• Korea Trade Review
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• v.45 no.5
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• pp.37-53
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• 2020

This study aims to provide the implications of research development by comparing domestic and international studies conducted on the subject of FTA. To this end, among the papers written during the period from 2000 to July 23, 2020, papers whose title is searched by FTA (Free Trade Agreement) were selected as research data. In the case of domestic research, 1,944 searches from the Korean Citation Index (KCI) and 970 from the Web of Science and SCOPUS were selected for international research, and the research trend was analyzed through keywords and abstracts. Frequency analysis and word embedding (Word2vec) were used to analyze the data and visualized using t-SNE and Scattertext. The results of the analysis are as follows. First, in the top 30 keywords of domestic and international research, 16 out of 30 were found to be the same. In domestic research, many studies have been conducted to analyze the outcomes or expected effects of countries that have concluded or discussed FTAs with Korea, on the other hand there are diverse range of study subjects in international research. Second, in the word embedding analysis, t-SNE was used to visually represent the research connection of the top 60 keywords. Finally, Scattertext was used to visually indicate which keywords were frequently used in studies from 2000 to 2010, and from 2011 to 2020. This study is the first to draw implications for academic development through abstract and keyword analysis by applying various text mining approaches to the FTA related research papers. Further in-depth research is needed, including collecting a variety of FTA related text data, comparing and analyzing FTA studies in different countries.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.2
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• pp.185-190
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• 2024

In 2022, we can see the real estate market in Korea going down. Corona 19 and the Russian invasion of Ukraine are cited as the biggest causes for this. These two problems ignited the economic recession, causing prices to fall and subsequently raising exchange rates and interest rates. Due to the aforementioned problems in the previously active real estate market, the number of actual transactions has decreased, resulting in a decline in the real estate market due to high interest rates. Data provided by the public data portal, KOSIS, and the Seoul Metropolitan Government were collected through Logstash, transferred to Elasticsearch, and visualized inflation, exchange rates, and loan interest rates using the dashboard function provided by Kibana, to analyze causes and derive results. In addition, three specific apartments in Nowon-gu and Jongno-gu, which have the highest number of actual transactions in Seoul, are selected and the actual transaction prices that change every month are displayed in the Data Table.

• Journal of the Korean Society for information Management
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• v.37 no.1
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• pp.153-177
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• 2020

In the context of open science, data sharing and reuse are becoming important researchers' activities. Among the discussions about data sharing and reuse, data journals and data papers shows visible results. Data journals are published in many academic fields, and the number of papers is increasing. Unlike the data itself, data papers contain activities that cite and receive citations, thus creating their own intellectual structures. This study analyzed 14 data journals indexed by Web of Science, 6,086 data papers and 84,908 cited references to examine the intellectual structure of data journals and data papers in academic community. Along with the author's details, the co-citation analysis and bibliographic coupling analysis were visualized in network to identify the detailed subject areas. The results of the analysis show that the frequent authors, affiliated institutions, and countries are different from that of traditional journal papers. These results can be interpreted as mainly because the authors who can easily produce data publish data papers. In both co-citation and bibliographic analysis, analytical tools, databases, and genome composition were the main subtopic areas. The co-citation analysis resulted in nine clusters, with specific subject areas being water quality and climate. The bibliographic analysis consisted of a total of 27 components, and detailed subject areas such as ocean and atmosphere were identified in addition to water quality and climate. Notably, the subject areas of the social sciences have also emerged.

• Journal of Biomedical Engineering Research
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• v.37 no.1
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• pp.39-45
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• 2016

A pressure measurement system was developed to verify magnitude and position of transferred pressure on the body surface during the intermittent pneumatic compression (IPC) which is one of the most well-known methods for the prevention of deep vein thrombosis (DVT). Eighty force sensing resistors (FSR) were arranged on a mannequin leg and a hardware controller sensed, digitized, and transferred pressure data every second while IPC was being applied. Finally, sensed pressure data were color coded and visualized on the 3D model with lab-developed software. The pressure data were also saved to files for further analysis. Using this measurement system, the changing pattern of pressure was measured on the mannequin leg by changing both chamber pressure and cuff tightness. As a result, net pressure transferred onto the body surface is dependent on chamber pressure and cuff tightness. Under the same chamber pressure, the tighter a cuff was worn, the wider compressed area was and the shorter compression cycle was. Also transferred pressure was proportional to both chamber pressure and cuff tightness.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38C no.12
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• pp.1095-1105
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• 2013

This paper proposes the RDMS(Rough Set Theory based Disease Monitoring System) which efficiently manages diseases in Healthcare System. The RDMS is made up of DCM(Data Collection Module), RDRGM(RST based Disease Rules Generation Module), and HMM(Healthcare Monitoring Module). The DCM collects bio-metric informations from bio sensor of patient and stores it in RDMS DB according to the processing procedure of data. The RDRGM generates disease rules using the core of RST and the support of attributes. The HMM predicts a patient's disease by analyzing not only the risk quotient but also that of complications on the patient's disease by using the collected patient's information by DCM and transfers a visualized patient's information to a patient, a family doctor, etc according to a patient's risk quotient. Also the HMM predicts the patient's disease by comparing and analyzing a patient's medical information, a current patient's health condition, and a patient's family history according to the rules generated by RDRGM and can provide the Patient-Customized Medical Service and the medical information with the prediction result rapidly and reliably.

• The Journal of Society for e-Business Studies
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• v.20 no.4
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• pp.61-76
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• 2015

In general, we have utilized the hierarchical concept tree as a crucial data structure for indexing huge amount of textual data. This paper proposes a generality rank-based method that can automatically develop hierarchical concept structures with the Wikipedia data. The goal of the method is to regard each of Wikipedia articles as a concept and to generate hierarchical relationships among concepts. In order to estimate the generality of concepts, we have devised a special ranking function that mainly uses the number of hyperlinks among Wikipedia articles. The ranking function is effectively used for computing the probabilistic subsumption among concepts, which allows to generate relatively more stable hierarchical structures. Eventually, a set of concept pairs with hierarchical relationship is visualized as a DAG (directed acyclic graph). Through the empirical analysis using the concept hierarchy of Open Directory Project, we proved that the proposed method outperforms a representative baseline method and it can automatically extract concept hierarchies with high accuracy.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.5
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• pp.2519-2525
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• 2016

There are several existing reports of microarray chip use for assessment of altered gene expression in different diseases. In fact, there have been over 1.5 million assays of this kind performed over the last twenty years, which have influenced clinical and translational research studies. The most commonly used DNA microarray platforms are Affymetrix GeneChip and Quality Control Software along with their GeneChip Probe Arrays. These chips are created using several quality controls to confirm the success of each assay, but their actual impact on gene expression profiles had not been previously analyzed until the appearance of several bioinformatics tools for this purpose. We here performed a data mining analysis, in this case specifically focused on ovarian cancer, as well as healthy ovarian tissue and ovarian cell lines, in order to confirm quality control results and associated variation in gene expression profiles. The microarray data used in our research were downloaded from ArrayExpress and Gene Expression Omnibus (GEO) and analyzed with Expression Console Software using RMA, MAS5 and Plier algorithms. The gene expression profiles were obtained using Partek Genomics Suite v6.6 and data were visualized using principal component analysis, heat map, and Venn diagrams. Microarray quality control analysis showed that roughly 40% of the microarray files were false negative, demonstrating over- and under-estimation of expressed genes. Additionally, we confirmed the results performing second analysis using independent samples. About 70% of the significant expressed genes were correlated in both analyses. These results demonstrate the importance of appropriate microarray processing to obtain a reliable gene expression profile.

• The Journal of the Korea institute of electronic communication sciences
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• v.6 no.4
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• pp.595-601
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• 2011

This study proposed the system to automatically control the optimized raising environment for vegetation, raised in an equipment house, in which u-IT agricultural technology concept was applied. The system consists of environment sensors such as temperature, humidity, etc., biosensors such as EC, PH, etc., and requested automatic control devices, in which they were automatically controlled by the software system. The system is established in client systems, installed in each equipment house and the server system, collecting data from each client system as well. In addition, the system collects each farmer's data through the Internet and 3G network. In this phase, collected raising environment data comes to be analyzed in order to find out the optimized vegetation raising environment, finally, which is visualized and used for consulting each farmer.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.8
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• pp.1449-1458
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• 2006

Electronic Navigational Charts (ENCs) are digital charts which contain a great variety of data on coast and sea regions. Although they contain much information that ordinary people are interested in, there is no easy way to access because they are coded in the specialized data forma, and can be visualized by using specialized system. Therefore, supporting systems need to be developed for ordinary people to easily access ENCs. This paper proposes a framework for the ENC systems based on the Web. It relies on quite general standards such as Ceography Markup Language (GML) and Scalable Vector Graphics (SVG). In the framework, ENCs coded in S-57 format are first translated into GML to be stored in a database. Once the database is built, users can request to the database what they want. According to the user request, relevant data are retrieved, and then translated into SVG to be displayed on the Web browser. By using the framework, ordinary people may easily access coast and sea information contained in the ENCs. Furthermore, the framework may provide interoperability by virtue of XML-based standards such as GML and SVG, and efficiency by virtue of database. To validate the feasibility of proposed framework, a prototype system is developed and tested.

• Journal of KIISE:Computer Systems and Theory
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• v.34 no.1
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• pp.19-27
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• 2007

Entering the 21st century, the demand on information service via mobile devices is skyrocketing along with the popularization of computers and mobile communication devices and the rapid development of wireless communication technology. In particular, as mobile device service such as LBS and Telematics becomes highlighted, the management of mobile devices is ever more drawing attention. However, since there is no fixed standard on geographical space data, many commercialized monitoring systems do not use common geographical space data but independent geographic information. Furthermore, as it is impossible to save location information of each mobile device by integrating such information after acquiring them, it is difficult to trace management. Therefore, in this paper, geographic data with DXF. DWG and SHP format, which are commonly used files, were created and visualized by GML format, OGC standard advice. And then, TMS(Trace Monitoring System of Mobile Device) that can trace and manage information after acquiring and saving space information that show the movement of users was implemented.