• Women's Health Nursing
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• v.29 no.1
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• pp.20-31
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• 2023

Purpose: As more newborns have received expanded newborn screening (NBS) for metabolic disorders, the overall number of false-positive results has increased. The purpose of this study was to explore the psychological impacts experienced by mothers related to the NBS process. Methods: An online parenting community in Korea was selected, and questions regarding NBS were collected using web crawling for the period from October 2018 to August 2021. In total, 634 posts were analyzed. The collected unstructured text data were preprocessed, and keyword analysis, topic modeling, and visualization were performed. Results: Of 1,057 words extracted from posts, the top keyword based on 'term frequency-inverse document frequency' values was "hypothyroidism," followed by "discharge," "close examination," "thyroid-stimulating hormone levels," and "jaundice." The top keyword based on the simple frequency of appearance was "XXX hospital," followed by "close examination," "discharge," "breastfeeding," "hypothyroidism," and "professor." As a result of LDA topic modeling, posts related to inborn errors of metabolism (IEMs) were classified into four main themes: "confirmatory tests of IEMs," "mother and newborn with thyroid function problems," "retests of IEMs," and "feeding related to IEMs." Mothers experienced substantial frustration, stress, and anxiety when they received positive NBS results. Conclusion: The online parenting community played an important role in acquiring and sharing information, as well as psychological support related to NBS in newborn mothers. Nurses can use this study's findings to develop timely and evidence-based information for parents whose children receive positive NBS results to reduce the negative psychological impact.

• Journal of the Korean Association of Geographic Information Studies
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• v.20 no.1
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• pp.98-112
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• 2017

Recently, various research has been conducted on the use of a game engine instead of a commercial geographic information system (GIS) engine for the development of 3D GIS. The advantage of the 3D game engine is that it allows developers to develop various modules according to their abilities. In particular, in the area of disasters, a wide range of alternatives for prevention as well as prediction can be presented when new analyses are attempted by combining geographic information and disaster-related information. Furthermore, 3D analysis can be an important factor in analyzing the phenomena occurring in the real 3D world because of the nature of disasters. Therefore, in this study, we tried to develop a visualization module for flood disaster information through a 3D game engine by considering the solutions for cost and manpower problems and the degree of freedom of development. Raw flood data was mapped onto spatial information and interpolation was performed for the natural display of the mapped flood information. Furthermore, we developed a module that intuitively shows dangerous areas to users by generating cumulative information in order to display multidimensional information based on this information. The results of this study are expected to enable various flood information analyses as well as quick response and countermeasures to floods.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.93-111
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• 2013

As Internet and information technology (IT) continues to develop and evolve, the issue of big data has emerged at the foreground of scholarly and industrial attention. Big data is generally defined as data that exceed the range that can be collected, stored, managed and analyzed by existing conventional information systems and it also refers to the new technologies designed to effectively extract values from such data. With the widespread dissemination of IT systems, continual efforts have been made in various fields of industry such as R&D, manufacturing, and finance to collect and analyze immense quantities of data in order to extract meaningful information and to use this information to solve various problems. Since IT has converged with various industries in many aspects, digital data are now being generated at a remarkably accelerating rate while developments in state-of-the-art technology have led to continual enhancements in system performance. The types of big data that are currently receiving the most attention include information available within companies, such as information on consumer characteristics, information on purchase records, logistics information and log information indicating the usage of products and services by consumers, as well as information accumulated outside companies, such as information on the web search traffic of online users, social network information, and patent information. Among these various types of big data, web searches performed by online users constitute one of the most effective and important sources of information for marketing purposes because consumers search for information on the internet in order to make efficient and rational choices. Recently, Google has provided public access to its information on the web search traffic of online users through a service named Google Trends. Research that uses this web search traffic information to analyze the information search behavior of online users is now receiving much attention in academia and in fields of industry. Studies using web search traffic information can be broadly classified into two fields. The first field consists of empirical demonstrations that show how web search information can be used to forecast social phenomena, the purchasing power of consumers, the outcomes of political elections, etc. The other field focuses on using web search traffic information to observe consumer behavior, identifying the attributes of a product that consumers regard as important or tracking changes on consumers' expectations, for example, but relatively less research has been completed in this field. In particular, to the extent of our knowledge, hardly any studies related to brands have yet attempted to use web search traffic information to analyze the factors that influence consumers' purchasing activities. This study aims to demonstrate that consumers' web search traffic information can be used to derive the relations among brands and the relations between an individual brand and product attributes. When consumers input their search words on the web, they may use a single keyword for the search, but they also often input multiple keywords to seek related information (this is referred to as simultaneous searching). A consumer performs a simultaneous search either to simultaneously compare two product brands to obtain information on their similarities and differences, or to acquire more in-depth information about a specific attribute in a specific brand. Web search traffic information shows that the quantity of simultaneous searches using certain keywords increases when the relation is closer in the consumer's mind and it will be possible to derive the relations between each of the keywords by collecting this relational data and subjecting it to network analysis. Accordingly, this study proposes a method of analyzing how brands are positioned by consumers and what relationships exist between product attributes and an individual brand, using simultaneous search traffic information. It also presents case studies demonstrating the actual application of this method, with a focus on tablets, belonging to innovative product groups.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.10a
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• pp.378-381
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• 2012

Increasingly the frequency of use of mathematical modeling and computer simulation, in order to solve complex engineering problems in the field of Applied Science, the researchers need a simulation framework that can make their simulation-based research easier and more convenient. computer simulation framework is composed of various components such as preprocessor, solver, visualization program, computational resources and job scheduler. However until now, no standardized schema for the components of the simulation framework exist, so it is difficult to config that make a general-purpose simulation framework. In other words, most of the existing simulation framework is a structure that provides only limited functionality is dependent on the particular solver code. In this paper, we designed the meta-information schema that can be contained of a various solver code to be used for the simulation framework and we implemented the Web-based simulation environment using our meta-information schema.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.6
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• pp.454-458
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• 2009

The technology of virtual environments has been developed with better-quality appearance on a computer display in mind, but without consideration for objects' precise measurements in physical units. With the increased application of computer graphics in a variety of areas, there is a need for precise measurement functionality in addition to visualization. This paper describes the definition of physical properties using measurement units for X3D based virtual objects, to provide their precise physical information in virtual environments. To this end, we have included the physical property node in the X3D specification. The physical measurement units, such as length, mass, time, temperature, etc., are based on SI units (International System of Units).

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.5
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• pp.77-83
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• 2013

Nowadays, the limitation of Lighting control and management skills is the excessive cost of equipments, the operational difficulties and wasting energy. To solve this problem is in need of communication and management S/W that is worked out complexly well as a information system of smart lighting energy, which is loaded wireless network facility. This paper made a study od the energy saving technology through energy monitoring and we developed LEIS(Lighting Energy Information Sysem) to converge this one. LEIS is monitoring and control lighting energy data that is collelcted from sensors by Zigbee mesh network and shows lighting use information by visualization to users. It is consists of lighting energy information data base based on LEM(Lighting Energy Metering) information and LEIS Web application, provide function scenario to manage energy optimization through LEIS.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.12
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• pp.2601-2608
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• 2010

It is difficult to merge text document and to remake use of documents on the most collaborative document authoring system using text document, and also to provide the storage place for saving and keeping documents. It has vulnerable drawbacks about the security though it provides the accessible abilities due to basing it on Web. In this paper, we design and implementation the collaborative document authoring system for XML document to improve a couple of problems on these systems. For these, we based on the DOM to manipulate the modeling object documents and utilized RMI on this system without considering socket communication when it transmits and receives Java objects. We improved the security through processes of authentication. By providing templates and editing functions such as annotation, visualization of document structures, we made easier making collaborative document authoring more than ever.

• Korean Journal of Oriental Medicine
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• v.17 no.3
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• pp.77-85
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• 2011

Objectives : The purpose of this study was to develop a simulator which can analyze the anti-inflammatory effects of medical herbs based on e-cell concerning p38 MAPK signal pathway. Methods : We collected data concerning medical herbs with anti-inflammatory effects and the active compounds to provide as a fundamental databse and to validate the newly developed algorithm. At this time, we used the target database as pubmed and gathered the data by data mining tool, pathway studio. Also we have developed the web-based search system for confirming database related to anti-inflammation. We researched the mechanism of actions of proteins in p38 MAPK signal pathway when active compound has been inserted into the network. We reduced total network into TAK-MKK3-p38 and made the two types of mathematical model about active compounds' interaction. Results & Conclusion : We constructed the database which have 69 cases of medical herbs, 71 cases of active compounds, about 8,000 cases of URL(Uniform Resource Locator) related to papers and reports. We designed the ordinary differential equations for response of TAK, MKK3, p38 in e-cell's cytosol and nucleus. We used this formular as measure whether an active compound of medicinal plants which is inputted by an user would have an anti-inflammation effects. We developed the visualization program which could show the change of concentration over time.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.109-122
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• 2014

People are nowadays creating a tremendous amount of data on Social Network Service (SNS). In particular, the incorporation of SNS into mobile devices has resulted in massive amounts of data generation, thereby greatly influencing society. This is an unmatched phenomenon in history, and now we live in the Age of Big Data. SNS Data is defined as a condition of Big Data where the amount of data (volume), data input and output speeds (velocity), and the variety of data types (variety) are satisfied. If someone intends to discover the trend of an issue in SNS Big Data, this information can be used as a new important source for the creation of new values because this information covers the whole of society. In this study, a Twitter Issue Tracking System (TITS) is designed and established to meet the needs of analyzing SNS Big Data. TITS extracts issues from Twitter texts and visualizes them on the web. The proposed system provides the following four functions: (1) Provide the topic keyword set that corresponds to daily ranking; (2) Visualize the daily time series graph of a topic for the duration of a month; (3) Provide the importance of a topic through a treemap based on the score system and frequency; (4) Visualize the daily time-series graph of keywords by searching the keyword; The present study analyzes the Big Data generated by SNS in real time. SNS Big Data analysis requires various natural language processing techniques, including the removal of stop words, and noun extraction for processing various unrefined forms of unstructured data. In addition, such analysis requires the latest big data technology to process rapidly a large amount of real-time data, such as the Hadoop distributed system or NoSQL, which is an alternative to relational database. We built TITS based on Hadoop to optimize the processing of big data because Hadoop is designed to scale up from single node computing to thousands of machines. Furthermore, we use MongoDB, which is classified as a NoSQL database. In addition, MongoDB is an open source platform, document-oriented database that provides high performance, high availability, and automatic scaling. Unlike existing relational database, there are no schema or tables with MongoDB, and its most important goal is that of data accessibility and data processing performance. In the Age of Big Data, the visualization of Big Data is more attractive to the Big Data community because it helps analysts to examine such data easily and clearly. Therefore, TITS uses the d3.js library as a visualization tool. This library is designed for the purpose of creating Data Driven Documents that bind document object model (DOM) and any data; the interaction between data is easy and useful for managing real-time data stream with smooth animation. In addition, TITS uses a bootstrap made of pre-configured plug-in style sheets and JavaScript libraries to build a web system. The TITS Graphical User Interface (GUI) is designed using these libraries, and it is capable of detecting issues on Twitter in an easy and intuitive manner. The proposed work demonstrates the superiority of our issue detection techniques by matching detected issues with corresponding online news articles. The contributions of the present study are threefold. First, we suggest an alternative approach to real-time big data analysis, which has become an extremely important issue. Second, we apply a topic modeling technique that is used in various research areas, including Library and Information Science (LIS). Based on this, we can confirm the utility of storytelling and time series analysis. Third, we develop a web-based system, and make the system available for the real-time discovery of topics. The present study conducted experiments with nearly 150 million tweets in Korea during March 2013.

• Journal of Navigation and Port Research
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• v.40 no.6
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• pp.369-374
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• 2016

Recently, due to the rapid development of smart computing technology, there have been a lot of studies on 3D navigation, and consequently the advanced commercial 3D navigation system and 3D VTS system are on the market. Even the 3D technology is well known and wide spreaded, unfortunately, the secret of code behind is still unleashed. The purpose of this paper is to show the basic methodologies to display ENC features under 3D display environment to meet the requirement of S-52 standards. The OpenGL ES is used to develop 3D ENC Viewer for further use on mobile platforms and web based vessel monitoring system. P articularly, area object triangulation, complex line drawing, polygon pattern filling and symbol drawing by texture mapping are explained in detail. The result of performance test is shown as table for correlation of SENC file size to display speed.