• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.27 no.5
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• pp.585-597
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• 2009

This research aims to develop a registration method to remove the geometric inconsistency between aerial images and LIDAR data acquired from an airborne multi-sensor system. The proposed method mainly includes registration primitives extraction, correspondence establishment, and EOP(Exterior Orientation Parameters) adjustment. As the registration primitives, we extracts planar patches and intersection edges from the LIDAR data and object points and linking edges from the aerial images. The extracted primitives are then categorized into horizontal and vertical ones; and their correspondences are established. These correspondent pairs are incorporated as stochastic constraints into the bundle block adjustment, which finally precisely adjusts the exterior orientation parameters of the images. According to the experimental results from the application of the proposed method to real data, we found that the attitude parameters of EOPs were meaningfully adjusted and the geometric inconsistency of the primitives used for the adjustment is reduced from 2 m to 2 cm before and after the registration. Hence, the results of this research can contribute to data fusion for the high quality 3D spatial information.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.18 no.4
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• pp.395-403
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• 2000

It is so sensitive that the matter of compensation for private possessions caused in the course of public construction planning is very important. Especially, more logical planning is necessary when the dam be constructed, because it is mainly controlled by the surface of water, and if that planning is made public, artificial change is occurred in land use in that area for the purpose of rising the compensation. In this study, the plan for the application of aerial photo based ortho image was drew up for solving these problems and for the rational, rapid compensation. Ortho image was made by aerial photo, used as reading material for the change in land use. The modeling of drainage basin, came under the planning surface of water, and the 3D simulation were performed for the scene analysis, the change understanding in land use for a lot number in a certain period by overlapping the digital image, the digital land registration map, and the digital topography map as well as the analysis of the admitted land followed by the height of reservoir water.

• Ecology and Resilient Infrastructure
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• v.8 no.4
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• pp.266-272
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• 2021

Water friendly space refers to a place designated to plan and manage spaces for residents Water friendly activities. Efficient management of river Water friendly parks requires automated GIS data and DB construction of the water friendly facilities. Object-based classification using drone images or aerial images is attracting attention as an efficient means to acquire 3D spatial information in the country. To remove the miscellaneous image included in the extracted outline, a linear simplification of the outline is required, and it is difficult to apply manually, so various automation methods have been developed to overcome this, and among them, the most widely studied and utilized is the linear simplification method. In this study, the suitability of linear simplification algorithms such as Douglas-Peucker, Visvalingam-Whyatt, and Bend-simplify algorithms for the geometric shape of hydrophilic facilities was determined.

• Journal of Biomedical Engineering Research
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• v.25 no.5
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• pp.323-328
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• 2004

The development of group-specific tissue probability maps (TPM) provides a priori knowledge for better result of cerebral tissue classification with regard to the inter-ethnic differences of inter-subject variability. We present sequential procedures of group-specific TPM and evaluate the age effects in the structural differences of TPM. We investigated 100 healthy volunteers with high resolution MRI scalming. The subjects were classified into young (60, 25.92+4.58) and old groups (40, 58.83${\pm}$8.10) according to the age. To avoid any bias from random selected single subject and improve registration robustness, average atlas as target for TPM was constructed from skull-stripped whole data using linear and nonlinear registration of AIR. Each subject was segmented into binary images of gray matter, white matter, and cerebrospinal fluid using fuzzy clustering and normalized into the space of average atlas. The probability images were the means of these binary images, and contained values in the range of zero to one. A TPM of a given tissue is a spatial probability distribution representing a certain subject population. In the spatial distribution of tissue probability according to the threshold of probability, the old group exhibited enlarged ventricles and overall GM atrophy as age-specific changes, compared to the young group. Our results are generally consistent with the few published studies on age differences in the brain morphology. The more similar the morphology of the subject is to the average of the population represented by the TPM, the better the entire classification procedure should work. Therefore, we suggest that group-specific TPM should be used as a priori information for the cerebral tissue classification.

• Journal of the Korea Society of Computer and Information
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• v.19 no.9
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• pp.1-10
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• 2014

In this paper, we propose MPI gridding algorithm of LiDAR data that minimizes the communication between the cores. The LiDAR data collected from aircraft is a 3D spatial information which is used in various applications. Since there are many cases where the LiDAR data has too high resolution than actually required or non-surface information is included in the data, filtering the raw LiDAR data is required. In order to use the filtered data, the interpolation using the data structure to search adjacent locations is conducted to reconstruct the data. Since the processing time of LiDAR data is directly proportional to the size of it, there have been many studies on the high performance parallel processing system using MPI. However, previously proposed methods in parallel approach possess possible performance degradations such as imbalanced data size among cores or communication overhead for resolving boundary condition inconsistency. We conduct empirical experiments to verify the effectiveness of our proposed algorithm. The results show that the total execution time of the proposed method decreased up to 4.2 times than that of the conventional method on heterogeneous clusters.

• Journal of the Korean Association of Geographic Information Studies
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• v.17 no.1
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• pp.35-49
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• 2014

In order to understand the impacts of surface characteristics and the distance from the urban heat island center to suburban areas on the mean night time air temperature, we analyzed GIS and AWS observational data. Spatial distributions of mean night time air temperature during the summer and winter periods of 2004-2011(six years) were utilized. Results show that the temperature gradients were different by distance and direction. We found high correlation between mean night-time air temperature and artificial land cover area within 1km and 200m radii during both summer(R=0.84) and winter(R=0.78) seasons. Regression models either from 1km and 200m land surface data explained the distribution of night-time temperature equally well if the input data had sufficient resolution with detailed attribute including building area and height.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.3
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• pp.1293-1297
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• 2016

Cholangiocarcinoma (CCA) is a serious problem in Thailand, particularly in the northeastern and northern regions. Database of population at risk are need required for monitoring, surveillance, home health care, and home visit. Therefore, this study aimed to develop a geographic information system (GIS) database and Google map of the population at risk of CCA in Mueang Yang district, Nakhon Ratchasima province, northeastern Thailand during June to October 2015. Populations at risk were screened using the Korat CCA verbal screening test (KCVST). Software included Microsoft Excel, ArcGIS, and Google Maps. The secondary data included the point of villages, sub-district boundaries, district boundaries, point of hospital in Mueang Yang district, used for created the spatial databese. The populations at risk for CCA and opisthorchiasis were used to create an arttribute database. Data were tranfered to WGS84 UTM ZONE 48. After the conversion, all of the data were imported into Google Earth using online web pages www.earthpoint.us. Some 222 from a 4,800 population at risk for CCA constituted a high risk group. Geo-visual display available at following www.google.com/maps/d/u/0/edit?mid=zPxtcHv_iDLo.kvPpxl5mAs90&hl=th. Geo-visual display 5 layers including: layer 1, village location and number of the population at risk for CCA; layer 2, sub-district health promotion hospital in Mueang Yang district and number of opisthorchiasis; layer 3, sub-district district and the number of population at risk for CCA; layer 4, district hospital and the number of population at risk for CCA and number of opisthorchiasis; and layer 5, district and the number of population at risk for CCA and number of opisthorchiasis. This GIS database and Google map production process is suitable for further monitoring, surveillance, and home health care for CCA sufferers.

• Journal of Korean Society for Geospatial Information Science
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• v.24 no.3
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• pp.11-18
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• 2016

Since GNSS signals get blocked by buildings in urban canyons or narrow alleys, it is very difficult to secure a enough number of visible satellites for satellite navigation in those poor signal-reception environments. In those situations, one cannot get their coordinates or obtain accurate positions. In this study, a couple of strategies for improving positioning accuracy in urban canyons were developed and their performance was verified. First of all, we combined GPS and GLONASS measurements together and devised algorithms to quality-control observed signals and eliminate outliers. Also, a new multipath reduction scheme was applied to minimize its effect by utilizing SNR values of the observed signals. For performance verification of the developed technique, a narrow alley of 10m width located near the back gate of the Inha University was selected as the test-bed, and then we conducted static and kinematic positioning at four pre-surveyed points. We found that our new algorithms produced an 45% improvement in an open-sky environment compared with the positioning result of a low-cost u-blox receiver. In the alleys, 3-D accuracy improved by an average of 37%. In the case of kinematic positioning, especially, biases showing up in regular receivers got eliminated significantly through our new filtering algorithms.

• Journal of Radiation Protection and Research
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• v.30 no.3
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• pp.121-130
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• 2005

Geographical Information System(GIS) was established to display the calculation results which show the concentration change with time and regions in case of an accidental release of radionuclides from Kori Nuclear Power Plants. GIS included the commercial program, ArcView(ESRI), and a basic digital map of 1:5000 scale lot 20km by 20km around Kori area. The object for the presentation was $^{131}I$ concentration in rice which is one of staple foodstuffs. Provided by deposited $^{131}I$ concentrations, ECOREA-II code computed the $^{131}I$ concentration of the soil and the plant in the area divided by In unit cells in total, in which the concentrations also varied with time. The results were introduced into the attributed data of previously designed polygon cells in ArcView. In order to display the concentration change with time by monotonic color, the RGB value for ArcView color lamp was controlled. This display definitely helped the concentration change around Kori area be acceptable to public.

• The Journal of the Convergence on Culture Technology
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• v.6 no.2
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• pp.437-447
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• 2020

The purpose of this study is to research the countermeasures and expected effects through the use of drones in the field of disaster prevention as a drone-based smart quarantine performance method. The environmental, market, and technological approaches to the review of the current quarantine performance task and its countermeasures are as follows. First, in terms of the environment, the effectiveness of the quarantine performance business using drone-based control is to broaden the utilization of forest, bird flu, livestock, facility areas, mosquito larvae, pests, and to simplify and provide various effective prevention systems such as AI and cholera. Second, in terms of market, the standardization of livestock and livestock quarantine laws and regulations according to the use of disinfection and quarantine missions using domestic standardized drones through the introduction of new technologies in the quarantine method, shared growth of related industries and discovery of new markets, and animal disease prevention It brings about the effect of annual budget savings. Third, the technical aspects are (1) on-site application of disinfection and prevention using multi-drone, a new form of animal disease prevention, (2) innovation in the drone industry software field, and (3) diversification of the industry with an integrated drone control / control system applicable to various markets. (4) Big data drone moving path 3D spatial information analysis precise drone traffic information ensures high flight safety, (5) Multiple drones can simultaneously auto-operate and fly, enabling low-cost, high-efficiency system deployment, (6) High precision that this was considered due to the increase in drone users by sector due to the necessity of airplane technology. This study was prepared based on literature surveys and expert opinions, and the future research field needs to prove its effectiveness based on empirical data on drone-based services. The expected effect of this study is to contribute to the active use of drones for disaster prevention work and to establish policies related to them.