• The Journal of the Acoustical Society of Korea
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• v.43 no.1
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• pp.1-8
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• 2024

For measuring the performance of passive sonars, we usually consider the maximum Detection Range (DR) under the environment and system parameters in operation. In shallow water, where sound waves inevitably interacts with sea surface or bottom, detection generally maintains up to the maximum range. In deep water, however, sound waves may not interact with sea surface or/and bottom, and thus there may exist shadow zones where sound waves can hardly reach. In this situation, DR alone may not completely define the performance of each sonar. For complete description of sonar performance, we employ the concept 'Robustness Of Detection (ROD)'. In the coastal region of the East Sea, the spatial variations of water masses have close relations with DR and ROD, where the two parameters show reverse spatial variations in general. The spatial and temporal analysis of the temperature by employing the Empirical Orthogonal Function (EOF) shows that the 1-st mode represents typical pattern of seasonal variation and the 2-nd mode represents strength variations of mixed layers and currents. The two modes are estimated to explain about 92 % of the variations. Assuming two types of targets located at the depths of 5 m (shallow) and 100 m (deep), the passive sonar performance (DR) gives high negative correlations (about -0.9) with the first two modes. Most of temporal variations of temperature occur from the surface up to 200 m in the water column so that when we assume a target at 100 m, we can expect detection performance of little seasonal variations with passive sonars below 100 m.

• International Journal of Contents
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• v.9 no.4
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• pp.1-10
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• 2013

The electroencephalogram (EEG) time series is a measure of electrical activity received from multiple electrodes placed on the scalp of a human brain. It provides a direct measurement for characterizing the dynamic aspects of brain activities. These EEG signals are formed from a series of spatial and temporal data with multiple dimensions. Missing data could occur due to fault electrodes. These missing data can cause distortion, repudiation, and further, reduce the effectiveness of analyzing algorithms. Current methodologies for EEG analysis require a complete set of EEG data matrix as input. Therefore, an accurate and reliable imputation approach for missing values is necessary to avoid incomplete data sets for analyses and further improve the usage of performance techniques. This research proposes a new method to automatically recover random consecutive missing data from real world EEG data based on Linear Dynamical System. The proposed method aims to capture the optimal patterns based on two main characteristics in the coevolving EEG time series: namely, (i) dynamics via discovering temporal evolving behaviors, and (ii) correlations by identifying the relationships between multiple brain signals. From these exploits, the proposed method successfully identifies a few hidden variables and discovers their dynamics to impute missing values. The proposed method offers a robust and scalable approach with linear computation time over the size of sequences. A comparative study has been performed to assess the effectiveness of the proposed method against interpolation and missing values via Singular Value Decomposition (MSVD). The experimental simulations demonstrate that the proposed method provides better reconstruction performance up to 49% and 67% improvements over MSVD and interpolation approaches, respectively.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.28 no.6
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• pp.672-681
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• 2004

Direct numerical simulation was carried out to study the vortical structures of the flow around a wall-mounted cube in a channel at Re=1,000 and Re=3,500 based on cubic height and bulk mean velocity. The cubic obstacle is situated in the entrance region of the channel flow where the boundary layers are developing. Upstream of the obstacle, steady and unsteady laminar horseshoe vortex systems are observed at Re=1,000 and Re=3,500, respectively; the near-wake flow is turbulent in both cases. The flow separates at each leading sharp edge of the cube, and subsequent vortex roll-up is noticed in the corresponding free-shear layer. The vortex shedding from the upper leading edge (upper vortices) and that from the two lateral leading edges (lateral vortices) are both quasi-periodic and their frequencies are computed. The upper and lateral vortices further develop into hairpin and Λ vortices, respectively. A series of instantaneous contours of the second invariant of velocity gradient tensor helps us identify spatial and temporal behaviors of the vortices in detail. The results indicate that the length and time scales of the vortical structures at Re=3,500 are much shorter than those at Re:1,000. Correlations between the upper and lateral vortices are also reported.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.8
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• pp.2866-2880
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• 2014

We propose a video denoising method based on Kalman filter to reduce the noise in video sequences. Firstly, with the strong spatiotemporal correlations of neighboring frames, motion estimation is performed on video frames consisting of previous denoised frames and current noisy frame based on intensity and structure tensor. The current noisy frame is processed in temporal domain by using motion estimation result as the parameter in the Kalman filter, while it is also processed in spatial domain using the Wiener filter. Finally, by weighting the denoised frames from the Kalman and the Wiener filtering, a satisfactory result can be obtained. Experimental results show that the performance of our proposed method is competitive when compared with state-of-the-art video denoising algorithms based on both peak signal-to-noise-ratio and structural similarity evaluations.

• Asian Journal of Atmospheric Environment
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• v.10 no.1
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• pp.22-31
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• 2016

Active fire products from Moderate Resolution Imaging Spectroradiometer (MODIS) satellite observation during the 16 years from 2000-2015 were analyzed to estimate spatial and temporal variations of wildland fires over East Asia (region of interest: $20^{\circ}N-55^{\circ}N$, $100^{\circ}E-150^{\circ}E$). GLOBCOVER 2009 land cover data were also used to investigate the trend in wildfire occurrence with respect to each land cover type. Statistical analysis showed that the highest number of wildland fires occurred in the evergreen and vegetation covered areas, and strong seasonal variations were found in these areas. Total numbers of fires were 283,683 and 202,543, respectively. In particular, the wildland fires in croplands occurred mainly during summer season and distinguishable increasing trends were found. The correlations between number of wildland fires and air pollutants, such as black carbon, organic matter, and carbon monoxide, were also calculated in order to investigate the intensity of the air pollution caused by the wildland fires. Positive correlation between total column carbon monoxide contents and the occurrence of wildland fire was found. In addition, this correlation was higher than the correlation between fire occurrence and black carbon or organic matter. These results indicate that a significant amount of carbon monoxide originated from the wildland fires and influenced the regional atmospheric environment in East Asia.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.4
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• pp.1975-1988
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• 2019

Short-term traffic flow prediction plays an important role in intelligent transportation systems (ITS) in areas such as transportation management, traffic control and guidance. For short-term traffic flow regression predictions, the main challenge stems from the non-stationary property of traffic flow data. In this paper, we design an ensemble cascading prediction framework based on extremely randomized trees (extra-trees) using a boosting technique called EET to predict the short-term traffic flow under non-stationary environments. Extra-trees is a tree-based ensemble method. It essentially consists of strongly randomizing both the attribute and cut-point choices while splitting a tree node. This mechanism reduces the variance of the model and is, therefore, more suitable for traffic flow regression prediction in non-stationary environments. Moreover, the extra-trees algorithm uses boosting ensemble technique averaging to improve the predictive accuracy and control overfitting. To the best of our knowledge, this is the first time that extra-trees have been used as fundamental building blocks in boosting committee machines. The proposed approach involves predicting 5 min in advance using real-time traffic flow data in the context of inherently considering temporal and spatial correlations. Experiments demonstrate that the proposed method achieves higher accuracy and lower variance and computational complexity when compared to the existing methods.

• Transactions of the Korean Society of Mechanical Engineers
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• v.19 no.6
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• pp.1510-1517
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• 1995

A theoretical method is described to simulate the propagation of turbulent premixed flames in a closed vessel. The objective is to develop and test an efficient technique to predict the propagation speed of flame as well as the geometric structure of the flame surfaces. Flame is advected by the statistically generated turbulent flow field and propagates as a wave by solving twodimensional Hamilton-Jacobi equation. In the simulation of the unburned gas flow field, following turbulence properties were satisfied: mean velocity field, turbulence intensities, spatial and temporal correlations of velocity fluctuations. It is assumed that these properties are not affected by the expansion of the burned gas region. Predictions were compared with existing experimental data for flames propagating in a closed vessel charged with hydrogen/air mixture with various turbulence intensities and Reynolds numbers. Comparisons were made in flame radius growth rate, rms flame radius fluctuations, and average perimeter and fractal dimensions of the flame boundaries. Two dimensional time dependent simulation resulted in correct trends of the measured flame data. The reasonable behavior and high efficiency proves the usefulness of this method in difficult problems of flame propagation such as in internal combustion engines.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.5
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• pp.1019-1024
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• 2005

MPEG-2 achieves high compression radio, by exploiting the temporal and spatial correlations in real image sequence, using the motion compensated prediction and the transform coding, respectively. However, as the image sequence is more highly compressed, the encoded bitstream becomes more vulnerable to transmission error over the noisy channels. Furthermore, er개rs in the headers are fatal to decoding processes, because the header parameters in the video coding standard include a lot of important information connected to the syntax elements, fables, and decoding process. In this paper, we propose a new error resilience method using LSB coding for header parameters in MPEG-2 coded video transmissions. The experimental results for football and susie video sequence demonstrate that the proposed error resilience method for header parameters in MPEG-2 bitstream has good performance.

• Journal of the Korean Solar Energy Society
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• v.33 no.5
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• pp.51-59
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• 2013

It is usual to evaluate the performance of the cool roof by measuring in-site rooftop temperature using thermal infra-red camera. The principal advantage of rooftop thermal infrared image acquired in oblique vantage point of super high-rise building as a remote sensor is to provide, in a cost-effective manner, area-wide information required for a scattered rooftop target with different colors, utilizing wide view angle and multi-temporal data coverage. This research idea was formulated by incorporating the concept of traditional remote sensing into rooftop temperature monitoring. Correlations between infrared image of super high-rise building and in-situ data were investigated to compare rooftop surface temperature for a total of four different rooftop locations. The results of the correlations analyses indicate that the rooftop surface temperature by the infrared images of super high-rise building alone could be explained yielding $R^2$ values of 0.951. The visible permanent record of the oblique thermal infra-red image was quite useful in better understanding the nature and extent of rooftop color that occurs in sampling points. This thermal infrared image acquired in oblique vantage point of super high-rise made it possible to identify area wide patterns of rooftop temperature change subject to many different colors, which cannot be acquired by traditional in-site field sampling. The infrared image of super high-rise building breaks down the usual concept of field sampling established as a conventional cool roof performance evaluation technique.

• Journal of Biomedical Engineering Research
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• v.39 no.3
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• pp.124-133
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• 2018

We tried to investigate the changes in cortical activities according to emotional valence states during watching video clips. We examined the neural basis of two emotional states (positive and negative) using spectral power analysis and brain functional connectivity analysis of cortical current density time-series reconstructed from high-density electroencephalograms (EEGs). Fifteen healthy participants viewed a series of thirty-two 2 min emotional video clips. Sixty-four channel EEGs were recorded. Distributed cortical sources were reconstructed using weighted minimum norm estimation. The temporal and spatial characteristics of spectral source powers showing significant differences between positive and negative emotion were examined. Also, correlations between gamma-band activities and affective valence ratings were determined. We observed the changes of cortical current density time-series according to emotional states modulated by video clip. Gamma-band activities showed significant difference between emotional states for thirty seconds at the middle and the latter half of the video clip, mainly in prefrontal area. It was also significantly anti-correlated with the self-ratings of emotional valence. In addition, the gamma-band activities in frontal and temporal areas were strongly phase-synchronized, more strongly for negative emotional states. Cortical activities in frontal and temporal areas showed high spectral power and inter-regional phase synchronization in gamma-band during negative emotional states. It is inferred that the higher amygdala activation induced by negative stimuli resulted in strong emotional effects and caused strong local and global synchronization of neural activities in gamma-band in frontal and temporal areas.