• Proceedings of the Korean Society for Cognitive Science Conference
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• 2005.05a
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• pp.23-27
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• 2005

Humans perceptually segment events, but models that predict where events will be segmented are limited. Developing a detailed model may be hard because of the overlapping quality of events (i.e., one can smile and walk at the same time, but the endpoint of each event can be different). However, some aspects of events appear to be universally represented in the world's languages. For example, path, the trajectory of an object's movement, is one of the most universally encoded event features. Although it is generally encoded in the prepositions of English (e.g., up), in other languagesit is encoded in the verbs (e.g., descendere). Linguistic universals may represent basic levels of event perception. Here we consider how one of these, path, might be parsed. Because the spatiotemporal projection of paths to an observation point is similar to the spatial projection of objects, we tested the hypothesis that path segmentation and object segmentation would be based on similar image properties, such as discontinuities in orientation.

• Ocean and Polar Research
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• v.35 no.3
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• pp.229-237
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• 2013

We measured two-dimensional (2-D) oxygen distribution in the surface sediment layer of intertidal sediment using a simple and inexpensive planar oxygen optode, which is based on a color ratiometric image approach. The recorded emission intensity of red color luminophore light significantly changed with oxygen concentration by $O_2$ quenching of platinum(II)octaethylporphyrin (PtOEP). The ratios between the intensity of red and green emissions with oxygen concentration variation demonstrated the Stern-Volmer relationship. The 2-D oxygen distribution image showed microtopographic structure, diffusivity boundary layer and burrow in surface sediment layer. The oxygen penetration depth (OPD) was about 2 mm and the one-dimensional vertical diffusive oxygen uptake (DOU) was 12.6 mmol $m^{-2}d^{-1}$ in the undisturbed surface sediment layer. However, those were enhanced near burrow by benthic fauna, and the OPD was two times deeper and DOU was increased by 34%. The simple and inexpensive oxygen planar optode has great application potential in the study of oxygen dynamics with high spatiotemporal resolution, in benthic boundary layers.

• Journal of the Korean Vacuum Society
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• v.18 no.1
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• pp.54-59
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• 2009

We have measured the spatiotemporal behavior for the density of excited Xe atoms in the $1s_5$ metastable states by laser absorption spectroscopy in accordance with various shapes of ITO electrode. The maximum density of excited Xe atoms in the Is5 state in a discharge cell for fish-boned, T-shaped and squared ITO electrodes has been measured to be $3.01{\times}10^{13}\;cm^{-3}$, $2.66{\times}10^{13}\;cm^{-3}$ and $2.06{\times}10^{13}\;cm^{-3}$, respectively. Throughout this experiment, we could understand the influence of the shapes of ITO electrode of micro discharge cell on the high efficiency of AC-PDPs.

• Korean Journal of Remote Sensing
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• v.37 no.6_3
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• pp.1931-1942
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• 2021

As the utility of an optical satellite image with a high spatial resolution (i.e., fine-scale) has been emphasized, recently, various studies of the land surface monitoring using those have been widely carried out. However, the usefulness of fine-scale satellite images is limited because those are acquired at a low temporal resolution. To compensate for this limitation, the spatiotemporal data fusion can be applied to generate a synthetic image with a high spatio-temporal resolution by fusing multiple satellite images with different spatial and temporal resolutions. Since the spatio-temporal data fusion models have been developed for mid or low spatial resolution satellite images in the previous studies, it is necessary to evaluate the applicability of the developed models to the satellite images with a high spatial resolution. For this, this study evaluated the applicability of the developed spatio-temporal fusion models for KOMPSAT-3A and Sentinel-2 images. Here, an Enhanced Spatial and Temporal Adaptive Fusion Model (ESTARFM) and Spatial Time-series Geostatistical Deconvolution/Fusion Model (STGDFM), which use the different information for prediction, were applied. As a result of this study, it was found that the prediction performance of STGDFM, which combines temporally continuous reflectance values, was better than that of ESTARFM. Particularly, the prediction performance of STGDFM was significantly improved when it is difficult to simultaneously acquire KOMPSAT and Sentinel-2 images at a same date due to the low temporal resolution of KOMPSAT images. From the results of this study, it was confirmed that STGDFM, which has relatively better prediction performance by combining continuous temporal information, can compensate for the limitation to the low revisit time of fine-scale satellite images.

• Journal of the Korean Association of Geographic Information Studies
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• v.8 no.3
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• pp.34-43
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• 2005

We will catch the spatio-temporal changes that analyse the unknown topography of Go-Gunsan Islands using Landsat TM satellite images into an unsupervised ISODATA classification and a supervised nearest likelihood classification. Each sedimental topography has the different characteristics according to building the Saemangeum embarkment. We will deal with the distribution of sedimental shapes using ERDAS Imagine 8. 6. The result that classifies specifically topographic properties of our research area be considered to get use of establishing the reclaiming program and predicating the reclaimed sedimental topography. The research area can be classified into tidal flats and sea level using band 4 among 7 bands of Landsat TM. Also band 5 can be used to classify the special unknown shapes of tidal flats. We will clarify the efficiency that spatio-temporal sedimental changes can be extracted through processing satellite images. Therefore, the spatio-temporal unknown topography change monitoring using satellite images is expected to be very useful to clarify whether the tidal flat is generated or not in the Go-Gunsan Islands at the outer side of the embarkment after constructing completely the Saemangeum tidal embarkment.

• Journal of Korean Society for Atmospheric Environment
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• v.34 no.3
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• pp.493-507
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• 2018

Due to high spatio-temporal variability of amount and optical/microphysical properties of atmospheric aerosols, satellite-based observations have been demanded for spatiotemporal monitoring the major aerosols. Observations of the heavy aerosol episodes and determination on the dominant aerosol types from a geostationary satellite can provide a chance to prepare in advance for harmful aerosol episodes as it can repeatedly monitor the temporal evolution. A new geostationary observation sensor, namely the Advanced Himawari Imager (AHI), onboard the Himawari-8 platform, has been observing high spatial and temporal images at sixteen wavelengths from 2016. Using observed spectral visible reflectance and infrared brightness temperature (BT), the algorithm to find major aerosol type such as volcanic ash (VA), desert dust (DD), polluted aerosol (PA), and clean aerosol (CA), was developed. RGB color composite image shows dusty, hazy, and cloudy area then it can be applied for comparing aerosol detection product (ADP). The CALIPSO level 2 vertical feature mask (VFM) data and MODIS level 2 aerosol product are used to be compared with the Himawari-8/AHI ADP. The VFM products can deliver nearly coincident dataset, but not many match-ups can be returned due to presence of clouds and very narrow swath. From the case study, the percent correct (PC) values acquired from this comparisons are 0.76 for DD, 0.99 for PA, 0.87 for CA, respectively. The MODIS L2 Aerosol products can deliver nearly coincident dataset with many collocated locations over ocean and land. Increased accuracy values were acquired in Asian region as POD=0.96 over land and 0.69 over ocean, which were comparable to full disc region as POD=0.93 over land and 0.48 over ocean. The Himawari-8/AHI ADP algorithm is going to be improved continuously as well as the validation efforts will be processed by comparing the larger number of collocation data with another satellite or ground based observation data.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.8 no.5
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• pp.57-63
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• 2008

Recently, OGC(Open Geospatial Consortium) take the lead in SWE(Sensor Web Enablement) research that collection various context information from sensor networks and show it on map by web. OGC SWE WG(Working Group) defines a standard encoding about realtime spatiotemporal appear geographical feature, sensing data and support web services. This paper proposes a visualization scheme of sensing data based location on 2D maps. We show realtime sensing data on moving node that mapping GPS data on map. First, we present an algorithm and procedure that location information change to position of maps for visualization sensing data based on 2D maps. For verifying that algorithm and scheme, we design and implement a program that collecting GPS data and sensing data, and displaying application on 2D maps. Therefore we confirm effective visualization on maps based on web which realtime image and sensing data collected from sensor network.

• The Korean Journal of Applied Statistics
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• v.29 no.5
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• pp.859-872
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• 2016

Land cover classification is an important tool for preventing natural disasters, collecting environmental information, and monitoring natural resources. Hyperspectral imaging is widely used for this task thanks to sufficient spectral information. However, the curse of dimensionality, spatiotemporal variability, and lack of labeled data make it difficult to classify the land cover correctly. We propose a novel classification framework for land cover classification of hyperspectral data based on convolutional neural networks. The proposed framework naturally incorporates full spectral features with the information from neighboring pixels and has advantages over existing methods that require additional feature extraction or pre-processing steps. Empirical evaluation results show that the proposed framework provides good generalization power with classification accuracies better than (or comparable to) the most advanced existing classifiers.

• Korean Journal of Optics and Photonics
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• v.9 no.6
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• pp.368-372
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• 1998

A 16-views 3 dimensional imaging system is designed by spatially combinding two 8-views time multiplexed image channels. Each 8-views channel composed of 3 primary color CRTs and a dichroic beam splitter which combining the three CRTs as one channel. Each CRT displays 8-view images time sequentially. These images are projected to a holographic screen of a size 1$\times$0.8 $m^2$ through a projection optics. Characteristics of the three different configurations of projection optics are examined with the optics designing program "DEMOS" to select an optimized projection optics for the system. The configulation of the optimized projection optics is found like following; images from each channel combined by two-fold mirror are projected by a projection objective through a 16-strips LCD shutter. In this configuration, the shutter should be located at the entrance pupil of the objective, and the folded edge of the two-fold mirror should contact symmetrically to the center line of the shutter.e shutter.

• Journal of the Korean Association of Geographic Information Studies
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• v.15 no.1
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• pp.172-183
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• 2012

In 2011, floods were at the worst stage of devastation in Chao Phraya river basin of Thailand. The purpose of this study is to trace the flood inundation area around Chao Phraya river basin by using Terra MODIS image because it has the ability of spatiotemporal dynamics. The MODIS indices, which included the enhanced vegetation index(EVI), land surface water index(LSWI), and the difference in the values of EVI and LSWI(DVEL), were extracted from MODIS product MOD09 8-day composite datasets with a spatial resolution of 500m from Jul. 29, 2011 to Jan. 09, 2012. We found that combined application of EVI, LSWI, and DVEL was suitable for monitoring flood inundation. For the extracted flood inundation area and water-related area. The result can be used to acquire the flood inundation data scattered and demonstrate the potential for the use of MODIS data for temporal and spatial detection of flood effects.