• Smart Structures and Systems
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• v.29 no.2
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• pp.361-374
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• 2022

As civil infrastructure has continued to age worldwide, its structural integrity has been threatened owing to material deteriorations and continual loadings from the external environment. Structural Health Monitoring (SHM) has emerged as a cost-efficient method for ensuring structural safety and durability. As SHM research has gradually addressed an increasing number of structure-related problems, it has become difficult to understand the changing research topic trends. Although previous review papers have analyzed research trends on specific SHM topics, these studies have faced challenges in providing (1) consistent insights regarding macroscopic SHM research trends, (2) empirical evidence for research topic changes in overall SHM fields, and (3) methodological validations for the insights. To overcome these challenges, this study proposes a framework tailored to capturing the trends of research topics in SHM through a bibliometric and network analysis. The framework is applied to track SHM research topics over 15 years by identifying both quantitative and relational changes in the author keywords provided from representative SHM journals. The results of this study confirm that overall SHM research has become diversified and multi-disciplinary. Especially, the rapidly growing research topics are tightly related to applying machine learning and computer vision techniques to solve SHM-related issues. In addition, the research topic network indicates that damage detection and vibration control have been both steadily and actively studied in SHM research.

• Journal of the Korea Society of Computer and Information
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• v.21 no.5
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• pp.57-64
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• 2016

In this paper, we propose the design of railway safety common data model to provide common transformation method for collecting data from railway facility fields to Real-time railway safety monitoring and control system. This common data model is divided into five abstract sub-models according to the characteristics of data such as 'StateInfoMessage', 'ControlMessage', 'RequestMessage', 'ResponseMessage' and 'ExtendedXXXMessage'. This kind of model structure allows diverse heterogeneous data acquisitions and its common conversion method to DDS (Data Distribution Service) format to share data to the sub-systems of Real-time railway safety monitoring and control system. This paper contains the design of common data model and its DDS Topic expression for DDS communication, and presents two kinds of data transformation case studied for verification of the model design.

• Journal of the Korean Society for information Management
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• v.38 no.4
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• pp.129-152
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• 2021

This study proposed a plan to develop wearable devices suitable for female college students by analyzing female college students' perceptions and preferences for wearable devices and their needs for health care using topic modeling and network analysis techniques. To this end, 2,457 posts related to health care and wearable devices were collected from the community used by S Women's University students. After preprocessing the collected posts and comment data, LDA-based topic modeling was performed. Through topic modeling techniques, major issues of female college students related to health care and wearable devices are derived, and bi-gram analysis and network analysis are performed on posts containing related keywords to understand female college students' views on wearable devices.

• The Korean Journal of Applied Statistics
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• v.34 no.5
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• pp.795-806
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• 2021

Recently, as text data through online channels have become vast, there is a growing interest in research that summarizes and analyzes them. One of the fundamental analyses of text data is to extract potential topics. Although the researcher may read all the data and summarize the contents one by one, it is not easy to deal with large amounts of data. Blei and Lafferty (2007) and Blei et al. (2003) proposed topic modeling methods for extracting topics using a statistical model. Since the text data is generally collected over time, it is worthwhile to monitor the topic's changes. In this study, we propose a topic index based on the results of the topic model. In addition, a control chart, a representative tool for statistical process management, is applied to monitor the topic index over time. As a practical example, we use text data collected from Blue House National Petition boards between March 5, 2018, and March 5, 2020.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.21 no.5
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• pp.397-401
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• 2008

Most of the topic in PCB industry was about increasing the volume of product for the development of electronics in numerous industrial application area. However, it has been emerged that yield improvement quality manufacturing via detecting any suspicious process in order to minimize the scrapped product and material waste. In addition, recently, restriction of hazardous substances (RoHS) claims that electronic manufacturing environment should reduce the harmful chemicals usage, thus the importance of monitoring copper etchant and detecting any mis-processing is crucial for electronics manufacturing. In this paper, we have developed real-time chemical monitoring system using RGB sensor, which is simpler but more accurate method than commercially utilized oxidation reduction potential (ORP) technique. The developed Cu etchant monitoring system can further be utilized for copper interconnect process in future nano-semiconductor process.

• Journal of Korean Elementary Science Education
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• v.36 no.4
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• pp.405-427
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• 2017

This study aims to describe various teaching cases about 'earth revolution' in terms of PCK; knowledge of curriculum, knowledge of teaching strategies and knowledge of assessment. Based on these various cases we suggested PCK progressions about 'earth revolution'. For these, we recorded 'solar system and star' classes of nine elementary school teachers' in Kangwon, Gyeonggi, Gwangju, and Seoul. We adopted Lee & Lee (2016)'s topic-specific PCK framework to analyze the classes. As results, we suggested topic-specific PCK progression about 'earth revolution'. The results showed the upper anchor of the earth revolution class were exploring the reason of the change of constellation, finding the tendency of constellation change. These teachings were carried by the teachers' adaptive strategies. The upper anchor of the assessment was monitoring students' understanding during the whole class. The PCK progression about 'earth revolution' could help the teachers plan the earth revolution class, and reflect their own teachings.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.4
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• pp.246-262
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• 2023

The purpose of this study is to identify the major peacekeeping activities that the Korean armed forces has performed from the past to the present. To do this, we collected 692 press releases from the National Defense Daily over the past 20 years and performed topic modeling and social network analysis. As a result of topic modeling analysis, 112 major keywords and 8 topics were derived, and as a result of examining the Korean armed forces's peacekeeping activities based on the topics, 6 major activities and 2 related matters were identified. The six major activities were 'Northeast Asian defense cooperation', 'multinational force activities', 'civil operations', 'defense diplomacy', 'ceasefire monitoring group', and 'pro-Korean activities', and 'general troop deployment' related to troop deployment in general. Next, social network analysis was performed to examine the relationship between keywords and major keywords related to topic decision, and the keywords 'overseas', 'dispatch', and 'high level' were derived as key words in the network. This study is meaningful in that it first examined the topic of the Korean armed forces's peacekeeping activities over the past 20 years by applying big data techniques based on the National Defense Daily, an unstructured document. In addition, it is expected that the derived topics can be used as a basis for exploring the direction of development of Korea's peacekeeping activities in the future.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.4
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• pp.739-746
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• 2016

The real-time railway safety monitoring and control system is for prevention of safety accidents, and this system adopts DDS (Data Distribution Service) standard based data transmission method to support integrated management of data from existing on-site safety detection devices. In this paper, we introduce the design of DDS-based data specification from on-site signal equipment on the conventional railway. For this, we (1) design UML data model of KRS SG 0062 standard which defines existing data specification, (2) define DDS Topics for DDS transmission and map KRS model to DDS Topic model, (3) suggest data transformation rules and (4) design network control QoS polices. In addition, we analysis actual on-site log data and validate our data specification design. DDS-based data transmission enables data compatibility among on-site devices and the real-time railway safety monitoring and control system, and allows efficient network management for a large amount of data transfer.

• Journal of the Korean Society of Tobacco Science
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• v.19 no.2
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• pp.162-169
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• 1997

An important and somewhat under-emphasized issue in assessing the risk potentially associated with exposure to ETS is the reliability and objectivity of the methods used to measure the actual level of exposure. Objectivity of the science is crucial in this context since this topic tends to elicit strong social, emotional and political responses among the general public and the scientific community alike. This mini-review compares the strengths and limitations of various methods used in determining ETS exposure in scientific investigations. Methods reviewed include: questionnaire, area monitoring, bio-monitoring, and personal monitoring. In particular, results of several recent studies (conducted in the United States, Europe, and the Far East) using personal monitors in combination with questionnaire and bio-monitoring, which contribute to a more reliable, objective and realistic estimates of a person's actual exposure to 575, are discussed.

• The Korean Journal of Applied Statistics
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• v.36 no.5
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• pp.399-413
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• 2023

Recently, monitoring and detecting anomalies in social networks have become an interesting research topic. In this study, we investigate the detection of abnormal changes in a network modeled by the DCSBM (degree corrected stochastic block model), which reflects the propensity of both individuals and communities. To this end, we propose three methods for anomaly detection in the DCSBM networks: One method for monitoring the entire network, and two methods for dividing and monitoring the network in consideration of communities. To compare these anomaly detection methods, we design and perform simulations. The simulation results show that the method for monitoring networks divided by communities has good performance.