Reviewerly/exHarmony huggingface dataset:
Pengembangan video animasi powtoon sebagai media pembelajaran linguistik jarak jauh

Learning media innovation is important to support student learning success, one of which is the development of Powtoon media. This study aims to develop distance learning media in the form of animated Powtoon videos that will be used to visualize linguistic phenomena in society in linguistic learning and examine the level of feasibility. Research and Development is carried out using the ADDIE model which consists of stages of analysis, design, development and implementation, stage I revision, and evaluation. This activity was carried out by testing on 30 respondents with the aim of testing the revised product according to expert input to test the readiness of the product to be used in learning Linguistics in distance classes. This research and development resulted in 13 animated videos which were used as Linguistics learning media. Aspects of material, visual communication, accessibility and benefits were assessed as Very Appropriate by material experts, media experts, and respondents in small group and large group trials, with an achievement value of 95.2%. This value is obtained from the calculation of the results of the questionnaire which is then compared with the product feasibility table which is used as a guide for the final results in this research and development.
Sentimental Analysis on Live Twitter Data

Abstract: The entire world is transforming quickly under the present innovations. The Internet has become a basic requirement for everybody with the Web being utilized in every field. With the rapid increase in social network applications, people are using these platforms to voice them their opinions with regard to daily issues. Gathering and analyzing peoples’ reactions toward buying a product, public services, and so on are vital. Sentiment analysis (or opinion mining) is a common dialogue preparing task that aims to discover the sentiments behind opinions in texts on varying subjects. In recent years, researchers in the field of sentiment analysis have been concerned with analyzing opinions on different topics such as movies, commercial products, and daily societal issues. Twitter is an enormously popular microblog on which clients may voice their opinions. Opinion investigation of Twitter data is a field that has been given much attention over the last decade and involves dissecting “tweets” (comments) and the content of these expressions. As such, this paper explores the various sentiment analysis applied to Twitter data and their outcomes.
Research on Subject Service based on Subject Guide and Subject Librarian of Thirty-three University Libraries

The discipline services of University and professional libraries are developing rapidly, but there are also some difficulties in practice, which are mainly reflected in the planning and content of discipline services, the focus of discipline services, the role of discipline librarians, the construction of talent team and the practice of discipline services. This study takes the libraries of thirty-three universities that have entered the Times World University Ranking in 2021 and the top 50 universities in QS World University Ranking in 2021 as the research object. Starting with the discipline service of University Libraries in China, this paper finds the similarities and differences with the discipline service of foreign university libraries, and draws lessons from the discipline guides and discipline librarians of these university libraries. This paper summarizes some enlightenment, guides China's University Libraries to better carry out discipline services, and has reference significance for the improvement and development of domestic library discipline services.
Peer Review Statement

All papers published in this volume have been reviewed through processes administered by the Editors. Reviews were conducted by expert referees to the professional and scientific standards expected of a proceedings journal published by IOP Publishing. • Type of peer review : Single Anonymous • Conference submission management system : Morressier • Number of submissions received : 17 • Number of submissions sent for review : 17 • Number of submissions accepted : 13 • Acceptance Rate (Submissions Accepted / Submissions Received × 100) : 76.5 • Average number of reviews per paper : 2 • Total number of reviewers involved : 8 • Contact person for queries : Name : Dr. Alexander A. Iskandar Email : iskandar@fi.itb.ac.id Affiliation : Institut Teknologi Bandung, Indonesia
Actualizing Learning English Grammar Strategy Using New Inventory for University Students

Learning grammar strategies have been explored by students and teachers. Moreover, research on this issue has been done by several researchers. However, new inventory to measure learning English grammar strategy has been developed and not implemented to identify students’ learning strategy. Thus, the present study aimed to implement and identify the students’ English learning grammar strategy by using new inventory. Besides, this study also wanted to know the challenges of students in implementing those strategies. This study used Mixed method with sequential explanatory. The participants of this research were 30 students of English Language Department in one of the universities in Bengkulu. The instrument of this study used questionnaire of Grammar Learning Strategy Inventory (GLSI) and the interview guideline. Those instruments have been validated by two expert judgments and tried out to another class. The quantitative data were analysed by using simple statistic calculation and using percentage for every learning strategy type. However, the qualitative data analysis comprised several steps namely data collection, data condensation, data display, and conclusion. The result shows that students used all strategies in learning grammar, but the dominant one is cognitive strategy, while the least one is social strategy. The challenges in implementing learning strategy or in learning grammar were poor knowledge of grammar, ineffective time management, less group work, and less sociable because of Covid-19.
Integrating Mind-Mapping Collaborated with Think-Pair-Share to Teach Reading Comprehension in Descriptive Text

The study aims at explaining the effectiveness of integrating Mind-Mapping collaborated with Think-Pair-Share to teach reading comprehension in descriptive text. It employed quantitative method using control-group of non-equivalent of quasi experimental research design. The study was conducted at eighth graders of a private junior high school in Batang, Indonesia. The research procedure used pretest, post-test, and documentation. Data analysis technique applied t-test formula SPSS 25 version program. The finding shows that experimental class taught by Mind-Mapping collaborated with Think-Pair-Share has higher achievement in posttest than control class taught by traditional method. The mean post-test of experimental class, 85.00 is higher than that of control class namely 49.50. The conclusion infers that Mind-Mapping collaborated with Think Pair Share is effective to teach reading in descriptive text. It can be recommended to English teachers for using this learning model in EFL classroom in order to create meaningful and joyful learning.
Pendampingan Pelatihan Penulisan Artikel Populer Berbasis Manuskrip Jawa bagi Anggota Komunitas Jangkah Nusantara

The Jangkah Nusantara Community is one of the manuscript-loving communities that has successfully launched a website with the address Jangkah.id. The site has several menus in the form of news, popular articles, information about scriptoriums, manuscript researchers, etc. This web is certainly useful, for the community itself and also for people in general, as a source of information that can distribute knowledge related to ancient manuscripts and their contents. However, since its launching, not many posts have been accessible in it. The approach to community stakeholder results in finding the problem that the members of the community still find it difficult to write popular article on the website. At the same time, they also have difficulties in reading Javanese sources. For these reasons, community service activities are conducted in two forms of training, namely: (1) Translation Class; and (2) Popular Writing Class, by inviting competent speakers/presenters. The objectives of these activities are (1) to develop the potential of the members of the Jangkah Nusantara Community as actors in the recontextualization of Javanese manuscript studies to wider community; and (2) to initiate internal community activities that aim at increasing the knowledge and capacity of its members.
THE INFLUENCE OF YOUTUBE VIDEOS ON LISTENING ACHIEVEMENT OF THE SECOND-GRADE STUDENTS AT MA GUPPI

Listening skills have a significant part in learning English because receiving language input is a major skill that is important when learning a language. In addition, using YouTube videos are remarkable for enhancing the students’ listening achievements in the classroom. The research questions are: 1) how are the students’ listening achievements of the second grade students at MA Guppi Samata before learning listening using YouTube videos? 2) How are the students’ listening achievements of the second grade students at MA Guppi Samata after learning listening using YouTube videos? 3) Is there any significant difference of influence before and after using YouTube videos of the second grade at MA Guppi Samata? The design of the research was quantitative research which is pre-experimental research with one group pre-test and post-test design. The population was 50 students and the sample was chosen 25 students from XI B as the purposively. Tests were used as the instrument. All the collected data were analysed using the SPSS application showing all the students at MA Guppi Samata Gowa gained a 46.92 mean score, which convened as low classification in pre-test their first listening test. After some treatments, the mean score was increased 68.44 which classified as a reasonable classification. The degree of freedom (df) 24 pointed the students' listening achievement with t-test value (12.036) which turned out higher than the t-table value (2.064). This result analysis presented that this research's impact on the students effectively increased their scores and comprehension.
Engineering of spontaneous emission in free space via conditional measurements

We study the collective spontaneous emission of three identical two-level atoms initially prepared in the excited states by measuring Glauber's third-order photon correlation function. Assuming two atoms at subwavelength distance from each other such that they are subject to the dipole-dipole interaction while the third one is located several wavelengths away, we observe super- and subradiant decay alike, depending on the direction of observation. Unlike the case where no remote atom is introduced or no conditional measurements are performed, the spontaneous emission behavior of the conditioned three-atom system is strongly modified, i.e., differing from the single-atom and the canonical two-atom configuration. The conditional measurements associated with the three-photon correlation function in combination with the dipole-dipole interaction between the adjacent atoms lead to quantum interference among the different decay channels allowing one to engineer the spontaneous emission in space and time.
Evaluating The Usability of Three of The Lowermost Krg/Iraq University Websites in Webometrics Based on User Perspective

In the higher education sector, web based facilities perform a vital aspect to offer success of an academic institution, due to the users depend on the universities websites to achieve different academic instructions. Simultaneously, users may face many usability difficulties while having access to the websites. For that reason, this research investigates user based testing and questionnaires methods from user perspective to evaluate three of lowermost university websites in KRG/Iraq according to Ranking Web of Universities (webometrics); university of Raparin, university of Garmian, and university of Halabja. Thirty participants contribute to implementing six tasks of user-based methods and ten questions of questionnaire approach. Based on the analysing process, the accuracy of universities websites are; 86.7%, 79.5%, and 61.1% for each University of Raparin, University of Halabja, and University of Garmian respectively. Moreover, user satisfaction for the University of Raparin is 3.59, while 3.24 and 3.01 are the rates of satisfaction for University of Halabja and University of Garmian.
Pengenalan dan Pelatihan Tentang Ilmu Mawaris

In general, Muslims regarding the distribution of inheritance and calculation procedures lack understanding and the difficulty of also getting experts in the field of inheritance distribution according to Islamic law (faraidh), this is an issue for the Muslim community, especially for heirs who want to divide inheritance according to law Islam. The author uses backward chaining methods in designing expert systems. The result of this research is the design of an expert system for dividing inheritance that can be used by the general public to help Islam solve the problem of calculation &amp; inheritance.
InvPT: Inverted Pyramid Multi-task Transformer for Dense Scene Understanding

Multi-task dense scene understanding is a thriving research domain that requires simultaneous perception and reasoning on a series of correlated tasks with pixel-wise prediction. Most existing works encounter a severe limitation of modeling in the locality due to heavy utilization of convolution operations, while learning interactions and inference in a global spatial-position and multi-task context is critical for this problem. In this paper, we propose a novel end-to-end Inverted Pyramid multi-task Transformer (InvPT) to perform simultaneous modeling of spatial positions and multiple tasks in a unified framework. To the best of our knowledge, this is the first work that explores designing a transformer structure for multi-task dense prediction for scene understanding. Besides, it is widely demonstrated that a higher spatial resolution is remarkably beneficial for dense predictions, while it is very challenging for existing transformers to go deeper with higher resolutions due to huge complexity to large spatial size. InvPT presents an efficient UP-Transformer block to learn multi-task feature interaction at gradually increased resolutions, which also incorporates effective self-attention message passing and multi-scale feature aggregation to produce task-specific prediction at a high resolution. Our method achieves superior multi-task performance on NYUD-v2 and PASCAL-Context datasets respectively, and significantly outperforms previous state-of-the-arts. The code is available at https://github.com/prismformore/InvPT
VPFusion: Joint 3D Volume and Pixel-Aligned Feature Fusion for Single and Multi-view 3D Reconstruction

We introduce a unified single and multi-view neural implicit 3D reconstruction framework VPFusion. VPFusion attains high-quality reconstruction using both - 3D feature volume to capture 3D-structure-aware context, and pixel-aligned image features to capture fine local detail. Existing approaches use RNN, feature pooling, or attention computed independently in each view for multi-view fusion. RNNs suffer from long-term memory loss and permutation variance, while feature pooling or independently computed attention leads to representation in each view being unaware of other views before the final pooling step. In contrast, we show improved multi-view feature fusion by establishing transformer-based pairwise view association. In particular, we propose a novel interleaved 3D reasoning and pairwise view association architecture for feature volume fusion across different views. Using this structure-aware and multi-view-aware feature volume, we show improved 3D reconstruction performance compared to existing methods. VPFusion improves the reconstruction quality further by also incorporating pixel-aligned local image features to capture fine detail. We verify the effectiveness of VPFusion on the ShapeNet and ModelNet datasets, where we outperform or perform on-par the state-of-the-art single and multi-view 3D shape reconstruction methods.
ScoreNet: Learning Non-Uniform Attention and Augmentation for Transformer-Based Histopathological Image Classification

Progress in digital pathology is hindered by high-resolution images and the prohibitive cost of exhaustive localized annotations. The commonly used paradigm to categorize pathology images is patch-based processing, which often incorporates multiple instance learning (MIL) to aggregate local patch-level representations yielding image-level prediction. Nonetheless, diagnostically relevant regions may only take a small fraction of the whole tissue, and current MIL-based approaches often process images uniformly, discarding the inter-patches interactions. To alleviate these issues, we propose ScoreNet, a new efficient transformer that exploits a differentiable recommendation stage to extract discriminative image regions and dedicate computational resources accordingly. The proposed transformer leverages the local and global attention of a few dynamically recommended high-resolution regions at an efficient computational cost. We further introduce a novel mixing data-augmentation, namely ScoreMix, by leveraging the image's semantic distribution to guide the data mixing and produce coherent sample-label pairs. ScoreMix is embarrassingly simple and mitigates the pitfalls of previous augmentations, which assume a uniform semantic distribution and risk mislabeling the samples. Thorough experiments and ablation studies on three breast cancer histology datasets of Haematoxylin &amp; Eosin (H&amp;E) have validated the superiority of our approach over prior arts, including transformer-based models on tumour regions-of-interest (TRoIs) classification. ScoreNet equipped with proposed ScoreMix augmentation demonstrates better generalization capabilities and achieves new state-of-the-art (SOTA) results with only 50% of the data compared to other mixing augmentation variants. Finally, ScoreNet yields high efficacy and outperforms SOTA efficient transformers, namely TransPath and SwinTransformer.
Application of POA in Teaching Mode of College English Writing Based on Artificial Intelligence

Improving college students&#x2019; English writing ability is an urgent task for college English teaching in China. In the context of educational informatization 2.0, we explore the application of "POA (Production-oriented Approach)" in college English writing teaching based on the artificial intelligence (AI) technology of "PIGAI.ORG". Two parallel classes of 157 students participated in the one-semester teaching experiment. Through data analysis by using SPSS software, with the help of pre- and post-test papers, the results show that POA provides an effective theoretical support for the teaching mode of college English writing, and AI provides strong technological support. The questionnaire and interviews also indicate students&#x2019; recognition and acceptance of the teaching mode. This research result has enriched the empirical research results of POA, and also provided enlightenment for the reform and development of college English teaching in China.
<b>plot3logit</b>: Ternary Plots for Interpreting Trinomial Regression Models

This paper presents the R package plot3logit which enables the covariate effects of trinomial regression models to be represented graphically by means of a ternary plot. The aim of the plot is helping the interpretation of regression coefficients in terms of the effects that a change in values of regressors has on the probability distribution of the dependent variable. Such changes may involve either a single regressor, or a group of them (composite changes), and the package permits both cases to be handled in a user-friendly way. Moreover, plot3logit can compute and draw confidence regions of the effects of covariate changes and enables multiple changes and profiles to be represented and compared jointly. Upstream and downstream compatibility makes the package able to work with other R packages or applications other than R.
The online modality in the school performance of 8th grade students in the subject of mathematics

At present, school performance has been affected by severalfactors, one of these is the online modality, which has been imposed due tothe pandemic of covi-19 in the institutions, without having a previouspreparation of teachers and students to face this modality. The objective ofthis research is to determine the incidence of the online modality in the schoolperformance of 8th grade students in the subject of mathematics at theFrancisco Huerta Rendón school in a field study, for the development of amobile application; scientific methods were applied both theoretical andempirical, by applying as instruments a guide of observation of entry wherethe problem was detected, in turn surveys and interviews were applied tostudents, teachers and school principal, it was revealed how satisfied werethose involved in this modality given, with a total sample of 121 students, in addition to the participation of teachers and vice principal of the school already mentioned. The students themselves suggested that they need helpsuch as the proposal put forward in this study to create a mobile applicationcontaining the most complex topics in the subject of mathematics forreinforcement and improvement of school performance.
Application of Evaluation Scale for Evaluating Chemical Experiments

In this work, in view of the disadvantages of the previous assessment system based on summative evaluation of basic chemical experiments, an evaluation scale is proposed to evaluate the students' operation process in combination with an online platform.A comparative practice study of a traditional teaching class and an experimental teaching class reveals that the students' learning ability is improved and that the operation error rate is reduced according to the students' feedback results on the evaluation scale.Thus, the learning effect of students is significantly improved.Therefore, the use of the evaluation scale to evaluate operations in experimental course helps formulate the teaching objectives, which is conducive to the training of students and improvement of their experimental skills.