Reviewerly/exHarmony huggingface dataset:
The Role of Social Media to Attract Virtual Basketball Championship’s Participant during Pandemic Era

The Corona Virus originating from China entered Indonesia in March 2020.Regarding the number of infections caused by the Corona Virus in various parts of the world, the spread of this virus can be said to be a Pandemic.The pandemic has also caused public facilities and infrastructure to be temporarily closed, such as sports arenas, stadiums so that these things affect various activities, for example organizing sports events.Those statement showed that innovations related to organizing sports events are starting to emerge by involving technology in its implementation or it can be called virtual championships.With this condition, organizing committee needs to use technology for promoting their sport events, one solution that can be occurred is using social media.The purpose of this study was to measure the role of social media in attracting participants in a virtual basketball championship during a pandemic.This research is a quantitative research with a non-experimental research design.This study used survey methods and questionnaire sampling techniques.The sample used was 30 respondents.Social media variables include social media as a medium of information, product reviews, brand equity and brand attitude.Data processing using IBM SPSS 25 software.The results of this study found that the role of social media in attracting participants was categorized as strong and social media had a 48.9% influence in attracting participants.It can be concluded from this research that social media has a strong role to attract participants in the virtual basketball championship.
New Method for Precise Ideological Education for "post-00" Students in The New Media Era based on Big Data

The diversification, fragmentation, openness, and complexity of information in the online society in the new media era are constantly impacting their values and even behavioural norms, which also brings new opportunities and challenges to education management and profoundly affects the change of education methods.Based on big data theory, we collect massive basic data generated by college students during their school years and carry out deep mining and correlation analysis to explore the behaviour pattern of college students' networked life and learning style and its multi-dimensional influencing factors, to provide personalized education services for teachers and students, promote students' personalized growth and make college students' management twice as effective with half the effort.In this paper, we will start from the four major needs of college students' education management, such as academic prediction, precise funding, precise guidance, and early warning of lost connection, and build an integrated education management platform in digital space for "post-00" college students to solve the problems of precise, effective and early warning education in the Internet era.
Design and Development of University Teacher Management Information System Based on ASP.NET Technology

The information management of teachers plays an extremely important role in the quality management of talents in colleges and universities, but there are many problems in practice, such as untimely information processing and difficulty in information sharing.Therefore, it is very necessary to construct an efficient teacher information management system for the continuous management of school teachers, which provides a solid foundation for the integration and sharing of information within the college.Aiming at the outstanding problems in the management of university teachers' information, based on B/S architecture, this paper applies ASP.NET server development technology, absorbs the advantages of MVC development idea, builds the framework of WEB application system, and uses SqlServer database for further design and development.The development based on ASP.NET and MVC pattern not only improves the development efficiency, but also improves the maintainability and reusability of the code.To study the problems encountered in student information management, this paper first expounds the purpose and importance of system design, analyzes the current situation of faculty information management in colleges and universities, points out the difficulties encountered by faculty information in business management, and gives the solution and the main realization direction of system development combined with the actual needs.
The Application of Mobile Intelligent Terminal in High School Physics Learning

At present, the emergence of mobile smart terminals such as mobile phones, tablets, and laptops has broken the constraints of traditional education and teaching in space and information transmission, which can effectively expand the ways for high school students to learn, and can help achieve the teaching goals of high school physics in China for core literacy of high school students.Based on this, this paper mainly analyzes the application of mobile intelligent terminals in high school physics learning, and proposes new optimization measures.The information technology is used in high schools to establish intelligent information model, innovate teaching content and collect teaching information, enrich the relevant theories of high school physics teaching, innovate the teaching methods of physics teaching, and better realize high school physics teaching goal.
Construction of Teaching Performance Evaluation System for College Teachers Based on Data Mining

Data mining has become an important means to improve the level of educational management under the background of big data.In this paper, the CART decision tree algorithm of data mining is applied to the performance management of college teachers.On the basis of statistical data, the factors affecting teaching quality such as teaching attitude, teaching methods and teaching preparation are taken as decision attributes to construct a decision tree.The specific construction process of CART decision tree algorithm in teaching performance evaluation of university teachers is illustrated by examples, and the classification model of teaching performance based on CART tree is generated.It is found that teachers who are fully prepared for teaching often show good teaching attitudes and better teaching performance.For the staff with good teaching quality but low teaching preparation score, if they have good teaching means or good teaching attitude, their teaching performance will be higher; If the teaching method is not skilled or the attitude is not good, the performance is average.It can be seen that teaching performance and teaching quality, teaching preparation, teaching means and teaching attitude are mutually restricting and influencing each other.Finally, targeted and reasonable performance evaluation suggestions are put forward.
Multi-stage Semantic Attention with Transformer for Multi-label Image Classification

Multi-label image classification is a fundamental classification task, which seeks to assign numerous possible labels to an image.Many deep convolutional neural network (CNN)-based approaches to discovering the semantics of labels and learning the semantic representation of images by modeling label correlation have been proposed in recent years.However, some small and similar objects cannot be predicted accurately due to the limitation of convolutional kernel representation capability.As a result, in order to solve this problem, this paper introduces twins-transformer.Since different stages of image representation of this model capture different levels or scales of features and have different discriminative capacities, we design a multi-stage semantic attention with transformer (MAST) framework to learn the semantic representation of images using its own multi-stage mechanism, while employing a three-layer standard transformer decoder as an effective component for feature fusion.Experiments conducted on the VOC 2007 dataset show that MSAT achieves better experimental results and improves the performance of multi-label image classification tasks to some extent.
Optimization Analysis of University Music Education Mode Under the Background of Artificial Intelligence

In recent years, the active attempts and breakthrough progress of artificial intelligence (AI) in university music education have been amazing.In this regard, the purpose of this paper is to study the optimization of university music education models under the background of AI. this paper first describes the birth of AI and its evolution and development in music education.Then, this paper uses questionnaire survey methods to understand undergraduate' understanding, likes and cognition of college music education models, and obtains a true and reliable basis, so as to more truly understand the necessity of combining AI and music education.Based on the results of investigation and research, this paper uses AI technology to optimize the university music education model.this paper integrates AI technology into music education reasonably and effectively, and uses the powerful intelligence of AI to transform music education into interesting and passionate education, which can guide undergraduate to actively participate in learning.Finally, this paper compares the optimized university music education model with the traditional music education model.Experimental results show that the optimized college music education model has been recognized and loved by more undergraduate, and students' love for music has increased by about 15%, which has played an important role in improving students' enthusiasm for learning music, and is an optimization study of university music education models.Provide an important reference.
English Machine Translation System Based on Semantic Selection and Information Features

The development of machine translation system has not yet fully realized automatic and high-quality, because human language is complex, and there are certain limitations in understanding language rules.Therefore, in the research of machine translation, it not only is limited to the syntactic and semantic analysis of a single sentence, but also requires an in-depth analysis of the internal laws of the language, including: sentence groups, paragraphs, chapters, and contextual information inherent in genres.The English machine translation system based on semantic selection and information features conducts in-depth analysis of the source language sentences according to the semantic unit library, and completes the translation in combination with the target language sentences.A multi-language machine translation system based on semantic language needs a unified multi-natural language machine translation software and a multilanguage unified semantic unit library (the basis for the establishment of the machine translation system).
An English Test Paper Grouping Method Based on Improved Gray Wolf Algorithm

Aiming at the problems of slow speed, low success rate and uncontrollable quality of traditional English test paper formation method, an automatic test paper formation method based on improved Gray Wolf algorithm was proposed.Firstly, the mathematical model of automatic test paper formation is analyzed.Secondly, the traditional gray Wolf algorithm is improved to improve the convergence speed of the algorithm.Finally, the improved grey Wolf algorithm is applied to the English test paper composition problem.The experimental results show that the improved algorithm has higher success rate and better quality of test paper.
The Construction of Business English Blended Teaching Mode from the Perspective of Cloud Teaching-Research Community and Production-oriented Approach

The construction of Business English online and offline blended teaching mode is directly related to the cultivation of English teachers' professional knowledge, cloud teaching technology and teaching evaluation ability, which is of great significance to the cultivation of English input and output ability for Business English majors.Production-oriented Approach (abbreviated as POA) is an innovative, representative and practical theoretical system that has continuously developed and promoted the reform of College English teaching in China in the past decade.Based on this, this paper starts with POA and Cloud Teaching-Research Community (abbreviated as CTRC), as well as teacher's experiences in the National Foreign Language Teaching and Research Press (abbreviated as FLTRP) Teaching Competition and the Provincial Foreign Language Ideological and Political Course Teaching Competition, which explores the blended teaching mode of Business English, and proposes the ways to optimize and reconstruct the blended teaching mode of Business English.
Cloud Education Model and Evaluation Based on AHP and BP Neural Network

Study the current state of cloud technology use in teaching, and train the cloud teaching mode and operational process.To judge whether the cloud mode of instruction has achieved the desired effect, the method of combining the analytical hierarchy process with the BP neural network is selected.A system for evaluating teaching is being explored for cloudbased teaching through theoretical research.The AHP method is used to select three primary indicators and twelve secondary indicators respectively.The judgment matrix method is used to determine the weight of each evaluation index, and the BP neural network principle is used to train the evaluation data, Verify the scientificity and rationality of the evaluation system, which can be applied to other courses in the future in combination with the characteristics of specific courses.
The Realization of Intelligent Remote Multimedia Physical Education Teaching System

In the traditional physical education teaching methods need teachers and students two-way interaction, in this era of intelligent life everywhere, teaching has also become novel, remote multimedia teaching extended to physical education, greatly strengthening the teaching methods and teaching concepts, but also widely praised by teachers and students, for teachers and students to bring a convenient teaching method.The Advanced system relies on the CAI computer-aided teaching program to run, and the distance teaching is intelligent, advanced and mature in the current teaching practice, stability and convenience.
Predicting Invasive Ductal Carcinoma by Using Deep Convolutional Neural Network

Due to the nature of Breast Cancer, it is challenging to make correct diagnosis based on histopathology images.And it is crucial to make early diagnosis for a complete cure.In this paper, a Neural Network algorithm was proposed to train on sets of breast histopathology images.Based on Convolutional Neural Network (CNN), it can be realized to detect and extract spatial features of images.A deep Convolutional Neural Network architecture similar to VGGNet is proposed for this study, which contains 6 3×3 layers of depth-wise Convolutional layers, 3 pooling layers and 1 fully connected layer.The proposed model was trained using Kaggle dataset of breast histopathology images, 50 epochs, with batch size of 250.The model utilizes Adagrad optimizer with learning rate of 1×10-2, decay equal to value (i.e.learning rate/number of epochs), and Binary Crossentropy as loss function.The proposed model results in 91.28% accuracy and 0.22 loss.
Automatic Correction Method of ERP Data Entry Errors Based on Big Data

ERP (Enterprise Resource Planning) refers to the use of advanced management ideas and methods and standardized processes and data on the basis of information technology to integrate the resources owned by the enterprise, and finally achieve the purpose of optimal allocation of enterprise resources and business process optimization.ERP can improve the information level and resource allocation efficiency of enterprises.It is a management means that most modern enterprises will adopt.In order to further improve the accuracy and timeliness of enterprise resource management data entry, today's enterprises are considering introducing big data technology into ERP to realize the automatic correction of ERP data entry errors.Starting from the analysis of the current development status of ERP, this paper finds the shortcomings of the ERP system adopted in the enterprise, then puts forward the basic framework and specific application methods of using big data technology to transform the ERP system, and finally puts forward some suggestions on the operation and maintenance of the enterprise ERP system, hoping to improve the efficiency of enterprise resource management, Reduce the error rate of enterprise management data entry.
Bidirectional Transformer for Android Based Image Icon Text Generation

The image caption task is an important manifestation of the fusion of computer vision and natural language processing development in deep learning.The Image Caption task, which is an advanced kind of image comprehension, can effectively grasp image information and produce accurate and concise natural language descriptions to users.It has gotten a lot of attention in the subject of art intelligence, and it has a lot of uses in the field of assisting visually impaired guides and human-computer interaction.This research primarily presents a deep learning-based solution for completing the natural language generation task based on images and symbols in Android.The encoder-decoder framework is used as the core structure to help visually impaired persons interact with mobile phones.
Efficacy of Usage of Digital Game on Key Competencies among Prospective Chinese Language Teachers

As a new media, digital games are playing a more and more important role in intelligent education.However, few attempts have been made to investigate efficacy of usage of digital game on key competencies of students in the 21st century in higher education.The objective of the study was to determine efficacy of the usage of digital game on key competencies through new media literacy and critical thinking disposition.A cross-sectional survey conducted by convenience sampling, was adopted involving 159 prospective Chinese language teachers of Leshan Normal University in Southwest China.The research was based on frameworks of Jenkins et al.'s 12 new media literacy skills and Delphi consensus's 7 critical thinking disposition.Structured questionnaire was employed for data collection and one-way MANOVA and a series of one-way ANOVA, Post-Hoc Compare were operated for the data analysis.The findings of this study showed that usage of digital game have significant moderate efficacy on appropriation, inquisitiveness and significant small efficacy on performance, multitasking out of sub dimensions of new media literacy and critical thinking disposition.Accordingly, this study has made it clear in which aspects and to what extent digital games play an important role in key competencies among prospective Chinese language teachers.
Design of An Internationalized Intelligent Micro-credential Cloud Platform and Analysis of Operating Effectiveness

With the recurring global COVID-19 pandemic, colleges and universities in China are facing huge obstacles in engaging in international education.The original international students are also unable to enter and study normally due to the COVID-19 pandemic, and the enrollment of international students has been greatly affected as a result.Based on the above, this paper tries to build a platform applicable to international online teaching -Tiangong International Micro-credential Cloud Platform and two supplementary modules have been created to meet the needs of the offline smart classroom and the online international course resources, and explained the construction method and functions of the platform and auxiliary modules.An internationalized teaching management system, classroom teaching format, resource sharing and evaluation mechanism have been further developed for Tiangong International Micro-credential Cloud Platform.The platform has been applied in teaching, and this paper and the data analysis and summary of the effect produced by the platform in the process of teaching application.
Development of Interactive Teaching System for Preschool Education Classroom

With the advent of the Internet era, the rapid development of smart phones, ipads and other mobile handheld devices provides a suitable development platform for education.In the field of education, interactive teaching can enrich the teaching scene and enhance students' understanding of knowledge.Along with the progress of the society and the development of science and technology, human society has gradually entered the information era, with the computer as the core of multimedia technology is growing education a wave, gradually tends to digital, network and individualized teaching mode, preschool education way is also to the becoming an information based society to go forward, advanced education media and education mode for pre-school education brings new opportunity.This paper mainly aims at the current situation of interactive teaching system development in preschool education classroom, and makes its own opinions according to the current situation, the purpose is to speed up the open process of interactive teaching in preschool education classroom, so as to effectively promote the development of interactive learning system in preschool education classroom.
Teaching Reform Based on Correlation Analysis Algorithm

Taking the teaching data of the course "Artificial Intelligence Basic" as a sample, and IBM SPSS as a data analysis tool, through data collection, data extraction, data modelling, this paper uses the comparative analysis method to obtain valuable data analysis results, which can be applied to the teaching reform of the course, and finally achieve the purpose of fine teaching."Accurate teaching" is an important measure to improve teaching quality and learning effect in Colleges and universities.Using advanced mathematical analysis tools and scientific data analysis methods is the prerequisite and necessary process to achieve accurate teaching.
The Application of Online and Offline Hybrid Teaching Mode Based on Fanya Platfrom in English Translation Teaching

The emergence and development of information technology with the new scientific and technological revolution has changed people's work, life and learning at an astonishing rate in the process of human civilization.Under the background of information age, big data plays an increasingly important role in education.Online courses have gradually entered university campus with the new concepts and modes of teaching.English Translation teaching should also conform to the requirements of the times and develop towards informatization teaching.In order to explore a new way to reform curriculum teaching and design an informatization teaching of English Translation based on big data, this paper adopted ANOVA to analyse the students' using status of online learning platforms, put forward the blended teaching mode of English Translation teaching based on Fanya platform to cultivate college students' Chinese cultural confidence, which is of great significance for national cultural security and national spiritual independence in global cultural exchanges.The informatization teaching mode integrated English Translation course can combine traditional teaching methods with online course teaching to make full use of network resources and modern information technology, which can effectively improve the quality of curriculum teaching contributing to the development of English Translation teaching in the era of information technology.