• 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 Korean Data and Information Science Society
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• v.13 no.2
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• pp.261-270
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• 2002

Recently, the demand of the Intelligent Transportation System(ITS) has been increased to a large extent, and a real-time traffic information service based on the internet system became very important. When ITS companies carry out real-time traffic services, they find some traffic data missing, and use the conventional method of reconstructing missing values by calculating average time trend. However, the method is found unsatisfactory, so that we develop a new method based the spatial and spatial-temporal models. A cross-validation technique shows that the spatial-temporal model outperforms the others.

• ETRI Journal
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• v.32 no.3
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• pp.490-492
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• 2010

This letter proposes a robust feature extraction method using a spatially normalized mean for temporal ordinal measurement. Before computing a rank matrix from the mean values of non-overlapped blocks, each block mean is normalized so that it obeys the invariance property against linear additive and subtractive noise effects and is insensitive against multiplied and divided noise effects. Then, the temporal ordinal measures of spatially normalized mean values are computed for the feature matching. The performance of the proposed method showed about 95% accuracy in both precision and recall rates on various distortion environments, which represents the 2.7% higher performance on average compared to the temporal ordinal measurement.

• Journal of Broadcast Engineering
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• v.19 no.2
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• pp.257-267
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• 2014

Distributed compressive video sensing (DCVS) is a low cost sampling paradigm for video coding based on the compressive sensing and the distributed video coding. In this paper, we propose using a skip-mode coding in DCVS under the assumption that in case of high temporal correlation, temporal interpolation can guarantee sufficiently good quality of nonkey frame, therefore no need to transmit measurement data in such a nonkey frame. Furthermore, we extend it to use a hierarchical structure for better temporal interpolation. Simulation results show that the proposed skip-mode coding can save the average subrate of whole video sequence while the PSNR is reduced only slightly. In addition, by using the proposed scheme, the computational complexity is also highly decreased at decoder on average by 43.75% for video sequences that have strong temporal correlation.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.499-499
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• 2002

The goal of this study is to apply and evaluate the precipitation outflow in river basin using satellite data and GIS for proposing the efficient watershed management method. Not only precipitation outflow data but also various spatial data such as digital map, soil map, geologic map and multi-temporal TM images were used. Using landcover classification result and soil map were applied to estimate the average CN. The CN value of 63.37 by SCS method was produced in AMC-2 condition otherwise the result of direct estimation with observation method was 63 CN value. The relative error of two results was 0.59%. It can be possible to apply the satellite data for precipitation outflow analysis. For more accurate and credible analysis of this, the more multi-temporal satellite and real observation data will be needed.

• Journal of KIISE:Databases
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• v.28 no.3
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• pp.384-394
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• 2001

In this paper, we propose AST-AET(Average valid Start Time-Average valid End Time) data migration strategy based on the storage structure where temporal data is divided into a past segment, a current segment, and a future segment. We define AST and AET which are used in AST-AET data migration strategy and also define entity versions to be stored in each segment. We describe methods to compute AST and AET, and processes to search entity versions for migration and move them. We compare average response times for user queries between AST-AET data migration strategy and the existing LST-GET(Least valid Start Time-Greatest valid End Time) data migration strategy. The experimental results show that, when there are no LLTs(Long Lived Tuples), there is little difference in performance between the two migration strategies because the size of a current segment is nearly equal. However, when there are LLTs, the average response time of AST-AET data migration strategy is smaller than that of LST-GET data migration strategy because the size of a current segment of LST-GET data migration strategy becomes larger. In addition, when we change average interarrival times of temporal queries, generally the average response time of AST-AET data migration strategy is smaller than that of LST-GET data migration strategy.

• Journal of Communications and Networks
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• v.5 no.2
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• pp.104-115
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• 2003

It is well known that Multiple Input Multiple Output (MIMO) systems offer the promise of achieving very high spectrum efficiencies (many tens of bit/s/Hz) in a mobile environment. The gains in MIMO capacity are sensitive to the presence of spatial and temporal correlation introduced by the radio environment. In this paper, we examine how MIMO capacity is influenced by a number of factors e.g., a) temporal correlation b) various combinations of low/high spatial correlations at either end, c) combined spatial and temporal correlations. In all cases, we compare the channel capacity that would be achievable under independent fading. We investigate the behaviour of "capacity fades," examine how often the capacity experiences the fades, develop a method to determine level crossing rates and average fade durations and relate these to antenna numbers. We also evaluate the influence of channel correlation on the capacity autocorrelation and assess the fit of a Gaussian random process to the temporal capacity sequence. Finally we note that the particular spatial correlation structure of the MIMO channel is influenced by a large number of factors. For simplicity, it is desirable to use a single overall correlation measure which parameterizes the effect of correlation on capacity. We verify this single parameter concept by simulating a large number of different spatially correlated channels.

• Journal of KIISE:Software and Applications
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• v.29 no.9
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• pp.631-644
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• 2002

In this paper efficient algorithms for content-based video retrieval using motion information are proposed, including temporal scale-invariant retrieval and temporal scale-absolute retrieval. In temporal scale-invariant video retrieval, the distance transformation is performed on each trail image in database. Then, from a given que교 trail the pixel values along the query trail are added in each distance image to compute the average distance between the trails of query image and database image, since the intensity of each pixel in distance image represents the distance from that pixel to the nearest edge pixel. For temporal scale-absolute retrieval, a new coding scheme referred to as Motion Retrieval Code is proposed. This code is designed to represent object motions in the human visual sense so that the retrieval performance can be improved. The proposed coding scheme can also achieve a fast matching, since the similarity between two motion vectors can be computed by simple bit operations. The efficiencies of the proposed methods are shown by experimental results.

• Korean Journal of Remote Sensing
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• v.32 no.1
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• pp.25-38
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• 2016

With the increasing need for high temporal resolution satellite imagery for monitoring land surfaces, this study evaluated the temporal resolution of the NDVI composites from Geostationary Ocean Color Imager (GOCI) data. The GOCI is the first geostationary satellite sensor designed to provide continuous images over a $2,500{\times}2,500km^2$ area of the northeast Asian region with relatively high spatial resolution of 500 m. We used total 2,944 hourly images of the GOCI level 1B radiance data obtained during the one-year period from April 2011 to March 2012. A daily NDVI composite was produced by maximum value compositing of eight hourly images captured during day-time. Further NDVI composites were created with different compositing periods ranging from two to five days. The cloud coverage of each composite was estimated by the cloud detection method developed in study and then compared with the Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua cloud product and 16-day NDVI composite. The GOCI NDVI composites showed much higher temporal resolution with less cloud coverage than the MODIS NDVI products. The average of cloud coverage for the five-day GOCI composites during the one year was only 2.5%, which is a significant improvement compared to the 8.9%~19.3% cloud coverage in the MODIS 16-day NDVI composites.

• Journal of Positioning, Navigation, and Timing
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• v.2 no.2
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• pp.109-114
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• 2013

The vulnerability of GPS to interference signals was reported in the early 2000s, and an eLORAN system has been suggested as a backup navigation system for replacing the existing GPS. Thus, relevant studies have been carried out in the United States, Europe, Korea, etc., and especially, in Korea, the research and development is being conducted for the FOC of the eLORAN system by 2018. The required performance of the eLORAN system is to meet the HEA performance, and to achieve this, it is essential to perform ASF correction based on a dLORAN system. ASF can be divided into temporal ASF, nominal ASF, and spatial ASF. Spatial ASF is the variation due to spatial characteristics, and is stored in an eLORAN receiver in the form of a premeasured map. Temporal ASF is the variations due to temporal characteristics, and are transmitted from a dLORAN site to a receiver via LDC. Unlike nominal ASF that is obtained by long-term measurement (over 1 year), temporal ASF changes in a short period of time, and ideally, real-time correction needs to be performed. However, it is difficult to perform real-time correction due to the limit of the transmission rate of the LDC for transmitting correction values. In this paper, to determine temporal ASF correction frequency that shows satisfactory performance within the range of the limit of data transmission rates, relative variations of temporal ASF in summer and winter were measured, and the stability of correction values was analyzed using the average of temporal ASF for a certain period.