Reviewerly/exHarmony huggingface dataset:
The Why and How of Korean Primary School Teachers Teaching English Using Fairy Tales: Qualitative Research

Objectives The purpose of this study is to analyze in detail the motives and methods of English classes using fairy tales through in-depth interviews with primary school teachers who have conducted English classes using fairy tales.&#x0D; Methods Through the qualitative research method, three primary English teachers were selected as intentional sampling(convenient sampling) method, and data were collected through triangulation such as interviews, non-participatory observation(class videos), documents, and class photos, and analyzed using constant comparative analysis, which is an open coding, categorization, and category confirmation process. Efforts were made to report validity and reliability through member checks with the analyzed data.&#x0D; Results The motivations of primary English teachers who used fairy tales were analyzed as three main themes: ‘Striving for overcoming the limitations of primary English textbooks,’ ‘Development of students' critical thinking skills,’ and ‘Will to improve as English teachers.’ The English class method using fairy tales was analyzed into three main topics: first, ‘whole language learning’, second, ‘real communication-oriented class’, and third, ‘student-centered class’.&#x0D; Conclusions It is not only necessary to develop primary English textbooks that can provide a rich context, communicate in practice, and improve students' interest, motivation, and confidence but also needed to train English teachers as an in-service on related textbooks.
Artificial intelligence based health indicator extraction and disease symptoms identification using medical hypothesis models

Patient health record analysis models assist the medical field to understand the current stands and medical needs. Similarly, collecting and analyzing the disease features are the best practice for encouraging medical researchers to understand the research problems. Various research works evolve the way of medical data analysis schemes to know the actual challenges against the diseases. The computer-based diagnosis models and medical data analysis models are widely applied to have a better understanding of different diseases. Particularly, the field of medical electronics needs appropriate health indicator extraction models in near future. The existing medical schemes support baseline solutions but lack optimal hypothesis-based solutions. This work describes the optimal hypothesis model and Akin procedures for health record users, to aid health sectors in clinical decision-making on health indications. This work proposes Medical Hypothesis and Health Indicators Extraction from Electronic Medical Records (EMR) and International Classification of Diseases (ICD-10) patient examination database using the Akin Method and Friendship method. In this Health Indicators and Disease Symptoms Extraction (HIDSE), the evidence checking procedures find and collect all possible medical evidence from the existing patient examination report. Akin Method is making the hypothesis decision from count-based evidence principles. The health indicators extraction scheme extracts all relevant information based on the health indicators query and partial input. Similarly, the friendship method is used for making information associations between medical data attributes. This Akin-Friendship model helps to build hypothesis structures and trait-based feature extraction principles. This is called as Composite Akin Friendship Model (CAFM). This proposed model consists of various test cases for developing the medical hypothesis systems. On the other hand, it provides limited accuracy in disease classification. In this regard, the proposed HIDSE implements Deep Learning (DL) based Akin Friendship Method (DLAFM) for improving the accuracy of this medical hypothesis model. The proposed DLAFM, Convolutional Neural Networks (CNN) associated Legacy Prediction Model for Health Indicator (LPHI) is developed to tune the CAFM principles. The results show the proposed health indicator extraction scheme has 8-10% of better system performance than other existing techniques.
The Development and Application of Computer Vision Technology in The Era of Artificial Intelligence

With the increasing popularity and wide application of Internet technology, the computer field is in the stage of vigorous development, the world is moving towards the economic development period dominated by information industry.In recent years, with the birth of the emerging field of artificial intelligence, which solves problems that traditional computer technology can not solve, more and more people have a strong interest in it and devote themselves to this research, making artificial intelligence has evolved into a mainstream discipline in the field of computer.As one of the core technologies of artificial intelligence, computer vision has made remarkable progress in theoretical research and technical application, and has been widely used in home furnishing, medical treatment, network and security.This paper mainly introduces the concept and relationship between artificial intelligence and computer vision, discusses the main technology and application scenarios of computer vision, and proposes a vision for the future development.
PELATIHAN MEMBUAT KARYA MONTASE DAN MENGHIAS KELAS DI SEKOLAH DASAR AL ZAHRA INDONESIA PAMULANG

Al Zahra Indonesia Elementary School is located at Jalan Vila Dago Boulevard Blok G, Benda Baru Village, Pamulang District, South Tangerang City, Banten Province. Al Zahra Elementary School currently has 24 local classes for teaching and learning activities where each level has 4 parallel classes. In addition, this school is also equipped with facilities that support teaching and learning activities, namely a library, computer laboratory, science laboratory, hall, indoor swimming pool, outdoor basketball court, indoor badminton court, administration room, teacher room, and principal's room. His deputy. Elementary school students in the curriculum are taught the subjects of Arts, Culture and Skills where for each grade level different levels of difficulty are learned. Art, Culture and Skills lessons for grade 4 include lessons on making montage works. According to the Big Indonesian Language Dictionary, montage is making a work with a composition of images resulting from mixing elements from several sources so as to produce a new work. In teaching students to be creative, sometimes teachers are constrained by creative ideas to be creative, so we need to play an active role in increasing the creativity of teachers so that in conveying material, making works of art can be more developed and produce diverse works. Making montage works can help students in expressing creative ideas, expressing their emotions which can lead to a sense of satisfaction, and provide pleasure so as to reduce the psychological burden that may arise due to online learning activities
On Data Analysis and Design and Implementation of Data Preprocessing Scheme Based on Low-quality Rock Datasets

With fast progress of deep learning technology, breakthroughs are achieved in many industries by virtue of efficient artificial intelligence models.In addition, computer hardware is cheaper, which makes it easier to acquire an excellent deep learning model.However, output of a model with good generalization rests with not only powerful hardware computing speed, but also quality of dataset involved in the calculation.Unfortunately, high-quality dataset is probably more expensive than high-end hardware, and this forces deep learning engineers or practitioners to use lower-quality dataset.Anyway, it doesn't mean excellent deep learning programs can't be created by such dataset.In particular, dataset preprocessing is equally important, and even engineers need to spend most of time elaborately formulating preprocessing strategies.This study mainly analyzes data and formulates preprocessing schemes of low-quality rock datasets.It aims to make deep learning programs more efficient and general-purpose at the lowest possible cost.
Using Meta Path Information to Adjust Embedded Recommendation System

The data information on the Internet is growing exponentially every day. A large amount of data not only brings convenience to people’s life, but also brings some problems, especially the retrieval of film resources. Nowadays, there are many types of online movie resources. Video Websites release new movies every day, which makes it difficult for users to quickly find the movie resources they need. Personalized recommendation system helps users solve this problem, but due to the scarcity of user’s ratings, sometimes, the dataset adopted by the current recommendation system only takes one’s user ID into account, which makes the embedding of users single and rigid, and affects the accuracy of recommendation. In this paper, the nodes in heterogeneous network are connected as a meta path so as to deeply develop the relationship between users and items. This method to adjust the embedding of items by modifying the path achieved good results, which proves that this method is effective for improving the effect of the recommendation system.
Rock, Scissors, and Paper: Multi-agent Simulation

We have touched so many different kinds of simulations so far. There is another very important type called agent-based simulation (ABS). Sometimes, it is also referred to as agent-based modeling (ABM). Agent-based simulation is an umbrella term that you can categorize a lot of context-specific or domain-specific simulations as agent-based simulation.
Pseudoleukocytopenia: a Case Report

Hematology analyzers provide quick and accurate results in most situations. However, spurious results related to the parameters from the complete blood count (CBC) may be observed in several instances. False increases in WBC count can occur for many reasons, including erythroblasts, insufficiently lysed red blood cells (RBC), platelet aggregates, lipids, and cryoglobulins. However, cases of pseudoleukocytopenia due to plasma related factors are rare.Here, we report a case of pseudoleukocytopenia in CBC test. It was identified by the peripheral blood smears and different scatter plots of WNR and WDF channel. The interference from plasma was con-firmed by simulating the state of blood in the WBC channel and plasma exchange.It was confirmed that the interference of pseudoleukocytopenia was from the plasma. This may be due to the high amount of albumin and other therapeutic drug reactions. Observation of peripheral blood smears and scatter plots can identify this interference.
Controlling for Latent Confounding by Confirmatory Factor Analysis

When estimating an average treatment effect with observational data, it's possible to get an unbiased estimate of the causal effect if all confounding variables are observed and reliably measured.In education, confounding variables are often latent constructs.Covariate selection methods used in causal inference applications assume that all predictors are measured without error; in contrast, confirmatory factor analytic models account for measurement error.The effectiveness of using CFA to remove selection bias and reduce covariate set dimension is not yet understood well.In this paper, we will investigate how confirmatory factor analysis could be used for controlling for selection bias caused by a latent confounding variable.We compare the effectiveness of different approaches in a Monte Carlo simulation study.
A Lightweight Digital Voting Platform Using Blockchain Technology

Elections are a very significant event in true democracy, but huge segments of society throughout the world do not believe in their electoral system which makes it the main concern for democracy. An ideal election is one that provides the public with a transparent voting procedure that protects the secret of the elector’s identity, the privacy of information transmission, and the verification of votes throughout the billing phase. In this chapter, a lightweight digital voting platform is developed for the voters by integrating Ethereum Blockchain technology with encrypted data strategy and cryptographic techniques to achieve a decentralized e-voting system without the need of a third party. The e-voting system’s frontend is developed using HTML/CSS and JavaScript, while the backend is made with solidity smart contracts and a customizable Ethereum Blockchain supplied by Ganache. These features make the proposed system quite effective for elections conducted on a large scale by providing accurate voting results and reducing the cost of elections to as minimal as possible. This voting system permits the citizen to not just legally vote for a candidate but also provide the infrastructure for the citizen to legally change their vote to a candidate all the time (not just election time) if it’s necessary. Due to high population density and insufficient infrastructure in many countries, peer-to-peer connections are unable to reach the majority of regions (particularly in rural areas) where a decentralized voting system is required.
A UAV multi-agent countermeasures behavior planning for improving positioning

The positioning system based on the time difference of arrival (TDOA) has a systematic error in a specific direction. This paper uses the Multi-agent Deep Deterministic Policy Gradient (MADDPG) method for environmental modeling to improve the error distribution of the positioning system. The element configuration and execution steps of reinforcement learning modeling are analyzed in detail. And then the travel path is planned for the purpose of improving the positioning accuracy. At the same time, the model of the positioned unit under the confrontation condition is established to better get rid of the positioning. In the simulation environment, the camp of unmanned aerial vehicle (UAV) constantly learns and adjusts the strategy to detect the strategy of enemy using the effective area critical line to avoid positioning. The training process is summarized, and suggestions are put forward for the confrontation decision of both camps.
Studying – A Way Towards Justice? A Response to Special Issue: Answering the Question: What Is Studying? PTHE 3(3)

By focusing on study practices and the meaning of studying as a hybrid, or cross-over, activity, the special issue provides a welcome contribution to the philosophy and theory of higher education. As Schildermans rightfully points out in his introduction, putting practices center stage “allows for reformulating the problem of the future university (…) in an ongoing experimentation with the practices of study that still find place at the university.” 1 The various contributions show that studying as an experimental practice overflows institutional borders and disciplinary boundaries through various collaborations and partnerships with different publics and stakeholders. The call for a reclaiming of study practices as experiment 2 certainly is a most timely and inspiring invitation to move higher education teaching and learning practices beyond disciplinary silos and institutional trenches, and to encourage cross-stakeholder collaboration and transdisciplinary practices and knowledge understandings in higher education. 3
Syntaktisk komplexitet i inlärarsvenska: en jämförelse mellan finska universitets-studenters muntliga och skriftliga produktion på två olika färdighetsnivåer

This study examines how proficiency level affects syntactic complexity in written and spoken L2 Swedish. Spoken production can be more challenging for learners at lower proficiency levels due to the limited resources for processing the target language (Skehan 1998), whereas the possibility for more extensive planning during the writing process enables the production of syntactically complex structures in writing (Skehan &amp; Foster 2012, Tavakoli 2014). Automaticity at higher proficiency levels reduces the cognitive load that the spoken production imposes on learners and facilitates the production of complex structures in speech (Leonard &amp; Shea 2017). However, few studies have directly compared complexity in written and spoken L2 production, and earlier studies have resulted in contradictory results (Kuiken &amp; Vedder 2012b:364–365). The data in this study consist of monologues and essays produced by 31 Finnish university students. Some subjects study Scandinavian languages as their major, while others take part in a Swedish course at the Centre for Language and Communication Studies. The analysis is based on surface-level complexity measures, such as the mean length of production units and the dependent clause ratio. The results show that proficiency plays an important role especially in spoken production and, therefore, also in the differences between written and spoken production. At the lower proficiency level, written production is significantly more complex when it comes to the mean length of T- and AS-units, the dependent clause ratio, and the ratio of dependent clauses with a sentence adverbial. Surprisingly, the mean clause length shows higher complexity in speech at the lower proficiency level. At the higher proficiency level, there are no statistically significant differences between the modalities. These results indicate that the cognitively more demanding task of producing L2 speech can lead to the use of simple structures at the lower proficiency level, resulting in a greater difference between written and spoken complexity. The learners at the higher proficiency level seem to be able to produce complex structures also in the spoken mode, and therefore, there are no significant differences between written and spoken complexity at this level.
A Survey on Function Level Scheduler to Minimize the Cloud Provider Resource Cost in Serverless Cloud Computing

Industry started providing the services in the form of function executions and charge the clients based on the execution time and not on the machine idle time. This change the paradigm change the way in which people started looking at cloud computing. In this paper we survey on many things which are not known to the user when they are using the platforms like AWS lambda, IBM Open Whisk and Microsoft Azure Funtions, Google cloud functions as the payment model. How the runtime is brought and saved back upon the policy of the service provider in Serverless cloud computing function as a service platforms.
Does Physicality Impact Learner Interactions? Evidence From Tangible and Digital 3-D Models

This study investigated differences in how students interacted with tangible (3D prints) and digital 3D models.Sixth grade students worked in collaborative groups during an in-class inquirybased science activity.Each group was recorded using a video camera during the learning activity and student behaviors while interacting with the 3D models were coded and analyzed.Results showed that students chose different interactions when examining tangible vs. digital 3D models.Tangible models elicited more dynamic action and simulated behaviors than the digital models but these behaviors were relatively rare across all models.Distracted behaviors occurred at a higher rate when students interacted with the digital 3D models.Implications for learning with 3D models are discussed.
Integration of Blockchain Technology and Intelligent System for Potential Technologies

The introduction of artificial intelligence (AI) enhances the capability of some objects to think for themselves, allowing for greater privacy and security. It may also be said that blockchain and AI are two fascinating new technologies today that are organically linked.Bringing out the smarts of blockchain facilitates an increase in AI’s independence and trustworthiness. We discuss AI from an industry perspective, taking into account its many facets. Blockchain and AI here, we discuss the way the two are converging at home, as well as around the world, and how they can be harnessed to realise an idea. In addition, we identify the current issues and difficulties associated with both technologies. The future projects are exciting to us and we are looking forward to them.
Heterogeneous Teams of UGVs and UAVs for Multipurpose Operations

The development of heterogeneous teams of unmanned ground vehicles (UGVs) and unmanned aerial vehicles (UAVs) for different mission types has deserved increasing attention of researchers in recent years, as the technology enables building more complex and resilient robot systems. In this talk I will describe some of the work done by my group on developing a multipurpose, autonomous, mobile manipulator for building outdoor structures and for firefighting, developed to participate in the Mohamed Bin Zayed International Robotics Challenge (MBZIRC) 2020, but also as a first step towards a team of UAVs and UGVs designed to inspect and regularly monitor solar farms. I will present with some detail the hardware and software architectures of the developed mobile manipulator, and the developed methods for building outdoor structures consisting of heterogeneous brick patterns, and entering buildings to locate and extinguish fires. Solutions were successfully deployed in the near-realistic arenas of the MBZIRC 2020 competition and resulted in the first-place award for the firefighting scenario. Then I will provide some insight on ongoing work concerning the use of this UGV and an UAV fleet to search for solar panel defects in large-area solar farms, where autonomy is an important step for future operation.
The Effects of Organizational Commitment on Non-Financial Performance: Insights from Public Sector Context in Developing Countries

Electric energy companies in developing countries face challenges such as low employee organizational commitment, which affects productivity and performance, thereby limiting the ability to fulfill the necessary obligations towards citizens. Therefore, this study aims to examine the effects of organizational commitment on non-financial performance in the electricity sector in the context of developing countries. The quantitative approach was used in this research to achieve the study's objectives. The data of the study were collected from 408 respondents and analyzed in two steps; the first step is the assessment of the measurement via Confirmatory Factor Analysis (CFA) while the second step is the testing of the developed hypotheses for the study using Structural Equation Modelling (SEM). The outcome of the study showed a direct positive and significant impact of organizational commitment on organizational performance. The limitations of this study and some recommendations for future research were also presented in this study. Keywords: Organizational Commitment, Organizational Performance, Electricity Sector, Non-Financial Performance, Public Sector in Developing Countries