Reviewerly/exHarmony huggingface dataset:
English Teacher Strategies in Writing Activities at the Eighth Grade of Junior High Schools at Kembayan Sub-district

This research aims to describe the English teachers’ strategy in writing activities at the eighth grade of Junior High Schools at Kembayan sub-district and how the English teachers implement the strategy. This research used a descriptive qualitative design. The data were gathered from observation, interviews, and documentation. The result of this research showed that there were four teachers’ strategies for writing activities in the eighth grade. The strategies were guided writing strategy, repeating strategy, cooperating with peers strategy, and translation strategy. In implementing the teaching strategy, the English teacher asked the students to write some expressions and dialogues depending on the strategy used. The teacher who used the repeating strategy asked students to copy the expressions or dialogues in the textbook into their workbooks. For the translation strategy, the teacher asked students to translate expressions or dialogues and then asked them to write the translation in the workbook. For the guided writing strategy, the teacher wrote a dialogue on the whiteboard and asked students to write a dialogue using the random words given by following the template on the whiteboard. For the cooperating with peers strategy, the teacher asked students to discuss in a group and then write a dialogue. These strategies could help teachers in teaching students and also encourage students to participate in the teaching and learning process actively.
Information System Planning Integrated database of training in food and nutrition at SEAMEO RECFON Using Togaf Architecture

Southeast Asian Ministers of Education Organization Regional Center for Food and Nutrition (SEAMEO RECFON), is an organization of Southeast Asian ministers of education that focuses on food and nutrition. Currently, the application of SI / IT in the SEAMEO RECFON environment is not optimal, referring to the data base system that has not been integrated so that data and information exchange is not effective, the SI / IT investment made has also not given a good return, the training program in the field of food and nutrition each year is consistently not optimal, and several performance indicators are found not to meet their targets. Therefore, enterprise architecture planning is needed at SEAMEO RECFON which aims to formulate the principles and fundamentals of SEAMEO RECFON in accordance with the direction of its goals so as to produce healthy business processes, systems that can support training activities in the fields of food and nutrition, operations and infrastructure that can support the system to run well. This enterprise architecture planning is made using TOGAF (The Open Group of Architecture Framework) version 9.2 with the ADM (Architecture Development Method) method. This enterprise architecture planning produces a map of the main activities and support for food and nutrition training at SEAMEO RECFON, stakeholders, their focus, business objectives and basic principles, blueprints for business architecture targets, information systems architecture, technology architecture, and application implementation roadmap.
SOVIET WRITER SAMUEL ЕIDLIN (BASED ON THE MATERIALS OF THE PERSONAL FUND)

The article examines the biography of the children's writer, satirist and member of the Union of Writers of the USSR S.M. Eidlin, gives a description of his creative activity, reveals the structure, content and informational value of the documents of S.M. Eidlin's personal fund in the Central State Archive of the Samara region, contains a brief primary analysis of the composition of the fund.To date, a complete source analysis of the documents of the personal personal fund of Samuel Matveevich Eidlin has not been carried out.
THE EARLY YEARS OF THE SARATOV SCIENTIFIC ARCHIVIAL COMMISSION (1887-1888S)

The early years of the Saratov Scientific Archival Commission (SSAK) have not attracted much of researchers’ attention. However, based on the published materials, it can be concluded that from its first years of existence the Commission intensively worked in all areas of its activities. The aggregation of documents that came from various institutions began, and their expertise started. An approach to the expertise was worked out. The library and the museum of the Commission were being assembled; archaeological excavations were organised. In the first two years the Commission membership expanded significantly.
PERSONAL FUNDS OF THE CENTRAL STATE ARCHIVE OF THE SAMARA REGION. ANALYSIS OF NEW ARRIVALS

The material of the article contains a classification, review and brief source analysis of funds with documents of personal origin received for permanent storage in the Central State Archive of the Samara Region (TsGASO) in recent years. The performed analysis allows us to present the information potential of the documents deposited according to the author's principle, their chronological framework, the life path and professional composition of the fund creators, the categories of documents of specific funds. The content of the analysis will help researchers navigate in finding and using a significant layer of archival documents.
FROM «ANALOGUE» TO «DIGITAL»: PROBLEMS OF IMPLEMENTATION OF ELECTRONIC ARCHIVES

The article discusses theoretical and applied problems of storing technotronic documentation. The analysis of information properties of retrospective electronic documents is presented. The specific features of digital documents are highlighted: machine-readable, reference copying, non-attachment to the carrier. The characteristic of methods for ensuring the reliability and authenticity of archival documentation is given. The necessity of developing a strategy for longterm storage of electronic resources at the local (intra-organizational) level is substantiated.
PECULIARITIES OF DIGITALIZATION IN THE ARCHIVE WITH A POLY-TYPE COMPOSITION OF DOCUMENTS (BY THE EXAMPLE OF THE RUSSIAN STATE ARCHIVE OF SCIENTIFIC AND TECHNICAL DOCUMENTATION)

The article discusses the features of the organization of the digitalization of the activities of the archive. On the example of the Russian State Archive of Scientific and Technical Documentation, practical experience in digitizing inventories is described in detail. The question of using and adapting catalogs and databases already available in the archive to solve the problem is considered.
ARCHIVAL FUND AS A HISTORICAL SOURCE

The author sees his task in showing the influence of V.N. Avtokratova about the archival fund on modern methods of research of mass sources The author concludes that acceptance by the scientific community of historians of thought V.N. Avtokratov that in the archival fund there are connections that have arisen in the process of documenting would undoubtedly accelerate the development of the huge documentary heritage of the past stored in our archives
DOCUMENTARY LEGACY OF N.A. MELGUNOV OF THE 30-50'S OF THE XIX CENTURY

The article provides an overview of the published and unpublished documentary heritage of the writer and journalist Nikolai Alexandrovich Melgunov. Special attention is paid to his unpublished letter about the death of the famous historian T. N. Granovsky.
PERSONAL ARCHIVE FUNDS IN EDUCATION AND CULTURAL ACTIVITIES OF CENTRAL STATE ARCHIVE OF SAMARA REGION

The article deals with using personal documents of Central state archive of Samara region in education and cultural activities. Papers of outstanding public persons, actors, writers, scientist are useful in social media, contributions, exhibitions. Abundantly contributions of some personal archive funds is especially important
ClassPoint Application for Enhancing Motivation in Communication among ESL Young Learners

Teachers and students have been exposed to an influx of educational technology in the classroom since the outbreak of COVID-19. Young students require constant stimulation, especially when learning English; otherwise, they will lose interest. The ClassPoint application (hereafter referred to as the app) is an interactive learning tool that can be tailored to the needs of individual students. This research examines how the ClassPoint app motivates students of English as a Second Language to learn English. This research employed a mixed-method design with a sample of thirty-five Year 3 primary students. They responded to a 15-item questionnaire prior to the implementation of the app, and researchers completed an observation checklist during the implementation. Ten students were randomly selected to participate in a semi-structured interview following the app's performance. The data were then analysed using descriptive statistics and thematic analysis. The findings identified several reasons why Year 3 students struggle to learn English, such as a lack of motivation towards the language and ineffective teaching strategies.The ClassPoint app also increased students' engagement and motivation to learn English. Students were more engaged in learning English when the ClassPoint app was utilised. Results indicate that interactive teaching and learning methods increase second-language acquisition motivation among students.
Strategi Pengembangan Perpustakaan Digital UIN Alauddin Makassar

The purpose of this study is to explain how the digital library of UIN Alauddin Makassar and its development focuses on developing digital collections and analyzing the constraints and challenges faced by the UIN Alauddin Makassar university library. Digital library development. This study uses a qualitative descriptive case study with the stages of observation, interviews, and documentation as research tools. Through this research, we obtained results that show the development of the digital library of UIN Alauddin Makassar. It can be concluded that the Library Center has made or experienced significant progress. This can be seen from the availability of collection data, types of collections and digital library application management systems.
From vision to action: Catalyzing the U.S. Repository Network

O pen infrastructure is foundational to the conduct of open research, and repositories are a key component of open research infrastructure, providing an avenue for the open dissemination of research outputs.Repositories also play a crucial role in increasing equity of access and supporting compliance with funder policies for open access.The U.S. Repository Network (USRN) seeks to support the nation's open research repositories in cementing their position as an essential component of our national research infrastructure.In summer 2021, the Scholarly Publishing and Academic Resources Coalition (SPARC) announced its partnership with the Confederation of Open Access Repositories (COAR) to catalyze a US repository network and its intention to hire a visiting program officer to lead that work. 1 I was lucky enough to secure that role and began work in September 2021.SPARC is a nonprofit advocacy organization driven by the belief that sharing knowledge is a human right.SPARC's membership includes more than 200 libraries and academic organizations across North America that share the desire to create more open and equitable systems of research and education. 2 COAR is an international association with 155 members and partners representing libraries, universities, research institutions, government funders, and others.COAR brings together individual repositories and repository networks to build capacity, align policies and practices, and act as a global voice for the repository community. 3 To further its Next Generation Repositories vision, COAR launched the Modernizing the Global Repository Network initiative. 4 Through its Modernizing initiative, COAR identified institutional silos and the lack of a cohesive, collaborative approach to repositories as the greatest challenges to catalyzing a US repository network.SPARC and COAR came together to address these challenges and create the USRN.The USRN is envisioned as an inclusive community committed to advancing repositories through advocacy, good practices, and community building.In this context, "US repositories" refers to all open research repositories based in the US regardless of content, host, or platform.That is, repositories containing articles, data, gray literature, and emerging forms of scholarship; repositories hosted by higher education institutions, research centers, or other nonprofit organizations; and repositories using open source or vended platforms, are considered part of this network.All such repositories are welcome to participate in the USRN as we seek to build value for all repositories in the US.
The Problematic of Arabic Emphatic &amp; Guttural Segmental Sounds among Malay Students

The Arabic language is made up of a set of emphatic and guttural consonants that exert a phonological influence on adjacent segment sounds by moving the tongue's root back towards the pharynx.This paper discusses the pronunciation difficulties among Malaysian students who learn Arabic words.There are three approaches to account for the production and perception of Arabic segmental difficulties namely speech perception, phonology and phonetic.Data for this research were obtained from two sources: Shehata's study (2018) and observations of Malaysian mispronunciation which were recorded.Data analysis also displays five phonological aspects of mispronunciation involving: substitution, addition, interference, omission and vowel changes.A number of opaque and difficult phonemes of Arabic including : / t ‫,/ت‬ / θ ‫ث‬ / , / ħ ‫/ح‬ , / ð ‫/ذ‬ , / sˤ ‫,/ص‬ dˤ ‫,/ض‬ / ðˤ ‫ظ‬ / , /ʕ ‫/ع‬ , / ɣ ~ ʁ ‫غ‬ / , /q ‫ق‬ /, / k ‫ك‬ /,that can be unfamiliar for Malay students.The paper concludes with findings that indicated Malay Arabic is mostly phonetic rather than phonological.Arabic emphasis spread among Malay students can be a syllabic words or an entire phonological word.Arabic pronunciation difficulties has its implications to other researchers in phonetics and future phonological theory.Malay phonological Arabic system needs more intensive highlights studies for further researchers.
Git and GitHub Application Training Program to Support Vocational High School Students in Collaborative Computer Programming Learning

The training program aims to improve students’ ability to operate the Git/GitHub application in collaborative computer programming learning. The partners who are the subject of training activities are three Vocational High Schools of the Computer and Informatics Engineering Expertise Program (SMK TKI) in Malang City and Batu City, East Java Province, Indonesia. The training program was developed with the ASSURE model. The learning strategy used by the training team is peer-to-peer learning. Each vocational school determines 40 students as participants in the training program. Training activity success data were collected using knowledge tests, performance tests, self-evaluation sheets, and questionnaires. The analysis design uses One-Group Pretest-Posttest. The data were analyzed with the One Sample T-test technique. The Posttest value (M=74.88; SD=6.68) is higher than the pretest (M=46.62; SD=9.28). One Sample T-test analysis on the Pretest and Posttest scores yielded t(119)=26.28; p 0.01; d=3.50. The Pretest score significantly differs from the Posttest score, where the effect size score is 3.50, and the p-value is smaller than 0.05 (α).
ImageNet Pre-training Also Transfers Non-robustness

ImageNet pre-training has enabled state-of-the-art results on many tasks. In spite of its recognized contribution to generalization, we observed in this study that ImageNet pre-training also transfers adversarial non-robustness from pre-trained model into fine-tuned model in the downstream classification tasks. We first conducted experiments on various datasets and network backbones to uncover the adversarial non-robustness in fine-tuned model. Further analysis was conducted on examining the learned knowledge of fine-tuned model and standard model, and revealed that the reason leading to the non-robustness is the non-robust features transferred from ImageNet pre-trained model. Finally, we analyzed the preference for feature learning of the pre-trained model, explored the factors influencing robustness, and introduced a simple robust ImageNet pre-training solution. Our code is available at https://github.com/jiamingzhang94/ImageNet-Pretraining-transfers-non-robustness.
Task-Specific Scene Structure Representations

Understanding the informative structures of scenes is essential for low-level vision tasks. Unfortunately, it is difficult to obtain a concrete visual definition of the informative structures because influences of visual features are task-specific. In this paper, we propose a single general neural network architecture for extracting task-specific structure guidance for scenes. To do this, we first analyze traditional spectral clustering methods, which computes a set of eigenvectors to model a segmented graph forming small compact structures on image domains. We then unfold the traditional graph-partitioning problem into a learnable network, named Scene Structure Guidance Network (SSGNet), to represent the task-specific informative structures. The SSGNet yields a set of coefficients of eigenvectors that produces explicit feature representations of image structures. In addition, our SSGNet is light-weight (56K parameters), and can be used as a plug-and-play module for off-the-shelf architectures. We optimize the SSGNet without any supervision by proposing two novel training losses that enforce task-specific scene structure generation during training. Our main contribution is to show that such a simple network can achieve state-of-the-art results for several low-level vision applications including joint upsampling and image denoising. We also demonstrate that our SSGNet generalizes well on unseen datasets, compared to existing methods which use structural embedding frameworks. Our source codes are available at https://github.com/jsshin98/SSGNet.
Gradient-Based Graph Attention for Scene Text Image Super-resolution

Scene text image super-resolution (STISR) in the wild has been shown to be beneficial to support improved vision-based text recognition from low-resolution imagery. An intuitive way to enhance STISR performance is to explore the well-structured and repetitive layout characteristics of text and exploit these as prior knowledge to guide model convergence. In this paper, we propose a novel gradient-based graph attention method to embed patch-wise text layout contexts into image feature representations for high-resolution text image reconstruction in an implicit and elegant manner. We introduce a non-local group-wise attention module to extract text features which are then enhanced by a cascaded channel attention module and a novel gradient-based graph attention module in order to obtain more effective representations by exploring correlations of regional and local patch-wise text layout properties. Extensive experiments on the benchmark TextZoom dataset convincingly demonstrate that our method supports excellent text recognition and outperforms the current state-of-the-art in STISR. The source code is available at https://github.com/xyzhu1/TSAN.
The

Background:The era of the COVID-19 pandemic has triggered education for a learning innovation to keep it running safely, effectively and efficiently.Student practical learning needs to be facilitated by the existence of a virtual laboratory.The virtual electronic patient medical record laboratory is an integration of e-learning systems and health information systems.This system is a recommendation for independent practicum activities for health students, especially medical records and health information.The research objective is to design an electronic laboratory medical record system to increase access to independent learning. Subjects and Methods: The research design is an action research conducted at PoltekkesTasikmalaya with stages of diagnosis, planning, action and evaluation system.The evaluation was carried out to see the level of usability of the system for users, namely students of medical records and health information.54 respondents who filled out the online usability questionnaire using the total usability scale (SUS) method.Results: the electronic patient record laboratory system was successfully built up to the mockup design stage.This system is acceptable and feasible to be used as a recommendation for a virtual laboratory practice model for students.The usability score obtained 61 which means the marginal high and "ok" of adjective rating to use.Conclusions: the system gets a high marginal usability rating and ok to use.System design to be more attractive and the interaction between features that need to be developed.It is recommended that this system be developed for mobile-based applications so that it can make it easier and increase motivation for practical learning for students independently.
Cross-Category Highlight Detection via Feature Decomposition and Modality Alignment

Learning an autonomous highlight video detector with good transferability across video categories, called Cross-Category Video Highlight Detection(CC-VHD), is crucial for the practical application on video-based media platforms. To tackle this problem, we first propose a framework that treats the CC-VHD as learning category-independent highlight feature representation. Under this framework, we propose a novel module, named Multi-task Feature Decomposition Branch which jointly conducts label prediction, cyclic feature reconstruction, and adversarial feature reconstruction to decompose the video features into two independent components: highlight-related component and category-related component. Besides, we propose to align the visual and audio modalities to one aligned feature space before conducting modality fusion, which has not been considered in previous works. Finally, the extensive experimental results on three challenging public benchmarks validate the efficacy of our paradigm and the superiority over the existing state-of-the-art approaches to video highlight detection.
Grouped Knowledge Distillation for Deep Face Recognition

Compared with the feature-based distillation methods, logits distillation can liberalize the requirements of consistent feature dimension between teacher and student networks, while the performance is deemed inferior in face recognition. One major challenge is that the light-weight student network has difficulty fitting the target logits due to its low model capacity, which is attributed to the significant number of identities in face recognition. Therefore, we seek to probe the target logits to extract the primary knowledge related to face identity, and discard the others, to make the distillation more achievable for the student network. Specifically, there is a tail group with near-zero values in the prediction, containing minor knowledge for distillation. To provide a clear perspective of its impact, we first partition the logits into two groups, i.e., Primary Group and Secondary Group, according to the cumulative probability of the softened prediction. Then, we reorganize the Knowledge Distillation (KD) loss of grouped logits into three parts, i.e., Primary-KD, Secondary-KD, and Binary-KD. Primary-KD refers to distilling the primary knowledge from the teacher, Secondary-KD aims to refine minor knowledge but increases the difficulty of distillation, and Binary-KD ensures the consistency of knowledge distribution between teacher and student. We experimentally found that (1) Primary-KD and Binary-KD are indispensable for KD, and (2) Secondary-KD is the culprit restricting KD at the bottleneck. Therefore, we propose a Grouped Knowledge Distillation (GKD) that retains the Primary-KD and Binary-KD but omits Secondary-KD in the ultimate KD loss calculation. Extensive experimental results on popular face recognition benchmarks demonstrate the superiority of proposed GKD over state-of-the-art methods.