• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.7
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• pp.76-84
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• 2013

In the passive emitter localization using instantaneous TDOA (time difference of arrival) and FDOA (frequency difference of arrival) measurements, the estimation accuracy can be improved by collecting additional measurements. To achieve this goal, it is required to increase the number of the sensors. However, in electronic warfare environment, a large number of sensors cause the loss of military strength due to high probability of intercept. Also, the additional processes should be considered such as the data link and the clock synchronization between the sensors. Hence, in this paper, the passive localization of a stationary emitter is presented by using the successive TDOA and FDOA measurements from two moving sensors. In this case, since an independent pair of sensors is added in the data set at every instant of measurement, each pair of sensors does not share the common reference sensor. Therefore, the QCLS (quadratic correction least squares) methods cannot be applied, in which all pairs of sensor should include the common reference sensor. For this reason, a Gauss-Newton algorithm is adopted to solve the non-linear least square problem. In addition, to show the performance of the proposed method, we compare the RMSE (root mean square error) of the estimates with CRLB (Cramer-Rao lower bound) and derived the CEP (circular error probable) planes to analyze the expected estimation performance on the 2-dimensional space.

• Journal of the Korean Association of Geographic Information Studies
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• v.17 no.4
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• pp.10-27
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• 2014

HAZUS-MH is a GIS-based computer program that estimates potential losses from multi-hazard phenomena: earthquakes, floods and hurricanes. With respect to seismic disaster, characteristics of a hypothetical or actual earthquake are entered into HAZUS. Then HAZUS estimates the intensity of ground shaking and calculates the correspondent losses. In this study, HAZUS was used as a part of the preparations of the future seismic events at a coastal plant facility area. To reliably characterize the target facility area, many geotechnical characteristics data were synthesized from the existing site investigation reports. And the buildings and facilities were sorted by analyzing their material and structural characteristics. In particular, the study area was divided into 17 blocks taking into account the situation of both land development and facility distribution. The ground conditions of blocks were categorized according to the site classification scheme for earthquake-resistant design. Moreover, seismic fragility curves of a main facilities were derived based on the numerical modeling and were incorporated into the database in HAZUS. The results estimated in the study area using HAZUS showed various seismic damage and loss potentials depending on site conditions and structural categories. This case study verified the usefulness of the HAZUS for estimating earthquake losses in coastal facility areas.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1413-1425
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• 2023

The increasing frequency of wildfires due to climate change is causing extreme loss of life and property. They cause loss of vegetation and affect ecosystem changes depending on their intensity and occurrence. Ecosystem changes, in turn, affect wildfire occurrence, causing secondary damage. Thus, accurate estimation of the areas affected by wildfires is fundamental. Satellite remote sensing is used for forest fire detection because it can rapidly acquire topographic and meteorological information about the affected area after forest fires. In addition, deep learning algorithms such as convolutional neural networks (CNN) and transformer models show high performance for more accurate monitoring of fire-burnt regions. To date, the application of deep learning models has been limited, and there is a scarcity of reports providing quantitative performance evaluations for practical field utilization. Hence, this study emphasizes a comparative analysis, exploring performance enhancements achieved through both model selection and data design. This study examined deep learning models for detecting wildfire-damaged areas using Landsat 8 satellite images in California. Also, we conducted a comprehensive comparison and analysis of the detection performance of multiple models, such as U-Net and High-Resolution Network-Object Contextual Representation (HRNet-OCR). Wildfire-related spectral indices such as normalized difference vegetation index (NDVI) and normalized burn ratio (NBR) were used as input channels for the deep learning models to reflect the degree of vegetation cover and surface moisture content. As a result, the mean intersection over union (mIoU) was 0.831 for U-Net and 0.848 for HRNet-OCR, showing high segmentation performance. The inclusion of spectral indices alongside the base wavelength bands resulted in increased metric values for all combinations, affirming that the augmentation of input data with spectral indices contributes to the refinement of pixels. This study can be applied to other satellite images to build a recovery strategy for fire-burnt areas.

• Journal of Korea Water Resources Association
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• v.36 no.6
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• pp.1059-1068
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• 2003

Geographic Information System (GIS) combined with Universal Soil Loss Equation (USLE) was used to estimate the soil erosion of Asan Bay experiment watershed in Korea. Spatial data for each USLE factors were obtained from the Landsat-5 TM remote sensing images and 1/25,000 scale digital contour maps. Sediment yield to Asan Bay was estimated by the sediment delivery ratio and trap efficiency. The estimated sediment yield was compared with observed on the Asan and Sapgyo estuary sub-watershed within Asan Bay experimental watershed for the period from 1981 to 2000. The calculated total annual sediment yields from Asan and Sapgyo estuary sub-watershed to Asan Bay were 5,665tonnes/yr and 6,766tonnes/yr, respectively. The measured sediment yields were 12,937tonnes/yr and 12,395tonnes/yr, respectively on an average.

• The KIPS Transactions:PartB
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• v.17B no.5
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• pp.355-362
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• 2010

Face tracking is to estimate the motion of a non-rigid face together with a rigid head in 3D, and plays important roles in higher levels such as face/facial expression/emotion recognition. In this paper, we propose an AAM-based face tracking algorithm. AAM has been widely used to segment and track deformable objects, but there are still many difficulties. Particularly, it often tends to diverge or converge into local minima when a target object is self-occluded, partially or completely occluded. To address this problem, we utilize the scale invariant feature transform (SIFT). SIFT is an effective method for self and partial occlusion because it is able to find correspondence between feature points under partial loss. And it enables an AAM to continue to track without re-initialization in complete occlusions thanks to the good performance of global matching. We also register and use the SIFT features extracted from multi-view face images during tracking to effectively track a face across large pose changes. Our proposed algorithm is validated by comparing other algorithms under the above 3 kinds of occlusions.

• Journal of Korean Society on Water Environment
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• v.32 no.1
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• pp.89-97
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• 2016

Digital Elevation Models (DEMs) have been used to represent the effects of topography on soil erosion. A DEM of 30 m resolution is frequently used in hydrology and soil erosion studies because the National Water Management Information System (WAMIS) provides a 30 m resolution DEM at national scale on its web site. However, the Ministry of Environment recommends the use of a DEM with 10 m resolution for evaluation of soil erosion due to the fact that soil erosion estimation is to some degree affected by the spatial resolution of DEM. In this regard, a DEM with 5 m resolution was resampled for 10 × 10 m, 20 × 20 m, 30 × 30 m, 50 × 50 m, 70 × 70 m, and 100 × 100 m resolutions, respectively. USLE LS factors and soil erosion values were evaluated using these datasets. Use of a DEM with at least 30 m resolution provided reasonable LS factors and soil erosion values at a watershed.

• The Journal of the Korea institute of electronic communication sciences
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• v.5 no.1
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• pp.23-30
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• 2010

The H.264/AVC is increasingly used in broadcast video applications such as Internet Protocol television (IPTV), digital multimedia broadcasting (DMB) because of high compression performance. But the H.264/AVC coded video can be delivered to the widespread end-user equipment for MPEG-2 after transcoding between this video standards. This paper suggests a new transcoding algorithm for H.264/AVC to MPEG-2 transcoder that uses motion vector clustering in order to reduce the complexity without loss of video quality. The proposed method is exploiting the motion information gathered during h.264 decoding stage. To reduce the search space for the MPEG-2 motion estimation, the predictive motion vector is selected with a least distortion of the candidated motion vectors. These candidate motion vectors are considering the correlation of direction and distance of motion vectors of variable blocks in H.264/AVC. And then the best predictive motion vector is refined with full-search in ${\pm}2$ pixel search area. Compared with a cascaded decoder-encoder, the proposed transcoder achieves computational complexity savings up to 64% with a similar PSNR at the constant bitrate(CBR).

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.38 no.11
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• pp.30-40
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• 2001

In this paper, we propose a dynamic slot allocation algorithm for efficient transmission of VBR services in wireless ATM networks. The proposed algorithm is based on a hybrid dynamic parameter(DP) control which combines the strength of in-band control and out-of-band control by considering the variation characteristics of buffer length in distributed mobile terminals. This algorithm consists of four sub-algorithms: dynamic parameter determination algorithm, dynamic parameter transmission algorithm, estimation algorithm of the number of request slots, and prorated-allocation algorithm. As the proposed allocation algorithm based on the hybrid DP control scheme can offer nearly precise MAC level estimations of the requirements for each VBR, the algorithm makes it possible to obtain ideal allocation efficiency. The allocation efficiency of the algorithm is shown by numerical analysis. Simulation results show that the proposed algorithm has better performance than conventional schemes in terms of allocation efficiency, delay and cell loss ratio under VBR traffic.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.29 no.9 s.240
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• pp.1235-1242
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• 2005

A district heating(DH) system supplies environmentally-friend heat and is appropriate for reduction of energy consumption and/or air pollutions. The DH transmission pipe, composed of supply and return pipes, has been used to transmit the heat and prevent heat loss during transportation. The two types of pipes are operated at a temperature of $75\~115^{\circ}C\;and\;40\~65^{\circ}C$, respectively, with an operating pressure of less than 1.568MPa. The objectives of this paper are to systematize data processing of transition temperature and investigate its effects on fatigue life of DH pipes. For the sake of this, about 5 millions temperature data were measured during one year at ten locations, and then available fatigue lift estimation schemes were examined and applied to quantify the specific thermal fatigue life of each pipe. As a result, a relational database management system as well as reliable fatigue lift evaluation procedures is established for Korean DH pipes. Also, since the prototypal evaluation results satisfied both cycle-based and stress-based fatigue criteria, those can be used as useful information in the future fer optimal design, operation and energy saving via setting of efficient condition and stabilization of water temperature.

• Journal of The Korean Society of Agricultural Engineers
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• v.52 no.3
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• pp.39-45
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• 2010

Quantification of carbon absorption and understanding the human induced land use changes (LUC) forms one of the major study with respect to global climatic changes. An attempt study has been made to quantify the carbon absorption by LUC through remote sensing technology. The Landsat imagery four time periods was classified with the hybrid classification method in order to quantify carbon absorption by LUC. Thereafter, for estimating the amount of carbon absorption, the stand biomass of forest was estimated with the total weight, which was the sum of individual tree weight. Individual tree volumes could be estimated with the crown width extracted from digital forest cover type map. In particular, the carbon conversion index and the ratio of the $CO_2$ molecular weight to the C atomic weight, reported in the IPCC guideline, was used to convert the stand biomass into the amount of carbon absorption. Total carbon absorption has been modeled by taking areal estimates of LUC of four time periods and carbon factors for land use type and standing biomass. Results of this study, through LUC suggests that over a period of construction, 7.10 % of forest and 9.43 % of barren were converted into urban. In the conversion process, there has been a loss of 6.66 t/ha/y (7.94 %) of carbon absorption from the study area.