Reviewerly/exHarmony huggingface dataset:
Reform Strategy of College English Teaching Based on Big Data

<p style="text-align: justify;"><span style="font-family: "times new roman";">With the development of network information technology and related software technology, college English is also facing powerful teaching reforms. The English teaching model of traditional higher education can neither increase students' interest in learning nor improve teaching quality, which has a significant impact on English teaching. With the development of big data technology, a large number of multimedia devices have been introduced into college English teaching. Under the influence of network media, the teaching environment has undergone great changes, which have had a huge impact on English teaching. In order to meet the needs of the development of the times and cultivate a new generation of practical English talents, our country's higher English teaching must undergo a comprehensive reform. However, in the current network environment, there are still some problems in the reform of college English teaching in our country. Therefore, this article discusses these issues, and on this basis puts forward the benefits of network higher education English teaching reform and practice. Through the effective use of cellular networks and various information tools, the reform of higher education English teaching has created an effective teaching model, which has greatly improved students' learning enthusiasm, improved the quality of higher education English teaching, and met the teaching needs. Therefore, this article briefly introduces the importance of reforming higher English teaching from the perspective of cellular network for the first time, and then actively explores the strategy of reforming higher English teaching from the perspective of cellular network for reference.</span>
CODE SWITCHING BY THE TEACHER IN EFL ONLINE TEACHING AND LEARNING PROCESS AT SMAN 7 MEDAN

Abstract The aims of this study are to analyze the types of code switching by the teachers in EFL online teaching and learning process and to analyze the teachers’ reasons of the use code switching. This study was conducted by using descriptive qualitative design. The sources of this data were the two EFL teachers at SMAN 7 Medan. To collect the data, the researcher used zoom video recording platform to record the EFL teaching and learning process. Then, Teachers were interviewed after the teaching and learning process. There were three ways of action to analyze the data, they were data condensation, data display and conclusion drawing/verification. After analyzing the data, the researcher found that there were three types of code switching used by the teacher while teaching, namely intra-sentential switching, inter-sentential switching and tag switching. Inter-sentential switching was dominantly used by the teachers, meanwhile tag switching was the lower frequently used by teachers. In line with that, the researcher also found that there were five reasons why the teacher switched their language in EFL teaching and learning process, namely: to translating unknown vocabulary, to manage the classroom, to explain grammar, to emphasize some points, and to give empathy and solidarity.Keywords: Code switching, EFL teacher, intra-sentential switching, inter-sentential switching, tag-switching
PENGARUH TEKNIK TRI-FOKUS STEVE SNYDER TERHADAP KECEPATAN EFEKTIF MEMBACA SISWA KELAS X SMA SWASTA MUHAMMADDYAH RANTAU PRAPAT TAHUN AJARAN 2018/2019

Abstract Reading is one of the four aspects of language skills. Reading including receptive skills, which serve to absorb the information. The low reading proficiency will greatly affect the effectiveness of students' reading. This paper describes the influence of engineering Steve Snyder Tri-focus on effective speed reading class X SMA Muhammaddyah academic year 2019/2020. This study is quasi-experimental. The research sample is the class X-1 and X-2. The research concludes effective speed reading speed of students by using Tri-Focus on high school students of class X Muhammaddyah Rantau Prapat classified in either category with an average value of 72.72. While in the classroom with hands-on learning techniques belong to the category of fairly 50.3 Keywords: Read fast , kecepatan efektif membaca ( KEM ) , Tri - Focus technique Steve Snyder
SENTIMENT ANALYSIS PROTOKOL KESEHATAN VIRUS CORONA DARI TWEET MENGGUNAKAN WORD2VEC MODEL DAN RECURRENT NEURAL NETWORK LEARNING

Sentiment analysis is a computational study of opinion from various opinions, which is part of the work that conducts a review related to the computational treatment of opinions, sentiments, and perceptions of the text. To solve various problems in sentiment analysis, needed a good text representation method. In this study, a deep learning analysis was carried out using the Recurrent Neural Network (RNN) method and the Word2Vec Model as word embedding in sentiment classification. The sentiment dataset used comes from user reviews on Twitter (tweets) on the health protocols implemented by the public from the government's appeal. The results showed that the RNN model using sigmoid activation resulted in the greatest accuracy of 66%. The training process in this test uses 10 epochs and 32 batch sizes so that the precision value for negative sentiment is 54% and for positive sentiment is 67%.
Zero-Trust Model of Cybersecurity: A Significant Challenge in the Future

To address future cybersecurity challenges, this paper proposes a real-time three-factor authentication scheme (RT3FA). The proposed model integrates the characteristics of multi-factor authentication and real-time actual information. The additional layer of protection raises the obstacles for data access; face biometric is needed in addition to two-factor authentication. Facial biometric is accomplished by synchronizing real-time information with feature recognition via an instantaneous live feed from the user&#x2019;s camera. However, the improved protection may cause efficiency issues and thus, require higher capacities for both the user&#x2019;s device and the database system.
Academics’ and Institutional Leaders’ Perception of Transparency: Lesson from Ethiopian Public Universities

This study explored academics’ and institutional leaders’ perception of transparency in decision-making in Ethiopian higher education institutions. Three universities were selected from the 31 public universities using a stratified sampling technique. The study employed a mixed-method exploratory research design. Descriptive statistics (mean and standard deviation) and inferential statistics (ANOVA and Tukey’s post-hoc test) were used to analyse the quantitative data while thematic analysis was used to identify emerging themes and meanings within qualitative data. The findings of this study showed that the Ethiopian public universities have hierarchal (top-down) governance lacking in transparency in decision-making. Academics and institutional leaders called for greater transparency in the flow of information and decision-making for the academic community to accomplish their academic core activities effectively. Transparency is a key element of the university governance, and we argue that a lack of transparency at the university upper levels of the university will discourage transparency at lower levels. We recommend shift to more shared governance or consultative governance for mutual accommodation if the Ethiopian universities are to become transparent and optimise their contribution to national development.
PENGEMBANGAN SISTEM PENGELOLAAN LAUNDRY BERBASIS WEB (STUDI KASUS ARIN LAUNDRY)

Arin Laundry is a laundry service business located in Gedong Tataan, Pesawaran Regency, Lampung Province. Management of business activities at Arin Laundry still uses the old method, namely the manual method. Therefore, this research was conducted to build an information system that can help Arin Laundry in running its business, so that business management at Arin Laundry can run well. The business management includes transactions, user management, laundry type management, expenses, monitoring of laundry raw materials, expense and income reports, bar graph reports, profit reports, and sending SMS notifications to customers so that customers can know for sure that the laundry belongs to the customer. have been completed. SMS notifications can also inform customers that washing is being picked up and being delivered. In the development of information systems, a system development method is applied, namely the waterfall method developed in conjunction with the PHP and MySQL programming languages and using the Laravel framework. System testing is carried out using black box testing, namely by observing the results of execution through test data and checking the functionality contained in the system. This research has succeeded in developing a web-based information system that can be accessed by admins, employees, and customers.
KEPUASAN PESERTA PELATIHAN JARAK JAUH TERHADAP LAYANAN VIDEO TUTORIAL CARA MENGOPERASIKAN LMS BERBASIS MOODLE

This study aims to determine the level of satisfaction of distance training participants (PJJ) with video tutorial services on how to operate a Moodle-based learning management system. One of the reasons for the success of participants in participating in remote training is their technical ability to operate the Bandung Religious Education and Training Center's PJJ application. The satisfaction of remote training participants is a reflection of the quality of video tutorial services produced as an effort to serve participants who have difficulty operating the learning management system. descriptive, namely analyzing the satisfaction of PJJ participants on the dimensions of reliability, tangibles and Responsiveness to video tutorials containing technical explanations for operating a moodle-based learning management system which is the application platform for the Bandung Religious Education and Training Center PJJ application platform. Population and Sample The population of this research is the participants of the long distance training at the Bandung Religious Education and Training Center in 2021, with a total of 800 participants. The sample in question is the object under study is the participants who are taken as respondents from this study. The results showed that the training participants were very satisfied with the video tutorial service. Video tutorial services have reliability and are in accordance with the needs and expectations of participants, which can be seen repeatedly, owned and felt by participants as in the second dimension, namely tangible. Regarding the Quick Response variable, the video tutorial service is able to respond to complaints from PJJ participants who have difficulty operating a moodle-based learning management system.&#x0D; Keywords: Video tutorials; Satisfaction; PJJ.
Latent Space Data Augmentation for Facial Diagnosis from Face Images of Multiple Diseases

Deep learning solved many real-world problems that were impossible to computer a few decades ago like image classification. Facial diagnosis is one such problem in which facial photographs are used to find the type of disease a person is having. To solve these problems efficiently it depends on large data. Unfortunately, domains like medical image analysis do not have access to this large data. In this paper, we use latent space data augmentation to synthesize the data to perform facial diagnosis. Supervised auto-encoder with transfer learning is used to learn important features from facial images. Interpolation transformation is applied to latent space to synthesize the data. A Deep Neural Network and Support Vector Machine is trained on synthetic data and achieved 94.4 and 95.0 percent accuracy, respectively.
The use of Augmented Reality to promote learning in Science Laboratories

This paper presents a research on the use of Augmented Reality (AR) in Science teaching laboratories, aiming to verify features and functionalities that promote the interaction and participation of students in line with learning theories while supporting experiential learning. From this research, a prototype of a virtual laboratory involving the use of AR was developed, and a strategy was built for applying it in learning activities about the planet Earth in elementary school.
TAGCN: Typed Attention Graph Convolutional Networks for Entity Alignment in Cross-lingual Knowledge Graphs

Cross-lingual entity alignment aims at integrating complementary knowledge graphs (KGs) presented in different languages. It bridges cross-lingual knowledge for knowledge discovery. In this paper, we propose a new embedding-based framework named Typed Attention Graph Convolutional Networks (TAGCN) for cross-lingual entity alignment. In TAGCN, the relation type information is fully utilized with the typed attention mechanism. Then we incorporate entity information and the relation type information of neighbors into entities through attention mechanism to iteratively learn better representation for entities. The experimental results show that our model consistently outperforms the state-of-the-art alignment methods.
Prediksi Indikator Perawatan Menggunakan Random Forest Classification dan Classification and Regression Trees

Electronic medical record is a hospital information system facility that contains patient social and medical data to facilitate patient data documentation, improve health services, and access patient data. Medical records can be used to predict length of stay and estimated costs during treatment, so that patients can choose the desired treatment. The method for predicting length of stay uses the Random Forest Classification and Classification and Regression Trees (CART) algorithm which describes the relationship between the dependent and independent variables by producing a binary tree as a decision in the prediction. The model is built by changing the variables into multiclass and binary classes and using hold out split data and cross validation to measure model performance. Each model is compared and the model with the highest accuracy is selected as the best model. The highest model accuracy in the Random Forest Classification is 61.70% and the CART algorithm is 63%. The CART algorithm is the best model for predicting length of stay in this study because it produces the highest accuracy of 63%. Based on the prediction of length of stay, the estimated total cost of hospitalization can be calculated by considering the cost of drugs and inpatient rooms.
The influence of playing digital game in distance learning towards students’ speaking skill

The lack of class interaction in distance learning makes students can not practice their speaking skill. In another case, the use of digital game have been familiar among students. This situation forces teacher to serve students with creative teaching-learning in the class. Novelty is on the specific game which was used in this research. The researcher experimented to apply digital games namely “Among Us” then investigated the impact on students’ speaking skill. This research aimed to answer the question, how were digital games become an alternative medium to learn English in the distance learning situation? Inherently, this research was a pre-experimental research method with a design of one shoot case study. The main data source in this research was based on students' assessments scores and students’ questionnaire scores then supported by other questionnaires and semi-structured interviews. The averages scores indicate that students were good in speaking skills overall, it could be known by the detailed results of the assessments that were pre-activity 2.64, during-activity 2.50, and post-activity 2.22. Moreover, the results of regression analysis indicated digital games influenced students' achievement and students' motivation. It can be known by the significance of Annova tables results that students’ achievement 0.022 &lt; 0.05 and students motivation 0.000 &lt; 0.05. The Researcher concluded that students were comfortable and more confident to learn and practice their speaking skill during playing the digital game. Finally, through giving correct treatment, digital game activity was possible to be an alternative way to learn English especially to practice speaking skill.
Penyuluhan Kesehatan Perawatan Luka di Leuwianyar

Wounds have a variety of causes some arise from surgical intervention, result from injury, and others are the consequence of extrinsic factors, such as pressure or friction, even underlying comorbidities such as diabetes or vascular disease. The results of the community representatives are that there are those who do not know how to treat wounds, but there are also some who already know by using NaCl infusion fluids. Sodium Chloride (NaCl) which is known as salt is a substance that has a high osmotic level. Poviden iodine (betadine) is a complex compound of Iodine and Povidone which is usually used as an antiseptic on wound surfaces because it can damage enzymes. Discussion and demonstration methods were used, so that people could better understand how to treat wounds at home. In the future, you can do it yourself at home for the use of this method in treating wounds, so it can be better.
Reopen Offline Business during a Pandemic? Characterization of Health Certificate Exchange for Human Movement Management

The COVID-19 pandemic has significantly restricted the regular offline business activities. Nevertheless, as certain offline business activities are still indispensable, to conduct offline business under pandemic control becomes a valuable research question. This paper addressed this problem by studying business movement management based on health certificate exchange. We first observed three patterns of health certificate exchange multiplicity that serve as a basis for business movement management. Then, we reviewed published literature along two orthogonal directions, health certificates and exchange systems. We studied different health certificates published during the COVID-19 pandemic to identify the categories of health certificates and their characteristics. Meanwhile, we further studied different design paradigms and characteristics of health certificate exchange systems. Last, we mapped our findings on health certificate exchange into the four challenges of movement management systems in a pandemic, namely flexible controllability, scalable accessibility, adaptive reusability, and spatiotemporal traceability, and conceptualized how such the requirements should be achieved and a complete system should operate.
Optimized Quantum Program Execution Ordering to Mitigate Errors in Simulations of Quantum Systems

Simulating the time evolution of a physical system at quantum mechanical levels of detail - known as Hamiltonian Simulation (HS) - is an important and interesting problem across physics and chemistry. For this task, algorithms that run on quantum computers are known to be exponentially faster than classical algorithms; in fact, this application motivated Feynman to propose the construction of quantum computers. Nonetheless, there are challenges in reaching this performance potential. Prior work has focused on compiling circuits (quantum programs) for HS with the goal of maximizing either accuracy or gate cancellation. Our work proposes a compilation strategy that simultaneously advances both goals. At a high level, we use classical optimizations such as graph coloring and travelling salesperson to order the execution of quantum programs. Specifically, we group together mutually commuting terms in the Hamiltonian (a matrix characterizing the quantum mechanical system) to improve the accuracy of the simulation. We then rearrange the terms within each group to maximize gate cancellation in the final quantum circuit. These optimizations work together to improve HS performance and result in an average 40% reduction in circuit depth. This work advances the frontier of HS which in turn can advance physical and chemical modeling in both basic and applied sciences.
Sistem Informasi Pendataan Masyarakat Kurang Mampu Berbasis Web di Kelurahan Cisalak

Poverty is a complex problem that is influenced by various interrelated factors, including: income levels, health, education, and housing conditions. Data collection on the poor must be done well, therefore it should have a computerized system so that the data collection of the poor has parameters of income and housing conditions. To support the purpose of this research, the method used in making the information system is the Waterfall and Tools model that uses the PHP programming language, MySql Boostrap Database, and Macromedia Dreamweaver. The results of the research design in accordance with the research objectives are expected to help the poor data collection officers with an information system for collecting data on the poor using income parameters and housing conditions. This system can provide complete and accurate information in accordance with the criteria for the poor, which is displayed in pdf form, making it easier for officers and the community to identify optimally.
Penerapan Simple Additive Weighting Pada Sistem Otomatisasi Surat Teguran SAMSAT Mataram Melalui SMS Gateway

Remind or notify the Taxpayer of unnecessary obligations so that a Reprimand letter arises. Choosing a Reprimand letter and sending a Reprimand letter is not effective because it takes a lot of time and money. Therefore, to be able to overcome the existing problems, it is necessary to automate the selection of Reprimand letters using the Simple Additive Weighting (SAW) method which is a multi-criteria decision support method. As well as sending automatic Reprimand letters using Short Message Service (SMS) using the Gammu library. So that it can make it easier for users to choose and send letters so that it can be done faster and at lower costs. The results of the tests carried out in terms of time, SAW has a faster time with conventional systems by only taking 8,620 seconds. Furthermore, testing is carried out in terms of the cost of the SMS gateway, which is more affordable than the conventional system that was previously applied with a cost difference of 99.7%
Perception robustness testing at different levels of generality

Ensuring the success and safety of deployed robotic systems often requires predicting their behavior in a wide range of conditions, precluding practical testing of the physical system itself. We introduce an approach to predict the robustness of a perception system in a broad range of conditions through simulation of challenging real-world conditions achieved by modifying real images according to physical phenomena, producing physically-realistic, mutated images. Typical perception-system performance metrics are difficult to relate to system-level application- or safety-requirements. We propose performance-evaluating metrics that are more closely tied to these targets, a relationship dependent on the amount of application-specific context available and assumptions imposed. We also introduce a novel robustness metric, Robustness ROC, that can be applied to any of these performance metrics. We demonstrate this method on NREC-AgPD, a large dataset focused on person detection for off-road driving in orchard environments, assessing several recent person detectors, and showing how considerations of robustness can often change the best-choice algorithm.