the article uses SPSS software to process the data.It summarizes the satisfaction of college students with online courses, and concludes that most college students are satisfied with online courses.
Optimal Processing of English Education Model Based on Artificial Intelligence Technology

With the rapid development of science and technology, the society has entered a new era of knowledge and information.Modern information teaching has changed the traditional curriculum concept, improved the curriculum model and improved the teaching method in the curriculum field.This paper studies the optimization of English education mode based on artificial intelligence technology, mainly using SAIES system, so that middle school students are placed in an intelligent environment.The practice of SAIES system in middle school English teaching can be divided into six steps.The teaching process of SAIES system consists of ten steps.Finally, the reliability and validity of the system are tested.The results show that the overall reliability of the learning adaptability level questionnaire is 0.913, and the reliability of the system is very good.
Construction of Online Learning System of Construction Engineering Management Based on MOOC

With the rapid development of China's economy and science and technology, the overall development of the construction industry shows a good trend, which means that the construction industry will have a very broad development prospect and market in China in the next few years.Therefore, more and more students choose the major of construction engineering management when filling in their major.This major involves many courses, with a wide range of practical contents, which makes it difficult for most people to learn.The online learning system of construction engineering management based on Web technology developed in this paper, applying MOOC network teaching mode, provides a platform for teachers of famous schools to display their teaching ability and share teaching resources.The platform also provides students with an open, free and high-quality online learning system, which allows cash-strapped learners to obtain the richest teaching resources at the lowest cost, so as to improve their professional knowledge level, improve their learning enthusiasm and broaden their horizons.
Knowledge-enhanced Representation based-on Contrastive Learning and Informative Entities

In the field of NLP, sentence representation model is a popular task.The emergence of pre-trained representation model based on transformer structure yields significant results for downstream tasks.Besides, since the introduction of contrastive learning based on the pre-train representation model two years ago, there has been great interest in its notable benefits.For the sake of achieving better training results for sentence vector representation, we propose to use a training framework of contrastive learning and bring about knowledge graph information to improve language representation.This method enables the model to learn more linguistic information in sentence presentation and will improve the effect of sentences in tasks like semantic matching and classification.
An Empirical Study of PIAE Blended Learning in Cloud Classroom of College English Reading Course

PIAE is an innovative teaching model that integrates PBL teaching model and Teaching Interaction Theory into college English reading course.This study conducted an empirical study to test the effectiveness of PIAE blended teaching based on mobile learning platform Xue Xi Tong in English reading course, and uses SPSS to analyze the datum collected from the before-test, post-test and questionnaire.Through qualitative and quantitative analysis, the research results show that PIAE blended teaching model based on Xue Xi Tong is beneficial to the improvement of English major students' reading ability and has a positive impact on the teaching effect of English reading class.
Deep Learning in Chinese Text Recognition Program: Exploring the Influence of Program Parameters on Recognition Accuracy

Deep learning (DL), a class of pattern analysis methods for learning the intrinsic patterns and levels of representation of sample data, has gained more and more attention in recent years.However, deep learning still faces many problems.The difference of various parameters when deep learning is performed for a specific kind of data will have a large impact on the results, while the adjustment of parameters lacks a systematic logical support.Therefore, this paper, through literature research methods, empirical research methods and other relevant methods, will summarize the influencing factors of Chinese text recognition procedures, including the effect of each parameter in the procedure on the results and the differences between different algorithms, and suggest possible directions for future improvements.The paper finds that the choice of algorithm has a large impact on the accuracy of deep learning, and programmers should give priority to choosing the best algorithm rather than obsessing over fine-tuning parameters.The future direction of deep learning should focus on optimizing and improving old algorithms or even creating new, more targeted algorithms that are more efficient for some problems.
Screening for Sport Injuries Based on Android Application

Massage is a manual therapy that helps in the recovery process of injuries for athletes and non-athletes.A masseur must do a screening first.Treatment errors can be minimized by carrying out a screening process.The screening process is a process of looking at the injury criteria and the chronology of the injury.This study was conducted to assist the screening process so that the SOP for handling injuries remains in accordance with the rules for handling injuries with the conclusion that not all complaints that look the same will be given the same treatment, because it can be seen from the history of each individual who has a complaint.This study uses a research and development design from Borg and Gall, includes analyze the product to be developed; develop the initial product; expert validation; field trials; product revision; final result; and test the effectiveness of product development.Instruments used are questionnaire and interviews.
Link Prediction Model for Anchor Chain Connection Method

In order to improve the accuracy of the location-based social network (LBSN) multi-source heterogeneous data link prediction, a model named anchor link-predict (AL-P), based on the anchor link method is proposed.Firstly, the network representation learning method is used to obtain the user relationship topology in LBSN.The matrix decomposition method is used to obtain the user sign-in record representation space in LBSN.Then, the anchor link method is joined the user relationship topology and user check-in record, and the potential relationship between them is mined.Finally, the experimental analysis shows that the Al-P model can significantly improve the link prediction effect under different evaluation indexes compared with the existing predicting models of same type.
Research on the Influencing Factors of Postgraduate Research Innovation Behavior Based on MATLAB Software

Master student research innovation behavior is influenced by many factors.Through literature review and expert interviews, this study summarizes the influencing factors of research innovation behavior of postgraduate students from the three levels of individual, interpersonal and school.The interpretation structure model and hierarchical analysis are used in the analysis of influencing factors of system the complicated relationship between various influencing factors, and the hierarchical structure relation model is built.The hierarchical structure relationship model was constructed to determine the relative importance of complex factors in the hierarchy by pairwise comparison.The results show that personality and emotion are the surface influencing factors, research pressure and research ability are the middle influencing factors, and peer support, training mode, graduation requirements and research conditions are the deep influencing factors.
Impact of Research and Development Investment on the Performance

Artificial intelligence (AI) has gradually become an important factor in enhancing the core competitiveness of a country.This paper is based on the data of 40 AI companies from 2018 to 2020 as samples, and conducts an empirical research on the impact of research and development (R&D) investment on corporate performance.The results show that R&D investment cannot significantly influence the performance of AI companies in the short term, but have a positive effect in the long run, especially in the second lag period.AI companies should take measures to improve their R&D activities and relevant works, thus promoting the AI development in China.
A Method for Online Course Evaluation Based on Continuous Bag-of-Words Model and Semantic Analysis—A Case Study of Statistics

With the rapid development of the Internet and multimedia, online courses have become one of the main ways for students to learn.Online course reviews are the comments the learners or students published voluntarily based on their real learning experience of a course, which include diverse information.This paper selects the statistics-related courses in the MOOC platform as the research object and obtains online reviews of seven courses, then employs natural language processing techniques to deal with the review data and further develops a method for online course evaluation.First, the continuous bag-of-words model is used to extract the feature words of courses from the online course reviews.Secondly, based on mutual information and semantic similarity analysis, this paper identifies and clusters the learners' preferences for online courses, the preferences include six aspects.Finally, we compute the value and weight of each aspect of preference according to the sentiment propensity and the occurrence frequency of preference words, respectively.Then the overall score of each course is calculated using the above values.Based on the results, we proposed suggestions and enlightenments for the online course development and improvement.
The Application and Research of Artificial Intelligence in The Field of Music Education

AI technology will be used in music teaching, bringing the easiest way to music teaching.This work aims to study the application of artificial intelligence in music teaching.On the basis of full investigation and research on intelligent piano music teaching, combined with the advantages of intelligent piano teaching, the construction of intelligent piano teaching functions complements each other to form the basic framework of intelligent piano teaching.Starting from teaching practice, this paper makes a beneficial exploration of students' piano learning, and combines teaching methods such as game teaching and situational teaching with the functional characteristics of intelligent pianos to improve students' learning efficiency.The results show that 118 students especially like intelligent piano teaching.It provides a new idea and method for educational reform and theoretical support for innovative research on piano education.
The Construction of Prediction Model based on Decision Tree-Neural Network Algorithm for Identifying Poverty-Stricken College Students

In the context of "three comprehensive education" in campus, the support for economically disadvantaged students in campus is still one of the key tasks that need to be solved.With the limited resources of financial support for povertystricken college students, the identification of these students faces serious challenges.In this essay, a prediction model based on decision-tree and neural network algorithm is designed to predict and analyze students' poverty recognition.After testing and validation, it proves the effectiveness of the model applied to the prediction of college poverty-stricken college students.Based on the author's database, the recognition accuracy of the model can reach 97.52% at present, and the prediction results of student poverty recognition can be realized with data update.
Design and Application Research of Education Management System Based on Block Chain

With the development of computer technology and the improvement of economic level, data archives management system has been widely used in archives management.Archives record the development history and social activities of countries, organizations and individuals, and are an important wealth for the development of human society.Paper file management has the disadvantages of slow search speed and complex management process.Digital archives management system can and improve the retrieval speed of archives through database query, simplify the management process of archives through online approval, reduce labor costs, improve office efficiency.This paper mainly describes the design and application research of education management system based on block chain.It puts forward its own opinions and views on the current problems and puts forward corresponding solutions according to the practical application of education management system, aiming at speeding up the application process of education management system.
Partial Multi-Label Learning with Global and Local Manifold Disambiguation

In Partial Multi-Label learning (PML), each training example is assigned with a candidate label set where only partial labels are correct.Existing PML methods only focus on global label correlation, while they lack the consideration of the local label correlation.To alleviate this issue, a novel framework is proposed to jointly consider the feature manifold structure over the global instances and local instances.Specifically, we firstly explore the global feature manifold and local feature manifold by the affinity information conveyed by feature vectors.Then, a trade-off parameter is introduced to character the relative contribution of the feature manifold structures optimized by different methods.Afterwards, in order to disambiguate the candidate labels, we utilize the joint feature manifold in the label space.Finally, the predicted results are learned by training a linear multi-label classification model.Extensive experiments on six PML datasets demonstrate the effectiveness of our proposed method.
The Design of Comprehensive Assessment System for Computer Major of SCM via CIPP-CDIO

In the background of the transformation of the application-oriented undergraduate majors, the concepts of CDIO engineering education and CIPP curriculum evaluation have been widely accepted by many domestic universities.Under the new educational concept and teaching mode, how to evaluate the students' progresses of the course effectively is a key problem, which needs a solution in the educational reform.In this paper, a comprehensive assessment system for the curriculum of single-chip-microcomputer is presented based on the fuzzy inference.Via four characteristics of the teaching process, the students' progresses are well evaluated by the assessment system, which will lay a solid foundation for the improvement of the quality of teaching.
Mobile-Based VR Technology and Its Application in English Learning

In recent years, with the development and progress of the times, mobile technology has gradually developed, and the development momentum of mobile terminals including smart phones is also very rapid.And the application of mobile technology to education in mobile learning has become an inevitable trend in education.English subjects have high requirements for immersion language learning environments in all aspects, which makes them suitable for such mobile learning.On the basis of mobile English learning with mobile technology, we will create a free, practical and situational learning environment for vocational students that is not limited by time and space.
Research on Distance Education of French as A Foreign Language in Colleges Based on SPSS Data Analysis Software

Taking the course of French as a second foreign language in Wuhan Business University as an example, this paper elaborates on the distance education design of French as a second foreign language, including pre-class preparation, inclass design and after-class homework design.In addition, this paper explains the influence of online courses on teachers and students.This paper uses SPSS data analysis software to study the effect of distance education in French as a foreign language.The results show that distance education increases the information output of teachers and creates more vivid learning environment of language learning, greatly improving the teaching efficiency and quality.
Design of Mathematics Teaching Quality Evaluation System Based on Grey Correlation Analysis

The current teaching quality evaluation method cannot meet the needs of college mathematics teaching quality evaluation, so a more efficient teaching quality evaluation system is in need.Based on teaching quality evaluation, this paper develops the teaching quality evaluation system, then uses hierarchical analysis and gray correlation analysis to obtain the evaluation index and evaluation index weight, and finally proposes an efficient teaching quality evaluation system with higher accuracy.The test results also show that the mathematics teaching quality evaluation system based on grey correlation analysis has higher accuracy and higher evaluation efficiency than other systems.Of course, in the subsequent research, further research should be done on the efficiency improvement of the teaching quality evaluation system.