Reviewerly/exHarmony huggingface dataset:
Quantitative Analysis of Classroom Attention Teaching Based on Stochastic Cascade Regression and PnP Method

In the process of quantitative analysis of classroom teaching, it is often necessary to evaluate individual indicators related to attention such as "whether the teacher's teaching attracts students, whether it stimulates the enthusiasm for learning" and "whether there is eye contact between teachers and students".Learning attention reflects the students' learning state and learning psychology, and meets the observable, reproducible, and interpretable requirements for quantitative analysis of the classroom teaching process.The project team used random cascade regression to obtain the coordinate information of 11 facial feature points.Used to provide 2D information in PnP solutions.Based on a standard face model obtained by statistical measurement, the mapping relationship between 2D/3D is obtained by solving PnP, and the rotation and translation matrices of the head pose are output.According to the rotation and translation matrix information of the head posture, the student's viewpoint is projected into the teacher's teaching video shot by the rear camera by using the transformation relationship of the spatial coordinates, so as to realize the visual display of learning attention.
Research on the Factors Influencing College Associations’ Development—Based on Analytic Hierarchy Process

To evaluate the performance of college associations scientifically and effectively is a considerable work to ensure the sound development of societies and to promote the cultural construction of universities.Selecting 3 factors as criterion layer-cadres' quality, management mechanism and organization construction and subdividing them into 12 specific indicators that affect college associations' development, this paper uses AHP to measure the performance of college associations and calculate the importance of different factors.The conclusions can provide useful suggestions to boost the blossom of societies and clubs, enrich the second classroom for students and build more colorful campuses.
The Application of PBL in TESOL Education

Problem-based Learning (PBL) is a teaching method in which students learn by engaging in real-world and personally meaningful projects actively.In Project Based Learning, teachers provide more opportunities for students to develop their problem-solving and critical thinking abilities.Students work on a project over an extended period of time (from a week up to a semester), which engages them to solve a real-world problem or answer a complex question.Through this method, they demonstrate their knowledge and skills by creating a public product or presentation for a real audience.This paper introduces PBL and the relationship between PBL and (Teaching English to Speakers of Other Languages) TESOL education, along with considering the possible risks in PBL application with proposed solutions.
Inquiry Teaching Design of Plant Tissue Culture Experiments in Secondary Vocational Education

Based on the experiment of "establishing plant tissue regeneration culture system", this paper briefly discusses the general steps of inquiry teaching design of plant tissue culture experiments in secondary vocational education.Inquiry experiment teaching begins with posing questions, which is the premise that makes students think.Ask questions to inspire students' desire and curiosity for inquiry and in-depth learning, guide students to design the experiment procedure, and conduct students to implement laboratory activities.Not only can inquiry experiment teaching deepen students' understanding of the knowledge they have learned, but also improve students' experimental operational level.More importantly, it can cultivate students' exploration consciousness and enhance teaching effect.
The Design and Construction of Online Teaching Mode of Chinese Language and Literature Under the Background of Internet + Education

In view of the problems in the current teaching of Chinese language and literature, such as lagging teaching resources, single teaching mode, and students' low interest in learning, etc.In this paper, based on the idea of digital education, the traditional teaching mode of Chinese language and literature is reformed, and a brand-new online teaching mode of Chinese language and literature is designed by constructing a comprehensive application platform system of digital education of Chinese language and literature in colleges and universities.In this system, the front end is developed in the mode of separation of front end and back end.The front end is developed in HTML + CSS + JavaScript language and VUE.JS framework, and the back end is developed in PHP language combined with yii framework and B/S mode combined with ajax asynchronous information transmission technology.On the surface, this system helps teachers realize online teaching by video, meets the needs of students to learn diverse and excellent teaching resources, and effectively promotes students' interest in learning Chinese language and literature.
The Design and Implementation of Interactive Online Training Teaching System in Digital Education Environment

With the digital transformation and upgrading of modern education, based on virtual reality, multimedia, visual interaction, network communication and other technologies, a virtual simulation interactive online training teaching system is constructed.Aiming at many problems existing in the current college training teaching process, comprehensive application solutions are put forward.This system will use 3ds Max, Unity3D and other key technical means to complete the design and development of virtual simulation training environment and training project based on the actual training teaching content, and complete the encapsulation and release of functional modules in ASP.NET development environment to form a standard Web application.By using multimedia resources, 3D digital models, virtual interaction and other ways to help students fully grasp the operation principle and workflow of the practical training project, and by consolidating and strengthening theoretical knowledge, it is not only beneficial to improve students' ability to integrate theory with practice, but also to enhance students' comprehensive ability and professional quality.It is also a useful attempt to realize the organic combination of modern education and practical training and promote the reform of digital teaching in colleges and universities.
Utilizing Random Forest Algorithm for Sentiment Prediction Based on Twitter Data

Information sharing throughout the globe or universe has become a characteristic of social media.There has been a lot of research into the classification of sentiments.In this study, Twitter has been mined for unstructured GoFood Reviews data.It has been preprocessed to analyze the reviews' sentiment with polarity analysis, feature extraction with TF-IDF, and supervised learning with random forest.From June 1, 2022, to June 30, 2022, a total of 28763 tweets with the keyword GoFood were retrieved from Twitter.The data is processed by the Python programming language utilizing NLTK, Sastrawi for the Indonesian language, Textblob, TF-IDF, Random Forest Classification, and other algorithms.Twitter is a nearly limitless source for classifying text.This algorithm takes roughly five minutes to compute.
Construction of Online Teaching Quality Assurance Index System Based on Big Data and TQM Theory

Through the analysis of the online teaching of teachers in universities and colleges, online teaching has key shortcomings in teaching technology concepts, teachers' role reshaping, teacher-student interaction, teaching evaluation, etc.The root cause is that the online teaching quality assurance index system in colleges and universities has not been further improved in the data age, and has not played its due role in guiding teachers and students to solve problems and promoting online teaching reform.Based on big data technology and total quality management (TQM) theory, a systematic index system of online teaching quality assurance is constructed to clarify the main factors affecting the quality of online teaching and to help the healthy development of online teaching reform in colleges and universities.
Evaluation of Professional Command Ability Based on Cloud Model

On the basis of existing effectiveness evaluation methods, combined with the characteristics of professional command ability of growing officer cadets, an evaluation method based on cloud model is proposed.In view of the fuzziness and uncertainty of the evaluation object, a cloud center of gravity evaluation method based on the cloud model is proposed to obtain the cloud model representation of quantitative indicators.Through the application of weighted deviation degree, the evaluation of students' professional command ability can realize the quantitative and qualitative transformation, and the evaluation results can be more intuitive and suitable for decision-making.Finally, the effectiveness and superiority of the proposed evaluation method are verified by an example.
Bayesian Network Student Modelling on Intelligent Tutoring System

Intelligent Tutoring System (ITS) is an electronic tutorial that has intelligence for adapting learning materials.It adjusts the contents of learning materials depending on the users' requirements.This research developed an ITS for Object Oriented Programming course that is based on Bayesian Network as its inference engine.It has run well which is shown by the variation of the study tracks of each student based on the Bayesian Network Student Model.This tutorial is also divided into two part, there are basic parts that contains basic programming technique and the advanced part that provides the concepts of Object Oriented Programming.Based on those two parts, this study wants to examine their differences of them.By the Levenshtein distance, the highest distance between students' ways of learning is 11 and its average is 5.385 for the basic part of Programming and 4.8 for the advanced part of the advanced part.The advanced part also has a positive value of skewness of the frequency distribution, it is 0,81 (left skew), which means that this distance is majority short.Whereas the basic of programming has a negative value that is -0.68 (right skew), in the other words, it shows that the elementary part has a longer distance of learning way.Data of the distances of advanced material parts concentrated on the second quartile by median is 4, whereas the basic part, by median is 6, data is concentrated in the third quartile.Mean Opinion Score shows that students are more interested to use the ITS than the classical Tutoring System, it is because the ITS has an average value is 8 (very agree) and the classical tutorial is 7 (agree).Besides that, the other criteria such as user-friendly, speed, report response, and appearance have 8 scores or very agree, and only a criterion has 7 (agree) in the stability.
Reform and Innovation Mode of College Music Teaching Under the Background of Internet Plus Times

In view of the various problems in the teaching practice of college music education under the background of "internet plus", and the requirements of the times for the innovation and development of college music subject under the construction of "new liberal arts".This paper will focus on the reform of college music teaching as the research object, take the idea of Web application development as the guide, adopt Java language, and combine SSH framework to complete the construction of college music online teaching platform.The platform will support curriculum learning, teaching resources, ideological connotation education, communication and interaction, and online assessment, and put forward comprehensive application solutions from the daily teaching practice and subject research fields.With the help of the application advantages of network information technology, online education is innovatively introduced into music teaching in colleges and universities, and then a new teaching mode is formed through integration.It not only improves the teaching effect, but also promotes the improvement of the teaching system of music major in colleges and universities, and promotes the process of information reform of higher education, and also makes a new attempt for the construction and development of music discipline.
Indonesian SMS Spam Detection Using TF-RF Feature Weighting Method and Support Vector Machine Classifier

SMS Spam is an unsolicited or unwanted text message by a user that is sent to a mobile device.At this time, increasingly criminal acts can annoy recipients by spreading unsolicited or unwanted spam SMS, including promotions, fraud, pornographic messages, and others.Therefore, the classification of SMS needs to be developed to assist in categorizing SMS.In existing research, to try to overcome these problems, the term frequency-inverse document frequency (TF-IDF) feature is applied.However, this method has a disadvantage, namely eliminating category information on each document, so in this study, a comparison will be made with the Supervised Term Weighting feature method, which is one of the terms frequency relevance frequency (TF-RF) using the Support Vector Machine, K-nearest Neighbor, and Multinomial Naïve Bayes.The total data used is 500 SMS with a comparison of 325 non-spam SMS and 175 spam SMS.After the experiment is conducted, SVM Kernel Sigmoid has the highest average accuracy value where the difference in average accuracy with Kernel RBF is 2.26%, Linear Kernel is 0.09%, k-Nearest Neighbor is 27.56%, and Multinomial Naïve Bayes is 4.37%.
A Hybrid Automated Essay Scoring Using NLP and Random Forest Regression

Assessing the performance of students through subjective assessments namely essays is critical in measuring their achievement during the learning process in an educational system.The essay test will evaluate the student's ability to remember and express their ideas or opinions toward certain topics.A teaching staff is usually required to assess and grade the students' essays.This paper presents a hybrid Automated Scoring System based on Natural Language Processing (NLP) and Random Forest Regression.The model focused on regression task where the predicted score is in a continuous value.Natural Language Processing (NLP) has also been applied in this work to extract features from essays.Finally, all the proposed model is compared to Linear Regression and Deep Learning and are then evaluated to compare the performance of the models by using the Mean Absolute Error (MAE), Mean Squared Error (MSE), and Root Mean Squared Error (RMSE).
Comparison of Word Embeddings for Sentiment Classification with Preconceived Subjectivity

This research looks into objectivity and subjectivity's effects on sentiment analysis through word embeddings, namely Word2Vec, Term Frequency-Inverse Document Frequency (TF-IDF), and Bidirectional Encoder Representations from Transformers (BERT).Objectivity corpora are defined as data with a neutral point of view and no biases.In contrast, subjectivity corpora are defined as data from a non-neutral point of view and may contain biases.The goals are to compare the efficacy of numerous embedding methods on sentiment analysis classification after subjectivity analysis.In terms of embedding methods, results from our work show that BERT embedding gives the best outcome for subjectivity classification with an accuracy score of 99.77%.For sentiment classification, TF-IDF provides the highest accuracy with 91.29%.
Data-Centric Analysis to Combat Cybercrime in Malaysia

One of the objectives of the National Policy on Industry 4.0 is to transform Malaysia's industry capabilities in both a holistic and an accelerated manner and an integral component is the adoption of appropriate legislation against the misuse of ICTs for criminal purposes.These changes, it has become the catalyst for creating a new sophisticated cybercriminal environment using more advance and complex tools to find their target victims.The study reveals that the potential economic loss in Malaysia due to cybercrime technologies can hit a staggering US$12.2 billion with the financial sector having the worst hit.Cybercrime grows with the development of technology and these figures show that there must be something lacking either in the analysis, prosecution, or the laws.To achieve a successful prosecution in cybercrime cases, Malaysia needs comprehensive new legislation which can prosecute cybercrime effectively instead of having peace meals of legislation and regulations currently.Besides, there is also a glaring insufficiency in understanding cybercrime and a tremendous lack of qualitative and quantitative data in the empirical aspects of cybercrime including the types of incidences, the analysis process, and contemporary tool support.This is primary towards shaping the intended legislation with consideration for the technological aspects.
Needs Analysis for the Development of Digital Materials for Indonesian Language Skills Subject Based on Melayu Culture for PGSD Students, Universitas Riau

This study aims to analyze the needs of PGSD students at Universitas Riau for developing digital materials for Indonesian Language Skills subject based on Melayu Culture with Project Based Learning.The research was conducted at PGSD in May-June 2022.The research sample was 72 students.The development model chosen is the research and development education model developed by Bord and Gall, which consists of three stages: preliminary studies, product development, and product implementation.The researcher was limited to the preliminary study stage in this study.Data collection techniques are used in the form of observation, interviews, and questionnaires (questionnaire) analysis of the development needs of digital teaching materials.The questionnaire was distributed to respondents via a google form.The data obtained were then analyzed using descriptive analysis based on the results of the number of answers given by the respondents.The analysis shows that there are no printed or digital teaching materials for Indonesian Language Skills courses that can be used as a guide in the learning process.On the other hand, teaching materials that need to be developed in the Indonesian Language Skills subject for PGSD students, FKIP Universitas Riau, are digital materials.The digital materials contain material on developing four Indonesian language skills, namely reading, listening, speaking, and writing skills based on Riau Melayu culture with Project Based Learning.
Implementation of Student Team Achievement Division (STAD) Method in Learning Indonesian Language at SMA Negeri Karangpandan

This research aims to describe: (1) program development on the Student Team Achievement Division (STAD) method in learning Indonesian language at SMA Negeri Karangpandan, (2) implementation of STAD method in learning Indonesian language at SMA Negeri Karangpandan, and (3) evaluation of implementation, success, supporting factors, and inhibiting factors for learning STAD method in learning Indonesian language at SMA Negeri Karangpandan.This research is a qualitative with a case study design.The participants were Indonesian language teachers at SMA Negeri Karangpandan.Data collection techniques were carried out by observation, in-depth interviews, and documentation.Data validation used source and technical triangulations.Data analysis technique was done by summarizing the data, presenting the data, and drawing conclusions.The results indicated that the implementation of STAD method in learning Indonesian language at SMA Negeri Karangpandan include: (1) development of learning programs that have been implemented by Indonesian language teachers, including annual programs, semester programs, weekly programs, module programs, and remedial programs, (2) the implementation of Indonesian language learning is carried out using STAD method on the material of imagination in poetry starting from student grouping, teacher presentations, division of tasks, quizzes, and awarding, and (3) the evaluation of the implementation of learning is measured by the suitability of the teaching and learning activities carried out by the teacher in the classroom with the lesson plan; evaluation of learning success is carried out by means of tests; factor supporting is the teacher be able to take advantage of the facilities; and the cooperation of students in groups, while the inhibiting factor is the attitude of students who are introvert.
The Application of Cornell-Note Method in Note-Taking for Online Learning During the Covid-19 Pandemic Period Cornell Note Practice for Reading in English for Students

Online learning becomes students' daily routine during the COVID-19 pandemic period.It makes the learning activity must be implemented at home virtually and learning from school is not recommended.However, not all students can follow online learning.They admit if they are complicated in understanding the class materials delivered or shared by their teacher.To make better conditions, there is a way to make students stay motivated to learn by making notes to keep the material be memorized in their mind.In this article, the writer wants to explain the application of Cornell note-taking for students during the online class or virtual learning or school from home in the COVID-19 pandemic.This article is nonresearch based paper.Cornell note is considered an effective way to make notes for school lectures.To be more specific, this article chooses English lectures for school and the writer picks reading as the basic English skill to become the focus.Cornell note has benefits for students because the display of its note will gain students' attention while they reading the passage of school's material.Hopefully, Cornell notes can be practiced for students for a better understanding of materials in the classroom activity.
ControversialQA: Exploring Controversy in Question Answering

Controversy is widespread online. Previous studies mainly define controversy based on vague assumptions of its relation to sentiment such as hate speech and offensive words. This paper introduces the first question-answering dataset that defines content controversy by user perception, i.e., votes from plenty of users. It contains nearly 10K questions, and each question has a best answer and a most controversial answer. Experimental results reveal that controversy detection in question answering is essential and challenging, and there is no strong correlation between controversy and sentiment tasks.
General, Single-shot, Target-less, and Automatic LiDAR-Camera Extrinsic Calibration Toolbox

This paper presents an open source LiDAR-camera calibration toolbox that is general to LiDAR and camera projection models, requires only one pairing of LiDAR and camera data without a calibration target, and is fully automatic. For automatic initial guess estimation, we employ the SuperGlue image matching pipeline to find 2D-3D correspondences between LiDAR and camera data and estimate the LiDAR-camera transformation via RANSAC. Given the initial guess, we refine the transformation estimate with direct LiDAR-camera registration based on the normalized information distance, a mutual information-based cross-modal distance metric. For a handy calibration process, we also present several assistance capabilities (e.g., dynamic LiDAR data integration and user interface for making 2D-3D correspondence manually). The experimental results show that the proposed toolbox enables calibration of any combination of spinning and non-repetitive scan LiDARs and pinhole and omnidirectional cameras, and shows better calibration accuracy and robustness than those of the state-of-the-art edge-alignment-based calibration method.