• Transactions of the Korean Society of Mechanical Engineers B
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• v.21 no.9
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• pp.1198-1206
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• 1997

The flow characteristics of an intermittent fuel injection into a stationary ambient air were investigated using gasoline. The measurements were made by two-channel, air cooling type Phase Doppler Anemometer(PDA) system (DANTEC, 750 MW). And a pintle type injector of MPI (Multi-point Port Injection) system was utilized as a fuel injector. The PDA receiver optic was set up in a 60.deg. C forward scatter arrangement to obtain the optimum scattering signal of fuel droplets. The data were obtained by synchronizing PDA system with the fuel injection period, and the axial and radial velocity and turbulent components of fuel droplets were mainly measured for the analysis of temporal and spatial distribution depending upon the fuel injection pressures.

• Geophysics and Geophysical Exploration
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• v.2 no.3
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• pp.154-158
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• 1999

This paper introduces a partial edge detection technique, that improves the processing time of an automatic change tracking system for multi-temporal images. In the conventional change tracking systems for multi-temporal images, the edge detection is performed over the whole image. In the proposed method, however, the necessary portions for the edge detection is selected first and the edge detection is performed over the selected parts only. As a consequence, the improvement in the processing time could be achieved. The proposed change tracking system is expected to be utilized as a very efficient tool to configure changes in large data set such as remotely sensed satellite imagery or geophysical time laps images.

• Journal of Korea Multimedia Society
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• v.12 no.12
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• pp.1718-1727
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• 2009

Traditional character recognition systems usually aim at characters with simple variation. With the development of multimedia technology, printed characters may appear more diversely. Existing recognition technologies can't deal with Hangul recognition effectively in diverse environments. This paper presents a recognition system for multi-form Korean characters called RSMFK, which is based on the model of Hierarchical Temporal Memory (HTM). Our system can effectively recognize the printed Korean characters of different fonts, scales, rotation, noise and background. HTM is a model which simulates the neocortex of human brain to recognize and memorize intelligently. Experimental results show that RSMFK performs a good recognition rate of 97.8% on average, which is proved to be obviously improved over the conventional methods.

• Korean Journal of Remote Sensing
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• v.26 no.6
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• pp.721-730
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• 2010

In satellite remote sensing, irregular temporal sampling is a common feature of geophysical and biological process on the earth's surface. Lee (2008) proposed a feed-back system using a harmonic model of single period to adaptively reconstruct observation image series contaminated by noises resulted from mechanical problems or environmental conditions. However, the simple sinusoidal model of single period may not be appropriate for temporal physical processes of land surface. A complex model of multiple periods would be more proper to represent inter-annual and inner-annual variations of surface parameters. This study extended to use a multi-periodic harmonic model, which is expressed as the sum of a series of sine waves, for the adaptive system. For the system assessment, simulation data were generated from a model of negative errors, based on the fact that the observation is mainly suppressed by bad weather. The experimental results of this simulation study show the potentiality of the proposed system for real-time monitoring on the image series observed by imperfect sensing technology from the environment which are frequently influenced by bad weather.

• Korean Journal of Remote Sensing
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• v.19 no.3
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• pp.263-269
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• 2003

This research examined the capabilities of KOMPSAT-1 EOC images for the application of urban environment, including the urban changes of the study areas. This research is constructed in three stages: Firstly, for the application of change detection techniques, which utilizes multi-temporal remotely sensed data, the data normalization process is carried out. Secondly, the change detection method is applied for the systematic monitoring of land-use changes. Lastly, using the results of the previous stages, the land-use map is updated. Consequently, the patterns of land-use changes are monitored by the proposed scheme. In this research, using the multi-temporal KOMPSAT-1 EOC images and land-use maps, monitoring of urban growth was carried out with the application of land-use changes, and the potential and scope of the application of the EOC images were also examined.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.5
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• pp.323-330
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• 2019

Radiometric normalization with multi-temporal satellite images is essential for time series analysis and change detection. Generally, relative radiometric normalization, which is an image-based method, is performed, and histogram matching is a representative method for normalizing the non-linear properties. However, since it utilizes global statistical information only, local information is not considered at all. Thus, this paper proposes a histogram matching method considering local information. The proposed method divides histograms based on density, mean, and standard deviation of image intensities, and performs histogram matching locally on the sub-histogram. The matched histogram is then further partitioned and this process is performed again, iteratively, controlled with the wasserstein distance. Finally, the proposed method is compared to global histogram matching. The experimental results show that the proposed method is visually and quantitatively superior to the conventional method, which indicates the applicability of the proposed method to the radiometric normalization of multi-temporal images with non-linear properties.

• Proceedings of the KSRS Conference
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• 2006.03a
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• pp.271-274
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• 2006

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.2
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• pp.538-561
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• 2020

Recommender Systems (RecSys) have a major role in e-commerce for recommending products, which they may like for every user and thus improve their business aspects. Although many types of RecSyss are there in the research field, the state of the art RecSys has focused on finding the user similarity based on sequence (e.g. purchase history, movie-watching history) analyzing and prediction techniques like Recurrent Neural Network in Deep learning. That is RecSys has considered as a sequence prediction problem. However, evaluation of similarities among the customers is challenging while considering temporal aspects, context and multi-component ratings of the item-records in the customer sequences. For addressing this issue, we are proposing a Deep Learning based model which learns customer similarity directly from the sequence to sequence similarity as well as item to item similarity by considering all features of the item, contexts, and rating components using Dynamic Temporal Warping(DTW) distance measure for dynamic temporal matching and 2D-GRU (Two Dimensional-Gated Recurrent Unit) architecture. This will overcome the limitation of non-linearity in the time dimension while measuring the similarity, and the find patterns more accurately and speedily from temporal and spatial contexts. Experiment on the real world movie data set LDOS-CoMoDa demonstrates the efficacy and promising utility of the proposed personalized RecSys architecture.

• Journal of the Korean association of regional geographers
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• v.21 no.1
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• pp.98-113
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• 2015

In this study, spatial and temporal patterns and changes in seasonal multi-day cumulative extreme precipitation events defined by maximum 1~5 days cumulative extreme precipitation observed at 61 weather stations in the Republic of Korea for the recent 40 years(1973~2012) are examined. It is demonstrated that the magnitude of multi-day cumulative extreme precipitation events is greatest in summer, while their sensitivity relative to the variations of seasonal total precipitation is greatest in fall. According to analyses of linear trends in the time series data, the most noticeable increases in the magnitude of multi-day cumulative extreme precipitation events are observable in summer with coherences amongst 1~5 days cumulative extreme precipitation events. In particular, the regions with significant increases include Gyeonggi province, western Gangwon province and Chungcheong province, and as the period for the accumulation of extreme precipitation increases from 1 day to 5 days, the regions with significantly-increasing trends are extended to the Sobaek mountain ridge. It is notable that at several scattered stations, the increases of 1~2 days cumulative extreme precipitation events are observed even in winter. It is also observed that most distinct increasing tendency of the ratio of these multi-day cumulative extreme precipitation to seasonal total precipitation appears in winter. These results indicate that proactive actions are needed for spatial and temporal changes in not only summer but also other seasonal multi-day cumulative extreme precipitation events in Korea.

• Journal of Broadcast Engineering
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• v.9 no.3
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• pp.214-224
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• 2004

In this paper, an adaptive spatio-temporal predictive coding based on the H.264 is proposed for 3D immersive media encoding, such as 3D image processing, 3DTV, and 3D videoconferencing. First, we propose a spatio-temporal predictive coding using the same view and inter-view images for the two TPPP, IBBP GOP (group of picture) structures 4hat are different from the conventional simulcast method. Second, an 2D inter-view direct mode for the efficient prediction is proposed when the proposed spatio-temporal prediction uses the IBBP structure. The 2D inter-view direct mode is applied when the temporal direct mode in B(hi-Predictive) picture of the H.264 refers to an inter-view image, since the current temporal direct mode in the H.264 standard could no: be applied to the inter-view image. The proposed method is compared to the conventional simulcast method in terms of PSNR (peak signal to noise ratio) for the various 3D test video sequences. The proposed method shows better PSNR results than the conventional simulcast mode.