• Proceedings of the Korea Contents Association Conference
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• 2009.05a
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• pp.12-16
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• 2009

Exponentially increasing UCC, experiences which some people get at the specific time and in the specific location are shared on the Web more easily. Also, UCC have been more reliable and more efficient resources, because of many people's natural valuation on each UCC. UCC have potential possibility to be primary factor in all ubiquitous computing environment. However, like ubiquitous computing techniques themselves the current availability and utilization of online UCC is far from realizing their full potential. In this paper, we propose a technique that integrates existing methods from information retrieval and tagging technologies to correspond with user's underlying need for some information in ubiquitous computing environment.

• Proceedings of the KSRS Conference
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• v.1
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• pp.390-393
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• 2006

It is well known that synthetic aperture radar (SAR) provides information on ocean winds and surface waves. SAR data are of particularly high value in extreme weather conditions, as radar is able to penetrate the clouds providing information on different ocean surface processes. In this presentation some recent results on SAR observation of extreme wind and ocean wave conditions is summarised. Particular emphasize is put on the investigation of typhoons and extratropical cyclones in the North Pacific. The study is based on the use of ENVISAT ASAR wide swath images. Wide swath and scansar data are well suited for a detailed investigation of cyclones. Several examples like, e.g., typhoon Talim will be presented, demonstrating that these data provide valuable information on the two dimensional structure of the both the wind and the ocean wave field. Comparisons of the SAR observation with parametric and numerical model data will be discussed. Some limitations of standard imaging models like, e.g., CMOD5 for the use in extreme wind conditions are explained and modifications are proposed. Finally the study summarizes the capabilities of new high resolution TerraSAR-X mission to be launched in October 2006 with respect to the monitoring of extreme weather conditions. The mission will provide a spatialresolution up to 1m and has full polarimetric capabilities.

• The Journal of Information Systems
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• v.26 no.2
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• pp.105-121
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• 2017

Purpose It is a major goal to improve the product yields during production operations in the manufacturing industry. Therefore, factory is trying to keep the good quality materials and proper production resources, also find the proper condition of facilities and manufacturing environment for yields improvement. Design/methodology/approach We propose the hybrid framework to analyze to dataset extracted from MES. Those data is about the alarm information generated from equipment, both measurement and equipment process value from production and cycle/pitch time measured from production data these covered products during production. We adapt a data warehousing techniques for organizing dataset, a logistic regression for finding out the significant factors, and a association analysis for drawing the rules which affect the product yields. And then we validate the framework by applying the real data generated from the discrete process in secondary cell battery manufacturing. Findings This paper deals with challenges to apply the full potential of modeling and simulation within CPPS(Cyber-Physical Production System) and Smart Factory implementation. The framework is being applied in one of the most advanced and complex industrial sectors like semiconductor, display, and automotive industry.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.45 no.8
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• pp.11-16
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• 2008

In this paper, firstly we made of the rapid thermal processor equipment with the specifically useful structure to measure wafer stress. Secondly we made of the laser interferometry to inspect the wafer surface curvature based on the large deformation theory. And then the wafer surface fringe image was obtained by experiment, and the full field stress distribution of wafer surface comes into view by signal processing with thining and pitch mapping. After wafer was ground by 1mm and polished from the back side to get easily deformation, and it was heated by three to four times thermal treatments at about 1000 degree temperature. Finally the severe deformation between wafer before and after the heat treatment was shown.

• Journal of information and communication convergence engineering
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• v.12 no.2
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• pp.89-96
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• 2014

Here, we present a review of the proposals and advances in the field of three-dimensional (3D) imaging acquisition and display made in the last century. The most popular techniques are based on the concept of stereoscopy. However, stereoscopy does not provide real 3D experience, and produces discomfort due to the conflict between convergence and accommodation. For this reason, we focus this paper on integral imaging, which is a technique that permits the codification of 3D information in an array of 2D images obtained from different perspectives. When this array of elemental images is placed in front of an array of microlenses, the perspectives are integrated producing 3D images with full parallax and free of the convergence-accommodation conflict. In the paper we describe the principles of this technique, together with some new applications of integral imaging.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.42 no.2
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• pp.536-544
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• 2017

Wireless RSSI (Received Signal Strength Indication) fingerprinting is one of the most popular methods for indoor positioning as it provides reasonable accuracy while being able to exploit existing wireless infrastructure. However, the process of radio map construction (aka fingerprint calibration) is laborious and time consuming as precise physical coordinates and wireless signals have to be measured at multiple locations of target environment. This paper proposes a method to build the map from a combination of RSSIs without location information collected in a crowdsourcing fashion, and a handful of labeled RSSIs using a semi-supervised self organizing map learning algorithm. Experiment on simulated data shows promising results as the method is able to recover the full map effectively with only 1% RSSI samples from the fingerprint database.

• Proceedings of the IEEK Conference
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• 2002.07b
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• pp.999-1002
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• 2002

In this paper, we proposes an adaptive method for reducing the computational overhead of fine-to-coarse MRME at the finest resolution level by considering for the spatial and spectral characteristics between wavelet decomposition levels simultaneously. As we know, there is high correlation between the adjacent blocks and it can give the very important clue to estimate motion at finest level. So, in this paper, using the initial motion vector and the adjacent motion vector in the coarsest level, we determine the optimal direction that will be minimized the estimation error in the finest level. In that direction, we define the potential searching region within the full searching region that is caused to increase much computational overhead in the FtC method. Last, in that region, we process the efficient 2-step motion estimation. and estimate the motion vector at finest resolution level. And then, this determined motion vector is scaled to coarser resolutions. As simulation result, this method is similar to computational complexity of the CtF MRME method and very significantly reduces that of the FtC MRME method. In addition, they provide higher quality than CtF MRME, both visually and quantitatively

• Journal of Advanced Marine Engineering and Technology
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• v.40 no.8
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• pp.726-732
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• 2016

Clustering analysis is widely used in data mining to classify data into categories on the basis of their similarity. Through the decades, many clustering techniques have been developed, including hierarchical and non-hierarchical algorithms. In gene profiling problems, because of the large number of genes and the complexity of biological networks, dimensionality reduction techniques are critical exploratory tools for clustering analysis of gene expression data. Recently, clustering analysis of applying dimensionality reduction techniques was also proposed. PCA (principal component analysis) is a popular methd of dimensionality reduction techniques for clustering problems. However, previous studies analyzed the performance of PCA for only full data sets. In this paper, to specifically and robustly evaluate the performance of PCA for clustering analysis, we exploit an improved FCBF (fast correlation-based filter) of feature selection methods for supervised clustering data sets, and employ two well-known clustering algorithms: k-means and k-medoids. Computational results from supervised data sets show that the performance of PCA is very poor for large-scale features.

• Spatial Information Research
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• v.13 no.1 s.32
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• pp.19-29
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• 2005

In this study, Real Time Kinematic GPS(RTK GPS) was conducted twice at the same site in two different seasons, respectively to check the possibility of it as the mapping tool, and how the factor affecting the accuracy of it. As a result, most parts of a small garden except f3r the worst environments surrounded with lots of tree canopy and several buildings were mapped using RTK GPS even in spring, full of a green foliage and winter as well. However, the mapping accuracy and the availability of RTK GPS were not so high. The study showed that it is recommended in RTK GPS mapping to utilize Total Station, etc. in the worst urban environments unable to track the satellite signals with ease.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.1
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• pp.41-60
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• 2018

Recently, road traffic congestion is becoming a serious urban phenomenon, leading to massive adverse impacts on the ecology and economy. Therefore, solving this problem has drawn public attention throughout the world. One new promising solution is to take full advantage of vehicular ad hoc networks (VANETs). In this study, we propose a new traffic congestion detection and quantification method based on vehicle clustering and fuzzy assessment in VANET environment. To enhance real-time performance, this method collects traffic information by vehicle clustering. The average speed, road density, and average stop delay are selected as the characteristic parameters for traffic state identification. We use a comprehensive fuzzy assessment based on the three indicators to determine the road congestion condition. Simulation results show that the proposed method can precisely reflect the road condition and is more accurate and stable compared to existing algorithms.