• Knowledge Management Research
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• v.19 no.1
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• pp.119-132
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• 2018

Many advanced products and services are emerging in the market thanks to data-based technologies such as Internet (IoT), Big Data, and AI. The construction of a system for data processing under the IoT network environment is not simple in configuration, and has a lot of restrictions due to a high cost for constructing a high performance server environment. Therefore, in this paper, we will design a development environment for large data analysis computing platform using open source with low cost and practicality. Therefore, this study intends to implement a big data processing system using Raspberry Pi, an ultra-small PC environment, and open source API. This big data processing system includes building a portable server system, building a web server for web mining, developing Python IDE classes for crawling, and developing R Libraries for NLP and visualization. Through this research, we will develop a web environment that can control real-time data collection and analysis of web media in a mobile environment and present it as a curriculum for non-IT specialists.

• Journal of Korea Multimedia Society
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• v.14 no.6
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• pp.835-848
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• 2011

In this paper, we propose a client server based distributed/parallel system to effectively visualize huge geographic data. The system consists of a web-based client GUI program and a distributed/parallel server program which runs on multiple PC clusters. To make the client program run on mobile devices as well as PCs, the graphical user interface has been designed by using JOGL, the java-based OpenGL graphics library, and sending the information about current available memory space and maximum display resolution the server can minimize the amount of tasks. PC clusters used to play the role of the server access requested geographic data from distributed disks, and properly re-sample them, then send the results back to the client. To minimize the latency happened in repeatedly access the distributed stored geography data, cache data structures have been maintained in both every nodes of the server and the client.

• Korean Journal of Remote Sensing
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• v.31 no.1
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• pp.1-9
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• 2015

Mobility and cloud platform have become the dominant paradigm to develop web services dealing with huge and diverse digital contents for scientific solution or engineering application. These two trends are technically combined into mobile cloud computing environment taking beneficial points from each. The intention of this study is to design and implement a mobile cloud application for remotely sensed image fusion for the further practical geo-based mobile services. In this implementation, the system architecture consists of two parts: mobile web client and cloud application server. Mobile web client is for user interface regarding image fusion application processing and image visualization and for mobile web service of data listing and browsing. Cloud application server works on OpenStack, open source cloud platform. In this part, three server instances are generated as web server instance, tiling server instance, and fusion server instance. With metadata browsing of the processing data, image fusion by Bayesian approach is performed using functions within Orfeo Toolbox (OTB), open source remote sensing library. In addition, similarity of fused images with respect to input image set is estimated by histogram distance metrics. This result can be used as the reference criterion for user parameter choice on Bayesian image fusion. It is thought that the implementation strategy for mobile cloud application based on full open sources provides good points for a mobile service supporting specific remote sensing functions, besides image fusion schemes, by user demands to expand remote sensing application fields.

• The Journal of Engineering Geology
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• v.25 no.3
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• pp.395-401
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• 2015

An investigation of the tunnel face, as well as related measurement data collected during tunneling, is necessary for rock classification and to determine tunnel stability and the cost efficiency of tunneling. However, systematic management and efficient use of such data have yet to be successfully implemented domestically, and the number of experts in this field in Korea is limited. Thus, measures to develop and implement systematic management and effective use of data and expertise are urgently needed. This study aimed to develop measures to efficiently provide online tunnel design and construction data using a building information model (BIM)-based data visualization approach, based on an integrated 3D tunnel model generation module and a web viewer module. The development technology was verified through ○○ tunnel design and construction. Directions for future study and system improvement are proposed.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.5
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• pp.413-417
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• 2002

The Internet technology has been recognized not only as a tool far communication in the 21st century but also as an environment for enabling changes in the paradigm of teaching and learning. This paper describes a web-based system development for chemical engineering education. Simulation and visualization of dynamic systems in the environment of a standard web-browser is made possible by extending its capabilities. ActiveX control is used to simulate the system tool far online representation of Virtual Lab. System that is developed using visual basic. The courseware is classified into tutorial, exercises, and virtual experiments.

• Proceedings of the Korea Database Society Conference
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• 2008.05a
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• pp.211-224
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• 2008

As a lot of information and media are given to users in Internet space nowadays, users feel disoriented or "lost in space" intensively. So it is suggested that we have the system to reduce information overload and to propose effective and efficient information. In this study we present a visualizing technique which uses fisheye views on data adjacency to combine global context and local details for presentation of many results in limited space. Data Adjacency on graph theory is applied to set up degree of interest which is main focus in fisheye views. Graph theory is useful to solve the problem resulted from various combinational optimization, especially it has advantages to analyze issues in information space like Internet. To test the usability of the proposed visualization technique, we compared the effectiveness of different visualization techniques. Results show that our method is evaluated with respect to less time and high satisfaction for a task accomplishment.

• Journal of the Korean Data and Information Science Society
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• v.28 no.6
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• pp.1279-1290
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• 2017

R's {shiny} package provides an environment for creating web applications with only R scripts. Shiny does not require knowledge of a separate web programming language and its development is very easy and straightforward. In addition, Shiny has a variety of extensibility, and its functions are expanding day by day. Therefore, the presentation of high-quality results is an excellent tool for R-based analysts. In this paper, we present actual cases of large data analysis using Shiny. First, geological anomaly zone is extracted by analyzing topographical data expressed in the form of contour lines by analysis related to spatial data. Next, we will construct a model to predict major diseases by 16 cities and provinces nationwide using weather, environment, and social media information. In this process, we want to show that Shiny is very effective for data visualization and analysis.

• The KIPS Transactions:PartA
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• v.18A no.3
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• pp.81-92
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• 2011

There has been a number of attempts to apply 3D CAD data created in the design stage of product life cycle to various applications of the other stages in related industries. But, 3D CAD data requires a large amount of computing resources for data processing, and it is not suitable for post applications such as distributed collaboration, marketing tool, or Interactive Electronic Technical Manual because of the design information security problem and the license cost. Therefore, various lightweight visualization formats and application systems have been suggested to overcome these problems. However, most of these lightweight formats are dependent on the companies or organizations which suggested them and cannot be shared with each other. In addition, product structure information is not represented along with the product geometric information. In this paper, we define a dataset called prod-X3D(Enhanced X3D Dataset for Web-based Visualization of 3D CAD Product Model) based on the international standard graphic format, X3D, which can represent the structure information as well as the geometry information of a product, and propose a translation method from 3D CAD data to an prod-X3D.

• Korean Journal of Remote Sensing
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• v.23 no.1
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• pp.43-53
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• 2007

In this study, two standard specifications such as GML (Geography Markup Language) from OGC (Open Geo-spatial Consortium, Inc.) and X3D (extensible 3D) from Web3D consortium were dealt with for a web-based 3D urban application without using commercialized tools. In the first step of this study, DEM (Digital Elevation Model) and 3D GIS data sets were converted to GML structure with attribute schema. Then, these GML elements were projected onto a common coordinate system, and they were converted to the X3D format for visualization on web browser. In this work, a 3D urban data model, as a simple framework model, is extended to a framework model having further detailed information, depending upon application levels. Conclusively, this study is to demonstrate for practical uses of GML and X3D in 3D urban application and this approach can be applied to other application domains regarding system integrators and data sharing communities on distributed environments.

• Journal of the Semiconductor & Display Technology
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• v.20 no.4
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• pp.151-156
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• 2021

Low-end IoT devices do not have enough computation and memory resources for DNN learning and inference. Integer quantization of real-type neural network models can reduce model size, hardware computational burden, and power consumption. This paper describes the design and implementation of a web-based quantization platform for CNN deep learning accelerator chips. In the web service platform, we implemented visualization of the model through a convenient UI, analysis of each step of inference, and detailed editing of the model. Additionally, a data augmentation function and a management function of files that store models and inference intermediate results are provided. The implemented functions were verified using three YOLO models.