• Journal of The Korean Association For Science Education
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• v.39 no.4
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• pp.479-488
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• 2019

The purpose of this research is to derive competencies necessary for students with future convergent STEAM talents, and to explore ideal student images, teaching-learning strategies, evaluation methods, and teachers' competencies and their training methods for future schools developing students' competencies. In order to figure out the features of the future schools, 25 experts from related fields, including in-service teachers, administrators, and college students in science and technology, participated in a future workshop. According to the results, students with future convergent science and technology talents are expected to have flexible thinking and creative thinking competencies to solve problems in innovative ways rather than traditional ways. In other words, it takes the power to accept and accommodate unexpected situations and solve problems appropriately in those situations. To cultivate such competencies, therefore, future schools should also be flexible and proactive. Rigid schools delivering knowledge-based information make it impossible to cultivate flexible and creative talents. Future schools should change into leaner-centered project-based classes so that students can naturally cope with various situations and solve large and small problems, and prepare assessment systems that can provide feedback based on the student's performances rather than achievement standards.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.10
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• pp.243-249
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• 2019

This study examined the patient's advantage and respect self-decision to protect human dignity and values, who are on the pathway of the hospice palliative care and death process. The study subjects were the elderly who had signed the advance medical directives at C Christian religious facilities in S region. The survey period was started on July 1st, 2019 and lasted for ten days. The study resulted in four topics and eight sub-topics on the motivation for preparing advanced medical directives. The four topics were 'for children', 'fear of pain', 'want to clear my life', 'felt the necessity', and the sub-topics were 'don't want to make a burden to children', 'don't want to make a worry of medical expenses', 'fear of pain', 'have experience of taking caring of painful death process', 'relaxed mind', 'importance of self-decision', 'have known it before but now decided', and 'it is the new information and decided'. This research is meaningful in that it can form the basis for improving well-dying education programs for the good death of the elderly and supplementing effective systems for preparing advance medical directives.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.9 no.6
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• pp.773-782
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• 2019

Basel III (Third Basel Accord or Basel Standards) is a global, voluntary regulatory framework on bank capital adequacy, stress testing, and market liquidity risk. Basel III regulatory ratios include capital adequacy, asset soundness, and liquidity. The capital adequacy variables include BIS capital adequacy ratio, BIS tier 1 capital ratio, and tangible common equity ratio. The asset soundness variables include non-performing loan ratio and non-performing loan coverage ratio. The liquidity regulation variables include KRW liquidity coverage ratio and foreign currency liquidity coverage ratio. This study aims to investigate how capital adequacy standard affects efficiency of internet primary banks. As a result of this study, BIS capital adequacy ratio of domestic internet primary banks is lower than that of commercial banks. In order to maintain sustainable operation considering capital adequacy regulations, it is necessary to expand additional capital. In addition, the delinquency rate and non-performing loan ratio of domestic internet primary banks is gradually increasing due to the maturity of high-yield loans in 2019.

• Journal of Internet Computing and Services
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• v.22 no.2
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• pp.29-39
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• 2021

As damages to individuals, private sectors, and businesses increase due to newly occurring cyber attacks, the underlying network security problem has emerged as a major problem in computer systems. Therefore, NIDS using machine learning and deep learning is being studied to improve the limitations that occur in the existing Network Intrusion Detection System. In this study, a deep learning-based NIDS model study is conducted using the Convolution Neural Network (CNN) algorithm. For the image classification-based CNN algorithm learning, a discrete algorithm for continuity variables was added in the preprocessing stage used previously, and the predicted variables were expressed in a linear relationship and converted into easy-to-interpret data. Finally, the network packet processed through the above process is mapped to a square matrix structure and converted into a pixel image. For the performance evaluation of the proposed model, NSL-KDD, a representative network packet data, was used, and accuracy, precision, recall, and f1-score were used as performance indicators. As a result of the experiment, the proposed model showed the highest performance with an accuracy of 85%, and the harmonic mean (F1-Score) of the R2L class with a small number of training samples was 71%, showing very good performance compared to other models.

• Safety and Health at Work
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• v.12 no.4
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• pp.530-535
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• 2021

Background: Despite the lack of official COVID-19 statistics, various workplaces and occupations have been at the center of COVID-19 outbreaks. We aimed to compare legal measures and governance established for managing COVID-19 infection risks at workplaces in nine Asia and Pacific countries and to recommend key administrative measures. Methods: We collected information on legal measures and governance from both general citizens and workers regarding infection risks such as COVID-19 from industrial hygiene professionals in nine countries (Indonesia, India, Japan, Malaysia, New Zealand, Republic of the Philippines, Republic of Korea, Taiwan, and Thailand) using a structured questionnaire. Results: A governmental body overseeing public health and welfare was in charge of containing the spread and occurrence of infectious diseases under an infectious disease control and prevention act or another special act, although the name of the pertinent organizations and legislation vary among countries. Unlike in the case of other traditional hazards, there have been no specific articles or clauses describing the means of mitigating virus risk in the workplace that are legally required of employers, making it difficult to define the responsibilities of the employer. Each country maintains own legal systems regarding access to the duration, administration, and financing of paid sick leave. Many workers may not have access to paid sick leave even if it is legally guaranteed.

• KIPS Transactions on Computer and Communication Systems
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• v.8 no.1
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• pp.17-28
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• 2019

In the financial investment management strategy, the distributed investment selecting and combining various financial assets is called portfolio management theory. In recent years, the blockchain based financial assets, such as cryptocurrencies, have been traded on several well-known exchanges, and an efficient portfolio management approach is required in order for investors to steadily raise their return on investment in cryptocurrencies. On the other hand, deep learning has shown remarkable results in various fields, and research on application of deep reinforcement learning algorithm to portfolio management has begun. In this paper, we propose an efficient financial portfolio investment management method based on Asynchronous Advantage Actor-Critic (A3C), which is a representative asynchronous reinforcement learning algorithm. In addition, since the conventional cross-entropy function can not be applied to portfolio management, we propose a proper method where the existing cross-entropy is modified to fit the portfolio investment method. Finally, we compare the proposed A3C model with the existing reinforcement learning based cryptography portfolio investment algorithm, and prove that the performance of the proposed A3C model is better than the existing one.

• Journal of Cadastre & Land InformatiX
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• v.49 no.1
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• pp.85-101
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• 2019

Recently, thank to the popularization of light-weight drone through the significant developments in computer technologies as well as the advanced automated procedures in photogrammetry, Unmanned Aircraft Systems have led to a growing interest in industry as a whole. Documentation, maintenance, and restoration projects of large scaled cultural property would required accurate 3D phenomenon modeling and efficient visual inspection methods. The object of this study verify on the accuracies achieved of 3D phenomenon reconstruction as well as on the validity of the preservation, maintenance and restoration of large scaled cultural property by UAS photogrammetry. The test object is cltural heritage(treasure 1324) that is the rock-carved standing Bodhisattva in Soraesan Mountain, Siheung, documented in Goryeo Period(918-1392). This standing Bodhisattva has of particular interests since it's size is largest stone Buddha carved in a rock wall and is wearing a lotus shaped crown that is decorated with arabesque patterns. The positioning accuracy of UAS photogrammetry were compared with non-target total station survey results on the check points after creating 3D phenomenal models in real world coordinates system from photos, and also the quantified informations documented by Culture Heritage Administration were compared with UAS on the bodhisattva image of thin lines. Especially, tests the validity of UAS photogrammetry as a alternative method of visual inspection methods. In particular, we examined the effectiveness of the two techniques as well as the relative fluctuation of rock surface for about 2 years through superposition analysis of 3D points cloud models produced by both UAS image analysis and ground laser scanning techniques. Comparison studies and experimental results prove the accuracy and efficient of UAS photogrammetry in 3D phenomenon modeling, maintenance and restoration for various large-sized Cultural Heritage.

• KIPS Transactions on Computer and Communication Systems
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• v.8 no.5
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• pp.103-110
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• 2019

In this research, one common chapter, Problem Solving and Programming, in seven different types of high school informatics textbooks was analyzed in terms of the aspect of learners' explorations. These textbooks were newly developed based on the 2015 revised national curriculum. Romey's analysis was used to the textbooks along with four analytic elements: texts, data, activities, and evaluation. The study results showed that the textbooks can highly encourage learners' further explorations according to the four analytic elements reflected in the seven textbooks: one out of the six textbooks well designed for texts, three for data, six for activities, two for evaluation. In terms of Romey's involvement index points, six of the seven textbooks had low indexes of texts, ranging from 0.175 to 0.393. Data indexes were extremely low in four out of the seven textbooks, ranging from 0.058 to 0.226. Five out of the seven textbooks had very high indexes of evaluation in the broad range of 2 to 6.333 points. Furthermore, these newly designed textbooks can more greatly facilitate students' explorations than previously existing textbooks in three elements: texts, data, and activities. Evaluation indexes significantly increased in these new textbooks from 0.916 to 3.914, which had excessive points in terms of promoting students' explorations. Further methods to improve the textbook quality is proposed based on the results from this analysis.

• KIPS Transactions on Computer and Communication Systems
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• v.10 no.10
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• pp.285-290
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• 2021

In the medical field, disease diagnosis and prediction research using artificial intelligence technology is being actively conducted. It is being released as a variety of products for disease diagnosis and prediction, which are most widely used in the application of artificial intelligence technology based on medical images. Artificial intelligence is being applied to diagnose diseases, to classify diseases into benign and malignant, and to separate disease regions for use in identification or reading according to the risk of disease. Recently, in connection with cloud technology, its utility as a service product is increasing. Among the diseases dealt with in this paper, liver disease is a disease with very high risk because it is difficult to diagnose early due to the lack of pain. Artificial intelligence technology was introduced based on medical images as a non-invasive diagnostic method for diagnosing these diseases. We describe the development of a web service to help the most meaningful clinical reading of liver cirrhosis patients. Then, it shows the web service process and shows the operation screen of each process and the final result screen. It is expected that the proposed service will be able to diagnose liver cirrhosis at an early stage and help patients recover through rapid treatment.

• Journal of the Korean School Mathematics Society
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• v.23 no.4
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• pp.449-468
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• 2020

TIMSS is a representative international comparative study that analyzes changes in mathematics and science achievement, and it collects information on the educational system, curriculum, teaching and learning situation of participating countries as well as research and check, and provides implications for each country's mathematics and science education. Although domestic TIMSS studies focused on the results of achievement related to the evaluation of mathematics, not many have taken a closer look at the content and characteristics of the assessment framework. Therefore, the purpose of this study was to analyze the characteristics of the TIMSS 2019 mathematics assessment framework, and to derive implications for the mathematics curriculum and mathematics learning by examining the students' study time in light of the Korean mathematics curriculum. The implications derived from the results of this study are summarized as follows: First, it is necessary to check the connection between content elements in the mathematics and education process. Second, it is necessary to check the appropriateness and connectivity of the learning timing of the content elements in the mathematics and education courses. Finally, it is necessary to verify that the hierarchy of content areas and the structure of content systems in mathematics and education courses are consistent with the direction of mathematics education at the international level. This study can be used as a basis for mathematics and curriculum revisions, and can be used to set directions for the development of large-scale evaluation frameworks.