• The Korean Journal of Applied Statistics
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• v.14 no.1
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• pp.177-190
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• 2001

전통적으로 많이 사용하는 군집분석의 방법들은 개체간의 거리를 고려하여 이들을 분류해 내는 것이며, 따라서 거리 측정 방법에 따라 여러 형태의 군집분석 방법이 나타나게 된다. 어떤 방법을 적용하던 간에 그 결과는 고정된 수치로써 나타난다. 다차원 자료의 구조파악이 몇 개의 수치로 나타나게 되면 어쩔 수 없이 정보의 손실이 발생하게 된다. 이를 보완하기 위해 시각적 매체를 동원하여 다차원 자료의 구조를 파악하는 연구가 있었으며, 이를 시각적 군집분석이라고 명명하고 있다. 본 연구에서는 시각적 군집분석에 대한 기본적 개념과 이를 위한 통계 도형의 활용, 구현방법 등에 대해 살펴보기로 한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.12
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• pp.5842-5861
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• 2019

A current autonomous vehicle determines its driving strategy by considering only external factors (Pedestrians, road conditions, etc.) without considering the interior condition of the vehicle. To solve the problem, this paper proposes "An Optimal Driving Support Strategy(ODSS) based on an Genetic Algorithm for Autonomous Vehicles" which determines the optimal strategy of an autonomous vehicle by analyzing not only the external factors, but also the internal factors of the vehicle(consumable conditions, RPM levels etc.). The proposed ODSS consists of 4 modules. The first module is a Data Communication Module (DCM) which converts CAN, FlexRay, and HSCAN messages of vehicles into WAVE messages and sends the converted messages to the Cloud and receives the analyzed result from the Cloud using V2X. The second module is a Data Management Module (DMM) that classifies the converted WAVE messages and stores the classified messages in a road state table, a sensor message table, and a vehicle state table. The third module is a Data Analysis Module (DAM) which learns a genetic algorithm using sensor data from vehicles stored in the cloud and determines the optimal driving strategy of an autonomous vehicle. The fourth module is a Data Visualization Module (DVM) which displays the optimal driving strategy and the current driving conditions on a vehicle monitor. This paper compared the DCM with existing vehicle gateways and the DAM with the MLP and RF neural network models to validate the ODSS. In the experiment, the DCM improved a loss rate approximately by 5%, compared with existing vehicle gateways. In addition, because the DAM improved computation time by 40% and 20% separately, compared with the MLP and RF, it determined RPM, speed, steering angle and lane changes faster than them.

• Journal of Contemporary Eastern Asia
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• v.14 no.2
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• pp.87-96
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• 2015

Social media comprises a vast and consequential landscape that has been poorly mapped and understood. Hundreds of millions of people have eagerly moved many of the conversations and discussions that compose civil society into these services and platforms. There is a need to document and analyze these social spaces for many academic and commercial purposes. The Social Media Research Foundation has engaged a strategy to cultivate better research into the structure and dynamics of social media. The foundation is dedicated to the creation of open tools, open data, and open scholarship related to social media. It has implemented a free and open network collection, analysis, and visualization tool called NodeXL to facilitate social media network research. Using NodeXL a group of researchers has collectively authored a publicly available archive, called the NodeXL Graph Gallery, composed of network data sets and visualizations from users around the world. This site has enabled the aggregation of tens of thousands of network datasets and images. Use of the archive has led to scholarly research results that are based on the wide range and scope of social media data sets available.

• Journal of the Korean Society of Visualization
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• v.15 no.2
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• pp.41-47
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• 2017

Microring/nanoring structure has high applicability for nano-antenna and biosensor thanks to its superior optical characteristics. Although coiling nanowires manufactured using immiscible emulsion droplets have an advantage in mass production, this process also forms nanowire bundles. In this study, we solved the nanowire bundle problem by size-selective sorting of the emulsion droplets in a pinched flow fractionation microchannel. Utilizing silver nanowires and immiscible emsulsion droplets, we investigated the correlation between the size of ring droplets and bundle droplet. We visualized the sorting process for glass particles and microring-containing emulsion droplets. Droplets were sorted based on their size, and the ratio of bundle droplets in solution decreased. This droplet-sorting strategy has potential to help the printing and coating process for manufacturing of ring structure patterns and developing of functional materials.

• Journal of Information Technology Applications and Management
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• v.20 no.1
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• pp.87-106
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• 2013

This study is to explore the airline network patterns of Incheon and Narita International Airports using passenger flight departure and arrival data of the two airports. The so-called Origin-Destination data is collected from the airports' websites and some of the important data items are flight number, city of origin, destination city, departure/arrival time, number of flights, and delay time. A snowflake schema dimensional model is proposed and implemented. Tableau Public, a well-known visual analytic tool, is used to connect the dimensional model and played an important role in navigating the data space to find interesting and visual patterns among corresponding airports and airlines. For the efficiency of analyzing this spacious data mart, data visualization method was used. Four types of visualization method proposed by Yau was used; visualizing patterns over time, visualizing proportions, visualizing relationships, and visualizing spatial relationships. The strength of connectivity of each flight segments is calculated to evaluate the degree of globalization of Seoul and Tokyo. We anticipate that various patterns and new findings produced by the data mart would provide airline managers, airport authorities, and policy makers in the field of travel and transportation with insightful information.

• Transactions of the Korean hydrogen and new energy society
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• v.26 no.2
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• pp.136-147
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• 2015

Dead-ended operation of Proton Exchange Membrane Fuel Cell(PEMFC) provides the simplification of fuel cell systems to reduce fuel consumption and weight of fuel cell. However, the water accumulation within the channel prohibits a uniform supply of fuel. Optimization of the purge strategy is required to increase the fuel cell efficiency since fuel and water are removed during the purge process. In this study, we investigated the average voltage output which depends on two interrelated conditions, namely, the supply gas pressure, purging valve open time. In addition, flow visualization was performed to better understand the water build-up on the anode side and cathode side of PEMFC in terms of a variety of the current density. We analyzed the correlation between the purge condition and water flooding.

• Journal of Information Technology Applications and Management
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• v.24 no.1
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• pp.33-43
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• 2017

The content curation service through big data analysis is receiving great attention in various content fields, such as film, game, music, and book. This service recommends personalized contents to the corresponding user based on user's preferences. The existing book curation systems recommended books to users by using bibliographic citation, user profile or user log data. However, these systems are difficult to recommend books related to character names or spatio-temporal information in text contents. Therefore, in this paper, we suggest a personalized book curation system based on integrated mining of a book. The proposed system consists of mining system, recommendation system, and visualization system. The mining system analyzes book text, user information or profile, and SNS data. The recommendation system recommends personalized books for users based on the analysed data in the mining system. This system can recommend related books using based on book keywords even if there is no user information like new customer. The visualization system visualizes book bibliographic information, mining data such as keyword, characters, character relations, and book recommendation results. In addition, this paper also includes the design and implementation of the proposed mining and recommendation module in the system. The proposed system is expected to broaden users' selection of books and encourage balanced consumption of book contents.

• Journal of the Korean Society of Visualization
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• v.17 no.2
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• pp.48-57
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• 2019

A straightforward strategy for particle image velocimetry (PIV) interrogation and post-processing has been proposed, aiming at reducing errors and clarifying vortex structures. The interrogation window size should be kept small to reduce bias error and improve spatial resolution. A spatial filter is then applied to the velocity field to reduce random error and clarify flow structure. The performance of three popular spatial filters were assessed: box filter, median filter, and local quadratic polynomial regression filter. In order to quantify random uncertainty, the image matching (IM) method is applied to an experimental dataset of homogeneous and isotropic turbulence (HIT) obtained by 2D-PIV. We statistically analyze the uncertainty propagation through the spatial filters, and verify the reduction in random uncertainty. Moreover, we illustrate that the spatial filters help clarify vortex structures using vortex identification criteria. As a result, PIV random uncertainty was reduced and the vortex structures became clearer by spatial filtering.

• International conference on construction engineering and project management
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• 2005.10a
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• pp.1181-1186
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• 2005

In many construction projects, progress and efficiency are hampered by poor communication of discipline-specific models. For example, architects use 2D or 3D CAD models and builders use CPM diagrams, Gantt charts, and spreadsheets to show their view of the project. Nowadays, advanced computer visualization tools, 4D CAD or VR, can show these disparate models to understand cross-disciplinary impacts of design and construction decisions. In Korea, several leading companies have tried to apply these tools to their pilot projects from the design phase to the maintenance phase. These companies have expected that more project stakeholders could understand a construction schedule more quickly and completely with 4D visualization than with the traditional construction management tools. However, modeling of the 4D CAD or VR can be quite time-consuming and expensive to generate manually and has therefore limited the spread and use of these models. In order to adopt widely those models in construction industry, the areas that those tools could support to take large benefits in diverse functional areas of construction management need to be analyzed. In this study, researchers analyze the usefulness and limitations of the 4D models and VR in the construction industry, develop the strategy of application priority, and improve the 4D modeling method.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.3
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• pp.226-230
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• 2009

Intelligent Tutoring System (ITS) is a procedure of analyzing collected data for teaming, making a strategy and performing adequate service for learners. To perform suitable service for learners, modeling is the first step to collect data from the process of their learning. The model, however, cannot be authentic if collected data can contain learners' inconsistent behaviors or unpredictable learning inclination. This study focused on how to sort normal and abnormal data by analyzing collected data from learners through visualization. A model has been set up to assort unusual data from collected learner's data by using DOLLS-HI which makes possible to diagnose learner's learning propensity based on housing interior learning contents in the experiment. The created model has been confirmed its improved reliability comparing to previous one.