Reviewerly/exHarmony huggingface dataset:
Design of Chinese pronunciation homework applying adaptive learning concept in the online classes

In Chinese language learning, there are many difficulties related to pronunciation. In classroom instruction, the teacher can observe the pronunciation problems in detail and tell the correct pronunciation method in the face-to-face way. However, in the online classes, it is difficult for learners to observe the instructor's articulation from various angles, and it is difficult to intuitively obtain feedback on their pronunciation because there are certain limitations of interaction between learner-teacher and learner-learner in the online classes. It is also difficult to teach Chinese pronunciation in the online classes. In this study, the concept of adaptive learning was introduced into the homework design to realize more efficient pronunciation education in the online education situation. First, the learner's learning propensity is diagnosed, and homeworks suitable for each individual are presented. At the end of the semester, learner participation satisfaction and learning achievement are measured, and compared with the control group, it is evaluated whether presenting the task adaptively helped the learner to learn pronunciation more effectively. As a result of observation in this study, it was confirmed that internal evaluations such as learning achievement and participation satisfaction increased when learners were able to select tasks that fit their individual tendencies.
Research on the Value of Ancient Chinese Family Precepts Culture to Contemporary Humanistic Education

The long history of the development of the Chinese nation breeds extensive and profound cultural resources. As an important branch of Chinese culture, It provides the practice of family humanistic education and good family traditions that can be inherited for the society of all dynasties in China. Ancient Chinese family precepts culture, rich in philosophical concepts and humanistic care. Lay a good cultural foundation for the development of humanistic education. Integrate the experience and wisdom of ancient family precepts culture into contemporary humanistic education, It not only improves the family education quality of the Chinese nation ideologically, but also helps to improve the moral cultivation of contemporary humanistic education. This thesis draws from Chinese culture, Taking some specific family precepts documents as an example, From the generation, development, classification and characteristics of family precepts culture, it deeply discusses the value paradigm of family precepts culture to contemporary humanistic education. Through the clear thoughts, the value of the ancient family precepts spirit to humanistic education in today's society is expounded. Comprehensively analyze and apply the essence of ancient family precepts culture, and integrate it in humanistic education work. Realize the perfect combination of historical culture and modern culture. It has important reference significance for building a good family style and improving the quality of parents' humanistic education.
Independent University Education in the Fourth Industrial Revolution

This paper classified the changing era as the standard of the industrial revolution and sought to improve educational policies to foster creative talents. The current university curriculum is classified into a single, multiple, coalition, connection, and autonomy. Among them, autonomous majors are a curriculum that is attracting attention today, and the Korean Ministry of Education also agreed with this purpose and announced a plan to fully apply the high school credit system by 2025. However, in order for universities to fully realize autonomous majors, several conditions must be preceded. Autonomous majors may certainly be one of the responses to the Fourth Industrial Revolution. However, there is a fine line between versatility and incompetence. It is also the right answer to cultivate in-depth people who have mastered one field, and people who are relatively shallow but can communicate with various fields are also the right answer. Today, living in a rapidly changing era, curriculum options must go to learners. The learner himself or herself should consult on what to aim for and what future to plan, and the educational institution should respond to it. Therefore, I would like to present independent education, a higher concept of autonomous major, as a solution.
A Study on Drift Phenomenon of Trained ML

In the learned machine learning, the performance of machine learning degrades at the same time as drift occurs in terms of learning models and learning data over time. As a solution to this problem, I would like to propose the concept and evaluation method of ML drift to determine the re-learning period of machine learning. An XAI test and an XAI test of an apple image were performed according to strawberry and clarity. In the case of strawberries, the change in the XAI analysis of ML models according to the clarity value was insignificant, and in the case of XAI of apple image, apples normally classified objects and heat map areas, but in the case of apple flowers and buds, the results were insignificant compared to strawberries and apples. This is expected to be caused by the lack of learning images of apple flowers and buds, and more apple flowers and buds will be studied and tested in the future.
Machine Learning and Deep Learning Techniques for Sentiment Analysis - A Comparative Study

In this day and age an increasing number of people are using online social networks and services to not only connect and communicate but also to voice their opinions. Sentiment Analysis is the identifying and categorizing of these opinions to determine the public’s opinion towards a particular topic, problem, product etc. The importance of Sentiment analysis is increasing day by day. Machine learning is a field of computer science that gives computers the ability to learn without being explicitly programmed. Deep Learning is a subfield of machine learning concerned with algorithms that are neural implementations, most commonly seen as neural networks, neural beliefs, etc. It is crucial to employ the most feasible and accurate technique while analyzing sentiments for a given data as this affects both producers as well as consumers. This paper puts forward a study that compares various Machine learning, Deep learning as well as their hybrid techniques. It compares their accuracy for Sentiment Analysis and thus it can be concluded that in most cases Deep learning techniques give better results. However, in some cases the difference in the accuracies of the two techniques is not substantial enough and thus it is better to use Machine Learning methods as they are easier to implement.
The Influence of Reading Interest, Learning Sources, and the People’s Environment on Learning Outcomes on Supplies Management of Students of Office Administration Education FE UNJ 2019

This study aims to determine the influence of reading interest, learning resources, and peer environment on the learning outcomes of Supplies Management.The population in the study were students of FE UNJ Office Administration Education 2019.The research sample was obtained using a simple random sampling technique.Reading interest is proven to have a positive linear relationship and there is a sign with a regression coefficient of 0.281.Then, the learning resources proved to have a positive relationship linearly and there is a sign with a regression coefficient of 0.425.Then the peer environment is proven to have a positive linear relationship and there is a sign with a regression coefficient of 0.313.
TRCA: Text Restoration for Chinese ASR with BERT

Text restoration plays a vital role in Chinese automatic speech recognition (ASR), which includes punctuation prediction and error correction. However, there are two inevitable challenges for this task. On the one hand, there are no public dataset and model for Chinese punctuation prediction. On the other hand, current text restoration methods for automatic speech recognition only focus on Chinese error correction instead of combining with Chinese punctuation prediction task. To address these problems, a BERT-based text restoration method called TRCA is proposed for Chinese ASR consisting of a Chinese punctuation prediction model and a Chinese error correction model. Experiments demonstrate that the proposed TRCA method outperforms state-of-the-art methods for both punctuation prediction and error correction tasks, among which the proposed TRCA improves the average accuracy to 98% in Chinese punctuation prediction.
Evaluation of 3D Point-Cloud Reconstruction Using Overlapped Frames in Fragment Construction

We present a 3D reconstruction system using RGB-D video. The key idea is to share both ends of RGB-D frames between adjacent subsequences. We implemented a novel 3D reconstruction system based on a conventional one, Open3D, and compared the conventional method to the system with the shared frames. We experimented with four datasets: three public datasets and one our proposed dataset. The our proposed dataset has quicker camera movement than the public datasets and is challenging to reconstruct. Our experiments demonstrate that our system reconstructs better synthetic scenes from the challenging dataset as the number of the shared frames increases and scenes from the other dataset retain reconstruction quality.
Employee Training

People are the weakest link when it comes to attackers’ getting access to the company’s internal network. To prevent employees’ being used to gain access to the company’s network, those employees need to be trained on spotting the ways in which attackers will attempt to use them to gain access to company systems.
A comparative analysis of neural network function: resilient back propagation algorithm (BPA) and radial basis functions (RBF) in multilingual environment

The most convenient speech processing tool is Artificial Neural Networks (ANNs). The effectiveness has been tested with various real-time applications. The classifier using artificial neural networks identifies utterances based on features extracted from the speech signal. The proposed approach to multilingual speaker identification consists of two parts, such as a training part and a testing part. In the training part, the classifier is trained using speech feature vectors. The spoken language contains complete information, such as details about the content of the message and details about the speaker of that message. In the present work, the speech signal databases of different speakers in a multilingual environment were recorded in three Indian languages, i.e., Hindi, Marathi, and Rajasthani. The cepstral characteristics of the speech signal were extracted: Mel-Frequency Cepstral Coefficients (MFCC) and Gammatone Frequency Cepstral Coefficients (GFCC). The system is designed for speaker recognition through multilingual speech signals using MFCC, GFCC, and combined functions as acoustic characteristics. Training and testing were performed using the Neural Network (NN) function, robust Backpropagation Algorithm (BPA), and Radial Basis Functions (RBF), and the results were compared. The accuracy of the speaker identification system is 94.89% using BPA and 96.62% using the RBF neural network.
Artificial Intelligence and Its Application in Educational Industry

This paper first introduces the basic concepts of artificial intelligence and the application of artificial intelligence, and then combines the educational industry, elaborated the application of artificial intelligence in the education industry, and finally prospects for the future of artificial intelligence.
The influence of the matching degree between teachers' teaching methods and students' learning methods on students' achievement

This paper analyses the relationship between the teachers' teaching methods and students' learning methods, emphasis on teachers' teaching methods and student to study the matching degree of impact on academic performance, and to improve the teaching methods and learning methods of compatibility method as a breakthrough point, to make use of teaching means, in a planned way and adjustment of teaching learning method through analyzing three aspects, It is expected to provide reference for relevant personnel.
Distributed Intelligent Transportation System Data Management and Processing Platform

In recent years, with the rapid development of China's road construction and the continuous improvement of people's living standards, the number of urban motor vehicles has continued to grow year after year.Motor vehicles have become one of the main means of transportation for urban residents.At the same time, due to the increasing amount of traffic information data, a single server platform can not meet the reception and storage of massive traffic data, nor can it meet the needs of rapid query of massive traffic data.Therefore, this paper will use the distributed system to process data to solve the above problems, so as to ensure the real-time transmission and storage of massive traffic data.This paper discusses and analyzes the characteristics of distributed intelligent transportation system and the design of communication system data management and processing platform.Through the behavior decision algorithm of distributed transportation system, the flow data of distributed intelligent transportation system are tested and analyzed.The experimental results show that in the time period from 6:00 to 8:00, from 12:00 to 14:00 and from 16:00 to 18:00 when the traffic data reaches the peak, the amount of data processed by each communication server is very different, and the difference data amount can reach 60000 traffic data.The statistical results of this traffic data amount can show that the ratio of the data amount sent by each front-end bayonet every moment is not equal to the ratio of the data amount of each front-end bayonet every day, which is enough to show that the data management and processing capacity and efficiency of the distributed intelligent transportation system have been greatly improved.
An Analysis of the Important Role of Ancient Poetry in Chinese Language Education

Chinese language education refers to Chinese language and culture education conducted mainly for overseas Chinese and overseas Chinese whose mother tongue or first language is not Chinese.By its nature, we can see that language and culture are inseparable, and language is the carrier of culture.This makes it clear that no matter what language teaching method we choose, the teaching of language will involve the teaching of related cultures.At the same time, as the essence of China's traditional culture, ancient poetry contains the rich cultural heritage of Chinese civilization and long-standing historical tradition, which is the crystallization of Chinese traditional culture.With the continuous development of Chinese language education, the teaching of ancient poems has become an important part of Chinese language education and plays a pivotal role in the teaching of Chinese language.Therefore, this paper will focus on the status, current situation and teaching methods of teaching ancient poems to explore how to better apply ancient poems to the teaching of Chinese as a foreign language in the classroom, and how to appropriately integrate some cultural teaching into the language teaching at the same time to help improve students' interest in learning.
Analysis of double reduction policy from the perspective of multi-source flow theory

The double reduction policy has had a great impact on the education sector since its promulgation.Using Jin Deng's multi-source theory to analyze and discuss the double reduction policy, it can be found that the double reduction policy still has a lot of room for optimization.In addition, the vigorous development of vocational education is also in line with the implementation of the double reduction policy to a certain extent.
Research on English Text Difficult Auditing Based on Artificial Neural Network

English text difficulty classification is very important in all walks of life, so it is very important to determine the text complexity of an article quickly and accurately.We select volumes 1 to 4 of New English Concept as a sample, in order to make up for the lack of terminology and applicability in the New Concept textbook, reader's Digest USA, Time and Nature, CET-4, CET-6 and IELTS are selected as the supplementary samples.The LCA method and L2SCA method were used to extract 33 lexicalrelated and 23 syntactic-related indicators from the sample articles as the original data set.The data were input into the artificial neural network for training and cross-validation, the training effect was excellent.After the above processing, the remaining five kinds of sample data were substituted into the trained artificial neural network for text complexity assessment.The standardized reading difficulty coefficients obtained from the assessment were drawn and the results of all kinds of data were found to be in line with the recognized difficulty ranking.
Research on the construction of integrated equipment support system based on combat cloud

In order to adapt to the change of our army's future combat command system, deal with the rapidly changing battlefield in the future and meet the development requirements of weapons and equipment, an integrated equipment support concept based on combat cloud, namely ""Equipment Cloud Support"", is proposed.The operation process of ""Equipment Cloud Support"" is conceived; The construction requirements of ""Equipment Cloud Support"" system are analyzed; Put forward the construction objectives and principles of ""Equipment Cloud Support"" system; The construction emphases of ""Equipment Cloud Support"" system are analyzed in detail; This paper puts forward management measures from four aspects: strengthening the infrastructure construction of ""Equipment Cloud Support"" data information, the development and application of technical support means, the optimal allocation of support resources and the construction and application of support forces.
Innovation of College English Teaching Mode Based on the Goal of Cultivating Innovative Talents

Innovative education is the basic idea of national education reform.The cultivation of innovative talents is the primary task of educational institutions at all levels.As a new force of society, college students should have innovative consciousness, innovative spirit, innovative thinking and innovative ability.English is a compulsory course for every college student.The current CET is generally time-consuming and inefficient, and can not fully meet the requirements of China's economic development and international exchange for talent quality.The reasons are not only the problems of teachers, students, but also the problems of the examination system.The cultivation of foreign language talents must also adapt to this new strategy.However, the students trained by traditional CET methods and means lack the sense of innovation, autonomy and practical ability, and are difficult to meet the needs of society.Therefore, the reform of CET mode is imperative.Starting from the understanding of the connotation and characteristics of English major, this paper discusses how to integrate the research teaching concept into the teaching system, so as to achieve the training goal of innovative talents.
Research on the Teaching Strategies of Senior High School English Continuous Writing Task

Considering the poor quality of English teaching in China, many domestic experts and scholars have spared no effort to explore effective teaching methods for foreign language teaching.The continuous writing task proposed by Wang Chuming in 2012 has been confirmed by a large number of experts and scholars from the theoretical and practical aspects of its excellent learning-promoting effect.In order to improve the quality of English teaching in our country, continuous writing task has gradually been adopted in the English writing questions of the New college entrance examination in various provinces.However, the new writing question type puts forward higher writing requirements for students' writing ability, thus this new writing question type is a new challenge for students.There are a series of problems in the students' continuous writing task, such as deviant theme and inconsistent continuous content with the given material gist; simple, bland and illogical continuous writing plots; improper use of vocabulary and grammar and confusing language expression, etc.In order to enhance students' continuous writing task performance, the author proposes three effective teaching strategies: firstly, analyse the original text carefully and focus on synergy with the original text and the coherence of the whole text; secondly, excavate the original text to enrich language expression; thirdly, pay attention to multiple evaluation methods to form a multidimensional interactive evaluation mode.
Research on Combining Pattern Mining and Evolutionary Algorithm for Critical Node Detection Problems

The critical node detection problems (CNDPs) have important applications in network security, smart grid, epidemic control, drug design, and risk assessment.The critical node problem (CNP) is one of well-known CNDPs, which is NP-hard.In this work, we combine frequent pattern mining with evolutionary algorithm for solving CNP, where pattern mined from high-quality solutions are used to guide the construction of offspring solution.More specifically, based on the memetic algorithm (Memetic Algorithm for CNP, MACNP), frequent pattern mining was integrated into the memetic algorithm framework.The frequent patterns mined were used to construct the offspring solution, instead of crossover operator in MACNP.In the research, the nodes in frequent items set were directly fixed as part of the offspring solution.So the offspring solution inherited excellent properties from more parent solutions, thus forming the algorithm called Frequent Pattern Based Search for CNP (FPBS-CNP).This strategy improved the algorithm efficiency.Experiments were conducted on synthetic and real-world benchmark.We experimentally compare FPBS-CNP with MACNP.The experiment results show that FPBS-CNP performs well on small instances and has potential in solving large instances.
new edition of the Guida al sistema italiano di indicizzazione per soggetto

This contribution reproduces the text of the speech that was held in the framework of the presentation of the second edition of the volume Nuovo soggettario. Guida al sistema italiano di indicizzazione per soggetto, that took place in Florence on June 7th, 2022. As happened in these years with the subject indexing tools of important national libraries, the National Central Library of Florence, too, has updated the Nuovo soggettario, that saw the light in 2007, today employed by the Italian National Bibliography (BNI) and by most libraries of the National Library System (SBN). The intervention recalls the context factors that led to the project and to the elaboration of the second edition of the Guida, fully revised and updated: the evolution of the international scene related to indexing (new standards, new conceptual models), the semantic web and the linked open data; the development of the Nuovo soggettario system as a whole (increase of terminology, connections with equivalents in other languages, with resources of archives and museums, availability of the Thesaurus in exchange formats and standard protocols, etc.). The second edition’s novelties are then illustrated: a better organized exposure of the standards, more functional to their use, a totally new first part dedicated to the principles and to the general aspects of the indexing, the confrontation with IFLA LRM, the references to the indexing of non-bibliographical resources (figurative works, photographs) of ancient works, etc. Finally, it ends by stressing the importance that the cooperation with other partner institutions and with ICCU has had in this work, and shall continue to have in the future, for a greater and greater sharing of the semantic data on behalf of the Italian libraries.