• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.26 no.5
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• pp.485-491
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• 2008

LiDAR systems are usually incorporated a laser scanner and GPS/INS modules with a digital aerial camera. LiDAR point clouds and digital aerial images acquired by the systems provide complementary spatial information on the ground. In addition, some of laser scanners provide intensity, radiometric information on the surface of the earth. Since the intensity is unnecessary of registration and provides the radiometric information at a certain wavelength on the location of LiDAR point, it can be a valuable ancillary information but it does not deliver sufficient radiometric information compared with digital images. This study utilize the LiDAR points as ground control points (GCPs) to adjust exterior orientations(EOs) of the stereo images. It is difficult to find exact point of LiDAR corresponding to conjugate points in stereo images, but this study used intensity of LiDAR as an ancillary data to find the GCPs. The LiDAR points were successfully used to adjust EOs of stereo aerial images, therefore, successfully provided the prerequisite for the precise registration of the two data sets from the LiDAR systems.

• Korean Journal of Radiology
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• v.22 no.10
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• pp.1628-1639
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• 2021

Objective: Based on the Liver Imaging Reporting and Data System version 2018 (LI-RADS, v2018), this study aimed to analyze LR-5 diagnostic performance for hepatocellular carcinoma (HCC) when threshold growth as a major feature is replaced by a more HCC-specific ancillary feature, as well as the frequency of threshold growth in HCC and non-HCC malignancies and its association with tumor size. Materials and Methods: This retrospective study included treatment-naive patients who underwent gadoxetate disodium-enhanced MRIs for focal hepatic lesions and surgery between January 2009 and December 2016. The frequency of major and ancillary features was evaluated for HCC and non-HCC malignancies, and the LR-category was assessed. Ancillary features that were significantly more prevalent in HCC were then used to either replace threshold growth or were added as additional major features, and the diagnostic performance of the readjusted LR category was compared to the LI-RADS v2018. Results: A total of 1013 observations were analyzed. Unlike arterial phase hyperenhancement, washout, or enhancing capsule which were more prevalent in HCCs than in non-HCC malignancies (521/616 vs. 18/58, 489/616 vs. 19/58, and 181/616 vs. 5/58, respectively; p < 0.001), threshold growth was more prevalent in non-HCC malignancies than in HCCs (11/23 vs. 17/119; p < 0.001). The mean size of non-HCC malignancies showing threshold growth was significantly smaller than that of non-HCC malignancies without threshold growth (22.2 mm vs. 42.9 mm, p = 0.040). Similar results were found for HCCs; however, the difference was not significant (26.8 mm vs. 33.1 mm, p = 0.184). Additionally, Fat-in-nodule was more frequent in HCCs than in non-HCC malignancies (99/616 vs. 2/58, p = 0.010). When threshold growth and fat-in-nodule were considered as ancillary and major features, respectively, LR-5 sensitivity (73.2% vs. 73.9%, p = 0.289) and specificity (98.2% vs. 98.5%, p > 0.999) were comparable to the LI-RADS v2018. Conclusion: Threshold growth is not a significant diagnostic indicator of HCC and is more common in non-HCC malignancies. The diagnostic performance of LR-5 was comparable when threshold growth was recategorized as an ancillary feature and replaced by a more HCC-specific ancillary feature.

• Korea Journal of Hospital Management
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• v.10 no.2
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• pp.1-25
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• 2005

This study purports to investigate the determinants of patient satisfaction and intent to revisit at national university hospitals in Korea. A total of 8 independent variables for outpatients, 9 independent variables for inpatients, and an intervening variable of overall patient satisfaction were selected through literature review. The independent variables for outpatients contain the level of satisfaction with physicians, nurses, ancillary staff, administrative procedure, medical cost, physical environment, facility convenience. and health recovery. With regard to the independent variables for inpatients, the quality of ward services was added to those of outpatients. Each variable contains 3 to 8 items measuring the level of satisfaction with various aspects of the variable. The sample used in this study consisted of 879 outpatients and 821 inpatients. Data were collected with interview survey and analyzed using path analysis. The major findings of the study are as follows: 1) The following variables have significantly positive effect on the intent to revisit of outpatients: health recovery, overall satisfaction, satisfaction with physicians, and ancillary staff. 2) The following variables have significantly positive effect on the intent to revisit of inpatients: health recovery, satisfaction with nurses and physicians, overall satisfaction, and administrative procedure. 3) The following variables of admission procedure, satisfaction with ancillary staff, facility convenience, quality of ward services were found to have significantly positive effect only on the level of overall satisfaction, even though they do not have significant total effect on the intent to revisit. The results of the study indicate that national university hospitals in Korea should make an effort to improve the satisfactory level of patients with clinical outcome, services provided by physicians, nurses, and ancillary staff, and the quality of administrative procedure for enhancing the intent to revisit of patients.

• Korean Journal of Remote Sensing
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• v.19 no.6
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• pp.447-456
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• 2003

This study investigated the method for obtaining 3-dimensional terrain information on inaccessable areas by evaluating geometric accuracy of the EOC pass image and scene image acquired from the KOMPSAT-1 satellite. For this purpose, the following four experiments were conducted to evaluate the accuracy of the KOMPSAT-1 EOC satellite data. 1) Calculation of ground coordinates by using ancillary data and image coordinates on Level 1R that were processed by the pre-processing system of KOMPSAT-1. 2) Calculation of 3-dimensional ground coordinates from the ground coordinates of stereo images calculated by using ancillary data, based on space intersections. 3) Execution of bundle adjustment by using GCP (Ground Control Point) extracted in a part of the stereo pass image (KOMPSAT-1 EOC, 1 scene size); and then, evaluation of the ground coordinates from the calculated exterior orientation. 4) Evaluation of accuracy by applying the exterior orientation calculated from 3) To the whole pass image.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1329-1331
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• 2003

Improvement of the classification accuracy is one of the major concerns in the field of remote sensing application research in recent years. Previous research shows that the accuracy of the conventional classification methods based only on the original spectral information were usually unsatisfied and need to be refined by manual edit. This present paper describes a method of combining the image processing, ancillary data (such as digital elevation model) and expert knowledge (especially the knowledge of local professionals) to improve the efficiency and accuracy of the satellite image classification in hilly land. Firstly, the Landsat TM data were geo-referenced. Secondly, the individual bands of the image were intensitynormalized and the normalized difference vegetation index (NDVI) image was also generated. Thirdly, a set of sample pixels (collected from field survey) were utilized to discover their corresponding DN (digital number) ranges in the NDVI image, and to explore the relationships between land use type and its corresponding spectral features . Then, using the knowledge discovered from previous steps as well as knowledge from local professionals, with the support of GIS technology and the ancillary data, a set of conditional statements were applied to perform the TM imagery classification. The results showed that the integration of image processing and spatial analysis functions in GIS improved the overall classification result if compared with the conventional methods.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1131-1133
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• 2003

Spatial image processing software requires various user interactions to make a plan, prepare necessary data such as images, vectors, ancillary data and user-defined data, execute functions according to pre-defined procedures, analyze and store the results. In this manner, overall processes are controlled by user interactions. In this paper, we propose visual modeler which has the automated spatial image processing technique to minimize user interactions and re -use repeatable procedure. The proposed visual modeler is designed to use inter-operable components proposed by OpenGIS consortium as well as conventional COM components.

• Journal of the Korean Association of Geographic Information Studies
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• v.13 no.1
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• pp.128-141
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• 2010

Drought indices such as SPI(Standard Precipitation Index) and PDSI(Palmer Drought Severity Index) estimated using ground observations are not enough to describe detail spatial distribution of drought condition. In this study, the drought index with improved spatial resolution was estimated by using the CART algorithm and ancillary data such as MODIS NDVI, MODIS LST, land cover, rainfall, average air temperature, SPI, and PDSI data. Estimated drought index using the proposed approach for the year 2008 demonstrates better spatial information than that of traditional approaches. Results show that the availability of satellite imageries and various associated data allows us to get improved spatial drought information using a data mining technique and ancillary data and get better understanding of drought condition and prediction.

• Journal of Forest and Environmental Science
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• v.24 no.3
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• pp.127-135
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• 2008

The mission of the Forest Inventory and Analyis (FIA) program of the Forest Service, U.S. Department of Agriculture, is to conduct the national forest inventory of the United States of America for purposes of estimating the area of forest land; the volume, growth, and removal of forest resources; and the health of the forest. Users of FIA data, estimates, and related products include land managers, policy and decision-makers, forest industry, environmental organizations, and university researchers. To accomplish its mission, the FIA program has established a sampling design with an intensity of approximately one permanent plot per 2,400 ha across the entire country. Depending on the region of the country, each plot is remeasured at intervals of five or 10 years. The program releases data annually and reports estimates at the county level for each state every five years. Due to budgetary constraints and natural variability among plot observations, sufficient numbers of plots cannot be measured to satisfy precision guidelines for the estimates of many variables unless the estimation process is enhanced using ancillary data. Classified satellite imagery has been demonstrated to be a source of ancillary data that can be used with stratified estimation techniques to increase the precision of estimates with little corresponding increase in costs. A crucial factor restricting the utility of FIA data is that the exact locations of inventory plots cannot be released to the public. Thus, users are generally not able to obtain estimates for small areas or for their own areas of interest if exact plot locations are required. To compensate, satellite imagery, inventory plot data, and the k-Nearest Neighbors technique are being used to construct Internet-based maps of forest attributes from which estimates for arbitrary user-defined areas of interest may be obtained.

• Journal of Korea Water Resources Association
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• v.43 no.7
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• pp.597-608
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• 2010

In this study, a method for soil moisture estimation was proposed to obtain the nationwide soil moisture distribution map using on-site soil moisture observations, rainfall, surface temperature, NDVI, land cover, effective soil depth, and CART (Classification And Regression Tree) algorithm. The method was applied to the Yong-dam dam basin since the soil moisture data (4 sites) of the basin were reliable. Soil moisture observations of 3 sites (Bu-gui, San-jeon, Cheon-cheon2) were used for training the algorithm and 1 site (Gye-buk2) was used for the algorithm validation. The correlation coefficient between the observed and estimated data of soil moisture in the validation sites is about 0.737. Results show that even though there are limitations of the lack of reliable soil moisture observation for various land use, soil type, and topographic conditions, the soil moisture estimation method using ancillary data and CART algorithm can be a reasonable approach since the algorithm provided a fairly good estimation of soil moisture distribution for the study area.

• Environmental and Resource Economics Review
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• v.20 no.3
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• pp.567-593
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• 2011

In 2005, five Korean generation companies suggested to include non-fuel ancillary costs incurring in the process of managing fuels and ashes as variable costs in Korean Cost-Based Pool. OLS analysis seeking statistical relation with the amount of generation did not provide sufficient ground for such argument. However, some cost items in this category showed meaningful statistical relation for certain generation facilities hinting some possibilities for the candidate of variable costs in the future. Time lag related to cost evaluation, problems related to inventory control and accounting method related to this may block the statistical relationship with the amount of generation. Unified criteria and standardization of the data are necessary before we proceed further to consider them as variable costs.