• Spatial Information Research
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• v.16 no.4
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• pp.411-420
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• 2008

To provide technological foundation for periodic and real-time land monitoring over the Korean peninsula where the land cover changes are prevailing, the Land Monitoring Research project was initiated as one of five core projects within the Intelligent National Land Information Technology Innovation Project operated by the Korean Land Spatialization Group (KLSG). This four year project can be categorized into two research themes with nine sub-projects. The first research theme is dealing with the real-time data acquisition from aerial platform and in-situ measurements by ubiquitous sensor network (USN), ground video camera, and automobile-based data collection systems. The second research theme is mainly focused on the development of application systems that can be directly utilized in several public organizations dealing with land monitoring over the nation. The Moderate Resolution Imaging Spectroradiometer (MODIS)-based land monitoring system that is currently under development is one of such application systems designed to provide necessary information regarding the status and condition of land cover in near real-time.

• Korean Journal of Remote Sensing
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• v.35 no.1
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• pp.29-37
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• 2019

Synthetic Aperture Radar (SAR) observations are powerful tools to monitor surface's displacement very accurately, induced by earthquake, volcano, ground subsidence, glacier movement, etc. Especially, radar interferometry (InSAR) which utilizes phase information related to distance from sensor to target, can generate displacement map in line-of-sight direction with accuracy of a few cm or mm. Due to decorrelation effect, however, degradation of coherence in the InSAR application often prohibit from construction of differential interferogram. Offset tracking method is an alternative approach to make a two-dimensional displacement map using intensity information instead of the phase. However, there is limitation in that the offset tracking requires very intensive computation power and time. In this paper, efficiency of parallel computing has been investigated using high performance computer for estimation of glacier velocity. Two TanDEM-X SAR observations which were acquired on September 15, 2013 and September 26, 2013 over the Narsap Sermia in Southwestern Greenland were collected. Atotal of 56 of 2.4 GHz Intel Xeon processors(28 physical processors with hyperthreading) by operating with linux environment were utilized. The Gamma software was used for application of offset tracking by adjustment of the number of processors for the OpenMP parallel computing. The processing times of the offset tracking at the 256 by 256 pixels of window patch size at single and 56 cores are; 26,344 sec and 2,055 sec, respectively. It is impressive that the processing time could be reduced significantly about thirteen times (12.81) at the 56 cores usage. However, the parallel computing using all the processors prevent other background operations or functions. Except the offset tracking processing, optimum number of processors need to be evaluated for computing efficiency.

• Journal of the Korean Society of Hazard Mitigation
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• v.8 no.6
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• pp.1-5
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• 2008

As bare Fiber Bragg Grating (FBG) sensors are very fragile, bare FBG without encapsulation is not properly applied in practical infrastructures directly due to the harsh environment in practical engineering. Steel sleeve packaged FBG strain sensor is widely used in civil engineering. Since FBG senses both strain and temperature simultaneously, for accurate measurement of strain, temperature compensation for FBG strain sensors is indispensable. In this paper, based on the FBG's strain and temperature sensing principles, the temperature compensation techniques for steel sleeve packaged FBG sensors are brought forward. And the experiment of concrete early-age shrinkage monitoring by dual FBG sensors is carried out to test the feasibility of the temperature compensation technique.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.251-253
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• 2003

Landsat images were globally used to monitoring the Earth's. But it is not positively applied to a field of environment such as coastal environment, heat island effect and drought condition and so on. Until recently, Information about a ecology natural environment came to do by direct investigation. But Information about a ecology·natural environment of wide area were quickly getting possible with the progress of remote sensing technique. Specially, the up-to-date characteristic information about an ecology·natural environment as the basic intelligence for a country development activity are very important. So, it applies the satellite images that the periodic observation of data is possible. In this study, We planned the function which is possible helping the renewal of an ecology·natural environmental information using Landsat imagery. Also planned the DB suitable for these purpose. For application of thermal infrared band images we developed the function that extracts an isothermal line. It used the thermal infrared band images and it grasped a temperature distribution. The result is useful in analysis of the city heat island effectiveness.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.11B
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• pp.1169-1177
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• 2009

This paper presents an energy efficient MAC protocol for delay-sensitive data transmission over wireless sensor network. In general, energy consumption and delay depend on Channel Monitoring Interval and data sensing period at each sensor node. Based on this fact, we propose a new preamble structure to effectively advertise Channel Monitoring Interval and avoid the overhearing problem. In order to pursue an effective tradeoff between energy consumption and delay, we also develop a Channel Monitoring Interval determining algorithm that searches for a sub-optimal solution with a low computational complexity. Finally, experimental results are provided to compare the proposed MAC protocol with existing sensor MAC protocols.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.28 no.4
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• pp.249-251
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• 2015

In this study, the application of biosensor having a large surface area for more effective and AAO (anomic aluminium oxide) template in order to gain concentration and voltage of anodizing process morphology changes to the control of experiments were conducted. The biosensor surface may increase the response characteristics by having a large surface area. So the entrance to a little more efficient wide depth sensing experiment was carried out to obtain a structure body with a branch shape with a large surface area with increasing. Experimental results from the FE-SEM observation was obtained template morphology. As a result, depending on the anodizing time, the depth of the layer of aluminum oxide was found that it was confirmed that the deepening of the pore size changes according to anodizing condition. And measuring the detection performance according to the conditions in the electrolyte and the reaction because of blood using a biosensor measuring sensing property according to the depth of the pore depth is considered that does not have a significant impact.

• Korean Journal of Materials Research
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• v.18 no.4
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• pp.193-198
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• 2008

$WO_3$-doped $SnO_2$ thin films were prepared in a solution-deposition method and their gas-sensing characteristics were investigated. The doping of $WO_3$ to $SnO_2$ increased the response ($R_a/R_g,\;R_a$: resistance in air, $R_g$: resistance in gas) to $H_2$ substantially. Moreover, the $R_a/R_g$ value of 10 ppm CO increased to 5.65, whereas that of $NO_2$ did not change by a significant amount. The enhanced response to $H_2$ and the selective detection of CO in the presence of $NO_2$ were explained in relation to the change in the surface reaction by the addition of $WO_3$. The $WO_3$-doped $SnO_2$ sensor can be used with the application of a $H_2$ sensor for vehicles that utilize fuel cells and as an air quality sensor to detect CO-containing exhaust gases emitted from gasoline engines.

• Korean Journal of Remote Sensing
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• v.17 no.4
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• pp.319-334
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• 2001

Extracting primitives from imagery plays an important task in visual information processing since the primitives provide useful information about characteristics of the objects and patterns. The human visual system utilizes features without difficulty for image interpretation, scene analysis and object recognition. However, to extract and to analyze feature are difficult processing. The ultimate goal of digital image processing is to extract information and reconstruct objects automatically. The objective of this study is to develop robust method to achieve the goal of the image processing. In this study, an adaptive strategy was developed by implementing Gabor filters in order to extract feature information and to segment images. The Gabor filters are conceived as hypothetical structures of the retinal receptive fields in human vision system. Therefore, to develop a method which resembles the performance of human visual perception is possible using the Gabor filters. A method to compute appropriate parameters of the Gabor filters without human visual inspection is proposed. The entire framework is based on the theory of human visual perception. Digital images were used to evaluate the performance of the proposed strategy. The results show that the proposed adaptive approach improves performance of the Gabor filters for feature extraction and segmentation.

• Korean Journal of Remote Sensing
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• v.37 no.4
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• pp.747-761
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• 2021

With the increasing application of UAVs in intelligent transportation systems, vehicle detection for aerial images has become an essential engineering technology and has academic research significance. In this paper, a vehicle detection method for aerial images based on the YOLOv4 deep learning algorithm is presented. At present, the most known datasets are VOC (The PASCAL Visual Object Classes Challenge), ImageNet, and COCO (Microsoft Common Objects in Context), which comply with the vehicle detection from UAV. An integrated dataset not only reflects its quantity and photo quality but also its diversity which affects the detection accuracy. The method integrates three public aerial image datasets VAID, UAVD, DOTA suitable for YOLOv4. The training model presents good test results especially for small objects, rotating objects, as well as compact and dense objects, and meets the real-time detection requirements. For future work, we will integrate one more aerial image dataset acquired by our lab to increase the number and diversity of training samples, at the same time, while meeting the real-time requirements.

• Korean Journal of Remote Sensing
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• v.35 no.1
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• pp.57-81
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• 2019

Satellite images can be integrated into a crop model to strengthen the advantages of each technique for crop monitoring and to compensate for weaknesses of each other, which can be systematically applied for monitoring inaccessible croplands. The objective of this study was to outline the productivity of paddy rice based on simulation of the yield of all paddy fields in North Korea, using a grid crop model combined with optical satellite imagery. The grid GRAMI-rice model was used to simulate paddy rice yields for inaccessible North Korea based on the bidirectional reflectance distribution function-adjusted vegetation indices (VIs) and the solar insolation. VIs and solar insolation for the model simulation were obtained from the Geostationary Ocean Color Imager (GOCI) and the Meteorological Imager (MI) sensors of the Communication Ocean and Meteorological Satellite (COMS). Reanalysis data of air temperature were achieved from the Korea Local Analysis and Prediction System (KLAPS). Study results showed that the yields of paddy rice were reproduced with a statistically significant range of accuracy. The regional characteristics of crops for all of the sites in North Korea were successfully defined into four clusters through a spatial analysis using the K-means clustering approach. The current study has demonstrated the potential effectiveness of characterization of crop productivity based on incorporation of a crop model with satellite images, which is a proven consistent technique for monitoring of crop productivity in inaccessible regions.