Reviewerly/exHarmony huggingface dataset:
Development of Automatic Evaluation System for Preschool Children's Speech Level Based on Speech Technology

Based on speech technology, combined with FFmpeg application, the development and construction of automatic evaluation system for preschool children's speech level is completed in Java Web application development system.In view of the shortcomings of the current standardized tools for evaluating preschool children's speech level, such as poor systematicness and large errors, the system will complete the real-time transcription of preschool children's speech and audio content by the speech transcription engine under the framework of deep full sequence convolutional neural network, and then complete the evaluation of children's language ability through quantitative indicators or manual analysis.This helps doctors or children's speech therapists to improve their mastery of preschool children's speech level by analyzing real and natural children's language samples, and combines the evaluation results of this language sample with the evaluation results of standardized tools to form a brand-new and multi-angle comprehensive evaluation system.It is not only helpful to have a more comprehensive understanding of children's language development, but also to find an appropriate treatment plan for preschool children with language disorders and promote their healthy growth.
A Meta-analysis based Study of the Factors Influencing Students' Engagement in Classroom Learning

To address the differences in current research on factors influencing student engagement in classroom learning, a combination of qualitative and quantitative meta-analysis was used to integrate a total of 43 high-quality empirical and relevant international literature that met the research criteria, and a total of 13 factors were found to influence student engagement in learning activities, such as teacher-student relationships, emotional factors, and student learning and thinking skills, all of which were significantly related.The analysis of the moderating variables also revealed significant differences between basic education and higher education in terms of personality traits, thinking skills and learning background on student engagement.
Bitcoin Trading using LSTM

Bitcoin is a high-risk and high-yield investment, and in recent years, more and more investors have begun to pay attention to Bitcoin, but its riskiness has deterred many.However, the data over the past few years has continued to show that Bitcoin is exceptionally profitable, and holding Bitcoin for a long time is an investment option.This paper analyzes how to use Bitcoin and gold for venture capital and uses LSTM neural network to demonstrate its capability in trading.Furthermore, this paper delineates the novel strategy making combined with LSTM and a traditional technical indicator which yield more winning rate.
Design and Research of Economics Online Learning Platform Based on Java Language Environment

Based on the Java language development environment, this paper takes Sakai CLE version 2.8.1 as the basic framework, selects appropriate functional components and related data API interfaces, and completes the construction of online learning platform of economics network with a feasible secondary development design form.With the help of the application advantages of network information technology, aiming at the difficulties and shortcomings in the current teaching process of economics courses in colleges and universities, this paper puts forward systematic and comprehensive solutions from the aspects of teaching contents, teaching forms, interactive communication and assessment.The construction of the platform not only conforms to the learning habits of contemporary college students, stimulates students' learning autonomy, but also effectively assists teachers to complete daily teaching tasks and improve teaching efficiency.For colleges and universities, the development and application of online learning platform is in line with the development requirements of the current "Internet + education" era, and it is an escort for cultivating economic talents for building a socialist modernization power.
Design and Construction of Business English "Double-qualified" Smart Classroom Learning Platform Based on Web Technology

With the development of social economy, more and more foreign enterprises have entered the domestic market, and the demand for "applied" business English talents is increasing.In order to meet this demand, colleges and universities have set up business English majors.Due to the particularity of this course, a relatively complete teaching system has not yet been formed.At present, this course is faced with difficulties such as the lack of close combination of theoretical knowledge and practice, the lack of professional teachers, and the imperfect practice platform.In order to improve the difficulties in business English teaching, this paper designs and develops a business English smart learning platform based on Web technology, Java language and big data Hadoop cluster tools.This platform is based on the smart classroom, using the platform to manage and control the intelligent equipment in the classroom, so that excellent "double-qualified" teachers with rich business practice experience can operate the platform and provide students with learning and practice opportunities.It helps schools to improve the dilemma of business English teaching and establish a relatively perfect business English teaching system, so that the business English major can develop healthily and continuously.
Construction of College Martial Arts Online Education Application Platform Based on JSP Technology

In the Java language environment, JSP technology combined with SSM framework is used to complete the construction of online education application platform of college martial arts.With the help of the application advantages of network information technology, aiming at the difficulties faced by the current college martial arts education and teaching process, this paper innovatively introduces online teaching into daily teaching, and puts forward practical and comprehensive solutions from the aspects of teaching content, teaching form, assessment and learning atmosphere.The application of the platform can not only meet the requirements of the content and standardization of martial arts education, but also further strengthen the talent cultivation concept of martial arts education in colleges and universities, and further improve the construction of professional teaching system while practically improving the teaching effect, thus making a new attempt to promote the implementation of the information education reform process in colleges and universities.
Research on the Development Technology of B-learning System Based on Web3.0

With the continuous promotion of educational informatization, blended learning, which combines the advantages of traditional teaching and learning methods with the advantages of online learning, has become the core issue of education reform in the era of Web3.0.Based on the theory of constructivism and humanism, guided by the basic idea of Blearning, this paper constructs a blended learning support service system from five dimensions of subject-object support, community support, resource support, collaborative support and evaluation support according to the thought and technology of Web3.0.At the same time, according to the technical architecture, it analyzes the development technology for realizing B-Learning3.0system, including PHP application development technology, Web database technology, x API monitoring technology, personalized recommendation technology, and Web3.0 technology, etc. and completes the basic work from system construction to technology implementation.In addition, we conducted two case studies: (1) Based on the Gradient Boosting Decision Tree (GBDT) model and two different educational data sets, the teaching quality is evaluated with the accuracy of 0.891 and 0.879 respectively.The experimental results show that our proposed model outperforms all the benchmark models; (2) To recommend a more accurate courses to students, a course recommendation algorithm is designed based on collaborative filtering, and achieved more than 80% accuracy.
Comparison of Cutting Edge Convolutional Neural Network for Breast Cancer Histopathology Image Diagnosis

Female breast cancer, especially the invasive ductal carcinoma, is a very common type of cancer.When breast cancer is diagnosed and treated at an early stage, patients can achieve a higher survival rate.In recent years, neural networks have shown their potential in medical fields.Therefore, this work focused on applying three state-of-the-art convolutional neural networks (CNNs), namely ResNet50V2, InceptionV3 and VGG16 to diagnosing breast cancer from histopathology images to verify whether CNNs can be an effective tool in this case.The three architectures were trained with an original dataset of breast cancer histopathology images.After the image pre-processing and the hyperparameter tuning, the evaluation and comparison of the networks' performance were performed.They were evaluated through several statistical analysis based on accuracy, recall, precision, F1-score and training time.The experimental results showed that InceptionV3 obtained the best performance with the accuracy of 87.12% and F1-score of 86.99.ResNet50V2 achieved a close performance with a 74% training time compared with InceptionV3.The result proved that the state-of-the-art CNNs can be considered as a supportive tool that can help diagnosing breast cancers.
Design and Implementation of College English Task-driven Network Teaching Platform Based on web Technology

English is a tool language with high versatility, so colleges and universities have set college English as a basic public required course.However, at present, there are many problems in English teaching in colleges and universities, which not only hinder the development of English teaching, but also affect the effect of students' learning English.This paper summarizes the present situation and problems of college English teaching, and uses task-driven teaching to provide methods, directions and theoretical support for solving the problems in English teaching.Combining theoretical research with web technology, this paper develops an English task-driven teaching platform, which is based on Python technology and Django framework, and is designed by using Nginx deployment server.While improving the quality and level of English teaching and expanding teaching methods, it can stimulate students' interest in learning, so as to improve college students' English autonomous learning ability.
Depth Estimation from a Single Image Based on Gradient and Wavelet Analysis

Recovering the depth information from a single image is a fundamental problem in computer vision field and has broad application prospects.To solve the problem that the accuracy of the depth recovered from a single image is not high enough, especially when there are several edges very close or intersecting, or when the edge is weak, a novel method to depth measurement is proposed in this article.Four steps are included in our method.Firstly, we obtain depth value of object edge point indirectly by measuring the defocusing degree of the object edge point.The gradient information of the 8 directions of edge point are employed during the process of measuring.Secondly, wavelet analysis is used to judge whether the measured depth value needs to be corrected or not.If necessary, it is corrected according to our formula.A sparse depth map is got when the depth values of all of edge points are measured and are corrected if necessary.Thirdly, the joint bilateral filter is employed to refine the sparse depth map.Lastly, the sparse depth map is extended to a dense depth map by the method of Matting Laplacian.The results of experiments show our method is effective.
Factor Analysis Algorithm and Precision Teaching

After the talent training plan is determined, how to arrange the teaching plan, teaching plan and teaching sequence of various courses in different periods of time is a very complex mathematical programming problem of "multifactor and multi-objective".This paper describes how to use "factor analysis", "principal component analysis", and other algorithms, use IBM SPSS as the data analysis tool, and take the actual teaching data as the sample to conduct a comprehensive quantitative analysis on the students' grades of various subjects at the end of the semester, and take this as the basis to guide the process of teaching work improvement.This kind of teaching research based on advanced computing tools, scientific quantification and accurate data is a necessary measure for digitization and standardization of the current teaching reform.In this paper, the basic conditions of using a factor analysis algorithm, the process of establishing a mathematical model, and the detailed operation steps of using IBM SPSS as a data analysis tool to solve problems are explained first, and then the calculation results are analyzed.And, the characteristics of the algorithm, the practical application, and even the taboo of the application are introduced.Finally, it is also mentioned that different algorithms have different characteristics and different applications.Only by flexibly applying various algorithms to deal with different problems can we improve work efficiency.This is our basic working principle
Application for Breast Cancer Detection Based on Convolutional Neural Network

Breast cancer starts in breast cells when they grow out of control.It is life-threatening and is common among women.Diagnosis of breast cancer is a challenging task as well as time consuming.In this paper, a new idea for breast cancer diagnosis is discussed.Namely, a convolutional neural network (CNN) method is proposed to assist classification of breast cancer.Two different models are discussed in this paper.Testing results is done using performance metric for all models.On top of the models that classify breast cancer, a practical application is also discussed and implemented that utilized the proposed model.It is not only capable of breast cancer diagnosis but delivers the results flexibly with an AI chatbot.The proposed model performs well with testing accuracy of 98%.The application is also well tested that can perform automated breast cancer diagnosis quickly to reduce the work of the clinic significantly.
How Researchers Could Obtain Quick and Cheap User Feedback on their Algorithms Without Having to Operate their Own Recommender System

The majority of recommendation algorithms are evaluated on the basis of historic benchmark datasets. Evaluation on historic benchmark datasets is quick and cheap to conduct, yet excludes the viewpoint of users who actually consume recommendations. User feedback is seldom collected, since it requires access to an operational recommender system. Establishing and maintaining an operational recommender system imposes a timely and financial burden that a majority of researchers cannot shoulder. We aim to reduce this burden in order to promote widespread user-centric evaluations of recommendation algorithms, in particular for novice researchers in the field. We present work in progress on an evaluation tool that implements a novel paradigm that enables user-centric evaluations of recommendation algorithms without access to an operational recommender system. Finally, we sketch the experiments we plan to conduct with the help of the evaluation tool.
Construction of Interactive Teaching Platform for University Clarinet Performance Based on Streaming Media Technology

Aiming at the single teaching method in the existing clarinet teaching, this system will use streaming media FFmpeg tool and JAVAweb technology to construct a clarinet teaching platform based on streaming media.This system can help teachers and students to carry out teaching activities of synchronous clarinet performance through the mode of live classroom, and use the barrage function to complete the interaction between teachers and students.With the help of streaming media technology, this system can make clarinet teaching more intuitive, interesting and vivid than traditional teaching methods.Because it is not limited by time and space, students can participate in it more flexibly, so as to realize the interactive teaching between teachers and students.The development of streaming media clarinet interactive teaching system will contribute to inheriting and developing the operation skills of clarinet instruments, enriching China's artistic and cultural forms, and continuously developing clarinet music.
Measuring Strain Distribution Around Inclusions and Matrix Interface Using Global Digital Image Correlation

A method for evaluating displacement and strain distributions around inclusion and matrix interface is studied in this chapter. Global digital image correlation (global DIC) is used for this method. Global DIC can obtain the displacement in inclusions and matrix parts separately. Strains are also computed using a mesh. The results show that strain distributions of rapid change around interface can be obtained by global DIC. Then, by comparing the measurement results of local DIC and global DIC, it is found that global DIC has the validity to measure strain around the interface.
Affine Monads and Lazy Structures for Bayesian Programming

We show that streams and lazy data structures are a natural idiom for programming with infinite-dimensional Bayesian methods such as Poisson processes, Gaussian processes, jump processes, Dirichlet processes, and Beta processes. The crucial semantic idea, inspired by developments in synthetic probability theory, is to work with two separate monads: an affine monad of probability, which supports laziness, and a commutative, non-affine monad of measures, which does not. (Affine means that $T(1)\cong 1$.) We show that the separation is important from a decidability perspective, and that the recent model of quasi-Borel spaces supports these two monads. To perform Bayesian inference with these examples, we introduce new inference methods that are specially adapted to laziness; they are proven correct by reference to the Metropolis-Hastings-Green method. Our theoretical development is implemented as a Haskell library, LazyPPL.
Machine Learning Algorithms for Natural Language Processing Tasks: A Case of COVID-19 Twitter data (Thailand)

This paper presents the use of natural language processing for the problem of information extraction and sentiment analysis. The dataset is from Twitter that has the information of people mentioning about COVID- 19, this study has two tasks: (i) classification approach for information extraction task and (ii) deep learning approach for sentiment analysis task. In information extraction task, the data was gathered from twitter that related to COVID-19 information, and the sequence labelling method applied to classify text before giving it to classification algorithms (K-NN, Naïve Bayes, Decision Tree, Random Forest, and SVM). In sentiment analysis task, data was classified by convert the word into index and using word embedding, then to process deep learning algorithm (Bi-directional GRU). The accuracy of two tasks are 98% and 79% respectively.
Parametrized Modal Logic II: The Unidimensional Case

We consider a syntax and semantics of modal logics based on parametrized modal connectives with $$\exists \forall $$ -satisfaction definitions, we axiomatically introduce different parametrized modal logics, we prove their completeness with respect to appropriate classes of parametrized relational structures and we show the decidability of some related satisfiability problems.
The Effect of Achievement Motivation, Self-Efficacy, and Self-Regulated Learning Strategies on Creative Leadership of College Students

This study was conducted to confirm the relevance of achievement motivation, self-efficacy, and self-regulated learning strategies related to creative leadership of college students, and to identify factors affecting creative leadership. The research design was a descriptive correlation research study targeting students at M university located in Jeollanam-do. Frequency and percentage, t-test, Pearson’s correlation coefficient, and multiple regression analysis were performed. As a result of the study, as a result of examining the correlation between achievement motivation, self-efficacy, self-regulated learning strategy, and creative leadership, creative leadership showed achievement motivation (r=.69, p<.001), self-efficacy (r=.77, p<.001) and self-regulated learning strategies (r=.80, p<.001), and self-regulated learning strategies, achievement motivation (r=.69, p<.001) and self-efficacy (r=.73, p<.001), self-efficacy was found to have a statistically significant positive correlation with achievement motivation (r=.74, p<.001). Factors influencing creative leadership were self-regulated learning strategy (β=.47, p= <.001), selfefficacy (β=.41, p= <.001), achievement motivation (β=.13, p= .04), and the self-regulated learning strategy was the most influential factor.
Design of Helicopter Avionics Maintenance Training System Based on Intelligent Teaching System

In view of the shortcomings of the traditional avionics maintenance training method for helicopters, the importance of designing a intelligence teaching system (ITS) for helicopter avionics maintenance training is proposed.The functional requirements of the ITS are analyzed, and the ITS for helicopter avionics maintenance training is designed and developed based on artificial intelligence technologies such as virtual human, intelligent voice, knowledge mapping, virtual reality and helicopter learning.The ITS solves the real problem of restricted helicopter avionics maintenance training equipment and sites, improves training efficiency and reduces training costs, and provides reference for the design of teaching system and construction of teaching environment in the context of current intelligent education.
The implementation behavioristic learning principles in santri's training of public speaking abilities through muhadharah's activities at PP Banin Banat Al-Mubtadien Kediri

The aim of this study was to the implementation behavioristic learning principles in santri's training of public speaking abilities through muhadharah's activities at PP Banin-Banat Al-Mubtadien Kediri. This research is descriptive qualitative research using interview, observation, and documentation methods. This study uses a purposive sampling technique to obtain sufficient in-depth data about the focus of the study. The data analysis technique used was the triangulation of the three research techniques used. This study's results indicate the application of behavioristic learning principles in practicing public speaking skills of students through muhadharah activities at PP Banin-Banat Al-Mubtadien Kediri, which can be seen in each process where the preparation, implementation, and evaluation use different learning principles for each process.
Analysis of the Development Trend of E-Commerce Based on Network Intelligence Technology: The Case of Jing Dong (JD)

With the continuous development of e-commerce, how to develop ecommerce in the future is the direction for enterprises to consider.This paper takes Jingdong (JD) e-commerce company as an example, and analyzes the development trend of this e-commerce company based on network intelligence technology: analyzes the current situation of JD.com, collects JD's annual balance sheet and profit and loss statement through network intelligence technology, and calculates its relevant financial ratios.Comparative analysis of financial ratios enables us to intuitively understand the economic status of assets, liabilities and shareholders' equity, and use computer technology to conduct Excel modeling analysis to visually view the company's financial trends, providing information for external investors, suppliers, Distributors and other stakeholders provide intuitive data analysis.