• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.05a
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• pp.441-443
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• 2010

Techniques for processing continuous queries are required to developing the various types of application services in ubiquitous environment where the real-time data acquisition from a lot of sensors, analysis, and processing are required. In the previous works of the continuous queries, they have represented all of the continuous queries as the interval queries or region queries, and proposed some methods for processing theses queries. The types of continuous queries, however, are very various, and could be presented by combining the attribute conditions, spatial conditions, and temporal conditions. In this paper, I have classify the types of continuous queries, and have proposed the continuous query model which could be presented by combining those conditions. The contributions of this paper include that it proposes the query model representing the continuous queries and suggests future research directions.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.1
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• pp.33-46
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• 1996

Inthis paper, we investigate the compatible coding technique, which receives much interest ever since the introduction of HDTV. First, attempts have been made to analyze the theoretical transform coding gains for various hierarchical decomposition techniques, namely subband, pyramid and DCT-based decomposition techniques. It is shown that the spatical domain techniques proide higher transform coding gains than the DCT-based coding technique. Secondly, we compare the performance of these spatial domain techniques, in terms of the PSNR versus various rate allocations to each layer. Based on these analyses, it is believed that the pyramid decomposition is more appropriate for the compatible coding. Also in this paper, we propose a hybrid prediction pyramid coding technique, by combining the spatio-temporal prediction in MPEG-2[3] and the adaptive MC(Motion Compensation)[1]. In the proposed coding technigue, we also employ an adaptive DCT coefficient scanning technique to exploit the direction information of the 2nd-layer signal. Through computer simulations, the proposed hybrid prediction with adaptive scanning technuque shows the PSNR improvement, by about 0.46-1.78dB at low 1st-layer rate(about 0.1bpp) over the adaptive MC[1], and by about 0.33-0.63dB at high 1st-layer rate (about 0.32-0.43bpp) over the spatio-temporal prediction[3].

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.7
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• pp.852-857
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• 2005

This paper discusses a human body extraction method for intelligent robot system. The intelligent robot system requires more robust silhouette extraction method because it has internal vibration and low resolution. The new hybrid silhouette extraction method is proposed to overcome this constrained environment. The temporal and gradient information is combined as hybrid silhouette. The motion region model is used to adjust combining parameters in hybrid silhouette. Finally, the experimental results show the superiority of the proposed method.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2004.03a
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• pp.173-187
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• 2004

The horizon of using GIS technologies can be expanded to analyzing spatial changes by time in reality. Traditional GIS technologies usually use maps for a snapshot aspect of spatial information. Limitations of the present GIS technologies in terms of dealing with spatial changes require more solutions for collecting, processing and analyzing spatial data with time. Traditional GIS technologies include Temporal GIS, Real-time GIS and Virtual GIS respectively but those are not capable enough to represent spatial change in an overall perspective. By reflecting dynamic changes the current GIS technologies can be more useful and valuable than before. This study assumes that '4D GIS', a composite of temporal, realtime and virtual GIS technology, will open a new horizon for the future sophisticated GIS applications. By identifying a technology application model for 4D GIS the new concept of 4D GIS can be clarified. The model is established by combining dynamic spatial information types and applicable 4D GIS technologies, which are identified from the most current 4D application and research efforts. The technology application model for 4D GIS can be expected to contribute to efficient in planning for 4D GIS technology development in the future.he future.

• Proceedings of the KSME Conference
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• 2007.05b
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• pp.2935-2940
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• 2007

To diagnose circulatory diseases in the viewpoint of hemodynamics, we need to get quantitative hemodynamic information of blood flows related with the vascular diseases with high spatial resolution of tens micrometer and high temporal resolution in the order of millisecond. For investigating in-vivo hemodynamic phenomena, a new diagnosing technique combining medical radiography and PIV method was newly proposed and developed. This angiographic PIV technique consists of a medical X-ray tube, an X-ray CCD camera, a shutter module for double pulses of X-ray, and a synchronizer. The feasibility of the angiographic PIV technique was tested and quantitative flow velocity field distribution of a flow inside an opaque conduit was acquired by the developed system. It can be used for measuring flow phenomena of nontransparent fluids inside opaque conduits.

• Journal of Korea Multimedia Society
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• v.23 no.8
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• pp.927-939
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• 2020

Gait recognition can identify people's identity from a long distance, which is very important for improving the intelligence of the monitoring system. Among many human features, gait features have the advantages of being remotely available, robust, and secure. Traditional gait feature extraction, affected by the development of behavior recognition, can only rely on manual feature extraction, which cannot meet the needs of fine gait recognition. The emergence of deep convolutional neural networks has made researchers get rid of complex feature design engineering, and can automatically learn available features through data, which has been widely used. In this paper,conduct feature metric learning in the three-dimensional space by combining the three-dimensional convolution features of the gait sequence and the Siamese structure. This method can capture the information of spatial dimension and time dimension from the continuous periodic gait sequence, and further improve the accuracy and practicability of gait recognition.

• Journal of Environmental Science International
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• v.22 no.3
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• pp.303-308
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• 2013

This paper proposed a new method for estimating missing values in time series rainfall data. The proposed method integrated the two most widely used estimation methods, general linear model(GLM) and ordinary kriging(OK), by taking a weighted average of covariance matrices derived from each of the two methods. The proposed method was cross-validated using daily rainfall data at thirteen rain gauges in the Hyeong-san River basin. The goodness-of-fit of the proposed method was higher than those of GLM and OK, which can be attributed to the weighting algorithm that was designed to minimize errors caused by violations of assumptions of the two existing methods. This result suggests that the proposed method is more accurate in missing values in time series rainfall data, especially in a region where the assumptions of existing methods are not met, i.e., rainfall varies by season and topography is heterogeneous.

• 한국전산유체공학회:학술대회논문집
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• 2008.03b
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• pp.683-686
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• 2008

To diagnose vascular diseases from the viewpoint of hemodynamics, detailed quantitative hemodynamic information of related blood flows with a high spatial resolution of tens micrometer and a high temporal resolution in the order of millisecond were required. For investigating the hemodynamic phenomena of vascular circulatory diseases, a new diagnosing technique combining a medical radiography and PIV method was newly developed. This technique consisted of a medical X-ray tube, an X-ray CCD camera, a shutter module for double pulse-type X-ray source, and a synchronizer. Through several preliminary tests, the feasibility of the angiographic PIV technique was verified. For in-vivo measurements to real blood flows, we developed tracer microcapsules which were optimized to this system by encapsulating a contrast material of iodine with a matrix material of PVA (polyvinylpyrrolidone). In near future, the angiographic PIV technique would be useful for diagnosing hemodynamic phenomena of vascular diseases and for their early detection.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.11
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• pp.3479-3492
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• 2022

Longitudinal quantification of brain changes due to development, aging or disease plays an important role in the filed of personalized-medicine applications. However, due to the temporal variability in shape and different imaging equipment and parameters, estimating anatomical changes in longitudinal studies is significantly challenging. In this paper, a longitudinal Magnetic Resonance(MR) brain image segmentation algorithm proposed by combining intensity information and anisotropic smoothness term which contain a spatial smoothness constraint and longitudinal consistent constraint into a variational framework. The minimization of the proposed energy functional is strictly and effectively derived from a fast optimization algorithm. A large number of experimental results show that the proposed method can guarantee segmentation accuracy and longitudinal consistency in both simulated and real longitudinal MR brain images for analysis of anatomical changes over time.

• Journal of Wetlands Research
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• v.12 no.1
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• pp.51-61
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• 2010

Changes in climate have largely increased concentrated heavy rainfall, which in turn is causing enormous damages to humans and properties. Therefore, it is important to understand the spatial-temporal features of rainfall. In this study, RADAR rainfall was used to calculate gridded areal rainfall which reflects the spatial-temporal variability. In addition, Kalman-filter method, a stochastical technique, was used to combine ground rainfall network with RADAR rainfall network to calculate areal rainfall. Thiessen polygon method, Inverse distance weighting method, and Kriging method were used for calculating areal rainfall, and the calculated data was compared with adjusted areal RADAR rainfall measured using the Kalman-filter method. The result showed that RADAR rainfall adjusted with Kalman-filter method well-reproduced the distribution of raw RADAR rainfall which has a similar spatial distribution as the actual rainfall distribution. The adjusted RADAR rainfall also showed a similar rainfall volume as the volume shown in rain gauge data. Anseong-Cheon basin was used as a study area and the RADAR rainfall adjusted with Kalman-filter method was applied in $Vflo^{TM}$ model, a physical-based distributed model, and ModClark model, a semi-distributed model. As a result, $Vflo^{TM}$ model simulated peak time and peak value similar to that of observed hydrograph. ModClark model showed good results for total runoff volume. However, for verifying the parameter, $Vflo^{TM}$ model showed better reproduction of observed hydrograph than ModClark model. These results confirmed that flood runoff simulation is applicable in domestic settings(in South Korea) if highly accurate areal rainfall is calculated by combining gauge rainfall and RADAR rainfall data and the simulation is performed in link to the distributed hydrological model.