Reviewerly/exHarmony huggingface dataset:
Pengaruh Penggunaan Video Animasi Terhadap Peningkatan Keterampilan Menyimak Teks Cerita Rakyat

This study aims to describe the effect caused after using animated video-based learning media on class X students of SMK Negeri 6 Pangkep. This research is a pre-experimental research with a quantitative approach, the population in this study were all students of class X SMK Negeri 6 Pangkep. Data collection techniques in this study were written tests and data analysis techniques, namely normality tests and hypothesis tests using the SPSS 23 computer program: student learning outcomes before using animated videos obtained an average value of 30.86. Student learning outcomes after using animated videos obtained an average value of 72.90. The use of animated videos can be concluded to have an effect on improving listening skills and learning outcomes of class X students of SMK Negeri 6 Pangkep in the 2022/2023 school year.
Action Research: Video-assisted Guided Conversation to Enhance Senior Secondary Students’ Speaking Skill

In reality, many English learners find it difficult to speak and to express their idea in English. Knowing less vocabulary, lack of self confidence, and pronunciation’s error have mostly become the most popular reasons of the students to always keep their briliant ideas to speak. It was proven by the current research at one of senior secondary school in Jember which the students also have the same problems as mentioned above. Therefore, the objective of this research was to enhance senior secondary students’ speaking skill. The researcher employed classroom action research as the research design. This research was conducted at one of senior high schools in Jember, East Java, Indonesia. The data were collected from 18 students in one class and from one cycle of teaching which consisted of five sessions. The cycle covered four stages, including plan, action, observation, and reflection. The result of this research showed that the students’ speaking skills were improved for nineteen percents (19%) after the implementation of video-assisted guided conversation. It was validated by the students’ average score which has improved from sixty seven to eighty. It indicates that the use of video-assisted guided conversation could enhance students speaking skills.
Online Learning Engagement in an EFL Writing Coursework: An Undergraduate Student’s Voice

This research aims to analyze the engagement of an EFL learner during an online writing course. The participant was a semester 3 student of English Education Department who had some experience and a great interest in writing skills in one of the universities in Indonesia. The data were collected through semi-structured interview and then were analyzed using thematic analysis. The finding shows that the participant has the three key aspects of learning engagement, there is behavioral, emotional, and cognitive engagement in the writing online courses. Though the participant had obstacles when involved in collaborative learning, she still managed to engage well in the online writing course in general. Thus, this study concluded that EFL learners who perform well in online collaborative writing tasks are more likely to have great engagement in online learning courses.
Research on Artificial Intelligence Empowering Teaching Reform in Higher Vocational Colleges

The development of artificial intelligence has triggered profound changes in social production relations and promoted changes in teaching methods and teaching scenarios in higher vocational colleges. At present, the intelligent teaching ability of teachers in higher vocational colleges needs to be improved, and the intelligent teaching equipment in higher vocational colleges needs to be strengthened. Higher vocational colleges should respond to the changes of the times, improve the level and ability of intelligent education in schools, and use human-machine collaboration to Innovate teaching models to promote the realization of the training goals of high-quality and high-skilled students in higher vocational colleges.
Research on the Construction Path of Innovative Teacher Team in Vocational Colleges

With the development of society and technological progress, innovation has become an important force driving social progress and development. In higher education, the construction of innovative teacher teams is an important prerequisite and foundation for cultivating innovative talents. This article takes vocational colleges as the research object, explores the path of building an innovative teacher team, in order to provide reference and reference for the construction of an innovative teacher team in vocational colleges.
Using Islamic Videos to Increase the Writing Skills of the Senior High School Students

The research aims to determine the effectiveness of Islamic Videos in increasing the students' writing skills and perceive the use of Islamic videos (History of Rasulullah). This research used Classroom Action Research (CAR); this study was located at Senior High School 1 Lasusua. The study was done on 28 September-02 November 2021. The research subject was XI IPA 2, and their total was 28. The instruments of this research were tests, observation techniques, and interviews. This research used two cycles in which every process had four steps: planning, implementing, observing, and reflecting. The researcher analyzed the observation qualitatively and then analyzed the test quantitatively. The students' mean score in cycle 1 was 74.46, while the mean score in cycle 2 was 80.21. it can be concluded that the Islamic video (history of Rasulullah) increased the students' ability to write narrative text students' learning outcomes. To overcome the lack of student mastery in writing narrative text, the researcher solved it in several ways: (1) the researcher applied an Islamic video (history of Rasulullah). (2) Doing exercise in every meeting. (3) Reviewing the current material in every meeting. Doing the action shows that students always made an improved learning activity and a vast understanding of the material. Besides that, the students felt enjoyed and fun during the learning process.
VERIFICATION OF THE MODEL AND METHOD FUNCTIONALITY FOR REMOTE HEALTH MONITORING ILLUSTRATED BY THE DEVIATIONS IN HUMAN BODY TEMPERATURE INDICATORS

The rapid development of telemedicine in the healthcare sector facilitates the active implementationof various methods and models for remote monitoring of human health indicators. Inthis regard, significant attention is paid to the development of mobile applications capable ofproviding accurate and timely monitoring of key health indicators in real-time. The aim of thisresearch is to evaluate the applicability of the proposed method and model for remote monitoringof human health indicators, and to analyze the effectiveness of the developed mobile applicationHelpMeTracker in identifying deviations in human body temperature indicators. To assess thefunctionality of the proposed health monitoring method, a comprehensive experiment was conducted,which included participants from different age categories and social groups. During theexperiment, the application was to analyze and track the dynamics of changes in human body temperatureindicators using sensors integrated into smartwatches or fitness trackers, and timelynotify about detected anomalies for the possibility of rapid response to changes in health status. The results obtained during the conducted research demonstrate that the proposed model andmethod for remote monitoring of human health indicators have a high degree of effectiveness forobserving the current health status. During the experiment, the HelpMeTracker application reliablydetected all deviations in body temperature indicators obtained from sensors of wearable devicesand successfully informed all participants of the process. Based on the obtained results, itcan be concluded that the application of the proposed approach for remote monitoring is sufficientto capture deviations in body temperature indicators, track the dynamics of changes, and form asubstantiated comprehensive assessment of human health based on the information received fromthe device sensors.
ANALISIS SISTEM PENGADAAN, PENGEMBANGAN DAN PENGENDALIAN INTERN SISTEM INFORMASI AKUNTANSI PADA PT. BANK SULSELBAR CABANG BULUKUMBA

The purpose of this study was to determine the Analysis Of The Procurement System,Development And Internal Control Of The Accounting Information System At PT. BankSulselbar Cabang Bulukumba. So that this research will provide results about howthe Sulselbar bank is doing to get the accounting information system, and how the development of the system it has used, and how to control the information bneeded, and have the right and relevant value.In this study using a qualitative approach. Where researchers directly observe. The object under study which will then describe, describe and explain the procuremen, development, and internal control of the accounting information system at Pt.Bank Sulselbar bulukumba branch. Furthermore, the data collection methods used are documentation, interviews, and library reviews.The results show that the system for procurement, development and internal control ofaccounting information systems at PT. Bank Sulselbar Cabang Bulukumba Branch, is still fully implemented at the head off office. Information systems are obtained by renting a system from a system developer which is then developed using the SLDC (System Development life Cycle) method.
Students’ Motivation in Learning English in Islamic Higher Education

In the learning process, motivation has an important role because motivation can foster interest in learning. This research will be conducted on semester 1 students of the Islamic Religious Education study program at IAIN Palopo with the aim of describing student motivation in learning English and the factors that influence student motivation in learning English. This research is a descriptive research, which describes existing events by combining quantitative and qualitative. Data collection techniques are questionnaires, observations, and interviews. The subjects of this study were first semester students of the Islamic Religious Education study program who took Basic English courses. The results showed that second semester students of Islamic Religious Education had high motivation in learning English, which consisted of internal and external factors
The Influence of the Hello English Application towards Students’ Learning Achievement in Vocabulary Mastery

The objective of this research was to determine the impact of the Hello English application on students' vocabulary acquisition. This study adopted a quasi-experimental design and quantitative research methodology. Data were obtained from 30 eighth-grade students, 15 of whom were in the experimental class and 15 of whom were in the control class. The instrument for data collection was vocabulary tests that were intended to determine if the Hello English program had an effect on students' vocabulary knowledge. The findings of the data analysis indicate that the experimental class's mean score on the pre-test was only 34 but climbed to 57.3 on the post-test. In contrast, the mean pre-test score for the control group was 43, whereas the post-test score was just 39.6. As a result, the class adopting Hello English as the treatment saw a considerable improvement.
Research on Project-driven Data Structure Teaching Reform

This paper proposes relevant solutions to the current problems in data structure teaching design. Introducing project-driven teaching methods into data structure courses, relying on actual projects, enables students to master data structure knowledge during the process of completing projects, and achieve the teaching purpose of data structure. Teaching practice has shown that project-driven teaching methods not only effectively overcome the drawbacks of traditional teaching methods, but also enhance students' comprehensive abilities and cultivate their comprehensive qualities.
A QUEST for Model Assessment: Identifying Difficult Subgroups via Epistemic Uncertainty Quantification.

Uncertainty quantification in machine learning can provide powerful insight into a model's capabilities and enhance human trust in opaque models. Well-calibrated uncertainty quantification reveals a connection between high uncertainty and an increased likelihood of an incorrect classification. We hypothesize that if we are able to explain the model's uncertainty by generating rules that define subgroups of data with high and low levels of classification uncertainty, then those same rules will identify subgroups of data on which the model performs well and subgroups on which the model does not perform well. If true, then the utility of uncertainty quantification is not limited to understanding the certainty of individual predictions; it can also be used to provide a more global understanding of the model's understanding of patient subpopulations. We evaluate our proposed technique and hypotheses on deep neural networks and tree-based gradient boosting ensemble across benchmark and real-world medical datasets.
Improving machine learning with ensemble learning on observational healthcare data.

Ensemble learning is a powerful technique for improving the accuracy and reliability of prediction models, especially in scenarios where individual models may not perform well. However, combining models with varying accuracies may not always improve the final prediction results, as models with lower accuracies may obscure the results of models with higher accuracies. This paper addresses this issue and answers the question of when an ensemble approach outperforms individual models for prediction. As a result, we propose an ensemble model for predicting patients at risk of postoperative prolonged opioid. The model incorporates two machine learning models that are trained using different covariates, resulting in high precision and recall. Our study, which employs five different machine learning algorithms, shows that the proposed approach significantly improves the final prediction results in terms of AUROC and AUPRC.
Computational Phenotyping of OMOP CDM Normalized EHR for Prenatal and Postpartum Episodes: An Informatics Framework and Clinical Implementation on All of Us.

The use of Electronic Health Records (EHR) in pregnancy care and obstetrics-gynecology (OB/GYN) research has increased in recent years. In pregnancy, timing is important because clinical characteristics, risks, and patient management are different in each stage of pregnancy. However, the difficulty of accurately differentiating pregnancy episodes and temporal information of clinical events presents unique challenges for EHR phenotyping. In this work, we introduced the concept of time relativity and proposed a comprehensive framework of computational phenotyping for prenatal and postpartum episodes based on the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM). We implemented it on the All of Us national EHR database and identified 6,280 pregnancies with accurate start and end dates among 5,399 female patients. With the ability to identify different episodes in pregnancy care, this framework provides new opportunities for phenotyping complex clinical events and gestational morbidities for pregnant women, thus improving maternal and infant health.
Single-Stage Diffusion NeRF: A Unified Approach to 3D Generation and Reconstruction

3D-aware image synthesis encompasses a variety of tasks, such as scene generation and novel view synthesis from images. Despite numerous task-specific methods, developing a comprehensive model remains challenging. In this paper, we present SSDNeRF, a unified approach that employs an expressive diffusion model to learn a generalizable prior of neural radiance fields (NeRF) from multi-view images of diverse objects. Previous studies have used two-stage approaches that rely on pretrained NeRFs as real data to train diffusion models. In contrast, we propose a new single-stage training paradigm with an end-to-end objective that jointly optimizes a NeRF auto-decoder and a latent diffusion model, enabling simultaneous 3D reconstruction and prior learning, even from sparsely available views. At test time, we can directly sample the diffusion prior for unconditional generation, or combine it with arbitrary observations of unseen objects for NeRF reconstruction. SSDNeRF demonstrates robust results comparable to or better than leading task-specific methods in unconditional generation and single/sparse-view 3D reconstruction. <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">6</sup>
Keep It SimPool:Who Said Supervised Transformers Suffer from Attention Deficit?

Convolutional networks and vision transformers have different forms of pairwise interactions, pooling across layers and pooling at the end of the network. Does the latter really need to be different? As a by-product of pooling, vision transformers provide spatial attention for free, but this is most often of low quality unless self-supervised, which is not well studied. Is supervision really the problem?In this work, we develop a generic pooling framework and then we formulate a number of existing methods as instantiations. By discussing the properties of each group of methods, we derive SimPool, a simple attention-based pooling mechanism as a replacement of the default one for both convolutional and transformer encoders. We find that, whether supervised or self-supervised, this improves performance on pre-training and downstream tasks and provides attention maps delineating object boundaries in all cases. One could thus call SimPool universal. To our knowledge, we are the first to obtain attention maps in supervised transformers of at least as good quality as self-supervised, without explicit losses or modifying the architecture. Code at: https://github.com/billpsomas/simpool.
Alignment-free HDR Deghosting with Semantics Consistent Transformer

High dynamic range (HDR) imaging aims to retrieve information from multiple low-dynamic range inputs to generate realistic output. The essence is to leverage the contextual information, including both dynamic and static semantics, for better image generation. Existing methods often focus on the spatial misalignment across input frames caused by the foreground and/or camera motion. However, there is no research on jointly leveraging the dynamic and static context in a simultaneous manner. To delve into this problem, we propose a novel alignment-free network with a Semantics Consistent Transformer (SCTNet) with both spatial and channel attention modules in the network. The spatial attention aims to deal with the intra-image correlation to model the dynamic motion, while the channel attention enables the inter-image intertwining to enhance the semantic consistency across frames. Aside from this, we introduce a novel realistic HDR dataset with more variations in foreground objects, environmental factors, and larger motions. Extensive comparisons on both conventional datasets and ours validate the effectiveness of our method, achieving the best trade-off on the performance and the computational cost. The source code and dataset are available at https://steven-tel.github.io/sctnet/.
Audit sistem informasi pada pelayanan e-government pemerintahan desa menggunakan framework COBIT 5

Suboptimal e-government implementation can make it difficult for people to get the information they need, as well as causing data security vulnerabilities. This research examines the implementation of service information system audits related to e-government using the COBIT 5 approach at the Oro-Oro Dowo Village Office, Malang City. The aim of this research is to determine the level of capability of the e-government service information system and identify potential improvements in information technology. The methods used involve observation, interviews, literature studies, and questionnaires. The research results show that information technology and e-government governance has not been managed well. The maturity level for implementing COBIT 5 in sub domains APO 02, 04, 07, 13, and variable Y is level 3 established process with several areas that require more attention in an effort to increase system efficiency and security. Recommendations are given to improve information technology governance, as well as monitoring so that it can support the development of a better public service system at the sub-district level. This research provides insight into the potential for improvements in e-government service information system audits at the local level.
Pemanfaatan layanan cloud computing dan docker container untuk meningkatkan kinerja aplikasi web

This research aims to analyze and implement the utilization of Content Delivery Networks (CDN) and cloud computing services in web applications using Nginx Proxy Manager and Docker containers. This research uses experimental methods and case studies to analyze the performance of web applications before and after using CDN services and implementing the application in a cloud computing environment using Docker containers. Next, Nginx Proxy Manager is used to provide a user-friendly interface for configuring and managing Nginx proxy servers. Docker containers are used to manage web applications and proxy servers. In the CDN and cloud computing environment, Cloudflare Google Cloud Platform will be used as service providers. The results of this research indicate a significant improvement in the security and reliability of web applications after implementing CDN services and adopting a cloud computing environment. Additionally, this research provides insight into how to use Nginx Proxy Manager and Docker container to manage web applications efficiently and effectively in a cloud computing environment.
PEMANFAATAN POJOK BACA UNTUK MENINGKATKAN MINAT BACA SISWA DI SD NEGERI 1 MENANGA

This study aims to describe interest in reading in class IV SD Negeri 1 Menanga by using the reading corner. This type of research is descriptive qualitative. Collecting data with the method of observation, interviews, questionnaires and documentation. As for data analysis, namely data reduction, data exposure and verification. The subjects of this study were school principals, guardian teachers, Hindu religious teachers and fourth grade students. The results of the study show that there are 3 stages in planning a reading corner at SD Negeri 1 Menanga, namely first holding a meeting with the board of teachers regarding the existence of a reading corner program in each classroom. The two stages of storybook procurement planning are budgeted at the Bos Fund. The three implementation stages carried out literacy activities 15 minutes before the learning activities began. Furthermore, the reading corner at SD Negeri 1 Menanga is used as follows: firstly as material for School Literacy Movement (GLS) activities, secondly as reference material and material for discussion, and thirdly as material to fill students' free time. Based on the use of the reading corner at SD Negeri 1 Menanga, it really helps to increase students' interest in reading, especially in grade IV. The obstacles faced by teachers in using the reading corner at SD Negeri 1 Menanga are the minimal collection of story books and the lack of student initiative in reading books in the reading corner.&#x0D; corner at SD Negeri 1 Menanga, it really helps to increase students' interest in reading, especially in grade IV. (3) The obstacles faced by teachers in using the reading corner at SD Negeri 1 Menanga were the minimal collection of story books and the lack of student initiative in reading books in the reading corner.