Reviewerly/exHarmony huggingface dataset:
Pemberdayaan Anak-Anak Usia Dini Melalui Program Bimbingan Les Belajar Bahasa Inggris di Kampung Baru RT 01 di Desa Bantarsari

This English tutoring programme is one form of community service programme (KKN-12 USA) in 2023 which aims to foster the ability of early childhood in learning English at Paud Insan Madani. In addition, there are other objectives, namely from the implementation of this programme, students can apply the knowledge and theories that have been obtained from the world of lectures, besides that the campus can show the community that students are able to reinforce the existence of universities that are able to create or give birth to the nation's successor cadres who are able to bring better changes to society. The target of this service is early childhood in Bantarsari Village RT 01 Rancabungur District, Bogor Regency. And this programme has the main objective, namely through the English tutoring programme, early childhood can get basic knowledge of English such as how to pronounce well and correctly, be it words or sentences used in daily activities related to their lives and ages. This tutoring programme lasts about 4 weeks with 2 meetings each on Friday and Saturday. From this programme it can be seen that before this activity the children did not understand anything about English and after this activity the children have a change in English language skills at a basic level.
Deep Learning Inpainting Model on Digital and Medical Images-A Review

Image inpainting is a method to restore the missing pixels on damaged images. Initially, the traditional inpainting method uses the statistics of the surrounding pixels to find the missing pixels. It sometimes fails to read the hidden information to attain plausible imagery. The deep learning inpainting methods are introduced to overcome these challenges. A deep neural network learns the semantic priors and hidden representation pixels in an end-to-end fashion in the digital and medical. This paper discusses the following: 1) The difference between the supervised and the unsupervised deep learning inpainting algorithm used in medical and digital images. 2) Discusses the merits and demerits of each deep learning inpainting model. 3) Discusses the challenges and solution for the deep learning inpainting model. 4) Discusses each model's quantitative and qualitative analysis in the digital and other medical images
An Analysis Of Students’ Ability to Using Punctuation In Writing Texts of English Education Students in the Fourth Semester at State Islamic University of Sjech M. Djamil Djambek Bukittinggi Academic Year 2021/2022

The purpose of the research was to find out the level of students’ ability about using punctuation marks in writing the text of English Education Students in the Fourth Semester at IAIN Bukittinggi academic year 2021/2022. The design of this research was descriptive quantitative research. The instruments of this research were punctuation tests in writing the text for measuring students’ ability in Using Punctuation in Writing Text. The population of this research was all Students in Fourth Semester at IAIN Bukittinggi Academic Year 2021/2022 which consists of 4 classes. The sample was 32 students taken by simple random sampling technique. The results of the research show that the mean score was 66 and the lowest score was 33 and a higher score was 93 from 67 students’ Fourth Semester at IAIN Bukittinggi academic year 2021/2022. As a result, the researcher used a ranting scale to arrange the level of students’ ability in using Punctuation Marks in Writing Text. The interpretation table showed that the percentage of the students' mean score was 66 with ranting 66%-79%. The finding showed that the level of students’ ability in using Punctuation Marks in Writing Text with a score percentage of 66 was a good category.
Students Perception on the Vocabulary Translation in Learning English at the Second Grade of SMKN 4 Payakumbuh

The research was due to several problems found in the field: the students less vocabulary in English. It was indicated when I tried asked some students to translate about some vocabulary, some of students knew the the meaning of those vocabulary but much of the students did not knew what the meaning is. The research is aimed to find out students perception on vocabulary translation in Learning English at the second grade students of SMKN 4 Payakumbuh.The research used descriptive quantitative research by using questionnaire as an instrument. The result of the research: first students perception on word to word method with 26,7% in rating quality is almost of half with the mean of the respondent’s answer moderate option. Second, students perception on free translation method with 30,2% in rating quality is almost of half with the mean of the respondent’s answer moderate option. students perception on teacher’s facial expression with 36,4% in rating quality of good. Third, students perception on literal translation method with 25,02% in rating quality is fraction with the mean of the respondent’s answer is hard option. It can be concluded that almost of half students have moderate opinion about all indicator of translate method on vocabulary translation in Learning English at the seventh grade students of SMKN 4 Payakumbuh in Academic Year 2020/2021.
Research on General Word List and Its Application

General high-frequency vocabulary and general academic vocabulary are important components of English core vocabulary, especially in EFL context. General high-frequency word list provides the general core vocabulary, while general academic word list provides the most core vocabulary that appears in a wide range of academic fields. By using literature analysis method, this study analyzed 5083 research articles related to the general word list retrieved from Scopus and Google scholar, and the results shows that: 1) GSL, BNC/COCA2000 and NGSL are widely used general high-frequency word lists, while UWL, AWL, AVL and NAWL are widely used in the academic context. 2) Researches on general word lists show that the selection of corpus, the criteria of word and the unit of counting are the key indicators of word list development. 3) General high-frequency word list and general academic word list are widely used in EAP teaching and research, including the creation of new word lists, especially subject-specific academic word list and technical word list, vocabulary profile analysis, vocabulary burden analysis, textbook design, vocabulary testing and vocabulary learning tools development. 4) Coverage analysis is the main method and approach in word list application, which can be conducted by some webs or software such as Compleat Lexical Tutor, RANGE and AntWordProfiler.
Residual Inter-slice Feature Learning for 3D Organ Segmentation

Although a large number of 2D convolutional neural networks have been reported and used for medical image segmentation, most of them still face the following two problems. First, these networks employ 2D convolution to achieve 3D organ segmentation, which ignores the relationship between different slices. Second, these networks depend on U-shape networks that employ skip-connection to fusion low-level and high-level features, which ignores the semantic gap between them. To address these two issues, we propose a residual inter-slices feature learning method employed by a 2D network that can achieve high-efficient 3D organ segmentation. First, we present an image pre-processing approach named residual inter-slice feature enhancement. We use the residual image including 3D information instead of the original medical slices, which is more efficient and effective than using a 3D network. Second, we present a double-focus skip-connection(DFSC) that is used for replacing the vanilla skip-connection in an encoder-decoder network. Because the DFSC is able to narrow the semantic gap between low-level and high-level features, it achieves better feature fusion. Experiments show that the proposed method is useful for improving feature representation ability of networks and achieving higher organ segmentation accuracy with lower cost.
Robust Digital Watermarking on Vital Archives using Hybrid SVD and DWT Methods

The development of Internet technology affects the dissemination of data, especially in vital government archives. This research uses a hybrid singular value decomposition (SVD) and discrete wavelet transform (DWT) method, which aims to protect the copyright of vital archives. The stages of the insertion and extraction process are carried out to test the effect of the alpha value on the quality (imperceptibility) and robustness of the inserted image by measuring the Peak Signal-to-Noise Ratio (PSNR), verifying similarity by measuring the Normalized Cross-Correlation (NC) and Structural Similarity Index (SSIM). The results of research with ten vital archives and a watermark protection logo in JPEG format with a size of 512x512 pixels obtained a maximum PSNR with a value of α = 0.01 of 41.0567 dB, NC of 0.98904, and SSIM of 0.98023 in the Cibereum Land Certificate. So, it can be proven that this method produces vital archive watermarks that can be extracted and are robust to JPEG compression attacks of 75%, median filtering 3x3, Gaussian noise 0.01, speckle noise 0.01, and salt and pepper noise 0.01 but not resistant to rotation 80 and cropping attacks 2%.
How Quantum is Quantum Gravity?

Nature does not compartmentalize its happenings into different theories or disciplines. The theories are put forth by us to approximately understand the finer workings of nature. All theories are mere mathematical models built to understand nature. Any or all of them can be superseded by a better model or combination of models. The current paper analyses the formulation of Planck scale quantities, the workings of the temporal gauge, the concept of time other related fundamental issues. In particular, the paper points out that the force at the Planck scale is non-quantum.
The Students' Motivation in Learning English Offline after Pandemic: A Study at State Senior High Schools in Bintuhan City Kaur Regency

Abstract&#x0D; The goal of this study was to understand the causes of students' low motivation to learn English. This study employed a descriptive quantitative approach. Documentation, interviews, observations, and questionnaires are the research's primary. Students in State Senior High Schools in Bintuhan City Kaur Regency are the focus of this study. As a result of the research, students are highly motivated to learn English offline following the epidemic in reading types with intrinsic points. Students so like reading things that interest and make them pleased.&#x0D; Key word : motivation, intrinsic, extrinsic, students
An Analysis of Grammatical Errors in Writing Made by English Education Students at IAIN Palopo

Considering the importance of grammatical knowledge in the writing process, this research aims at describing the grammatical errors that are committed by the fifth semester students of English Department at IAIN Palopo. The research study is classified into a descriptive-qualitative study. The data were collected from twenty two English texts written by the English Department students which were done as tasks and contained six familiar topics. Students were supposed to write an essay/paragraph about the given topics. In addition, the researcher had permission from the lecturer to take and analyse the students’ written works. The researcher and students’ written works are the main sources of data collection in this research. To identify the common errors, students’ writings were analysed with the help of checklists in order to classify different types of errors made by the respondents. The results of the study revealed that the most common and frequent errors made by the students are 387 (58.37%) places of omission errors, 213 (32.12%) places of mis formation errors, 131 (19.75%) places of addition errors, 8 (1.20%) places of mis ordering errors. Besides that, the causes of these errors were developmental found in 323 (36.17%) places, 306 (34.26%) of ambiguous, 205 (22.95%) of interlingual, and 59 (6.60%) unique errors. Based on these findings, teachers are suggested to raise students’ awareness on these errors and provide sufficient remedies to prevent students from internalizing such errors.
LGFat-RGCN: Faster Attention with Heterogeneous RGCN for Medical ICD Coding Generation

With the increasing volume of healthcare data, automated International Classification of Diseases (ICD) has become increasingly relevant and is frequently regarded as a medical multi-label prediction problem. Current methods struggle to accurately classify medical diagnosis texts that represent deep and sparse categories. Unlike these works that model the label with code hierarchy or description for label prediction, we argue that the label generation with structural information can provide more comprehensive knowledge based on the observation that label synonyms and parent-child relationships in vary from their context in clinical contexts. In this study, we introduce \tool, a heterogeneous graph model with improved attention for automated ICD coding. Notably, our approach represents the model to consider this task as a labelled graph generation problem. Our enhanced attention mechanism boosts the model's capacity to learn from multi-relational heterogeneous graph representations. Additionally, we propose a discriminator for labelled graphs (LG) that computes the reward for each ICD code in the labelled graph generator. Our experimental findings demonstrate that our proposed model significantly outperforms all existing strong baseline methods and attains the best performance on three benchmark datasets.
Enhancing Students' English Pronunciation With Cake Game Application

In this research, researchers make pronunciation and application the focus of research to improve students' ability to learn pronunciation. This research uses an experimental method with a quasi-experimental design. Participants in this study were divided into two groups, namely the control group and the experimental group. Based on the processing of data, improving the pronunciation ability of this cake game application has a positive impact on improving the ability of English pronunciation in students.
MIEP: Channel Pruning with Multi-granular Importance Estimation for Object Detection

This paper investigates compressing a pre-trained deep object detector to a lightweight one by channel pruning, which has proved effective and flexible in promoting efficiency. However, the majority of existing works trim channels based on a monotonous criterion for general purposes, i.e., the importance to the task-specific loss. They are prone to overly prune intermediate layers and simultaneously leave large intra-layer redundancy, severely deteriorating the detection accuracy. To address the issues above, we propose a novel channel pruning approach with multi-granular importance estimation (MIEP), consisting of the Feature-level Object-sensitive Importance (FOI) and the Intra-layer Redundancy-aware Importance (IRI). The former puts large weights on channels that are critical for object representation through the guidance of object features from the pre-trained model, and mitigates over-pruning when combined with the task-specific loss. The latter groups highly correlated channels based on clustering, which are subsequently pruned with priority to decrease redundancy. Extensive experiments on the COCO and VOC benchmarks demonstrate that MIEP remarkably outperforms the state-of-the-art channel pruning approaches, achieves a better balance between accuracy and efficiency compared to lightweight object detectors, and generalizes well to various detection frameworks (e.g., Faster-RCNN and FSAF) and tasks (e.g., classification).
The Use Of English Stories Applications In Developing Students' Reading Comprehension

This study aims to determine students' understanding of reading skills using the English stories application. The method used in this study was Quasi Experimental Design with 20 students at SMPN 10 Palopo as research subjects. Pretest and posttest techniques to collect data in this study. One of the teaching materials used is a story that is in the application with the theme of fable stories with the title the little mouse. Reading comprehension activities last 15 minutes. After that, students are asked questions about the contents of the story for evaluation using a written test. The results of the study showed that there was an activity to improve reading comprehension skills in class VIII students of SMPN 10 Palopo, as evidenced by the processing of the test results given to students. Thus it can be concluded that using the English stories application can improve students' reading comprehension skills significantly.Keywords: English stories,Application,Reading Comprehension
Quantum reading of quantum information

Abstract We extend the notion of quantum reading to the case where the information to be retrieved, which is encoded into a set of quantum channels, is of quantum nature. We use two-qubit unitaries describing the system-environment interaction, with the initial environment state determining the system’s input-output channel and hence the encoded information. The performance of the most relevant two-qubit unitaries is determined with two different approaches: (i) one-shot quantum capacity of the channel arising between environment and system’s output; (ii) estimation of parameters characterizing the initial quantum state of the environment. The obtained results are mostly in (qualitative) agreement, with some distinguishing features that include the CNOT unitary.
Using Multimedia Tools and Online Resources to Teach Listening

The problem faced by English teachers when teaching listening was how to make all students focus on the learning material and be active, considering that not all students can focus on what is conveyed and often there were students who also busy playing cellphones. To overcome this problem, the English teacher sometimes asked students some questions to regain their learning intention. The objective of this research is to analyze the strategies in teaching listening to students and the problems found by the English teacher in teaching listening as well as how they overcome the problems. The research was conducted by using descriptive qualitative research. The subject of this research was a English teacher. The research collected the data through interview guidance and uses library research, which compiles extensive documentation on a single or a number of topics. Both original sources and secondary sources are used in this investigation. As a conclusion, this study can argue that using multimedia to teach listening suppresses some of the unnatural aspects of the more conventional ear training in EFL classrooms while also bringing about a number of potential advantages.
Computer Vision with Optimal Deep Stacked Autoencoder-based Fall Activity Recognition for Disabled Persons in the IoT Environment

Remote monitoring of fall conditions or actions and the daily life of disabled victims is one of the indispensable purposes of contemporary telemedicine. Artificial intelligence and Internet of Things (IoT) techniques that include deep learning and machine learning methods are now implemented in the field of medicine for automating the detection process of diseased and abnormal cases. Many other applications exist that include the real-time detection of fall accidents in older patients. Owing to the articulated nature of human motion, it is unimportant to find human action with a higher level of accuracy for every application. Likewise, finding human activity is required to automate a system to monitor and find suspicious activities while executing surveillance. In this study, a new Computer Vision with Optimal Deep Stacked Autoencoder Fall Activity Recognition (CVDSAE-FAR) for disabled persons is designed. The presented CVDSAE-FAR technique aims to determine the occurrence of fall activity among disabled persons in the IoT environment. In this work, the densely connected networks model can be exploited for feature extraction purposes. Besides, the DSAE model receives the feature vectors and classifies the activities effectually. Lastly, the fruitfly optimization method can be used for the automated parameter tuning of the DSAE method which leads to enhanced recognition performance. The simulation result analysis of the CVDSAE-FAR approach is tested on a benchmark dataset. The extensive experimental results emphasized the supremacy of the CVDSAE-FAR method compared to recent approaches.
How do South African TVET lecturers rate their digital competencies, and what is their need for training for a digital transformation in the South African TVET sector?

Digital-transformation processes pose many challenges for South African technical and vocational education and training (TVET) colleges. In addition to improving infrastructure, lecturers must be equipped with new knowledge and skills to face the challenges in 21st-century classrooms and workforces. Based on the technological pedagogical content knowledge (TPACK) model, this study investigated the ways in which TVET lecturers (n = 364) self-assess their competence in digital teaching and learning, and the kind of additional training or support that they need to increase the effectiveness of their digital teaching. The findings suggest that the lecturers’ self-assessments of their digital-related knowledge are generally high. In addition, the sub-dimensions of TPACK differ significantly according to the educational background of a lecturer. Those with a regular teacher education rate their TPACK abilities higher than those who have only subject-specific training or a pedagogical education. Nevertheless, analysis of the qualitative data shows that TVET lecturers need extensive support in planning effective technology-enhanced lessons, including the creation of educational content.
E3ID: An efficient end to end person search model

Person Search has recently emerged as a challenging task that aims to jointly solve Pedestrian Detection and Person Re-identification (Re-ID). However, the existing approaches still stay at the image processing stage. In this paper, we proposed E3ID, an efficient end-to-end person search model for video, to better solve the person search problem in real densely populated areas. To speed up the model, a low-quality image filter is proposed to adaptively adjust the sampling frequency of Yolov5 according to the moving speed of pedestrians in the video with minimal computational effort. And the cropped pedestrian images are stored in the gallery library for the Re-ID step. Then, we exploit color feature enhancer to mine color features in specific regions that contribute significantly to the Re-ID process. Compared to other state-of-the-art methods, our proposed E3ID can reach 77.94 % on the evaluation index rank 1, which creates a feasibility of using this model in other complex real-world scenarios.