• Journal of KIISE:Software and Applications
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• v.31 no.11
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• pp.1534-1542
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• 2004

A novel vision-based scheme of extracting real-time traffic information parameters is presented. The method is based on a region classification followed by a spatio-temporal image analysis. The detection region images for each traffic lane are classified into one of the three categories: the road, the vehicle, and the shadow, using statistical and structural features. Misclassification in a frame is corrected by using temporally correlated features of vehicles in the spatio-temporal image. Since only local images of detection regions are processed, the real-time operation of more than 30 frames per second is realized without using dedicated parallel processors, while ensuring detection performance robust to the variation of weather conditions, shadows, and traffic load.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.1
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• pp.360-373
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• 2017

This paper presents a novel digital video steganalysis scheme against the spatial domain video steganography technology based on a spatial temporal detector (ST_D) that considers both spatial and temporal redundancies of the video sequences simultaneously. Three descriptors are constructed on XY, XT and YT planes respectively to depict the spatial and temporal relationship between the current pixel and its adjacent pixels. Considering the impact of local motion intensity and texture complexity on the histogram distribution of three descriptors, each frame is segmented into non-overlapped blocks that are $8{\times}8$ in size for motion and texture analysis. Subsequently, texture and motion factors are introduced to provide reasonable weights for histograms of the three descriptors of each block. After further weighted modulation, the statistics of the histograms of the three descriptors are concatenated into a single value to build the global description of ST_D. The experimental results demonstrate the great advantage of our features relative to those of the rich model (RM), the subtractive pixel adjacency model (SPAM) and subtractive prediction error adjacency matrix (SPEAM), especially for compressed videos, which constitute most Internet videos.

• 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.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.9 no.4
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• pp.945-951
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• 2008

In this paper, a new high performance data cache scheme that improves exploitation of both the spatial and temporal locality is proposed. The proposed data cache consists of a hardware prefetch unit and two sub-caches such as a direct-mapped (DM) cache with a large block size and a fully associative buffer with a small block size. Spatial locality is exploited by fetching and storing large blocks into a direct mapped cache, and is enhanced by prefetching a neighboring block when a DM cache hit occurs. Temporal locality is exploited by storing small blocks from the DM cache in the fully associative buffer according to their activity in the DM cache when they are replaced. Experimental results on Spec2000 programs show that the proposed scheme can reduce the average miss ratio by $12.53%\sim23.62%$ and the AMAT by $14.67%\sim18.60%$ compared to the previous schemes such as direct mapped cache, 4-way set associative cache and SMI(selective mode intelligent) cache[8].

• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.10
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• pp.60-68
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• 2012

Current wireless sensor networks are considered to support more complex operations ranging from military to health care which require energy-efficient and timely transmission of large amounts of data. In this paper, we propose an adaptive temporal suppression algorithm which exploits a temporal correlation among sensor readings. The proposed scheme can significantly reduce the number of transmitted sensor readings by sensor node, and consequently decrease the energy consumption and delay. Instead of transmitting all sensor readings from sensor node to sink node, the proposed scheme is to selectively transmit some elements of sensor readings using the adaptive temporal suppression, and the sink node is able to reconstruct the original data without deteriorating data quality by linear interpolation. In our proposed scheme, sensing data stream at sensor node is divided into many small sensing windows and the transmission ratio in each window is decided by the window complexity. It is defined as the number of a fluctuation point which has greater absolute gradient than threshold value. We have been able to achieve up about 90% communication reduction while maintaining a minimal distortion ratio 6.5% in 3 samples among 4 ones.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.5
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• pp.127-135
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• 2010

In motion adaptive temporal noise reduction filtering used for reducing video noises, the strength of motion adaptive temporal filtering should be carefully controlled according to temporal movement. This paper presents a motion adaptive temporal filtering scheme based on least-square training. Each pixel is classified to a specific class code according to temporal movement, and then, an iterative least-square training method is applied for each class code to find optimal filtering coefficients. The iterative least-square training is an off-line procedure, and the trained filter coefficients are stored in a lookup table (LUT). In actual noise reduction filtering operation, after each pixel is classified by temporal movement, simple filtering operation is applied with the filter coefficients stored in the LUT according to the class code. Experiment results show that the proposed method efficiently reduces video noises without introducing blurring.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.1B
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• pp.13-20
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• 2011

The spatio-temporal pattern in precipitation is a significant element in defining characteristics of precipitation. In this study, a new scheme on regionalization utilizing temporal information was introduced on the basis of existing approaches that is mainly based on simple moments of data and geographical information. Given the identified spatio-temporal pattern, this study was extended to characterize regional pattern of annual maximum rainfall over Korea. We have used circular statistics to characterize the temporal distribution on the precipitation, and the circular statistics allow us to effectively assess changes in timing of the extreme rainfall in detail. In this study, a modified K-means method was incorporated with derived temporal characteristics of extreme rainfall in order to better characterize hydrologic pattern for regional frequency analysis. The extreme rainfall was reasonably separated into five categories that considered most attributes in both quantitative and temporal changes in extremes. The results showed that the proposed approach is a promising approach for regionalization in term of physical understanding of extreme rainfall.

• IEMEK Journal of Embedded Systems and Applications
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• v.9 no.2
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• pp.61-66
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• 2014

Temporal disappearance of weather phenomena effect is frequently observed in flight simulator when large volume of terrain data are processed. This problem was solved by employing culling scheme at static ratio in the existing scheme. However, since this approach causes the irregular rendering speed according to volume of data, it is necessary to develop a new culling scheme to maintain steady rendering speed by adjusting the culling ratio dynamically. In this paper, we propose a new culling scheme to make use of distance of the visibility to determine culling ratio depending on volume of terrain data. The experimental results show that rendering speed is preserved by the proposed scheme without affecting the visuality at rendering the scene and weather phenomena effect together.

• 한국방재학회:학술대회논문집
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• 2008.02a
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• pp.233-236
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• 2008

To analyze the saline intrusion in the place, such as an estuary, the three-dimensional numerical model is developed. In this study, the advection terms of the governing equations are discretized by upwind scheme. By using an explicit scheme for the longitudinal direction and an implicit scheme for the vertical direction, the numerical model is free from the restriction of temporal step size caused by a relatively small grid ratio. The equation of state is used to consider the density, and the scalar transport equation for salinity is employed the third order TVD to scheme to prevent unphysical oscillation near discontinuity. In order to verify saline intrusion, the numerical model is conducted to compare the previous model in the lock exchange. The present model generally show a good agreement with the previous one.

• Journal of applied mathematics & informatics
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• v.39 no.5_6
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• pp.655-676
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• 2021

A parameter uniform numerical scheme is proposed for solving singularly perturbed parabolic partial differential-difference convection-diffusion equations with a small delay and advance parameters in reaction terms and spatial variable. Taylor's series expansion is applied to approximate problems with the delay and advance terms. The resulting singularly perturbed parabolic convection-diffusion equation is solved by utilizing the implicit Euler method for the temporal discretization and finite difference method for the spatial discretization on a uniform mesh. The proposed numerical scheme is shown to be an ε-uniformly convergent accurate of the first order in time and second-order in space directions. The efficiency of the scheme is proved by some numerical experiments and by comparing the results with other results. It has been found that the proposed numerical scheme gives a more accurate approximate solution than some available numerical methods in the literature.