Reviewerly/exHarmony huggingface dataset:
Teaching Reform and Practice of Electrical and Electronic Technology Courses Against the Background of Emerging Engineering Education

Emerging engineering education is the necessary road, strategic support and leading force for building a strong education country in China.Electrical and electronic technology course as a professional foundation course plays a key role in the realization of professional talents training objectives.In this paper, the reform is carried out in terms of modularization of teaching contents, modernization of teaching methods and diversification of teaching evaluation, focusing on the integration of curriculum ideological and political education, the implementation of online and offline hybrid teaching methods, application of simulation software, keeping the course contents up-to-date and integration with competitions and industries, etc.The comprehensive reform of the whole teaching process is carried out.Practices show that the reform has been recognized by students and has improved students' performance and the teaching level of the teaching team.
Design and Research of Online Education Data Platform Based on Hadoop

Online education is a convenient way to combine content dissemination and rapid learning with electronic products and Internet.Online education advantages include high content production efficiency, no time and space constraints, and study whenever or wherever you want.During COVID-19 pandemic, millions of students have switched to online learning, and online education platform has meet new development opportunities.This thesis specifically analyzes online education platform based on Hadoop through big data.Online education data platform includes four panels, such as access and consultation panel, user registration panel, user intention panel, and student attendance panel.Panel analysis results show that the number of registered users converted from intended customers, attrition rate and attendance of existing users.It helps us to accurately increase user number of online education platform.This provides reliable data support and important reference value for sustainable development of online education.
The State-of-the-art Technique for Determining the Identity and Uniqueness of Common Color Laser Printouts by Coded Dot Matrix Patterns

Recently, in forensic science studies, identification of the source of color laser printouts is one of the most challenging issues that hinder forensic document examiners. Although various methods for establishing the identity of the source of color laser printouts are currently available worldwide, none of those methods approaches an accuracy and precision of 100%. The coded dot matrix patterns are state-of-the-art prototypes of steganography based on the active technique. Upon tracking the coded dot matrix patterns of all investigated color laser printouts, the identity and uniqueness can be determined, respectively. In the current paper, nineteen variant brands of color laser printer machines were selected. The advanced security features embedded in their printouts have steganalysis and grouped them into two broad categories. A direct model of hyperspectral analysis integrated with video spectral comparator Regula® 4307 was applied. The complete identification of the investigated color laser printouts was achieved. The decisive degree of the results reached one hundred percent for the investigated color laser in this study. Moreover, the novel classification scheme of coded dot matrix patterns presents for completing the individual characteristics.
Analysis of Learning Effectiveness Based on Knowledge Graph

Based on the construction of the knowledge map of "Data Structure and Programming" course, the data of PTA platform, rain class data, MOOC and other platforms are integrated, and the comparative analysis is carried out according to the different granularity of knowledge points, trying to find out students' learning difficulties and blind spots, so as to provide more specific and effective help for students' learning.At the same time, it provides the basis for the adjustment of the follow-up curriculum exercises, the targeted adjustment of the textbook and the concrete implementation of the teaching work.
Evaluation Method of Vocational Undergraduate Practice Teaching Quality Based on Fractal Dimension

To improve the evaluation system of vocational undergraduate practical teaching and promote the sustainable development of practical education, an evaluation method of vocational undergraduate practical teaching quality based on fractal dimension is studied.This paper extracts the multi-dimensional evaluation index of vocational undergraduate practice teaching quality, applies the fractal dimension theory, constructs the sample matrix of the evaluation index of practice teaching quality, analyzes the correlation between evaluation indexes, determines the quantitative weight of fractal dimension, and realizes the evaluation of vocational undergraduate practice teaching quality.The simulation test results verify that for five random data samples, the error values of the evaluation results of this method are all lower than the set error target of 0.02.The average error value is 0.0056, which is accurate and stable, indicating that the application of fractal dimension theory improves the comprehensiveness and objectivity of the evaluation of practical teaching quality, and optimizes the teaching evaluation system.It provides an effective reference.
Analysis of Cognitive Factors Affecting Information Retrieval Behavior of University Library Users Based on RBF Network

The information retrieval behavior of library users is affected by many factors.Analysis of these factors will help libraries to formulate high-quality information service strategies.Sample data is obtained by questionnaire survey, and RBF neural network model is used to learn and analyze sample data in this paper.A method for calculating the importance of input components based on RBF neural network is proposed.The influence factors of university library users' information retrieval behavior are studied from a cognitive perspective.The influence results of relevant cognitive factors on information retrieval behavior are discussed.According to these cognitive factors, university libraries can take corresponding information service measures and improve the information retrieval efficiency of library users.
Waste Recovery and Sustainable Development. A Case Study of Material Development from Used Tires in Africa

This paper outlines a mechanical transformation process for rubber recycling, demonstrating the development of a new material from used tires.With the crumbs obtained using a crusher-compactor, a novel material for the manufacture of O-rings has been developed, with properties close to those found on the market.The process includes an experimental methodology of a sulfur vulcanization system choice and the quantification of ingredients, as well as the experimental determination of cure parameters.Mechanical tests on the samples completed the work by providing the mechanical characteristics of both unaged and aged (thermo-oxidative ageing) novel material.This process has a high potential for sustainable development and industrialization, making it a valuable contribution to the recycling of rubber in African developing countries.
Design and Implementation of College English Personalized Teaching Platform Under the Background of Internet Plus

With the further development of the data age, the trade and cultural exchanges between countries have become closer and closer, and the state has put forward new requirements for foreign language professionals.In order to ensure the quality of training foreign language talents, this paper takes computer as the development hardware, combines Web technology with multimedia technology, and builds a personalized college English teaching platform under the background of internet plus.The platform is developed with Windows 10.0 as the operating system, B/S architecture as the development framework of the platform, and C# as the programming language.With the layered advantages of MVC, each part of the content is deployed in layers, and the system functions of the teaching platform are refined to improve the running efficiency of the platform.In the evaluation platform, the qualitative and quantitative AHP analytic hierarchy process is used to calculate, which provides a more accurate evaluation guarantee for cultivating high-quality foreign language talents.
Machine Learning Based Analysis of the Curriculum Standards and Textbooks of Middle School Biology Teaching: Case of “Curriculum Ideological and Political”

Taking the course of biology curriculum standard and textbook analysis in middle school as an example, this paper introduces the example of introducing the dialectical relationship principle of practice and cognition into the teaching process of the first and second chapters of this course.This paper also aims to introduce similar ideological and political elements into the teaching of biology courses.This paper proposed a research method fused with machine learning.Students' feedback analysis has been performed using the machine learning classifier.Performance of the proposed method is analyzed from confusion matrix measures of Random Forest (RF) model.A detailed qualitative analysis of chapters 1 & 2 from biology textbooks has been presented with several advantages of the curriculum standards and textbook materials.The proposed RF model show 75% and 66.66% accuracy and precision, respectively.The proposed application of RF model is better than the state of the art proposed approaches.The experimental results suggest that the applications of machine learning with the teaching of biology textbooks, art of teaching and feedback from students may be undertaken in future works.
Construction and Feedback Research on Spoken English Blended Learning Mode Based on E-Learning Platforms and SPSSAU Data Analysis

E-learning platforms allow learners to use computers, mobile phones, tablets, and other handheld tools to study online.Tencent online homework platform, Wisdom Tree online learning platform and WJX questionnaire platform are widely used by Chinese teachers in recent years.But few studies integrated these e-learning platforms together to conduct spoken English blended learning.This study aims to construct a spoken English blended learning mode based on the e-learning platforms as well as research on learners' feedback.Data collected from a survey among undergraduate students were analyzed by SPSSAU system.The results of this study indicated that the majority of students hold positive attitude towards this blended learning mode.One-way anova showed no significant gender difference on its improvement of learners' English oracy.Pearson correlation analysis indicated that increasing the frequency of output training was beneficial to improve learners' oral fluency, accuracy as well as their attention and learning efficiency in class.Group work and individual presentation were conducive to enhancing learners' participation enthusiasm according to linear regression analysis, whereas they would not affect learners' oral fluency or accuracy improvement.
Dataset of Linkability Networks of Ethereum Accounts Involved in NFT Trading of Top 15 NFT Collections

In this paper, we present subgraphs of Ethereum wallets involved in NFT trades of the top 15 ERC721 NFT collections. To obtain the subgraphs, we have extracted the Ethereum transaction graph from a live Ethereum node and filtered out exchanges, mining pools, and smart contracts. For each of the selected collections, we identified the set of accounts involved in NFT trading, which we used to perform a breadth-first search in the Ethereum transaction graph to obtain a subgraph. These subgraphs can offer insight into the linkability of accounts participating in NFT trading on the Ethereum blockchain.
Few-shot and meta-learning methods for image understanding: a survey

Abstract State-of-the-art deep learning systems (e.g., ImageNet image classification) typically require very large training sets to achieve high accuracies. Therefore, one of the grand challenges is called few-shot learning where only a few training samples are required for good performance. In this survey, we illuminate one of the key paradigms in few-shot learning called meta-learning. These meta-learning methods, by simulating the tasks which will be presented at inference through episodic training, can effectively employ previous prior knowledge to guide the learning of new tasks. In this paper, we provide a comprehensive overview and key insights into the meta-learning approaches and categorize them into three branches according to their technical characteristics, namely metric-based, model-based and optimization-based meta-learning. Due to the major importance of the evaluation process, we also present an overview of current widely used benchmarks, as well as performances of recent meta-learning methods on these datasets. Based on over 200 papers in this survey, we conclude with the major challenges and future directions of few-shot learning and meta-learning.
The Influence of Online Media on College Students’ Self-identity in Mobile Learning Environment

With the maturity of information technology, the popularity of the network and the reduction of the cost of wireless equipment, mobile learning has attracted great attention in recent years and started to be popularized rapidly.Mobile learning based on recommendation algorithm has become the most convenient and most common way of learning for college students and even the whole society.College students are in the stage of mental growth, which is also the most important period of self-identity.The transition from high school to college and the network information explosion intervention, under the influence of network media gradually formed a new self-cognition.
Intelligent Identification and Prediction Mineral Resources Deposit Based on Deep Learning

In recent years, the intelligent identification and prediction of ore deposits based on deep learning algorithm and image processing technology has gradually become one of the main research frontiers in the field of geological and metallogenic prediction. However, this method also has many problems that need to be solved. For example: (1) There are very few trainable image samples containing mineral point labels; (2) the geological image features are small and irregular, and the image similarity is high; (3) it is difficult to calculate the influence of different geological prospecting factors on ore mineralization. Based on this, this paper constructs a deep learning network model multiscale feature attention framework (MFAF) based on geoimage data. The results show that the MFCA-Net module in the MFAF model can solve the problem of scarce mine label images to a certain extent. In addition, the channel attention mechanism SE-Net module can quantify the difference in influence of different source factors on mineralization. The prediction map is obtained by applying the MFAF model in the study of deposit identification and prediction in the research area of the southern section of the Qin-hang metallogenic belt. The experimental results show that the areas numbered 5, 9, 16, 28, 34, 41, 50, 72, 74, 75, 80, 97, 101, 124, and 130 have great metallogenic potential and this method would be a promising tool for metallogenic prediction. A large number of experimental results show that this method has obvious advantages over other state-of-the-art methods in the prediction of prospecting target areas, and the prediction effect in the samples with mines is greatly improved. The multi-scale feature fusion and attention mechanism MFAF in this paper can provide a new way of thinking for geologists in mineral exploration. The research of this paper also provides resource guarantees and technical support for the sustainable exploitation of mineral resources and the sustainable growth of society and economy.
Research on the Application of VR Technology in Taekwondo Teaching

As VR (virtual reality) technology gets better and better, VR reality course teaching realizes the transformation of teaching scenes, cultivates students' interests, and effectively improves the teaching effect.Under the background of the extensive promotion of VR, virtual reality technology has been applied in physical education teaching and training.The "immersive" taekwondo teaching mode under the application of virtual reality has broken the existing teaching forms and teaching methods.Through the integration of VR technology into taekwondo teaching, it can help to complete difficult demonstration movements and clearly express complex technical points, which can better optimize the teaching effect.This study applies VR technology to Taekwondo teaching, combines the characteristics of VR technology, analyzes the industry pain points of VR applied to Taekwondo teaching, and designs a 3D interactive system of VR technology applied to Taekwondo teaching.
Internet College Education Based on Artificial Intelligence and Social Computing

Internet education in colleges and universities is the inevitable result of the high popularization of college students' network use, and it is an important strategy for colleges and universities to actively adapt to the networked education environment.With the rapid development of artificial intelligence, traditional Internet education technology is no longer suitable for the increasingly large information scale of the modern education system, and new computer technologies need to be assisted in the completion of Internet education.To solve this challenge, we propose a novel internet education platform based on artificial intelligence and social computing, which can be utilized to mine students' interaction information and predict their future evolutions.In particular, we introduce the state-of-the-art graph learning models as the pre-training model in our platform.Such models can generate node embeddings in the student social graph, and these embeddings usually contain important information for future prediction.In the experiments, we demonstrate the models' performance and effectiveness.In addition, we also discuss what datasets can be used in our platform pre-training.
A Fuzzy Comprehensive Model to Evaluate PAD Class Teaching Quality Quantitatively and Qualitatively

PAD Class is carried out in the form of teacher's presentation and students' discussions, but the way to evaluate its teaching quality is the same as lecturing class currently.To address this problem, the paper provides a 2-level fuzzy comprehensive evaluation model for PAD Class specially.It takes teaching content, teaching organization, teaching literacy and teaching result as 1-level indexes, and 17 2-level indexes such as necessity, time allotment etc.It quantifies some unclear indexes to values by membership functions and then gets a qualitative conclusion according to the value.In this model the evaluation indexes focus on the teacher's ability to make discuss efficiently, and it lets fuzzy factors more accurate by quantifying.Through practical applications, the teachers' recognition of the evaluation conclusions reaches 93.3%, which is 13.3% higher than that in previous evaluation way.
Research on the Teaching Mode of Computer-Assisted Technology in English Classrooms of Application-Oriented Universities

Information technology plays an irreplaceable role in the development of education.To a great extent, the advent of the computer-assisted language learning model subverts the traditional classroom mode characterized by "teaching by teachers while listening by students", thereby effectively improving the disadvantages exposed by the traditional teaching mode.On the same note, English teaching in application-oriented universities in China has consistently followed the trend of the times, taking English as a basic subject to cultivate compound, innovative, and practical talents.Additionally, during the actual teaching process, with the basic goal of improving students' practical application ability, English teaching in application-oriented universities in China tends to fully arouse students' learning interest and effectively improve teaching quality and efficiency.Within this context, to improve the talent training quality of application-oriented universities, this paper first focuses on the English classroom teaching mode under the background of computer-assisted technology and then presents different English classroom modes by setting up an experimental group and a control group, tracking the English learning situation of students from non-English majors.Secondly, based on applying SPSS software to analyze the corresponding experimental results, this paper further explains the advantages of using computer-assisted software to conduct interactive teaching mode compared with traditional teaching mode.Regarding the research significance, this research intends to improve the integration of computer-assisted technology in English classrooms and explore an interactive teaching mode that can combine technology with classrooms, thus providing internal impetus for the sustainable development of application-oriented universities.
Research on Scratch Curriculum Ideology and Politics from the Perspective of STEAM and Maker

Curriculum Ideology and Politics is a new requirement put forward by the party and the state in China, which is of great significance for cultivating high-quality talents with correct values.With the development of information technology, STEAM and Maker education have become hot spots.Because STEAM and Maker have a lot in common, they can integrate.At present, there are problems in the teaching of Curriculum Ideology and Politics, such as fixed content and insufficient flexibility.This paper aims to explore a mode of Curriculum Ideology and Politics under the concept of STEAM and maker education to solve these problems.Taking the 'Scratch' course in primary schools as an example, Chongqing red elements are incorporated into each teaching project to promote the realization of 'three perfections' education.
Construction and Practice of Smart English Classroom Based on the Internet of Things in China

With the popularity of Internet of Things (IoT), rapid educational information, digitization, intelligence and ecology are affecting all aspects of teaching and learning.The outbreak of the epidemic in early 2020 has made China's online education show explosive growth, accelerated the formulation and implementation of online education security policies, and greatly improved the ability of teachers, students and teaching managers to apply information technology.The paper explores the theoretical foundations of Smart English Classroom Model based on IoT in terms of the teaching planing, process, production-oriented approach assessment and explains the application of those aspects by collecting and tracking the students' electronic study data in the practice of a particular course of American Literature from teaching goals, specific unit designs, ideological and political elements and teachers and students' feedback and comments.From the data analysis it can be seen that the American Literature course can cultivate the English independent speculative ability, interaction and communication, autonomous and mobile study ability of Chinese college undergraduates, which is of practical significance to the development of teaching theory and practice, to the reform of English teaching, to stimulate students' discourse right and identity consciousness, to improve their creativity and imagination to better meet the requirements and challenges of the new social era of transition and globalization.The study intends to give guidance for instructors and researchers in higher education to grasp the intelligence or digital educational development and utilize smart classroom empowered by intelligent technology to update teaching practice.