• Economic and Environmental Geology
• /
• v.55 no.4
• /
• pp.421-428
• /
• 2022

This study analyzes emerging earthquake and space use technologies from the latest Korean and Japanese scientific and technological foresights in 2022 and 2019, respectively. Unlike the earthquake prediction and early warning technologies presented in the 2017 study, the emerging earthquake technologies in 2022 in Korea was described as an earthquake/complex disaster information technology and public data platform. Many detailed future technologies were presented in Japan's 2019 survey, which includes largescale earthquake prediction, induced earthquake, national liquefaction risk, wide-scale stress measurement; and monitoring by Internet of Things (IoT) or artificial intelligence (AI) observation & analysis. The latest emerging space use technology in Korea and Japan were presented in more detail as robotic mining technology for water/ice, Helium-3, and rare earth metals, and manned station technology that utilizes local resources on the moon and Mars. The technological realization year forecasting in 2019 was delayed by 4-10 years from the prediction in 2015, which could be greater due to the Corona 19 epidemic, the declaration of carbon neutrality in Korea and Japan in 2020 and the Russo-Ukrainian War in 2022. However, it is required to more active research on earthquake and space technologies linked to information technology.

• The Journal of the Convergence on Culture Technology
• /
• v.9 no.5
• /
• pp.597-603
• /
• 2023

The paradigm of military operations has evolved from platform-centric warfare to network-centric warfare and further to information-centric warfare, driven by advancements in information technology. In recent years, with the development of cutting-edge technologies such as big data, artificial intelligence, and the Internet of Things (IoT), military operations are transitioning towards knowledge-centric warfare (KCW), based on artificial intelligence. Consequently, the military places significant emphasis on integrating advanced information and communication technologies (ICT) to establish reliable C4I (Command, Control, Communication, Computer, Intelligence) systems. This research emphasizes the need to apply data mining techniques to analyze and evaluate various aspects of C4I systems, including enhancing combat capabilities, optimizing utilization in network-based environments, efficiently distributing information flow, facilitating smooth communication, and effectively implementing knowledge sharing. Data mining serves as a fundamental technology in modern big data analysis, and this study utilizes it to analyze real-world cases and propose practical strategies to maximize the efficiency of military command and control systems. The research outcomes are expected to provide valuable insights into the performance of C4I systems and reinforce knowledge-centric warfare in contemporary military operations.

• Communications of the Korean Institute of Information Scientists and Engineers
• /
• v.5 no.2
• /
• pp.90-93
• /
• 1987

Relatively few papers are known to study the clustering the same kind of data records in a cylinder. In this article, I reviewed the clustering algorithms especially for the cellular list file which have been studied.

• Journal of the Korean Society for Library and Information Science
• /
• v.52 no.1
• /
• pp.341-357
• /
• 2018

Due to the paradigm of open science and advanced digital information technology, data sharing and re-use have been actively conducted and considered data-intensive in a wide variety of disciplines. This study aims to investigate the intellectual structure portrayed by the research products re-using the data sets from ICPSR. For the purpose of this study, a total of 570 research products published in 2017 from the ICPSR site were collected and analyzed in two folds. First, the authors and publications of those research products were analyzed in order to show the trends of research using ICPSR data. Authors tend to be affiliated with university or research institute in the United States. The subject areas of journals are recognized into Social Sciences, Health, and Psychology. In addition, a network with clustering analysis was conducted with using co-word occurrence from the titles of the research products. The results show that there are 12 clusters, mental health, tabocco effect, disorder in school, childhood, and adolescence, sexual risk, child injuries, physical activity, violent behavior, survey, family role, women, problem behavior, gender differences in research areas. The structure portrayed by ICPSR data re-uses demonstrates that substantial number of studies in Medicine have been conducted with a perspective of social sciences.

• The Journal of the Convergence on Culture Technology
• /
• v.10 no.5
• /
• pp.725-733
• /
• 2024

This study aims to develop an artificial intelligence-based model for predicting the causes of chemical accidents, utilizing data on 865 chemical accident situations and cases provided by the Chemical Safety Agency under the Ministry of Environment from January 2014 to January 2024. The research involved training the data using six artificial intelligence models and compared evaluation metrics such as accuracy, precision, recall, and F1 score. Based on 356 chemical accident cases from 2020 to 2024, additional training data sets were applied using chemical accident cause investigations and similar accident prevention measures suggested by the Chemical Safety Agency from 2021 to 2022. Through this process, the Multi-Layer Perceptron (MLP) model showed an accuracy of 0.6590 and a precision of 0.6821. the Multi-Layer Perceptron (MLP) model showed an accuracy of 0.6590 and a precision of 0.6821. The Logistic Regression model improved its accuracy from 0.6647 to 0.7778 and its precision from 0.6790 to 0.7992, confirming that the Logistic Regression model is the most effective for predicting the causes of chemical accidents.

• Proceedings of the Korea Technology Innovation Society Conference
• /
• 2017.11a
• /
• pp.969-988
• /
• 2017

4차 산업혁명에 대한 국가적 관심이 높아짐에 따라 ICT산업 분야의 연구개발(R&D)는 앞으로의 국가 성장에 핵심적인 역할을 할 가능성이 크다. 우리나라의 경우도 빠르게 변화하는 ICT 산업에 대응하기 위해, 국가차원에서는 중장기 전략을 수립하고 있으며, 민간차원에서는 관련 인력풀(pool)을 늘리는 등 다각화된 대처를 하고 있다. 하지만 미국과 중국 등 선진국들의 기술수준과 가격 경쟁력을 결코 무시할 수 없어, 우리나라의 ICT산업은 낙관할 수만은 없는 상황이다. 그러므로 지금은 오히려 우리나라 ICT산업에 대한 명확한 진단을 통해 효율적이고 효과적으로 기술기회와 R&D기회를 발굴하는 것이 보다 실효성 있는 정책 수립에 도움을 줄 수 있다. 본 논문에서는 한국과학기술정보연구원(KISTI)에서 개발한 교역활동 프로파일 분석 시스템을 통해 ICT산업에 관련된 상품들 전체를 거시적인 관점에서 확인함으로써 우리나라의 ICT산업 전반을 진단하고 분석하고자 한다. 이로 인해, 증거기반(evidence-based)의 과학적인 방법으로 연구개발 기회를 파악하여 효율적이고 효과적인 정책수립에 기여하고자 한다.

• Journal of KIISE
• /
• v.45 no.3
• /
• pp.294-302
• /
• 2018

With the emergence of the new service industry due to the development of information and communication technology, cyber space risks such as personal information infringement and industrial confidentiality leakage have diversified, and the security problem has emerged as a critical issue. In this paper, we propose a behavior-based anomaly detection method that is suitable for real-time and large-volume data analysis technology. We show that the proposed detection method is superior to existing signature security countermeasures that are based on large-capacity user log data according to in-company personal information abuse and internal information leakage. As the proposed behavior-based anomaly detection method requires a technique for processing large amounts of data, a real-time search engine is used, called Elasticsearch, which is based on an inverted index. In addition, statistical based frequency analysis and preprocessing were performed for data analysis, and the DBSCAN algorithm, which is a density based clustering method, was applied to classify abnormal data with an example for easy analysis through visualization. Unlike the existing anomaly detection system, the proposed behavior-based anomaly detection technique is promising as it enables anomaly detection analysis without the need to set the threshold value separately, and was proposed from a statistical perspective.

• Journal of Internet Computing and Services
• /
• v.7 no.1
• /
• pp.131-141
• /
• 2006

Recently, many researchers have been studied several high performance data transmission techniques such as TCP buffer Tuning, XCP and Parallel Sockets. The Parallel Sockets is an application level library for parallel data transfer, while TCP tuning, XCP and DRS are developed on kernel level. However, parallel socket is not analyzed in detail yet and need more enhancements, In this paper, we verify performance of parallel transfer technique through several experiments and analyze character of traffic interference among socket connections. In order to enhance parallel transfer management mechanism, we predict the number of socket connections to obtain SLA of the network resource and at the same time, affected network bandwidth of existing connections is measured mathematically due to the interference of other parallel transmission. Our analytical scheme predicts very well network bandwidth for applications using the parallel socket only with 8% error.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
• /
• v.7 no.9
• /
• pp.215-223
• /
• 2017

Various methods for creating interesting games are used in the development process. Because the empirical part is difficult to measure and analyze, it usually only measures and analyzes the parts where data are easy to quantify. This is a clear limit to the fact that the experience of the game is important.This study proposes a system that recognizes the face of a game user and measures the emotion change from the recognized information in order to easily quantify the experience of the user who is playing the game. The system recognizes emotions and records them in real time from the face of the user who is playing the game. These recorded data include time and figures related to the progress of the game, and numerical values for emotions recognized from the face. Using the recorded data, it is possible to judge what kind of emotion the game induces to the user at a certain point in time. Numerical data on the recorded empirical part using the system of this study is expected to help develop the game according to the developer 's intention.

• The Journal of the Convergence on Culture Technology
• /
• v.8 no.5
• /
• pp.431-435
• /
• 2022

The fields of STEM (Science, Technology, Engineering and Medicine) are changing rapidly. Recently, with the remarkable development of Internet and Web technologies, an environment that can be accessed worldwide has been created, thereby lowering the barriers to share STEM knowledge and information. The purpose of this study is to derive improvements by evaluating users' satisfaction with the information system developed by applying the open access model in the STEM field. Through an online survey using a structured questionnaire, a total of 204 users participated from January to February. The collected data were analyzed using quantitative statistical techniques. IPA (Importance Performance Analysis) technique was used. By identifying the importance and satisfaction (performance) between variables, areas with relatively low satisfaction compared to importance were derived. Users' overall satisfaction with the open access information system was 81.2 points and social reliability was 85.9 points, which were relatively high, respectively. What should be paid attention to in this study is the satisfaction with the system use environment, which is the most vulnerable area.