Reviewerly/exHarmony huggingface dataset:
Visualization Strategy: An Effective Strategy to Teach Reading to Middle School Students

This research was conducted to know the influence of the Visualization Strategy on students' reading comprehension of recount text. This study aimed to identify and describe the impact of the Visualization Strategy on students' reading comprehension. The researchers utilized a quasi-experimental method in this study. There were 283 students in nine classes. Cluster Random Sampling Technique was used to collect the sample. The sample consisted of two classes, with the following details: the first class was an experimental class of 31 students, while the second class was a control class of 31 students. The primary technique of this research was a reading test in multiple choices, which consisted of 40 items with four options. In analyzing the data, the researchers used the t-test formula. The findings show that the Visualization Strategy impacted students' reading comprehension at SMP Negeri 32 Bandar Lampung in 2021/2022. It can be seen from the result that the mean score of post-test in the experimental class (84.42) is higher than the mean score of post-test in the control class (72.54). Therefore, using a visualization strategy as a learning model is more effective than a conventional strategy. On the other hand, the pre-test score in the experimental class is 67.42 before utilizing the visualization approach, and the mean score for the post-test in the experimental class is 84.42. It indicates Visualization Strategy had a beneficial impact on reading comprehension, so the students can improve their reading skills using this learning strategy&#x0D; Keywords: Visualization Strategy, Reading Comprehension, Experimental Research
Comparison Of LBPH, Fisherface, and PCA For Facial Expression Recognition of Kindergarten Student

Face recognition is the biometric personal identification that gaining a lot of attention recently. An increasing need for fast and accurate face expression recognition systems. Facial expression recognition is a system used to identify what expression is displayed by someone. In general, research on facial expression recognition only focuses on adult facial expressions. The introduction of human facial expressions is one of the very fields of research important because it is a blend of feelings and computer applications such as interactions between humans and computers, compressing data, face animation and face image search from a video. This research process recognizes facial expressions for toddlers, precisely for kindergarten students. But before making this research system Comparing three methods namely PCA, Fisherface and LBPH by adopts our new database that contains the face of individuals with a variety of pose and expression. which will be used for facial expression recognition. Fisherface accuracy was obtained at 94%, LBPH 100%, and PCA 48.75%.
Representation of Economic Growth in Cambodia with The ARDL Approach

This study tries to find out how the long-term and short-term relationship between several variables related to economic growth such as CO2 emissions, internet literacy, and education in Cambodia. We use the World Bank as a supplementary source for statistics data, namely data from 2000 to 2020. We learn from our estimating findings that the elements we predicted, including economic development and internet literacy, have both long- and short-term associations, as well as economic growth and education, which in the short term internet literacy has a significant positive effect on economic growth. In line with that, the level of education also has a significant positive effect on economic growth. In contrast to the statistically significant inverse association between the economic growth variable for this year and the economic growth for the prior year, there is also a relationship between co2 emissions and economic growth. This shows that increasing internet literacy, in the short and long term will also increase economic growth, as well as education levels. In contrast, CO2 emissions have an inverse correlation with the gross domestic product which represents economic growth in Cambodia.
Research on Multi-UUV Path Planning Method Based on Recycling Task

This paper addresses the path planning process with various uncertainties in the multi-UUV recycling. According to the amount of environmental information obtained, it can be divided into global planning for the entire recycling task and local planning for unknown threats. As a result, different from the traditional path planning method, the proposed method can be described as comprising two distinct phases: (1) combined with artificial potential field method, an improved algorithm based on “domain” is proposed, and the fish population trust domain algorithm is used to obtain the sub-target points that meet the requirements and complete the global track planning. (2) a bidirectional RRT* local path planning algorithm based on the concept of rolling optimization under incomplete constraints is proposed to deal with the unknown threats that appear during navigation. Finally, the effectiveness and feasibility of the algorithm are verified by simulation.
Mechatronic Generation of Datasets for Acoustics Research

We address the challenge of making spatial audio datasets by proposing a shared mechanized recording space that can run custom acoustic experiments: a Mechatronic Acoustic Research System (MARS). To accommodate a wide variety of experiments, we implement an extensible architecture for wireless multi-robot coordination which enables synchronized robot motion for dynamic scenes with moving speakers and microphones. Using a virtual control interface, we can remotely design automated experiments to collect large-scale audio data. This data is shown to be similar across repeated runs, demonstrating the reliability of MARS. We discuss the potential for MARS to make audio data collection accessible for researchers without dedicated acoustic research spaces.
Race, Gender, and Social Class Discrimination in Intersection with Political Identification in Rio de Janeiro

This article discusses the prejudices and discrimination against afro-descendants, women, LGBTQ persons, the homeless, immigrants, and young adults, considering class, religion, and political differences within the population of the city of Rio de Janeiro, Brazil.These types of discrimination are analyzed through the intersectionality approach using a concept named "discrimination relational matrix of analysis".In a two-phase design of a representative sample 759 urban inhabitants answered a questionnaire asking for their perceptions, attitudes, practices, and intergroup relationships on racism, patriarchalism, sexism, homophobia, xenophobia, and self-identification within different social classes, religions, and political-ideological identifications; correlations and a statistical model of Principal Component Analysis was applied to explore the main factors of discrimination.Analysis results show how explicit and several kinds of masked discrimination are connected, spread, normalized and popularized through apparently liberal and democratic speeches, and ambiguous attitudes and practices according to different interests between ingroups and outgroups in an environment of competition for resources and historic cultural settings of conservatism, patriarchalism and social classes prejudices, attached mainly to poverty and low educational levels.They also highlight a recent global context impacted by the increase in hate speech and extremism of right-wing political activism of small groups.The main discriminatory discourses and practices in Rio de Janeiro are openly uncivilized, sexist, racist, and xenophobic, and discriminate against the lower social classes and other vulnerable groups via a multidirectional anti-equality and anti-democratic mainstream, and its radicalization is popularized by a core leader far right group and is disseminated to and appropriated by distinct groups based on resources competition.
Jurnal Penggunaan Metode Scrum Dalam Membentuk Sistem Informasi Penyimpanan Gudang Berbasis Web

Scrum method is a methodology that is included in agile software development. Scrum is considered capable of producing good quality software in accordance with the wishes of the user, can be used in large or small projects, and easy to adopt changes. Scrum activity stages include backlog, sprint backlog, daily scrum, sprint review, and sprint restropective products. Roles in Scrum include the product owner, Scrum Master, and Development Team. Scrum has stages that are structured and iterative, so that if the product in the first sprint does not adequately meet the needs, then the next sprint can be developed in accordance with the user's evaluation system. The results obtained on Scrum Method on Building Web Based Information System of Storage Inventory are proven to be able to overcome the changing requirements during the system development phase, producing products that are in accordance with the wishes of the user due to repeated reviews.
Different Information Systems in Cross-Cultural Communication Between China and the West Under Cloud Computing

In the context of the multicultural culture of the world, people submitted higher demands for understanding differences in different cultures in the context of multicultural culture. In the multicultural culture, the difference between western culture is derived from the difference between values, ideas, manners and customs. The purpose of cultural comparison is to explore the origin of cultural differences and cultural clashes, to organize the characteristics of the laws in association, and to predict the impact of cultural encounters. This paper is based on different information systems in the study of cloud computing technology.
V. A. Samsonova – manager and researcher

The article describes the contribution made by Valentina Andreevna Samsonova to the development of librarianship in Yakutia and the National Library of the Republic of Sakha (Yakutia) during her tenure as the director from 1990 to 2016. Her organizational, managerial, research activity is considered. Emphasis is placed on V. A. Samsonova’ study of the collection of the bibliophile and bibliographer, one of the organizers of the Russian Collection of the Library of US Congress – Mikhail Zinovievich Vinokurov.
IMPROVING STUDENTS' SPEAKING SKILL THROUGH DEBATE

Speaking is one of the important skills in language learning. Speaking is the act, utterance or discourse of one who speaks. It also can be defined as an activity in giving and asking information as if dialoguing by two or more people. In speaking, there is a process of communication between speaker and listener. People put ideas into words, talking about perceptions and feeling they want other people to understand. The writer observed that most students are difficult to put ideas into word through communication in speaking English. To solve the problem, the writer conducted classroom action research, by implementing debate. The writer applied two cycles in this research. Each cycle consist of three meetings. The participant of this study was one class consists of 32 students. The instrument for collecting the data was speaking test, observation sheet and document. Based on the research result, showed the progressive mean of the students. The first meeting was 46,87, second meeting was 50,09, third meeting was 60,28, the fourth meeting was 65,12, the fifth meeting was 73,56 and the sixth meeting was 77,81. So, the mean in the second cycle was higher than the first cycle.It is indicated that the application of debate technique improve students’ speaking skill.
Pengaruh Distribusi Panjang Data Teks pada Klasifikasi: Sebuah Studi Awal

In text classification, there is a problem with text domain differences (cross-domain) between the data used to train the model and the data used when the model is applied. In addition to the problem of domain differences, there are also language differences (cross-lingual). Many previous studies have looked for ways how classification models can be applied effectively and efficiently in these cross-domain and cross-lingual situations. However, there is one difference that is not given special attention because it is considered not very influential, namely the difference in text length (cross-length). In this study, we further investigated the cross-length condition by creating a special dataset and testing it with various commonly used classification models. The results showed that the difference in the distribution of text length between the training data and the test data could affect the performances. Cross-length transfers from long to short texts show an average decrease in F1-scores across all models of 14%, while transfers from short to long texts give an average decrease of 9%.
Exploring the perceptions of EFL learners towards mobile-assisted vocabulary acquisition

This research examined how high school students felt about using the Busuu app to learn new vocabulary. The study used a qualitative research approach to elicit in-depth opinions on the subject. In addition, it assessed the benefits and challenges experienced by the participants when using Busuu, a language learning application, to acquire English language vocabulary. With 25 high school students from a public high school in the Saudi Arabian educational district of Ar Rass, a semi-structured interview (questions asked in Arabic) was conducted. The collected data were coded, conceptually examined, and documented. The findings indicated that students have a positive attitude about utilizing the Busuu a language learning mobile application to aid in their vocabulary acquisition. The majority of users had a positive view of Busuu when it came to expanding their vocabularies. Additionally, it revealed that the Busuu helps students become more motivated, have fun, and expand their vocabulary. Finally, the study highlighted various technical or legal challenges that stop students from using mobile applications, which are summed up in the challenge of getting an internet connection or the prohibition of using mobile at school.
INDIVIDUAL AND GROUP AUTONOMY IN DIFFERENTIATED ESP INSTRUCTION OF INFORMATION TECHNOLOGY STUDENTS

This study was aimed to check the effectiveness of links between individual and group autonomy of information technology (IT) students who studied ESP at university with the use of differentiated tasks. The mixed type of research was used. The study was held in 2020-2021 academic year and involved 40 IT students of the Physics and Technology Department of National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”. For the purpose of the study we used a three-degree individual autonomy model involving the partial autonomy, semi-autonomy and conditionally full autonomy degrees, and a two-degree group autonomy including the minimum and relatively maximum degrees. Both models were based on the criteria of motivation; goal, content and procedure; control and reflection. The significantly and insignificantly effective links between individual and group autonomy of IT students in differentiated ESP instruction were identified. The relatively maximum degree of group autonomy combined with individual semi-autonomy of IT students, as well as the relatively maximum degree of group autonomy combined with conditionally full individual autonomy of IT students were found significantly effective. In contrast, the combinations of the minimum degree of group autonomy with partial individual autonomy of IT students, as well as the minimum degree of group autonomy with conditionally full individual autonomy of IT students were found insignificantly effective. It was concluded that the promotion of the individual and group autonomy in differentiated ESP instruction should be based on individual characteristics of students.
PENERAPAN MODEL PEMBELAJARAN INDEX CARD MATCH DALAM MENINGKATKAN HASIL BELAJAR IPA KELAS III DI MI NURUL ULUM TULUNGAGUNG

AbstractThis research is motivated by the low learning outcomes of IPA subjuc in MI Nurul Ulum Tulungagung, Gadingrejo subdistrict, Pringsewu District. This research is a class action research (ptk) through the application of the index card match learning model which is carried out twice a cycle in class III students (25 students). Instruments used were interviews, documentation, teacher and student observation sheets, student worksheets, the factor investigated were student learnig outcomes, teacher and student activities. The procedure of this study starts from planning, observation, action, evaluation, analysis and reflection. The results of this study indicate that the application of the index card match learning model in class III MI Nurul Ulum can significantly improve student learning outcomes. Pra cycly activities show that overall student learning outcomes only reach 35,52%, after taking action in cycle 1 using the indec card match learning method student learning outcomes have increased student learning completeness by 60,21%, then proceed to the cycle II action and have ancreased completeness by 87,50%.Keyword : learning, index card match, learning outcome
The Use of ICTs in the Digital Culture for Virtual Learning of University Students Applying an Artificial Neural Network Model

Artificial neural networks are mathematical models of artificial intelligence that intend to reproduce the behavior of the human brain and whose main objective is the construction of systems that are capable of demonstrating certain intelligent behavior.The purpose of the investigation is to determine the influence of the use of Information and Communication Technologies (ICTs) in the digital culture in the learning process of university students in Peru and Bolivia in the context of the Coronavirus -COVID 19 sanitary emergency, through the application of artificial neural network models.The investigation has a quantitative focus, the applied type, with a correlational level and a non-experimental design.Data was recollected by means of a digital questionnaire, applied to students of two universities.The population is composed of 3980 students of the Universidad Privada Domingo Savio (UPDS, Tarija, Bolivia) and 1506 of the Universidad Nacional de Moquegua (UNAM, Moquegua, Peru).The sample consists of 496 students.The hypothetical-deductive and the artificial intelligence methods were used.It was determined that the ability to install software and data protection programs, the use of mobile devices for academic purposes and the command of specialized software are the most influential factors in the digital culture of the students at UNAM and UPDS.
Aplikasi Metode Arima Box-Jenkins Untuk Meramalkan Penggunaan Harian Data Seluler

The Box-Jenkins method is one of the time forecasting methods series. This method uses values in the past as the dependent variable and variable independently ignored. The Box-Jenkins method has the advantage of being usable on non-stationary data can be used on all data patterns so that this method can be used to predict the daily use of cellular data. The purpose of the study to find out the model and predict the amount of cellular data daily usage using data from March 10, 2020 to May 29, 2020. Results of the analysis shows the best model for daily use of cellular data is ARIMA (0,1,2). The best model meets the test requirements, namely the parameter significance test and diagnostic checking.
Pengembangan Media Pembelajaran Berbasis Android dalam Pembelajaran Jarak Jauh untuk Guru Biologi Tersertifikasi

This research was conducted to develop an Android-based learning media that is innovative and easy to use by teachers who have been certified in distance learning. The research method used is the Research and Development research method, the development stage refers to the Borg and Gall design which only focuses on 9 steps, namely potential and problem analysis, data collection, product design, design validation, design revision, product testing, product revision, testing. user trial and product revision. Respondents in this study were biology teachers from high school and Madrasah Aliyah in Garut Regency who were certified as well as media and material experts. The results of the study show that android-based learning media is feasible to be developed, this is evidenced by the obtained average score of 3.6 in the good category. In conclusion, android-based learning media can be an alternative learning media that is effective, efficient, interesting, and can be used anywhere and anytime and can be used by teachers, especially Biology teachers who have been certified and are not yet so skilled in making learning media for use in learning. long distance.&#x0D; &#x0D; Keywords: Certified Biology Teacher, Android-Based Learning Media, Distance Learning
Sarcasm Detection with A New CNN+BiLSTM Hybrid Neural Network and BERT Classification Model

One of the most common effects in the use of social media today is that people constantly make fun of each other or certain issues or do not take them seriously. Some comments made by sarcastic people in this widespread effect are misunderstood or taken seriously by other users. Some sarcastic comments, especially in the news headlines, create false effects on the readers and create some misunderstandings for people who do not have this sense of humor. Although there are numerous studies on the problem of sarcasm detection, even low performance increment in automatic sarcasm detection is very important and popular task. In this paper, a new hybrid deep neural model is proposed for more efficient automatic detection of sarcastic context. It is aimed to detect sarcasm using a hybrid neural network model CNN+BILSTM and BERT models with bidirectional language processing in a dataset consisting of headlines of The Onion News, which made such sarcastic headlines, and professionally prepared headlines without any sarcastic comments. When the results of this study were examined, it was seen that the model that gave the best results was BERT. In addition, accuracy, precision, recall and F1 score values were checked without using Glove embeddings in the CNN+BiLSTM model, and then the results were compared by applying Glove embeddings. In this comparison, the CNN+BiLSTM model without Glove embeddings gave relatively better results.
Decision-Making System for Selection of Majors in Higher Education Using the Certainty Factor (CF) Method for Web-Based High School Students

Various information about college majors has been widely available in print media and on the internet so as to make it easier to get that information. However, the information provided only provides a general description, such as profile, costs, location, and other general information. This information has not fully helped provide input on majors that match the abilities, interests, and preferences of prospective students. the objectives of this research are; to determine the Decision-Making System for Selection of Departments in Higher Education Using the Certainty Factor (CF) Method for Web-Based High School Students, and design a prototype of the Decision-Making System for Selection of Departments in Higher Education Using the Certainty Factor (CF) Method which runs on various operating systems. Based on the results of research and testing on the design of the Decision-Making System for the Selection of Departments in Higher Education using the Certainty Factor (CF) Method for Web-based High School Students that has been carried out by the author, several conclusions can be drawn, namely; This study succeeded in making an expert system design for the selection of majors in higher education for high school students using the Certainty Factor (CF) method and this study succeeded in analyzing the results of the IF THEN ELSE calculation using Certainty Factor (CF).