Reviewerly/exHarmony huggingface dataset:
ANALYSIS OF THE ENGLISH TEACHING WRITING METHODS USED BY THE TEACHERS DURING THE COVID-19 PANDEMIC AT EMSA SCHOOL

The condition of the education system that changed from a face-to-face learning system to an online learning system as a reaction to the spread of the COVID-19 virus throughout Indonesia made this an inspiration for researchers to conduct research. Of course, given the new education system, teachers must develop efficient teaching techniques to optimize student learning. This study intends to describe the methods teachers use to teach English lessons online during the pandemic. The purpose of this study is to analyze the teachers' methods for teaching English during the COVID-19 pandemic: (1) the strategies that teacher used during COVID-19 pandemic to teaching writing, (2) the reasons of selecting those strategies. In order to create this thesis, the researcher used descriptive qualitative methods. Since the researcher completed a one- month internship at a school on October 25, 2022, the study data has been assessed. Two English teachers from EMSA School were interviewed to gather information.The findings of this study are as follows: (1) explain various devices to tech and providing detailed instruction on how to submit the assignment, (2) explain the use of online tools as the effective way, (3) evaluating the student’s comprehension of the materials, reminding students for the schedule and using online tools to provide the assignment.&#x0D; Key words: Teachers’ strategies, online learning, online platform.
The issue of similar handwritings with a particular focus on the determinants affecting the quality of producing a handwritten record

There are cases in the opinion-making practice where manuscripts produced by different persons demonstrate far-reaching similarities of graphisms. This may lead to a manifest error by an expert. Omitting the phenomenon of graphism similarity, which stems from the repetitiveness of analogous structural solutions in handwriting produced by different writers, may result in judicial errors. The objective of this paper is to present the problem of manuscripts showing far-reaching convergences regarding the handwriting features.
The Effect of Trust and Relationship Commitment on Supply Chain Performance through Integration and Collaboration

Purpose: This study analyzed the effects of supply chain management trust and relationship commitment on financial and non-financial performance, focusing on the mediating effect of supply chain management integration and collaboration.&#x0D; Design/methodology/approach: This study was designed as a conceptual research model to verify the mediating effect of integration and collaboration in the relationship trust and relationship commitment and supply chain performance. In order to design a conceptual research model, a total 30 items were investigated and the SEM method was verified using six observations variables.&#x0D; Findings: According to this study, it was found that financial and non-financial performance of companies adopting Korea's supply chain management increased when trust and relationship commitment were strengthened with partner companies. In particular, in the relationship between trust of supply chain management and supply chain management performance, integration with partner companies contributed to increase financial performance, but did not make a positive contribution to non-financial performance. On the other hand, in the relationship between supply chain management's relationship commitment and supply chain management, collaboration made a positive contribution to increasing financial and non-financial performance. What this study means is that higher trust and relationship commitment with partner companies in supply chain management contributed to a direct influence on financial and non-financial performance.&#x0D; Research limitations/implications: This study used the citation count to measure the effect of trust and relationship on supply chain performance. While this serves the purpose of this study, citation counts may not perfectly represent the value and impact of a study. The findings of this study provide a guide post for future studies.&#x0D; Originality/value: This study provides an updated, comprehensive literature review of the overall development, contributions and limitations of forecasting studies in the supply chain management fields. The researchers can see the subjects and types of research that already conducted and which topics remain unexamined.
Semantic Preservation and Natural Language Data Augmentation via Variational Autoencoder

Text augmentation, unlike image augmentation, is challenging because text modifications directly affect labels. Studies on text augmentation using generative and pretrained language models (PLMs) have been conducted; however, their application has limitations. This study proposes a PLM-based data augmentation technique using a variational autoencoder (VAE) structure. Latent variables were used to better understand the semantics, and the VAE was used to assign randomness. The PLM was placed in the encoder and decoder to improve the augmentation performance. We evaluated our proposed method on two benchmark datasets and demonstrated its augmentation effect.
Differential privacy protection method for trip‐oriented shared data

Summary While location information sharing technology provides convenience for unmanned driving and journey navigation, user journey information sharing has also become a disaster for privacy information leakage. The traditional differential privacy method can only perturb the data entirely and cannot consider the design of data availability. In this paper, the difference privacy algorithm is improved by combining it with the Apriori algorithm, and the relevant perturbation is carried out after mining the associated data of the user's trip. In the face of possible data attacks, the privacy protection of the sensitive information of the user's actual data is ensured while the availability of the data is ensured. By testing 3000 trip data generated by experimental simulation, the results show that the correlation information between the original datasets is destroyed. However good availability is maintained after the Laplace data perturbation of the proposed algorithm for both simultaneous and multi‐person trips.
WHIRLWIND DISASTER MITIGATION IN SUNGAI TABUK SUB-DISTRICT, BANJAR REGENCY

Mitigation is an adaptation in the form of efforts to prevent or protect community infrastructure and others from disasters based on an analysis of events that have occurred and losses experienced. Disaster mitigation is divided into 2: structural mitigation and non-structural mitigation. This research aimed to analyze the whirlwind disaster mitigation in Kecamatan Sungai Tabuk, Kabupaten Banjar. The method in this research is a qualitative method in which data collection uses the snowball technique. The research subjects were 12 informants consisting of stakeholders and the community, 3 of BPBD, 1 of the Dinas Sosial, 1 of Kecamatan, and seven people from the district. Data processing in this research uses source triangulation and method/technique triangulation. The data obtained were then analyzed descriptively, data collected, data reduced, data presented, and concluded. The results of the research indicate that the efforts of the government and the community regarding whirlwind disaster mitigation, both structural mitigation and non-structural mitigation, are still lacking. The lack of optimal disaster mitigation in the regions is due to the lack of coordination between stakeholders and the community and the lack of community enthusiasm for knowledge about disaster mitigation
UGANDA: <i>Twitter</i> Firestorm

Africa Research Bulletin: Political, Social and Cultural SeriesVolume 59, Issue 10 p. 23788B-23789C Military UGANDA: Twitter Firestorm First published: 10 November 2022 https://doi.org/10.1111/j.1467-825X.2022.10769.xRead the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat No abstract is available for this article. Volume59, Issue10November 2022Pages 23788B-23789C RelatedInformation
Trisections and cubes in elliptic curves

We show how to compute the pre-images of multiplication by 3 in the group of points of an elliptic curve E over a field k of characteristic different from 2 and 3 such that E[3](k)=E[3]. We show Q=(xQ,yQ)∈[3]E(k) if and only if yQ−d−m(xQ−c) is a cube in k for every 3-torsion point (c,d)∈E[3], where m is the slope of the tangent to E at (c,d). We reduce our problem to the computation of at most 2 independent cubic roots plus a few polynomial operations.
Science 4.0: Complex Security Problems and Solution Mechanisms

It is supposed to consider the conceptual issues of the reconstruction of science as a corporate environment of Science 4.0 based on the key technologies of Industry 4.0 – Internet of Things, Cyber-Physical Systems, Artificial Intelligence, Cloud computing, Big Data analytics and other Smart solutions. eScience is considered to be the technological base of Science 4.0. Complex security problems and their solution mechanisms are investigated within Science 4.0.
A Study on the use of Metacognitive Strategies in English Learning by Senior High School Students under the Background of New Curriculum Standards

Based on the new requirements of metacognitive strategies put forward by English Curriculum Standards for Senior High Schools (2017 Edition) (New Curriculum Standards), this paper comprehensively investigates the use of metacognitive strategies in English learning by 100 senior high school students and explores the differences in the application of different metacognitive strategies. The findings are as follows: (1) Senior high school students have a superficial understanding of metacognitive strategies in English learning, but the usage frequency is on average level; (2) Among metacognitive strategies, senior high school students use self-evaluation strategies more frequently than self-planning strategies and self-monitoring strategies; (3) There is a significant positive correlation between the usage frequency of metacognitive strategies and English achievement of high school students. On this basis, this paper further puts forward some suggestions to improve the scientificness, effectiveness and pertinence of metacognitive strategies of high school students through multiple evaluations.
Application of Natural Language Processing and IoT to Emulate Virtual Receptionist

Virtual assistants are touching everyone's life each day by optimizing the digital experience of many of the tasks. Either it be an instruction to play a song on Amazon's Alexa or to know the traffic on Google's Assistant, we are using these assistants. By changing these broad tasks into a localized set of tasks for an organization-only use, we can convert these assistants to be in operations as a virtual receptionist. This article focuses on the use of natural language processing and supervised learning to train a virtual assistant to be operated as a virtual receptionist. In this time of COVID, where the front desk admin/receptionists are more prone to get infected due to the direct contact with people visiting the organization, a virtual receptionist will try to replicate the task done by the human receptionist. This will digitalize the way information is rendered between third parties and receptionists as well as remove any possibilities of manual errors. Problems like long queues at reception, communication gaps, etc., can be solved as a machine won’t have biases as seen with humans. Similarly, using sensors and Internet of Things technology, many new features can be added to this system according to the need of any organization.
Deep Learning Algorithms for Real-Time Healthcare Monitoring Systems

As a result of smart wearable health devices and internet of things (IoT)-enabled smart home devices, healthcare monitoring systems are becoming more common. By shifting healthcare from face-to-face consultations to telemedicine, deep learning algorithms are preferred for reducing illnesses in the health sector. During training and games, accurate monitoring of physiological indications is critical for safeguarding athletes from life-threatening serious diseases and injuries. To track vital signs, advanced wearable sensors are deployed, and machine learning techniques are used to retrieve meaningful data. Even if doctors aren't there, deep learning algorithms assist specialists in accurately identifying these athletes' illnesses and administering the appropriate drugs.
Structural Control of Gold Deposits in the Northern Margin of the North China Platform

The North China Platform is one of the oldest continental crusts in China. The northern margin of the North China platform is one of the top gold mining concentration areas in China. Studying its ore-controlling factors is of great practical significance for finding similar gold deposits in areas with similar geological backgrounds. The authors of this paper have concluded that the gold deposits in the northern margin of the North China platform are mainly controlled by various faults. In the long geological history, these fault structures have undergone many stages of activation and transformation almost without exception. Generally, it has experienced the following three stages of development and evolution: 1. Beginning in the early stage of ductile deformation at the end of the Archean period, it is characterized by mylonite. The rock is transformed from the original high amphibolite facies-granulite facies into greenschist facies through ductile shearing. The typical mineral combination is sericite + chlorite + quartz ± feldspar. 2. The brittle-ductile deformation stage occurred in the Hercynian period, that is, the middle activation stage. Due to the different lithology of activation in different sections, the uneven strain of the mining area is caused. Some of the rocks are of continuous inhomogeneous strain, while others are of discontinuous inhomogeneous strain. As a result, hardening in plastic deformation occurs in some areas, and two different types of ore would appear in some mine. 3. The late transformation stage occurred in the early Yanshanian orogeny. It is mainly manifested in the strong fragmentation and transformation of the existing ore bodies, resulting in the dislocation of the ore bodies and complicating their occurrence. This late transformation stage has created favorable conditions for the later oxidative secondary enrichment of ore.
Graph-Based Framework on Bimanual Manipulation Planning from Cooking Recipe

It is difficult to effectively operate a dual-arm robot using only the information written in a cooking recipe. To cope with this problem, this paper proposes a graph-based approach on bimanual cooking motion planning from a cooking recipe. In our approach, we first decompose the cooking recipe into graph elements. Then, we try to connect the graph elements taking into account the attributes of the input/output nodes. If two graph elements cannot be connected to each other, we search for a graph element that can be inserted between them from a motion database. Since the constructed graph includes the whole sequence of the robot’s motions to perform the cooking task, we can generate a task sequence of a dual-arm manipulator simultaneously performing two different tasks by using two arms. Through experimental study, we show that it is possible to generate robot motions from a cooking recipe and perform the cooking motions while simultaneously moving the left and right arms.
Implementing Concatenative Text-To-Speech Synthesis System for Marathi Language using Python

A Text To Speech (TTS) synthesiser is a computer-based system which converts arbitrary input text into speech. A TTS system is helpful not only for speech or visually impaired people but also for educationally backward and underprivileged. Many TTS systems exist for English but still many people worldwide are not literate and comfortable in speaking, writing and reading English. A local language interface needs to be developed for such people. Considering this need, we have attempted to develop a TTS system for the Marathi language using python. Marathi is the fourth largest spoken language in India and an official language of the Indian state of Maharashtra and Goa. Marathi is known to and spoken by over 100 million people not only from India but also from Mauritius and Israel. Developing a Marathi TTS system will be useful for people in Maharashtra and several migrants coming to the state in search of jobs, business or education.
Modelling Disease Risk Faktors for Covid-19 on District/City in West Sumatera

The chain of transmission of COVID-19 cases has been increased from day to day. Based on data from the Ministry of Health, the province of West Sumatra is ranked 3rd in Indonesia. This research is aimed to find out the modelling of risk factor of COVID-19 disease in district/city in West Sumatera. This research is an observational analytic study using secondary data in 2020 and multivariate analysis includes a cluster analysis, biplot analysis and discriminant analysis. The unit of analysis in this study are all districts / cities in West Sumatra and uses 6 factors that cause COVID-19 in West Sumatra. Grouping process yieldedÂ threeÂ clustersÂ ofÂ districtsÂ /Â citiesÂ basedÂ on factorsÂ causesÂ COVID-19. The different variable between clusters based on the result of discriminant analysis, namely; the number of elderly, the percentage of poor people and the population density. To that end, it is advisable toÂ West Sumatra Provincial Health Office in the implementation of eradication programs and disease prevention COVID-19 to implement disease management based on the characteristics of each region of each district / city.
Automated Speckle Noise Suppression from Sentinel-1A Synthetic Aperture Radar Imagery Using Adaptive Filtering Techniques

Synthetic aperture radar (SAR) imagery is formed by measuring the backscattered microwave energy to the satellite. However, it is well known that such recorded SAR data is amended by inevitable multiplicative noise known as speckle due to the interference of the returning electromagnetic waves scattered from multiple surfaces. This results in granular appearances in SAR imagery, which not only exacerbate the overall quality (edge and texture information) and exert hindrance to the understanding of the image features but also make target detection challenging. In order to effectively analyze SAR imagery, speckle (the high frequency) must often be suppressed to the greatest extent possible before the image can be used for further analysis. In this paper, despeckling is performed by applying MAP, Lee, Frost, Kuan and Boxcar adaptive filtering techniques with 3 × 3, 5 × 5 and 7 × 7 sized kernels. Evaluation of these adaptive filtering techniques is then performed using metrics—speckle suppression index, enhanced number of looks, noise variance, mean square error, mean and standard deviation. It is observed from the experimental results that the Lee filter with 5 × 5 sized kernel has produced reasonably good results with high enhanced number of looks value, low mean square error, speckle suppression index, noise variance values, and a higher percentage change in standard deviation compared to that from the MAP, Frost, Kuan and Boxcar filters. In addition to these quantitative measures, qualitative visual inspection of the despeckled image is also performed to compare results from these filters.
Structural Relationships among Course Organization, Student Engagement and Perceived Learning Outcome in Online Learning

Objectives This study aimed to analyze the structural relationships among online course organization, student engagement and perceived learning outcome in university online learning environment. Methods The survey data were collected from a total of 359 students who took the 100% online course offered by K University in the fall semester of 2021. The structural equation modeling was conducted to examine the relationships among course organization, behavioral, emotional, cognitive engagement and perceived learning outcome. Results The findings showed that online course organization had significant effects on behavioral engagement and perceived learning outcome. Behavioral engagement had a positive(+) effect on emotional and cognitive engagement, and emotional engagement had a positive(+) effect on cognitive engagement. In addition, emotional engagement was found to mediate the relationship between behavioral, cognitive engagement and perceived learning outcome. Conclusions This study attempts to broaden the understanding of student engagement reflecting multidimensional concepts by identifying the interrelationships among behavioral, emotional and cognitive engagement. Also, the results of this study can provide implications for teaching strategies to promote student engagement in online learning.
Case: near-surface electromagnetic survey to support the design of urban development plans

This case history describes the use of an electromagnetic survey for mapping the top of bedrock below a clayey till as a new logistic centre was planned in the area. The case includes practical survey and planning considerations along with examples of interpretations and results.
Study on site selection evaluation of post-earthquake reconstruction in active fault area—Taking Qingshuihe plain in Tongxin county of Ningxia as an example

To fully consider the destructive effect of rare earthquakes, the post-earthquake reconstruction address was selected in the Qingshuihe plain, Tongxin County, Ningxia, in the active fault area without rain. Firstly, based on the delimitation of seismic risk areas and surface fracture zones, the concept of an “effective slope length ratio” is used to evaluate the risk of geological disasters that may be induced by earthquakes in the future. Then, the paper uses the information entropy method to further narrow the site selection scope by evaluating construction and environmental factors. Finally, it selects three relatively suitable addresses and summarizes their advantages and disadvantages to provide a reference for the emergency and recovery planning of post-disaster reconstruction.
Dynamic Graph Neural Networks

Graph Neural Networks aim to embed nodes into a low-dimensional space, while preserving the network structures and properties. However, in the real world, complex systems are commonly associated with multiple temporal interactions, forming the so-called dynamic graphs. In this chapter, we will introduce three dynamic graph neural networks for temporal modeling of evolving structures, including simple homogeneous topologies and temporal heterogeneous graphs.