Reviewerly/exHarmony huggingface dataset:
Korean Teacher’s Ability to Manage Non-face-to-face Classes A Study on Job Stress and Job Challenge

The purpose of this study is to empirically identify the job stress and job challenge perceived by Korean teachers in the non-face-to-face classroom environment caused by COVID-19. Today’s evolving technological advances and the variable COVID-19 have had a direct impact on the change in the educational field. The introduction of the non-face-to-face class method changed the educational paradigm and had an effect on the job of the professor. In particular, in the case of Korean classes for foreigners, there was a lot of trouble from designing the class method. In order to achieve the purpose of this study, qualitative data were collected and analyzed from 5 Korean language teachers at metropolitan universities. The research method was a semistructured interview based on a questionnaire, and took three forms: face-to-face, telephone, and video. The results of interview data analysis were able to draw contradictory results in job stress and job challenge. Job stress increased due to non-face-to-face classes, but on the other hand, job challenge also increased. The factors contributing to job stress were the application of the online job environment, the difficulty of interaction between teachers and learners, and the phenomenon of work overload. Nevertheless, the professor had the characteristic of being able to demonstrate job challenge by producing high-quality educational contents. Factors affecting job challenge include competency development and expansion, creative idea creation, and job prospect search. Based on the analysis results, conclusions and implications for improving job stress and job challenge of Korean teachers were presented.&#x0D;
Application of Virtual Reality in Medical Field

Virtual reality is an software technology that is used by the user to experience an real world scenario by sitting at their desired place. This paper is based on the analysis of how VR is used for solving medical related problem. VR provides a best way for planning major surgeries and it helps the young medical practitioner to excel their practical skills. It helps to make plan for any treatment before implementing it on patients. In this paper we will see its applications and uses in the medical field.(2) Keywords Virtual Reality, Visualization, Architecture, Diagnosis, Surgery.
A Phenomenological Study on the Learning Experiences of College Students in a Non-Face-to-Face, Non-Real-Time Class Environment after COVID-19

The purposes of this study were to explore the learning experiences of college students in a non-face-to-face, non-real time learning environment after COVID-19. In-depth interviews were conducted on nine college students’ learning experiences before and after COVID-19 for three months from September to November 2021, and the collected data was analyzed by applying Giorgi’s phenomenological research method. As a result of the analysis, 59 central meanings, 21 revealed themes, and 7 essential themes were derived. The themes derived were ‘a class consisting of difficult to communicate, poor quality contents and insincere explanations’, ‘convenience of non-face-to-face classes’, 'face-to-face classes that are easy to participate in and immerse sic’, ‘tasks with different types and difficulties due to the nature of the class’, ‘a well-remembered class’, ‘sloppy tests and evaluation methods without discrimination in non-face-to-face classes’ and ‘system and environmental improvements’. In the post COVID-19 era, changes in university teaching methods will be needed, and this study can be used as a basic study for this.
Malicious Detection of Links using Extension of Quick Response Codes

MALICIOUS DETECTION OF LINKS USING EXTENSION OF QUICK RESPONSE CODES Shamil Aripov Master degree, Department of Computer Engineering &amp; Information Security, IITU University, Kazakhstan, Almaty Abdul Razaque Full Professor and IT
Blockchain Enabled Healthcare Secure Data Storage System

Data security or secure storage of medical information is usually a significant concern for the bulk of the population. An efficient healthcare system needs a technology platform to speak firmly and seamlessly. Block chain has been emerging technology for a few years now. The key options of block chain which attract most developers are its immutableness, decentralization, transparency, distributed ledger. We tend to propose a Healthcare Secure Information Storage System (Life Care) that firmly manages personal medical records and creates an interaction between Doctors and Patients. The Life Care system is meant to improve the current systems because it provides interoperable, secure, and effective access for medical records by patients. It provides timed-based smart contract for governing transactions and dominant access to electronic medical records. The security is ensured by using SHA-256 encryption technique with Blockchain to store hash data for providing security, new incentive mechanism that leverages the degree of health suppliers concerning their efforts in maintaining medical records and making new blocks.
THE PROFESSIONALLY - IDENTIFYING COMPETENCE OF THE TEACHER IN PEDAGOGICAL ACTIVITY

THE PROFESSIONALLY - IDENTIFYING COMPETENCE OF THE TEACHER IN PEDAGOGICAL ACTIVITY Dinara Kodirova Master&rsquo;s degree in Pedagogical Sciences The Ablai Khan KazUIRandWL, Kazakhstan, Almaty &nbsp; ABSTRACT The article is concern
FINANCIAL RISK METER FOR CRYPTOCURRENCIES AND TAIL RISK NETWORK-BASED PORTFOLIO CONSTRUCTION

Cryptocurrencies have emerged as a new asset class. In order to provide a thorough understanding of this new asset class, we study the dependencies in tail risk events within cryptocurrencies, and provide a hedging alternative in this paper. First, we adopt the Financial Risk Meter approach for cryptocurrencies, which is able to identify individual risk characteristics and indicate systemic risk in a network topology. Next, we detect the interdependencies across digital coins and study the spillover effects. Finally, we construct tail event sensitive portfolios and test the performance versus traditional approaches from January 2019 to May 2022.
EFL Students’ Perceptions and Use of Google Translate in Afghanistan

Google Translate (GT) is widely used by EFL learners around the world. The current study examined the use of GT by EFL learners from Afghanistan. The author used a survey questionnaire to collect data from 132 randomly selected students from a public university in northeastern Afghanistan. They used descriptive and inferential statistics to analyze the data. The findings showed that the vast majority of the participants sometimes and often used GT, and they had positive attitudes towards it. The majority of them believed that GT helped them do their writing assignments, improve their vocabulary, understand reading passages and gain translation skills. They were aware of drawbacks of GT and believed that GT led to dependence, laziness and it demotivated students to learn vocabulary. They used GT for a number of reasons including lack of confidence in their own translation, saving time and convenience. Furthermore, EFL students often used GT to look up words, terminologies, collocations and idioms and to translate phrases, sentences, paragraphs and essays. The study showed that students’ gender had a significant impact on their attitudes towards GT but not on their use. The study recommends EFL teachers to provide their students with instructions on proper use of Google Translate.
Novel Approach for Access Control for Electronic Health Records with Hybrid Blockchain – Edge Architecture

The global electronic health record (EHR) industry is predicted to develop at a rapid pace, reaching $39.7 billion by 2022. Access control is a critical tool for managing EHR data to ensure its security and privacy. This study offers a hybrid architecture that uses both blockchain and edge nodes to facilitate access control of EHR data. A blockchain-based controller controls identity and access control regulations and acts as a tamper-proof log of access events inside the architecture. In addition, in combination with the blockchain-based access control logs, off-chain edge nodes store EHR data and apply policies provided in the Abbreviated Language For Authorization (ALFA) to impose attribute-based access control on EHR data. We test the proposed hybrid architecture by measuring the performance of executing smart contracts and ACL policies in terms of transaction processing time and response time against unauthorized data retrieval using the Hyperledger Composer Fabric blockchain.
Abstract 5058: Recurrence risk prediction based on automatic histopathologic analysis of breast cancer using whole slide images

Abstract The RS (Recurrence Score) is the results of a 21-gene test assessing the likelihood of breast cancer recurrence for hormone-positive, HER2-negative, and node-negative breast cancer patients. We conducted an experiment to find out whether there is a correlation between the RS value derived through genetic testing and specific morphological characteristics of breast cancer tissues with the expectation that these morphological features could predict RS values. Deep learning was utilized to assess the morphology of the hematoxylin-eosin (H&amp;E) stained whole slide images (WSIs) of breast cancer. In this study, we used 125 breast cancer cases associated with H&amp;E stained WSIs and RS scores which were divided into 3 risk groups based on the RS values: the low-risk group with 49 cases, the intermediate-risk group with 59 cases, and the high-risk group with 17 cases (low-risk for RS &amp;lt; 18, high-risk for RS &amp;gt; 31, and intermediate-risk for RS in between). On each WSI, an expert pathologist has annotated invasive breast tumor regions. We divided WSIs into 512x512 patches and trained a deep CNN model to classify the patches as benign (including DCIS), low-risk, intermediate-risk, or high-risk. In determining the risk group of each WSI, all patches from the WSI were classified by the model first, and then their majority class was assigned to the WSI. A nested cross validation was adopted to evaluate how well the model generalizes. The performance of the algorithm is shown in Table 1. According to the results, our model was able to distinguish between the low-risk group and the high-risk group to some extent. In particular, there was no case of misclassifying the low-risk group as high-risk. Since these high-risk patients require radiological examination, there is an advantage that the 21-gene test is not required. Although our model has yielded modest results, we believe that future studies through the integration of additional data with other clinical and pathological data will yield better results. Result Table 21-gene test result (*ground truth) Low Intermediate High Prediction Low 42 14 0 Intermediate 5 44 8 High 2 1 9 Accuracy 0.932 0.776 0.912 Sensitivity 0.857 0.746 0.529 Specificity 0.816 0.803 0.972 PPV 0.851 0.772 0.750 Citation Format: Geongyu Lee, Chungyeul Kim, Tae-Yeong Kwak, Sun Woo Kim, Hyeyoon Chang. Recurrence risk prediction based on automatic histopathologic analysis of breast cancer using whole slide images [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5058.
[Evaluation of Sysmex XN-3000 for Detection of Schistocyte].

Compared with the method of optical microscopy, to evaluate the accuracy of fragmented red cells(FRC) detection by Sysmex XN-3000.A total of 111 samples were collected from patients diagnosed as thrombotic thrombocytopenic purpura, autoimmune disease, hematological disease, malignant tumor and health examination in our hospital from June 2019 to February 2021, including 74 cases in the case group and 37 cases in the healthy control group. All samples were detected by optical microscope and Sysmex XN-3000, respectively. ROC was used to evaluate the detection ability of Sysmex XN-3000 for schistocyte. Bland-Altman method was used to evaluate the consistency of the results of the two methods for detection of schistocyte, and Pearson correlation analysis was conducted for the difference of the results.The area under the ROC curve was 0.890(95% CI: 0.828-0.952, P<0.01). Sysmex XN-3000 count did not quantitatively agree with schistocyte counts by microscopy in the case group(mean of difference:-1.53, 95% limits of agreement: -8.78~5.72). There was a weak positive correlation between platelet count and the difference of analyzer and microscopic results (r=0.32,P<0.05).Sysmex XN-3000 can be used as a reference for qualitative determination of schistocyte. However, the sensitivity of Sysmex XN-3000 should be improved. It is still necessary to combine with manual microscopy. The quantitative results are not reliable now and cannot be used as a reference for monitoring the results of schistocyte in clinical patients after treatment.Sysmex XN-3000对裂红细胞检测的结果评价.与光学显微镜方法比较，评价Sysmex XN-3000的检测参数破碎红细胞（FRC）对裂红细胞检测的准确性.收集中国医科大学附属第一医院2019年6月-2021年2月诊断为血栓性血小板减少性紫癜、自身免疫病、血液病、恶性肿瘤患者和健康查体者标本共111例，其中病例组74例，健康对照组37例。分别用光学显微镜和Sysmex XN-3000对所有标本进行检测，利用ROC曲线评估Sysmex XN-3000对裂红细胞的检测能力。用Bland-Altman法评价两种方法检测结果的一致性并对造成的结果差异进行Pearson相关性分析.ROC曲线分析Sysmex XN-3000对裂红细胞检测的曲线下面积为0.890(95%CI：0.828-0.952,P<0.01)。两种方法检测病例组裂红细胞结果不一致（差值平均值-1.53,95%LoA，-8.78~5.72）。血小板计数与检测结果差值呈弱正相关(r=0.32,P<0.05).Sysmex XN-3000可用于裂红细胞定性检测的参考，但敏感度低，仍需结合光学显微镜检查。定量结果暂不可靠，不作为对临床患者治疗后裂红细胞结果监测的参考.
Improving English Learning For Kindergarten Students Through Commma Application In New Normal Era

English is one of international languages for connecting and sharing knowledge throughout the world. As regulated in the national standards of early childhood education (PAUD), language is one of the measurement criteria in the early childhood education system. The aim of this research is to assist schools in improving human resources by providing training on English teaching methods with the Total Physical Response (TPR) method and English teaching applications with the android-based application called Comma. we collaborated with partners to design and create Comma application concept and system. The aim of this program is improving the quality of human resources in terms of teaching English for kindergarten students. The test results state that all operations can be performed on this Comma application which shows the system operated as expected or it can be said that the system testing is successful so that the Comma application is ready to be released and used by users who need this application to improve their English skills through the TPR method. With the Comma application, it can be used to improve understanding of the English language, especially in early childhood education and can be used as a good alternative in teaching English in the early childhood education environment
Browser Based Malicious Domain Detection through Extreme Learning Machine

The main aim of the project is to detect the malicious domains in the internet through Machine learning approaches and is helpful in preventing the cybercrime. For that Extreme Learning Machine(ELM) approach is used to find the malicious domains in the web. The Terms used for the project are Browser application, extreme learning machine, feature selection, malicious domain detection, machine learning, Real-time training. This approach will be helpful in reducing the cybercrime such as harmful websites, fake websites that stores the user information, malicious attack website domains.
AMCGWO : An enhanced feature selection based on swarm optimization for effective disease prediction

Missing data in datasets remain as a difficulty in terms of data analysis in various research fields, especially in the medical field, as it affects the treatment and diagnosis that the patient should receive. An enhanced imputation model using MFWCP (Mode Fuzzy Weight based Canonical Polyadic) and BN (Bayesian Networks) is proposed with respect to the dependency between the attributes and the type of incomplete attributes in order to especially improve the prediction of breast cancer (BC) and heart disease. The proposed work, Adaptive Mean Chaotic Grey Wolf Optimizer (AMCGWO) helps to identify new subsets of feature including evaluation metrics that are used to score various subset of features from the missing data imputed dataset. Most feasible technique is to analyze each feature set for reduced error rate. The proposed technique outperformed in terms of precision, recall, f-measure, accuracy, specificity and Normalized Root Mean Square Error (NRMSE) values in CNN than existing classifiers like KNN (K-Nearest Neighbour), DT (Decision Tree) and ANFIS (Adaptive Neuro Fuzzy Inference System)
Review of Case Study of Q. Finder - Real-Time Interface to Fetch Questions from YT Live Stream

Nowadays, all over the planet embedding live streaming YouTube video in our own responsive web site. Embedding videos is simply like making backlinks to your website. Like in SEO (Search Engine Optimization), embedding your videos in a very website behaves specifically sort of a back link and so facultative your videos to urge placed in program results and find a lot of views. A lot of number of views our videos receive, our video quality and complete image increase too. Not solely video quality, your product and website quality too increase so increasing your sales and profits. Video embedding is the method of adding a video player to our web site victimization of an internet video platform. There are several web sites that are building their own social media platforms, so it is as easy as copying and pasting a link. Video inserting works by adding associate degree embed code from your video hosting platform to the code of your web site. It permits you to integrate live streaming on our website. Ranking is to be provided for live chat of the live video stream. Relevance ranking is the process of sorting the chats so that those Questions which are most likely to be relevant to the topic are shown at the top of the chat window with the answer.
RHETORIC SYMBOLS AS THE KEY IN ORGANIZING IDEAS OF NARRATIVE TEXTS FOUND IN DR. SEUSS CHILDREN BOOKS

The aim of this research was to describe how the rhetoric symbols were reinforced to organize the Ideas of Narrative Texts found in Dr. Seuss Children Books. He had written the children books more than 60 childrens books including several of the most popular childrens narrative books of all time coming from America. This study was descriptive Qualitative by using textual analysis. The sources of data of this research were Dr. Seuss children books in the form of narrative Horton Hatches the Egg, Thidwick-the Big Hearted Moose, The Kings Stilts, and Bartholomew and the Oobleck while the data in this research were all kinds of information in the sources of data referring to the focus of research. They were analyzed synchronically and diachronically in the process of data analysis. The result showed that the rhetoric symbols were synergized to the other symbols such as animals, natures, and objects which were wrapped in the concept of id, ego, and superego through the generic structure of texts involving orientation, complication, evaluation, resolution, and coda. Its hoped it could give the contribution to the concept of creative writing especially in narrative.
Manhole Quality Management and Sensing Using IOT

'A novel design of a model method of quality management of manholes in metropolitan cities that can improve the efficiency of civic bodies in an urban and technology driven country'. In these recent times, aging and outdated public sewers and underground networks and facilities have caused increased needs for systems that support the robust maintenance and management of social infrastructure. There are dire needs for measure regarding manholes involved in water, sewage, gas and electric facilities, including the supplementary countermeasures to prevent the covers from being subjected to damaged or displaced due to ill manner of maintenance, aging or torrential rainfall that exceeds its drainage capacity. There is also concern regarding covers being stolen or manholes being used in acts of terrorism, and efforts to solve the problems caused by manholes are required so that people can live in a safe environment and are not subjected to any freak accidents or unfortunate mishaps. This social concern can be monitored and solved with the integration of Internet of Things (IoT) will enable us to effectively solve the problems regarding underground network of sewers. Internet of Things (IoT) consists of real-life objects, communication devices attached to sensor networks in order to provide communication and automated actions between real world and information and data driven world.
Differentially Private Wireless Federated Learning

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Research and Analysis on Voice Based System with Machine Learning

This Chatbots in banking are primarily used to improve the client experience. They do, however, benefit the personnel and help to avoid uncomfortable circumstances that can emerge from direct contact with clients. Customers might benefit from artificial intelligence in a variety of ways. The most prevalent use scenario for chatbots in bank customer service is the automation of mundane repetitive chores. These activities want quick and easy answers that necessitate self-learning. Banking chatbots can be implemented as standalone mobile banking applications or integrated banks' websites. Chatbots can be custom-made or ready-made in terms of their origin. Custom AI assistants are generally more effective and secure because they are built to exact requirements and under the close supervision of the financial institution where the hot will be incorporated. Ready-made solutions are generic bots designed to be as versatile as possible while yet allowing for some customization.
LEARNING INNOVATION IN THE MIDDLE OF A PANDEMIC: WHAT ARE THE PERCEPTIONS OF STUDENTS, TEACHERS AND PARENTS?

Online learning is one of the biggest innovations in the world of education in the pandemic era. All levels of education have implemented online learning, including in this case elementary school. This study aims to determine the perceptions of students, teachers, and parents in the application of online learning in elementary schools. The type of research used is descriptive qualitative. Data collection through questionnaires and interviews. The informants in this study were thirty-five elementary school students, one teacher, and four parents. The research was conducted at one of the elementary schools in the East Lombok district. The results of the study indicate that most students do not like online learning, many students have difficulty in learning online, lack focus in learning, cannot understand the subject matter well, and find it difficult to do assignments. In the perspective of online learning, teachers are considered to have many obstacles, one of the most severe obstacles is the use of technology and difficulties in explaining the subject matter to students properly. Parents' perceptions of online learning include online learning that costs more and adds to the burden on parents, especially when they have to help students do schoolwork at home. Student learning activities in online learning are less than optimal, students spend more time playing than studying. Based on the results of this study, shows that innovation in learning during a pandemic has many challenges. Serious intervention is needed to change the way all stakeholders think about online learning.