Reviewerly/exHarmony huggingface dataset:
Development of openEHR template for Coronavirus disease 2019 based on clinical guidelines

BACKGROUND: Coronavirus disease 2019 (COVID-19) was discovered in China since December 2019, it has developed into an extremely threatening emergency for international public health Except for China, the number of cases in other countries continues to increase Lots of studies about disease diagnosis and treatment have been carried out and many clinically proven effective results have been achieved Although information technology can improve the transferring of such knowledge to clinical practice rapidly, data interoperability is still a challenge due to the heterogeneous nature in hospital information systems This issue becomes even more serious if the knowledge for diagnosis & treatment is updated rapidly like the one for COVID-19 An open, semantic sharing and collaborative information modeling framework is needed to rapidly develop a shared data model for exchanging data among systems openEHR is such a framework supported by many open software that help to promote information sharing and interoperability OBJECTIVE: The study aims to develop a shared data model based on the openEHR modeling approach to improve the interoperability among systems for the diagnosis and treatment of COVID-19 METHODS: The study aims to develop a shared data model based on the openEHR modeling approach to improve the interoperability among systems for the diagnosis and treatment of COVID-19 RESULTS: The latest Guideline of COVID-19 Diagnosis & Treatment in China is selected as the knowledge source for modeling First, the guideline was analyzed and the data items used for Diagnosis&Treatment/Management were extracted Second, the data items were classified and further organized into domain concepts with mind map Third, searching was executed in the international openEHR Clinical Knowledge Manager (CKM) to find the existing archetypes which can represent the concepts New archetypes were developed for those concepts that cannot be found Fourth, these archetypes were further organized into a template using Ocean Template Editor Finally, a test case of data exchanging between CDR and CDSS based on the template has been conducted to verify the feasibility of the study CONCLUSIONS: 203 data items were extracted from the guideline in China, 16 domain concepts (16 leaf nodes in the mind map) were organized 22 archetypes have been used to develop the template for all data items extracted from the guideline All of them could be found in CKM and reused directly The archetypes and templates were reviewed and finally released in a public project within the CKM The test case showed that the template can facilitate the data exchanging and meet the requirements of decision support CLINICALTRIAL:
STRUCTURE OF THE CONCEPT: INFORMATION CULTURE OF THE FUTURE TEACHER OF CHEMISTRY

The article considers the preconditions for the emergence of the phenomenon and the concept of "information culture". The purpose of article is to identify the main components of the information culture of the individual, and to analyze their relationship. The author used the methods of logical comparison, systematization and generalization, which allowed to achieve the goal of the study and draw conclusions. The high rates of scientific and technological progress, the expansion of cognitive activity of people, the emergence of new sciences, the rapid change of not only production but also social technologies, the dynamism of modern society - all these aspects became the basis for significant growth of information resources. The factors of changing the attitude to the concept of "information culture" in chronological order are given. Distinctive and similar features in the views and attitudes to the "information culture" of scientists "East" and "West" are considered. The main approaches to the definition of "information culture" are highlighted. The views of scientists on the components of information culture are listed. The expediency and importance of using the activity approach to the formation of information culture are given. The main components of information culture of personality are singled out. A brief analysis of the interaction of each component is given.
Model of English Communicational Skill Development of Taxi-Driver in Thailand

The research purposes of the model of English communicational skill development of taxi-driver in Thailand were 1) to survey the English using skill of taxi-driver in Thailand  2) to create and determine the efficiency of the manual of developing of English using skill 3) to study satisfaction with the manual of developing of English using skill of taxi-driver in Thailand. The examples of the research were 20 taxi-derivers in Thailand at Mahachulalongkornrajavidyalaya University. The methodology of the research was the manual of developing of English using skill of taxi-driver in Thailand which was developed by the researcher. The tests of English communication of taxi-driver in Thailand and the questionnaires of satisfaction were analyzed by statistics.The results of the research were found that manual of developing of English using skill of taxi-driver in Thailand had sufficiency at 81.63/84.70 related with the standard at 80/80. The level of English communicational skill development of taxi-driver in Thailand after using the manual of developing of English using skill of taxi-driver in Thailand higher than former using the manual had statistical significance at .05 and the examples’ satisfaction for the manual of developing of English using skill of taxi-driver in Thailand in general was at high level. When considering each aspect was found that every aspect was high such as aspect of taking English for using real situation in daily life of taxi- drivers in Thailand, aspect of satisfaction for the manual of developing of English using skill and the aspect of satisfaction for teachers.
The approach to automating the processing stages of refracted seismic data

In this paper, we consider approaches to automating several stages of processing engineering seismic data: summing seismograms of different accumulations, picking the first arrival times, minimizing the residuals of mutual times for the hodograph system. The proposed methods are based on the comparison of waveforms of several traces using the cross-correlation function. The methods were tested on synthetic data to evaluate the optimal parameters of the procedures. Real data testing shows that the developed algorithms yield the results equal to manual processing.
Identification and Test Analysis of Scattered Objects in Traffic Accident Scene

Abstract The scattered objects contain a lot of important information on the scene of traffic accidents. The identification and extraction of relevant characteristic values of the scattered objects on the scene of traffic accidents can provide important basis for solving the collision speed of the vehicles in the accident and provide some evidence for the handling of traffic accidents. In this paper, scattered objects on the scene of traffic accidents are taken as the research object. According to the theoretical model of camera imaging and the characteristics of scattered objects in the accident site, a camera calibration system was proposed by combining with MATALB software. In order to reduce the error caused by background environment in the calibration process, the red calibration object with known structure size was designed to obtain the aerial photography image containing the calibration object. MATLAB was used to extract the calibration object in the image and establish the relationship model between the actual value of the calibration object and the image value. The image processing accuracy was improved by gray transformation, Wiener filter denoising, Laplace sharpening and Canny algorithm edge detection. Taking circular and irregular scattered objects as examples, the simulation test is designed. The proposed calibration method and image processing method are applied to identify the features of scattered objects. The identification results are calculated and compared with the actual measurement results to verify the accuracy of the proposed method and provide a reference for on-site accident treatment.
Conversion and Visualization of Remote Sensing Image Data in CAD

In this paper, a process visualization model for remote sensing image classification algorithms is constructed to analyze the current processing characteristics of process visualization in remote sensing application systems. The usability of the model is verified in a remote sensing application system with a remote sensing image classification algorithm based on support vector machines as an example. Given the characteristics of remote sensing applications that require high visualization process and a large amount of data processing, the basic process of an image classification algorithm for remote sensing applications is summarized by analyzing the basic process of existing image classification algorithms in remote sensing applications, taking into account the characteristics of process visualization. Based on the existing process of remote sensing image classification algorithm, a process visualization model is proposed. The model takes a goal-based process acts as the basic elements of the model, provides visualization functions and interfaces for human-computer interaction through a human-computer interaction selector, and uses a template knowledge base to save processing data and realize the description of customized processes. The model has little impact on the efficiency and accuracy of the support vector machine-based remote sensing image classification algorithm during the process of process visualization and customization. Finally, the application of the model to integrate business processing of earth observation can address the problem of process customization visualization for remote sensing applications to some extent.
Diagnostic of the Malarial Parasite in RBC Images for Automated Diseases Prediction

The malaria parasite is an ancient organism; it's been on Earth longer than humans. Malaria is one of the most dangerous diseases ever faced by humans. Nearly 1 to 3 million humans die annually due to this disease. As it is a serious health problem, we have built a model in which we used Giemsa blood samples to detect the malaria parasite in order to reduce deaths caused by it. In this procedure, we used segmentation using K-means clustering operations in order to detect the malarial parasite from the Giemsa blood samples so that our study could reduce errors caused by humans in the field of malaria detection. This segmentation process can further initiate development of computer-aided diagnostic tools. Automated disease detection can be useful in the case of patients staying in far flung areas or in the case of a pandemic or epidemic. The efficiency of the proposed methodology is done by using structural similarity content and comparing the parameters with the popular adaptive thresholding technique.
Fostering formal education by online education

Recently, education has transversed the unknown terrain of a quarantine imposed by the COVID-19 (popularly known as coronavirus), which has left over 850 million students around the world studying at home according to the United Nations Educational, Scientific, and Cultural Organization (UNESCO, 2020. This situation has stopped the formal education system and brought distance education and online education to the agenda. The objective of this study is to address the situation the education is in. A qualitative and descriptive study was conducted for in-depth and further probing and questioning of respondents based on their responses to the versus formal education halting due to Corona Virus, where researcher also tries to understand the problem and highlighting solutions in case of stopping education. From the results of the study, to achieve the ideal learning objectives, it is also necessary to have a sufficiently trained teaching staff in the methodological plane of online teaching, including the use of technical resources. At his point, using virtual online systems in education makes it necessary for both students and teachers to take new positions and acquire new roles in education. In the study, it is pointed out that teachers and students should fully plan lessons with integrated technological resources to support the digital transformation process by adopting predominantly technology-based teaching models and systems. By the new virtual classrooms, teachers create an environment where students can freely interact with one another and their education will continue without disruption.
The Role of Social Media as a Measures of Information Delivery to Reduce the Risk of Flood Disasters in Kecamatan Pasar Kliwon, Surakarta City in 2020

&lt;em&gt;This study aims to perceptions and responses to flood disaster risk reduction social media in Pasar Kliwon District, Surakarta City, 2020. Utilization of whatsapp social media as a means of delivering information to the public in an effort to reduce disaster risk flooding in Pasar Kliwon Subdistrict, Surakarta City, 2020. the impact of the use of whatsapp social media as a means of delivering information on community efforts to reduce the risk of flood disasters in Pasar Kliwon District, Surakarta.The results of the study are as follows: Perception of flood disaster in Pasar Kliwon Subdistrict, if viewed from the potential of the disaster, it can be categorized as very large. For flood disaster vulnerability is also categorized as flood disaster prone. And disaster mitigation is carried out in the form of responsiveness and preparedness from stakeholders. Here the use of social media as a means of delivering flood disaster information.&lt;/em&gt;
작문 교육의 관점에서 ‘저자성(authority)’ 논의를 위한 시론

The purpose of this study is to analyze the notion of authority in writing education and to suggest directions for writing education based on authority education. Authority refers to the role assumed by the writer and to the relationship he/she establishes with society in his/her writing activities. Authority is also present through an own voice and unity in the text.This study investigated texts of undergraduate students and categorized them into four levels of authority: (1) texts without an own voice, (2) texts with only an own voice, (3) texts that revealed an own voice on par with many other voices, and (4) texts that raise an own voice in response to various voices. The results revealed that, from level 1 to level 4, authority was strengthened and the process and regulatory aspects became more prominent in the perspective of writing education.If the ultimate goal of authority education is to train writers to conduct the dialogue process in writing through the recognition of authority, its most important strategy is to help writers recognize, monitor, regulate, and practice authority. The exploration of authority consists of a practical search for the incorporation of belief in the author''s growth in the writing process.
UPB at SemEval-2020 Task 12: Multilingual Offensive Language Detection on Social Media by Fine-tuning a Variety of BERT-based Models

Offensive language detection is one of the most challenging problem in the natural language processing field, being imposed by the rising presence of this phenomenon in online social media. This paper describes our Transformer-based solutions for identifying offensive language on Twitter in five languages (i.e., English, Arabic, Danish, Greek, and Turkish), which was employed in Subtask A of the Offenseval 2020 shared task. Several neural architectures (i.e., BERT, mBERT, Roberta, XLM-Roberta, and ALBERT), pre-trained using both single-language and multilingual corpora, were fine-tuned and compared using multiple combinations of datasets. Finally, the highest-scoring models were used for our submissions in the competition, which ranked our team 21st of 85, 28th of 53, 19th of 39, 16th of 37, and 10th of 46 for English, Arabic, Danish, Greek, and Turkish, respectively.
A Study on the Improvement for Problems of ICT-related laws system in Korea

Korea's laws regarding ICT must follow the Void for vagueness doctrine, the Principle of forbidden general delegation, the Principle of justification of system and the Principle of balancing test in the Constitution. The Act for the Promotion and Convergence and so on of Information and Communication in the Future should be improved as follows. It is desirable to improve the part where the principle of system justification of the Constitution is problematic in relation to existing laws. It is desirable to improve the ICT's policies on industry and convergence technologies so that they are well balanced between promotion and regulation of ICT's industries. It is desirable to improve the information service policy and legislative makeup relationship between various government agencies related to ICT. It is therefore desirable to improve the institutional complement to the post-regulatory framework for the protection of users of ICT in the future. It is desirable to create a device to replace the functions of the Information Service Budget Council in the special law of ICT.
Compressing Colour Images with Joint Inpainting and Prediction

Inpainting-based codecs store sparse, quantised pixel data directly and decode by interpolating the discarded image parts. This interpolation can be used simultaneously for efficient coding by predicting pixel data to be stored. Such joint inpainting and prediction approaches yield good results with simple components such as regular grids and Shepard interpolation on grey value images, but they lack a dedicated mode for colour images. Therefore, we evaluate different approaches for inpainting-based colour compression. Inpainting operators are able to reconstruct a large range of colours from a small colour palette of the known pixels. We exploit this with a luma preference mode which uses higher sparsity in YCbCr colour channels than in the brightness channel. Furthermore, we propose the first full vector quantisation mode for an inpainting-based codec that stores only a small codebook of colours. Our experiments reveal that both colour extensions yield significant improvements.
Algorithm For Quality Assurance Of Student Learning With A Lack Of Information

The article is devoted to assessing the quality of student learning at the university. At the present time the number of students receiving distance learning is increasing. There are experts believe that with distance learning the quality of education decreases. Therefore, it is important both to assess the quality of education and to improve the quality of student learning, both in full-time study and in distance learning. To solve this problem, it is necessary to develop algorithms for assessing the quality of student learning. When developing such algorithms, difficulties arise, in particular, due to the fact that information about the knowledge, skills and abilities of students is not complete, distorted, and contradictory. Therefore, an algorithm for assessing the quality of student learning with a lack of information is proposed. Based on this algorithm a program was written in PascalABC.NET for a cluster of high-performance parallel computing. Calculations on parallel computing systems can reduce the computational time by almost half. Various indicators have been used to characterize teachers, students and means of education. Based on these indicators, the following factors were determined: the quality of teachers, the quality of students and the quality of means of education. Based on the factors, the quality of education is determined. A modification of this algorithm was developed. The algorithm allows us to estimate by what values the input parameters should be changed in order to achieve a given level of quality.
Micro CT Image-Assisted Cross Modality Super-Resolution of Clinical CT Images Utilizing Synthesized Training Dataset

This paper proposes a novel, unsupervised super-resolution (SR) approach for performing the SR of a clinical CT into the resolution level of a micro CT ($\mu$CT). The precise non-invasive diagnosis of lung cancer typically utilizes clinical CT data. Due to the resolution limitations of clinical CT (about $0.5 \times 0.5 \times 0.5$ mm$^3$), it is difficult to obtain enough pathological information such as the invasion area at alveoli level. On the other hand, $\mu$CT scanning allows the acquisition of volumes of lung specimens with much higher resolution ($50 \times 50 \times 50 \mu {\rm m}^3$ or higher). Thus, super-resolution of clinical CT volume may be helpful for diagnosis of lung cancer. Typical SR methods require aligned pairs of low-resolution (LR) and high-resolution (HR) images for training. Unfortunately, obtaining paired clinical CT and $\mu$CT volumes of human lung tissues is infeasible. Unsupervised SR methods are required that do not need paired LR and HR images. In this paper, we create corresponding clinical CT-$\mu$CT pairs by simulating clinical CT images from $\mu$CT images by modified CycleGAN. After this, we use simulated clinical CT-$\mu$CT image pairs to train an SR network based on SRGAN. Finally, we use the trained SR network to perform SR of the clinical CT images. We compare our proposed method with another unsupervised SR method for clinical CT images named SR-CycleGAN. Experimental results demonstrate that the proposed method can successfully perform SR of clinical CT images of lung cancer patients with $\mu$CT level resolution, and quantitatively and qualitatively outperformed conventional method (SR-CycleGAN), improving the SSIM (structure similarity) form 0.40 to 0.51.
Linking mechanisms in data repositories: A case study of <scp>BioSample</scp> database

Abstract This poster reports upon a case study of the linking mechanisms in the NCBI BioSample database and its immediate connections, examining the types of links, their functions, and implications according to the FAIR data principles. The study allowed the authors to conduct a more detailed analysis of one area of data management by focusing on one database's linking mechanisms, providing a glimpse into the role of linking mechanisms to support biomedical research and discovery and serving as a model for future studies.
MALCOLM SINGER (b. 1953)i am a little church (1976)

This chapter discusses minimalism through the work of Malcolm Singer. Here he manipulates his numerically based systems with expertise and elan. The quirky originality and innately musical rhythms of e. e. cummings’s poetry is captured quite beautifully. The work’s tessitura is not high, but dynamics are often very light, hence the stipulation (on the score) for soprano. Absolute clarity and precision are essential, and there is no room whatever for rhythmic hesitancy or insecurity. Highly repetitive phrases in a similar pitch area (especially around E at the top of the stave) can become quite tiring vocally, and there is a real danger of seizing up through neglecting to relax throat, neck, and jaw muscles when preoccupied with counting tricky rhythms.