• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.56 no.4
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• pp.322-339
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• 2020

Temporal and spatial fluctuations of surface water temperature in Yeosu Bay for the period from 2010 to 2011 were studied using the data from temperature monitoring buoys deployed at 32 stations in the south coast of Korea. Temperatures in the northern part of the bay are higher in summer and lower in winter than in the southern part of the bay. The lowest and highest temperature of the annual mean are found at the eastern coast of POSCO and at the west of Dae Island, respectively. Cold water masses appear at estuarine area when the discharge of Sumjin river is affluent. Amplitude of temperature fluctuation whose period is less than semi-diurnal is largest at Hadong coast and around Dae Island. Spectral analysis of surface water temperature shows a significant peak at a periodic fluctuation of 0.5 to 24 days and about 15-day period of predominant fluctuation is most frequent in Yeosu Bay. From the cross-correlation analysis of temperature fluctuations, Yeosu Bay can be classified into six areas; the south area affected by South Sea of Korea, the mixed area in the center of the bay, the estuarine area affected by river discharge at the north of the bay, the hot waste water area near Hadong coast, the area around Dae Island and the area near Noryang Channel affected by the water in Jinju Bay, respectively.

• Journal of agriculture & life science
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• v.44 no.5
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• pp.117-127
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• 2010

The purpose of this study is to analyze the temporal and spatial characteristics of water quality data of Nakdonggang watershed which is second largest watershed in South Korea. The correlation between the water quality items for rainy and non-rainy seasons were also analyzed for two TMDL sites which are Gumi and Namji. BOD data of two Total Maximum Daily Loads (TMDL) target sites were compared with TMDL criteria, 3-year arithmetic mean BOD concentration of the target sites should not exceed the target concentration for 2 consecutive years, to figure out current water quality status. Spatial analysis results showed that the correlation coefficient between Goryeong and Hyunpung was highest with the value of 0.978 followed by Hapcheon and Namji with the value of 0.874. The observed BOD data of Gumi station fluctuated around the TMDL criterion, 1.8mg/L while Namji station mostly exceed the criterion, 2.6mg/L. The criteria values for each target sites are defined by Ministry of Environment. The major factor of correlation coefficient was the distance between the stations. The correlation between the water quality items for non-rainy season showed no relation while the correlation between COD and SS was high followed by COD and TP for Gumi and Namji.

• Communications for Statistical Applications and Methods
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• v.30 no.6
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• pp.561-575
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• 2023

Brain network analysis has attracted the interest of neuroscience researchers in studying brain diseases. Magnetoencephalography (MEG) is especially proper for analyzing functional connectivity due to high temporal and spatial resolution. The application of graph theory for functional connectivity analysis has been studied widely, but research on network modeling for MEG still needs more. Temporal exponential random graph model (TERGM) considers temporal dependencies of networks. We performed the brain network analysis, including static/temporal network statistics, on two groups of epilepsy patients who removed the left (LT) or right (RT) part of the brain and healthy controls. We investigate network differences using Multiset canonical correlation analysis (MCCA) and TERGM between epilepsy patients and healthy controls (HC). The brain network of healthy controls had fewer temporal changes than patient groups. As a result of TERGM, on the simulation networks, LT and RT had less stable state than HC in the network connectivity structure. HC had a stable state of the brain network.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.6
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• pp.64-72
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• 1996

In this paper, we propose predictive motion estimatin algorithm which can predict motion without additional side information considering spatio-tempral correlatio of motion vector. This method performs motion prediction of current block using correlation of the motion vector for two spatially adjacent blocks and a temporally adjacent block. Form predicted motion, the position of searhc area is determined. Then in this searhc area, we estimate motion vector of current block using block matching algoirthm. Considering spatial an temporal correlation of motion vector, the proposed method can predict motion precisely much more. Especially when the motion of objects is rapid, this method can estimate motion more precisely without reducing block size or increasing search area. Futhrmore, the proposed method has computation time the same as conventional block matching algorithm. And as it predicts motion from adjacent blocks, it does not require additional side information for adjacent block. Computer simulation results show that motion estimation of proposed method is more precise than that of conventioanl method.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.3
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• pp.122-128
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• 2013

This paper presents a detection algorithm that accurately finds the active area of a video player on monitors or smart TVs. Unlike the previous approaches, temporal difference-based detection algorithms or hooking programs, the proposed detection algorithm can locate the active video player by using the spatial and temporal correlation and a corner detection filter. First, an initial location of the video player is found using conventional temporal difference-based detection. Then, starting from the initial location, the four corners of the active video player are detected by the spatial edge information and the corner detection filter. The experimental results show that proposed algorithm provides fast detection speed and high accuracy.

• Journal of Environmental Science International
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• v.22 no.12
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• pp.1683-1690
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• 2013

We investigated the spatial and temporal variations of phytoplankton in Youngil Bay as well as the effect of water physico-chemical parameters. Water samples at three stations were collected and measured monthly from May to November in 2010. The taxa of phytoplankton observed in this study were classified as 33 Bacillariophyceae, 23 Dinophyceae, 1 Euglenophyceae, 2 Crysophyceae and 1 Cryptophyceae. The highest biomass of phytoplankton was observed at inner station in September, which was characterized high concentration of dissolved inorganic phosphate(DIP) in surface water after rainfall. Nutrient concentrations, chlorophyll-a and phytoplankton biomass values showed the marked trend to decrease from the inner bay to the outer bay. Pearson's correlation co-efficient between salinity and other water parameters including chlorophyll-a, pH and DIP showed the strong negative relationship r=-0.82, r=-0.78 and r=-0.75 (p<0.01), respectively. These results indicate that the water quality of Youngil Bay could be stimulated by nutrient enriched input from Hyeogsan River discharge, and the spatial and temporal distribution of phytoplankton biomass principally limited to DIP concentration from Hyeogsan river.

• Korean Journal of Remote Sensing
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• v.37 no.5_1
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• pp.999-1011
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• 2021

In spatio-temporal fusion aiming at predicting images with both high spatial and temporal resolutionsfrom multi-sensor images, the radiometric inconsistency between input multi-sensor images may affect prediction performance. This study investigates the effect of radiometric correction, which compensate different spectral responses of multi-sensor satellite images, on the spatio-temporal fusion results. The effect of relative radiometric correction of input images was quantitatively analyzed through the case studies using Sentinel-2, PlanetScope, and RapidEye images obtained from two croplands. Prediction performance was improved when radiometrically corrected multi-sensor images were used asinput. In particular, the improvement in prediction performance wassubstantial when the correlation between input images was relatively low. Prediction performance could be improved by transforming multi-sensor images with different spectral responses into images with similar spectral responses and high correlation. These results indicate that radiometric correction is required to improve prediction performance in spatio-temporal fusion of multi-sensor satellite images with low correlation.

• The Journal of the Korea Contents Association
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• v.12 no.4
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• pp.31-39
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• 2012

DVC(Distributed Video Coding) techniques have been attracting a lot of research works since these enable us to implement the light-weight video encoder and to provide good coding efficiency by introducing the feedback channel. However, the feedback channel causes the decoder to increase the decoding complexity and requires very high decoding latency because of numerous iterative decoding processes. So, in order to reduce the decoding delay and then to implement in a real-time environment, this paper proposes several parity bit estimation methods which are based on the temporal correlation, spatial correlation and spatio-temporal correlations between LDPCA frames on each bit plane in the consecutive video frames in pixel-domain Wyner-Ziv video coding scheme and then the performances of these methods are compared in fast DVC scheme. Through computer simulations, it is shown that the adaptive spatio-temporal correlation-based estimation method and the temporal correlation-based estimation method outperform others for the video frames with the highly active contents and the low active contents, respectively. By using these results, the proposed estimation schemes will be able to be effectively used in a variety of different applications.

• Korean Journal of Remote Sensing
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• v.36 no.5_1
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• pp.807-821
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• 2020

The objective of this study is to evaluate the applicability of representative spatio-temporal fusion models developed for the fusion of mid- and low-resolution satellite images in order to construct a set of time-series high-resolution images for crop monitoring. Particularly, the effects of the characteristics of input image pairs on the prediction performance are investigated by considering the principle of spatio-temporal fusion. An experiment on the fusion of multi-temporal Sentinel-2 and RapidEye images in agricultural fields was conducted to evaluate the prediction performance. Three representative fusion models, including Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM), SParse-representation-based SpatioTemporal reflectance Fusion Model (SPSTFM), and Flexible Spatiotemporal DAta Fusion (FSDAF), were applied to this comparative experiment. The three spatio-temporal fusion models exhibited different prediction performance in terms of prediction errors and spatial similarity. However, regardless of the model types, the correlation between coarse resolution images acquired on the pair dates and the prediction date was more significant than the difference between the pair dates and the prediction date to improve the prediction performance. In addition, using vegetation index as input for spatio-temporal fusion showed better prediction performance by alleviating error propagation problems, compared with using fused reflectance values in the calculation of vegetation index. These experimental results can be used as basic information for both the selection of optimal image pairs and input types, and the development of an advanced model in spatio-temporal fusion for crop monitoring.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.114-117
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• 2009

A new video inpainting algorithm is proposed for removing unwanted objects or error of sources from video data. In the first step, the block bundle is defined by the motion information of the video data to keep the temporal consistency. Next, the block bundles are arranged in the 3-dimensional graph that is constructed by the spatial and temporal correlation. Finally, we pose the inpainting problem in the form of a discrete global optimization and minimize the objective function to find the best temporal bundles for the grid points. Extensive simulation results demonstrate that the proposed algorithm yields visually pleasing video inpainting results even in a dynamic scene.