Reviewerly/exHarmony huggingface dataset:
Lexical Cohesion Devices in Students’ Narrative Text and Its Pedagogigal Implication in Language Teaching (A Discourse- Semantics Point of View)

Lexical Cohesion Devices in Students’ Narrative Text and Its Pedagogical Implication in Language Teaching: A Discourse- Semantics Point of View. Objective: This study aims at examing the lexical devices used in college students’ narrative writing. Method: Each students was requested to compose a free-topic narrative text which were subsequently analyzed following the principles of discourse- semantic analysis framework. Findings: Although the use of conjunction and reference contributed to the cohesiveness, the results still confirmed that the lexical relations distributed within the texts did not suit with the linguistic environment of the texts. Conclusion: Referring to the findings, the texts constructed by the students were not really being cohessive. As an implication, in language teaching, teachers and learners should pay attention on the use of cohesive devices to create more and better logical writing. Keywords: text, lexical device, cohesive, teaching. Abstrak: Lexical Cohesion Devices in Students Narrative Text and Its Pedagogical Implication in Language Teaching: A Discourse- Semantics Point of View. Tujuan: Penelitian ini bertujuan untuk menyingkap penggunaan perangkat kohesi pada tulisan narasi siswa. Metode: Setiap siswa diminta untuk menulis sebuah teks narasi dengan topik bebas yang selanjutnya dianalisis dengan menggunakan konsep diskursus semantik. Temuan: Walaupun penggunaan konjungsi dan referensi berkontribusi pada kepaduan teks, hasil penelitian ini menunjukan bahwa relasi leksikalnya tidak selaras dengan konteks penggunaan dalam teks. Kesimpulan: Merujuk pada temuan, peneliti menyimpulkan bahwa tulisan-tulisan siswa belum terpadu/kohesif. Sebagai implikasi, dalam pengajaran bahasa guru dan siswa harus memperhatikan penggunaan perangkat kohesi untuk menyususn tulisan yang lebih bagus dan logis. Kata kunci: teks, perangkat leksikal, kohesif, pengajaran. DOI: http://dx.doi.org/10.23960/jpp.v12.i1.202228
Pengaruh Metode Total Physical Response pada Perkembangan Kosakata Bahasa Inggris Anak Usia Dini

Since English has become an international language, more people are learning English in Indonesia and even English is taught from an early age. This is supported by the fact that many children learn foreign languages when they are very young. There are more tutoring places for the introduction of English to children, not only from schools. Therefore, the introduction of English to children varies, one of which is using the Total Physical Response (TPR) method. This study aims to determine whether there is an influence between the development of children’s vocabulary with the TPR method using the pre-experiment research method (one group pretest-posttest). The results of the assessment will be tested by conducting a t-test through SPSS-20. Based on the results of the study, there is an influence between the TPR method on the development of children’s English vocabulary, it can be seen from Ho is rejected and Ha is accepted, which means that there is an influence between the TPR method on the development of children’s English vocabulary, with the values of Sig. (2-tailed is 0.000 &lt; 0.05, with a pretes percentage result of 18.5% while the postes percentage score is 27.5%.
Online Multi-object Tracking Based on Deep Learning

Multi-object tracking task aims to identify and track all targets in the video. It has important applications in intelligent monitoring and other fields. Two problems can affect the accuracy of the multi-object tracking task. First, occlusion between targets will lead to interruption of tracking trajectory and switch of tracking target. Second, quality of the object detection results will directly affect the tracking accuracy. In this paper, we adopt a single-object tracking algorithm based on deep learning is introduced to solve the first problem and develop a discriminant network scoring the accuracy of detection and prediction bounding boxes to solve the second problem. The experimental results show that the proposed tracker performs better than other competing methods.
How Does Covid-19 Impact the Future Plans of Graduated College Students in China?

The Covid-19 has dramatically influenced society world widely.This work explored its influence on the future plans of graduated college students in China.This work extracted data of different employment plans of graduated college students from 20 universities in China, using statistical techniques and Python libraries, analysed the data and visualized the results.This shows the impact of Covid-19 on the college students' employment directly and vividly.
Detecting Hadith Authenticity Using a Deep-learning Approach

Hadith is a collection of texts containing sayings of the prophet Muhammad, which, along with accounts of his daily practice, constitute the second major source of legislation for Muslims after the Holy Koran. The Hadith collection comprises thousands of text pieces transferred over the years by many narrators with varying degrees of credibility. Hadith scholars are faced with the challenge of assessing the degree of a specific Hadith’s authenticity to classify the Hadith as Sahih (fully authentic and accepted) or Daif (rejected). Automatic Hadith classification has been addressed in the literature; however, the results vary and are not directly comparable, as no dataset has been made available for benchmarking. In addition, no previous work has utilised deep-learning (DL) approaches for Hadith classification. This work contributes by 1) collecting and publicly releasing a benchmark Hadith dataset of almost 4,000 Hadith texts to facilitate future research, 2) exploring DL model performance on binary Hadith classification tasks, and 3) benchmarking traditional machine learning against DL models. Our best results were recorded with an ARBERT DL model that provided an accuracy score of 91.56%. KEYWORDS Hadith classification; deep learning; Classical Arabic; machine learning; Hadith science; Hadith authenticity
American Art Education in the Context of Pandemic Era Culture

The article analyzes the processes of art education in a pandemic. In the article, on the example of the experience of educational institutions in the United States, the conditions for changing educational technologies for the sphere of education in the field of culture and art are considered. The article analyzes the changed conditions not only for educational institutions, but also for the education sector. Studies in the field of art education show a tendency to move away from the formalism inherent in the education system, the analysis allows us to talk about the formation of the priority of interactive practices in the field of culture and education, which allows cultural and leisure organizations to survive (museums, galleries, theaters, etc.).
The effect of Marlin Study Pack Application Towards Students’ English for Maritime Ability at Nautical Study Program

this article was expected to investigate the significant differences of using Marlin Study Pack Application toward students' English for Maritime ability at Nautical Study Program.The data was conducting by quasi experimental research, the writer tried to observe whether Marlin Study Pack Application is effective in helping maritime students to learn English for maritime.The sample was taken by purposive sampling.There were 13 students from class A of Nautical Study program and 13 students from class B of Nautical Study program.The results of the study show students' scores after taking a pre-and post-test.The average gained score after doing pre-and posttests was 29.92.Students that were taught using the Marlin Study Pack Application scored higher on the post-test than on the pre-test.When t-observed = 8.22 was more than t-table = 2.160, it was proven.It indicates that Ha has been accepted.Students who are taught using the Marlin Study Pack had better English skills than students who are taught using traditional techniques, according to the findings of this study.In conclusion, Marlin Test is a better teaching technique to be implemented in teaching English for Maritime process.
Illocutionary Acts in President Joe Biden’s Speech

This article aimed to specify the kinds of illocutionary acts and defined the existence of illocutionary acts and their meaning in a speech to discover the outcomes of the maximum dominant kinds of illocutionary acts in President Joe Biden's speech. The research method used in completing this research becomes the descriptive qualitative method. In studying the data, the theory of Searle (1979) becomes used to determine the illocutionary act category of the speaker utterances. The tool used in collecting and analyzing the information was the speech video of President Joe Biden and the script acquired from the internet. The result of this research confirmed that there was 41 information and the researcher observed five types of the illocutionary act by using Searle’s theory in President Joe Biden’s speech which are assertive, directive, commisive, expressive, and declarative. The most dominant was assertive illocutionary act that implies stating, announcing, reporting, assertion, claiming, telling, informing, assuring, complaining, and concluding.
A New Probe into the Effective Dissemination of Marxist Theories in the Network Environment

The Internet provides convenient conditions for the dissemination of Marxist theory and accelerates the popularization &#x0D; of Marxism among the majority of students.However, the dissemination of Marxist theory among college students in the network &#x0D; environment is also influenced by the strong academic color, the poor quality of theoretical workers,The challenge of non-Marxist &#x0D; ideology and the influence of factors such as the squeeze of diversified Internet content. The solution is to build attractiveEstablish &#x0D; a proactive communication concept, strengthen the construction of the network communication team, and improve the Marxist &#x0D; theoretical knowledge of college studentskeep.
PENGEMBANGAN MEDIA JENGA PADA LAYANAN INFORMASI UNTUK MENINGKATKAN PEMAHAMAN BAHAYA BULLYING DI MTs DDI KOTA TARAKAN

This study aims to develop a product in the form of Jenga media on guidance and counseling information services to students at MTs DDI Tarakan City. Bullying is an act of violence or responsiveness carried out by a person or group of people with the intent and purpose to frighten. Jenga media is one of the media that can be used by guidance and counseling teachers to carry out services, especially in information services to increase understanding of the dangers of bullying so that students can understand how to deal with bullying and the bad effects of bullying behavior. This study uses a research and development approach (Research and Development). The research and development procedure uses the Borg and Gall development model, but in this study, it was carried out until the fifth stage, namely the design revision stage due to conditions during the Covid-19 pandemic. The results of material expert validation with a score of 78% indicate the appropriate category, and the validation results of design experts with a score of 89% indicate the very feasible category. This shows that the Jenga media developed is feasible and good to use in guidance and counseling information services to increase students' understanding of the risks of bullying.
Single Image Joint Motion Deblurring and Super-Resolution Using the Multi-Scale Channel Attention Modules

During the last decade, deep convolutional neural networks have significantly advanced the single image super-resolution techniques reconstructing realistic textural and spatial details. In classical image super-resolution problems, it is assumed that the low-resolution image has a certain downsampling degradation. However, complicated image degradations are inevitable in real-world scenarios, and motion blur is a common type of image degradation due to camera or scene motion during the image capturing process. This work proposes a fully convolutional neural network to reconstruct high-resolution sharp images from the given motion blurry low-resolution images. The deblurring subnetwork is based on multi-stage progressive architecture, while the super-resolution subnetwork is designed using the multi-scale channel attention modules. A simple and effective training strategy is employed where a pre-trained frozen deblurring module is used to train the super-resolution module. The deblurring module is unfrozen in the last training phase. Experiments show that, unlike the other methods, the proposed method reconstructs relatively small structures and textural details while successfully removing the complex motion blur. The implementation code and the pre-trained model are publicly available at https://github.com/misakshoyan/joint-motion-deblur-and-sr.
Design of continuous organizational and pedagogical support of rural school

The article reveals the main directions of designing organizational and pedagogical support for rural schools in the context of the reform of professional education in the Russian Federation, based on the materials of « Kalmyk State University named after B.B. Gorodovikov», in the process of implementing the project « Scientific and pedagogical support of the teacher of a rural school in the system of continuous higher education». The goal of the project is to implement organizational, managerial, control and diagnostic conditions for the development of the continuous pedagogical education system to provide the population with affordable high-quality education involving the use of innovative, primarily digital network technologies, and the creation of a career guidance system. Project objectives: 1. Development of organizational and pedagogical infrastructure, information base and mobility of the continuous education system in the Republic of Kalmykia. 2. Preparing students in rural schools for a conscious choice of a profession, for obtaining pedagogical specialities. 3. Increasing the volume of the university's participation in the implementation of large-scale and socially significant federal and regional research and educational projects, significant scientific and applied problems. The project aims at increasing the social status and prestige of teacher labor, updating the content and structure of higher pedagogical education through the use of networked educational models; conducting targeted recruitment, creating conditions for rural youth to receive higher pedagogical education; providing the population of the Republic of Kalmykia with affordable high-quality modern education, involving the use of innovative, primarily digital, network technologies; an increase in the average USE score of students enrolled in undergraduate programs in the direction of «Pedagogical Education» is at least 70. The project provides for measures to create «growth points» in rural schools aimed at creating a system for identifying and supporting future teachers striving for self-actualization, self-realization, scientific pedagogical stimulation of improving educational performance, the activities of teachers in rural schools; the activities of the consortium «Evidence-based pedagogy» as the most important resource for the implementation of the priority national project «Education».
Local Differential Privacy for Belief Functions

In this paper, we propose two new definitions of local differential privacy for belief functions. One is based on Shafer’s semantics of randomly coded messages and the other from the perspective of imprecise probabilities. We show that such basic properties as composition and post-processing also hold for our new definitions. Moreover, we provide a hypothesis testing framework for these definitions and study the effect of "don’t know" in the trade-off between privacy and utility in discrete distribution estimation.
Inovasi Desain Pembelajaran Membaca Cepat melalui Metode Speed Reading bagi Guru SD Negeri 2 Pematang Tahalo

Community service in the form of mentoring Indonesian language subject teachers with the theme "Innovation of Speed Reading Learning Designs Through Speed Reading Methods for Teachers of SD Negeri 2 Pematang Tahalo, Jabung District, East Lampung Regency". Community service that is carried out personally for 11 Indonesian language teachers in Jabung District for 10 days, namely, 01 August to 10 October 2018. The formulation of the problem in community service is 1. An innovative speed reading learning method is needed, the concept of fast reading learning the speed reading method is relatively new so Indonesian language teachers need to receive counseling and training including guidance in its implementation, 2. Indonesian language teachers in the Jabung sub-district do not yet have a speed reading learning design that can develop interest and improve students' speed reading skills, 3. Teachers need training and assistance in designing learning to read include: syllabus, design of teaching materials for speed reading, development of indicators, learning scenarios, and development of assessment instruments. The percentage of speed reading ability and reading comprehension of elementary school students in Jabung Subdistrict showed an increase in the quality of teacher learning designs, increasing from 58% to 84.58% in the good category. Likewise, the impact that is directly felt in the classroom, teachers can improve student learning outcomes. This can be seen from the students' speed reading scores, an increase of about 30% from the initial value. If this service activity continues, it is possible to increase the professionalism of teachers in designing and implementing speed reading learning and learning innovations can be carried out by applying the Speedreading method.&#x0D; Keywords: Learning Design, Speed Reading, Speed Reading Method
Efektifitas Penerapan Aplikasi Google Classroom dalam Pembelajaran Bahasa Indonesia bagi Siswa SMK Negeri di Samarinda

When students are given assignments, sometimes some students do not respond. In fact, teachers have not provided creative learning innovations to students. As a result, the teacher's instructions do not do the task. The study aims to describe the use of Google Classroom applications to attract and train students' skills in writing literacy in Indonesian learning, particularly writing anecdotal texts. The method used in this study is qualitative as for obtaining the data by conducting in-depth interviews using a recording device, then collecting data through a questionnaire to get valid data from students. The subject of this study was a student of class X SMK Negeri Samarinda consisting of the high, medium, and low achievement. The results showed that students are happy to use classroom applications as a medium of learning anecdotal text because they can write creatively and want the application to remain used to share ideas. However, the use of classroom applications also requires a good internet network.
Development of an Embedded Device with Motion Detection by Dynamic Background Subtraction Using High-Level Synthesis

In this study, we develop a camera-equipped embedded system with a motion detection function using the dynamic background subtraction method. The main part of the hardware was created by high-level synthesis. In addition, we introduced the concept of a ring buffer for the memory of the entire system to achieve efficient memory access. As a result, a maximum frame rate of 194 fps was achieved when the image size was QVGA and the number of time-series images was 4, ignoring the performance of the actual camera. We also confirmed that the hardware processing is more power efficient than the software processing.
An Empirical Study of National Education and Economic Development Based on a Variable Coefficient Model

This paper studies the relationship between the level of national education and economic development in 31 provinces and cities in China from 2012 to 2019. Principal component analysis is used to comprehensively evaluate the level of national education, on the basis of which a variable coefficient model is tested and a constant coefficient model is established for comparison. The results show that: (1) there is a co-integration relationship between the level of national education and economic development, i.e. the two are in equilibrium in the long run. (2) In some provinces and cities in China, economic development is positively correlated with the level of national education, and some provinces and cities are negatively correlated. (3) Economic development has different effects on the level of national education in the east, middle and west. (4) Economic development and national education level are positively correlated in the average sense in China.
Joint generative and camera-aware clustering for unsupervised domain adaptation on person re-identification

Existing supervised person re-identification (Re-ID) methods demonstrate excellent performance. However, their performances suffer degradation when tested on an unseen different distributed domain. Generative adversarial network-based (GAN-based) and clustering- or pseudolabel-based methods are proposed to alleviate this problem. Due to the transfer scheme and the ignorance of correlations between the style-transferred and the original target images, the performance of GAN-based methods is unsatisfactory. We resolve these problems by jointly employing a generative strategy and performing camera-aware clustering for the target domain. Style-transferred images are generated from source cameras to target cameras, and then they are merged into the target domain selectively after exploiting their domain-specific discriminative information. To reduce the noise in generated images, we propose a domain-level boundary separation loss to group the transferred images and push them away from the original target images. The camera-level neighborhood-based clustering is proposed to learn well-clustered features in a camera-aware manner. Extensive experiments on two commonly used person Re-ID datasets demonstrate that our proposed method can achieve state-of-the-art performance.
Consensual based classification as emergent decisions in a complex system

In massive multi-agent systems that are used to model some complex systems, emergence is a key feature that allows to model high-level states of such systems.According to this perspective, the work we introduce in this paper entails the handling of emergence in massive multi-classifiers that we consider as complex systems.We aim to build a collaborative system for supervised data classification that we expect to provide better performance, compared to conventional classifiers.Modeled as a multi-agent system, the massive multi-classifier is composed of a high number of agents that are interconnected according to a given neighborhood.Each agent plays the role of a weak classifier.At the micro-level, the elementary interaction between agents consists of combining their respective classification results.Every agent, according to the majority vote rule, combines its result with those of its neighbors by taking into account their respective performances.This process is iterated continuously in a cyclic manner within the neighborhood of each agent.Therefore, a complex dynamic will be created within the system.After a certain time, this complex dynamic stabilizes, allowing the exhibition of an emergent structure that will be observed at the macro-level and is considered as a consensual class prediction for the data we want to classify.Obtained experimental results and the comparison with conventional classifiers show the potential of the approach to enhance classification and to be an alternative for classifier combination and aggregation.