• The Korean Journal of Nuclear Medicine Technology
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• v.13 no.1
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• pp.35-39
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• 2009

Purpose: Diagnostic and functional imaging softwares in Nuclear Medicine have been developed significantly. But, there are some limitations which like take a lot of time. In this article, we introduced that the basic concept of macro to help understanding macro and its application to Brain SPECT processing. We adopted macro software to SPM processing and PACS verify processing of Brain SPECT processing. Materials and Methods: In Brain SPECT, we choose SPM processing and two PACS works which have large portion of a work. SPM is the software package to analyze neuroimaging data. And purpose of SPM is quantitative analysis between groups. Results are made by complicated process such as realignment, normalization, smoothing and mapping. We made this process to be more simple by using macro program. After sending image to PACS, we directly input coordinates of mouse using simple macro program for processes of color mapping, adjustment of gray scale, copy, cut and match. So we compared time for making result by hand with making result by macro program. Finally, we got results by applying times to number of studies in 2007. Results: In 2007, the number of SPM studies were 115 and the number of PACS studies were 834 according to Diamox study. It was taken 10 to 15 minutes for SPM work by hand according to expertness and 5 minutes and a half was uniformly needed using Macro. After applying needed time to the number of studies, we calculated an average time per a year. When using SPM work by hand according to expertness, 1150 to 1725 minutes (19 to 29 hours) were needed and 632 seconds (11 hours) were needed for using Macro. When using PACS work by hand, 2 to 3 minutes were needed and for using Macro, 45 seconds were needed. After applying theses time to the number of studies, when working by hand, 1668 to 2502 minutes (28 to 42 hours) were needed and for using Macro, 625 minutes (10 hours) were needed. Following by these results, it was shown that 1043 to 1877 (17 to 31 hours were saved. Therefore, we could save 45 to 63% for SPM, 62 to 75% for PACS work and 55 to 70% for total brain SPECT processing in 2007. Conclusions: On the basis of the number of studies, there was significant time saved when we applied Macro to brain SPECT processing and also it was shown that even though work is taken a little time, there is a possibility to save lots of time according to the number of studies. It gives time on technologist's side which makes radiological technologist more concentrate for patients and reduce probability of mistake. Appling Macro to brain SPECT processing helps for both of radiological technologists and patients and contribute to improve quality of hospital service.

• Korean Journal of Ecology and Environment
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• v.33 no.3 s.91
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• pp.230-243
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• 2000

A large-scale community data were patterned by utilizing an unsupervised learning algorithm in artificial neural networks. Data for benthic macroinvertebrates in streams of South Korea reported in publications for 12 years from 1984 to 1995 were provided as inputs for training with the Kohonen network. Taxa included for the training were 5 phylum, 10 class, 26 order, 108 family and 571 species in 27 streams. Abundant groups were Diptera, Ephemeroptera, Trichoptera, Plecoptera, Coleoptera, Odonata, Oligochaeta, and Physidae. A wide spectrum of community compositions was observed: a few tolerant taxa were collected at polluted sites while a high species richness was observed at relatively clean sites. The trained mapping by the Kohonen network effectively showed patterns of communities from different river systems, followed by patterns of communities from different environmental disturbances. The training by the proposed artificial neural network could be an alternative for organizing community data in a large-scale ecological survey.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.34 no.1
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• pp.53-62
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• 2016

In recent years, UAV Photogrammetry based on an ultra-light UAS(Unmanned Aerial System) installed with a low-cost compact navigation device and a camera has attracted great attention through fast and accurate acquirement of geo-spatial data. In particular, UAV Photogrammetry do gradually replace the traditional aerial photogrammetry because it is able to produce DEMs(Digital Elevation Models) and Orthophotos rapidly owing to large amounts of high resolution image collection by a low-cost camera and image processing software combined with computer vision technique. With these advantages, UAV-Photogrammetry has therefore been applying to a large scale mapping and cadastral surveying that require accurate position information. This paper presents experimental results of an accuracy performance test with images of 4cm GSD from a fixed wing UAS to demarcate parcel boundaries in agricultural area. Consequently, the accuracy of boundary point extracted from UAS orthoimage has shown less than 8cm compared with that of terrestrial cadastral surveying. This means that UAV images satisfy the tolerance limit of distance error in cadastral surveying for the scale of 1: 500. And also, the area deviation is negligible small, about 0.2%(3.3m²), against true area of 1,969m² by cadastral surveying. UAV-Photogrammetry is therefore as a promising technology to demarcate parcel boundaries.

• Journal of the Korean Association of Geographic Information Studies
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• v.10 no.3
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• pp.80-92
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• 2007

Forest fire is the dominant large-scale disturbance mechanism in the Korean temperate forest, and it strongly influences forest structure and function. Moreover burn severity incorporates both short- and long-term post-fire effects on the local and regional environment. Burn severity is defined by the degree to which an ecosystem has changed owing to the fire. Vegetation rehabilitation may specifically vary according to burn severity after fire. To understand burn severity and process of vegetation rehabilitation at the damaged area after large-fire is required a lot of man powers and budgets. However the analysis of burn severity in the forest area using satellite imagery can acquire rapidly information and more objective results remotely in the large-fire area. Space and airbone sensors have been used to map area burned, assess characteristics of active fires, and characterize post-fire ecological effects. For classifying fire damaged area and analyzing burn severity of Samcheok fire area occurred in 2000, Cheongyang fire in 2002, and Yangyang fire in 2005 we utilized Normalized Burn Ratio(NBR) technique. The NBR is temporally differenced between pre- and post-fire datasets to determine the extent and degree of change detected from burning. In this paper we use pre- and post-fire imagery from the Landsat TM and ETM+ imagery to compute the NBR and evaluate large-scale patterns of burn severity at 30m spatial resolution. 65% in the Samcheok fire area, 91% in the Cheongyang fire area and 65% in the Yangyang fire area were corresponded to burn severity class above 'High'. Therefore the use of a remotely sensed Differenced Normalized Burn Ratio(${\Delta}NBR$) by RS and GIS allows for the burn severity to be quantified spatially by mapping damaged domain and burn severity across large-fire area.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.4
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• pp.268-279
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• 2021

The geospatial schemes based on topo-climatology have been developed to produce digital climate maps at a site-specific scale. Their development processes are reviewed here to derive the needs for new schemes in the future. Agricultural and forestry villages in Korea are characterized by complexity and diversity in topography, which results in considerably large spatial variations in weather and climate over a small area. Hence, the data collected at a mesoscale through the Automated Synoptic Observing System (ASOS) operated by the Korea Meteorological Administration (KMA) are of limited use. The geospatial schemes have been developed to estimate climate conditions at a local scale, e.g., 30 m, lowering the barriers to deal with the processes associated with production in agricultural and forestry industries. Rapid enhancement of computing technologies allows for near real-time production of climate information at a high-resolution even in small catchment areas and the application to future climate change scenarios. Recent establishment of the early warning service for agricultural weather disasters can provide growth progress and disaster forecasts for cultivated crops on a farm basis. The early warning system is being expanded worldwide, requiring further advancement in geospatial schemes and digital climate mapping.

• Review of Culture and Economy
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• v.20 no.2
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• pp.47-88
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• 2017

Creative industries and creative occupations have been attracting issues in recent years, in both policy and academic fields. Although no literature has yet made all-embracing definitions of creative sectors, it is important to measure creative workers who are contributing to the national economy. Since 2000, many countries including UK, France, Germany, Finland, Hongkong, US, Canada, etc. have tried to develop more refined mapping methodologies for measuring the creative economy. However we are lack of deep scrutiny in the criteria select which sector is creative or not, as well as in existing methodologies for measuring creative employment. This paper presents a creative mapping methodology, called 'Creative Trident' and criteria that can be applied to measuring the scale of creative employment in Korea. Using annual labor data from Statistics Korea and Ministry of Employment and Labor, this research found that creative employment in Korea amounts to 40,922 and 6.65% of total employment. Also the research found that there are many workers who are creatively occupied outside the creative industries, called embedded creative workers which are 248,445 and 33.5% of total creative employment. That means embedded workers take some large portion of all creative workers and are dispersed across all the sectors of the economy. The research demonstrates that creative trident can be useful to estimate the true size of creative employment in Korean and finishes with some academical and practical implications.

• Tunnel and Underground Space
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• v.31 no.1
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• pp.10-24
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• 2021

Rock mass classification for construction of underground facilities is essential to secure their stabilities. Therefore, the reliable values for rock mass classification from the precise information on rock discontinuities are most important factors, because rock mass discontinuities can affect exclusively on the physical and mechanical properties of rock mass. The conventional classification operation for rock mass has been usually performed by hand mapping. However, there have been many issues for its precision and reliability; for instance, in large-scale survey area for regional geological survey, or rock mass classification operation by non-professional engineers. For these reasons, automated rock mass classification using LiDAR becomes popular for obtaining the quick and precise information. But there are several suggested algorithms for analyzing the rock mass discontinuities from point cloud data by LiDAR scanning, and it is known that the different algorithm gives usually different solution. Also, it is not simple to obtain the exact same value to hand mapping. In this paper, several discontinuity extract algorithms have been explained, and their processes for extracting rock mass discontinuities have been simulated for real rock bench. The application process for several algorithms is anticipated to be a good reference for future researches on extracting rock mass discontinuities from digital point cloud data by laser scanner, such as LiDAR.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.21 no.1
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• pp.27-36
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• 2003

Generally, the latest acquisition method of geo-spatial informations in urban area is executed by generation of digital elevation model (DEM) and digital ortho image by digital photogrammetry method which is used large scale photo image. However, the biggest problem of this method is coarse accuracy of DEM which is automatically generated by digital photogrammetry workstation system. The coarse accuracy of DEM caused geo-spatial information in urban area to reduce of accuracy. Therefore, this study is purposed to increase of DEM accuracy which is applied to method terrain classification in urban area. As the results of this study, the proposed method of this study which is increased to accuracy of DEM by classification of terrain is better than accuracy of DEM which is automatically generated by digital photogrammetry workstaion system. And, the edge detection method which is proposed by this study is established to capability of 3D digital mapping in urban area.

• Korean Journal of Agricultural Science
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• v.44 no.4
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• pp.495-503
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• 2017

Genotyping-by-sequencing (GBS) is an outstanding technology for genotyping and single nucleotide polymorphism (SNP) discovery compared to next generation sequencing (NGS) because it can save time when analyzing large-scale samples and carries a low cost per sample. Recently, studies using GBS have been conducted on major crops and, to a greater extent, on fruit crops. However, many researchers have some problems due to low GBS efficiency resulting from low quality GBS libraries. To overcome this limitation, we developed an efficient GBS library construction method that regulates important conditions such as restriction enzymes (RE) digestion and a PCR procedure for grapevine. For RE digestion, DNA samples are digested with ApeKI (3.6U) at $75^{\circ}C$ for 5 hours and adapters are ligated to the ends of gDNA products. To produce suitable PCR fragments for sequencing, we modified the PCR amplification conditions; temperature cycling consisted of $72^{\circ}C$ (5 min), $98^{\circ}C$ (30 s), followed by 16 cycles of $98^{\circ}C$ (30 s), $65^{\circ}C$ (30 s), $72^{\circ}C$ (20 s) with a final extension step. As a result, we had obtained optimal library construct sizes (200 to 400 bp) for GBS analysis. Furthermore, it not only increased the mapping efficiency by approximately 10.17% compared to the previous method, but also produced mapped reads which were distributed equally on the19 chromosomes in the grape genome. Therefore, we suggest that this system can be used for various fruit crops and is expected to increase the efficiency of various genomic analysis performed.

• Korean Journal of Remote Sensing
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• v.29 no.5
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• pp.509-516
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• 2013

Since traditional linear feature extraction methods are unable to handle nonlinear characteristics often exhibited in hyperspectral imagery, nonlinear feature extraction, also known as manifold learning, is receiving increased attention in hyperspectral remote sensing society as well as other community. A most widely used manifold Isomap is generally promising good results in classification and spectral unmixing tasks, but significantly high computational overhead is problematic, especially for large scale remotely sensed data. A small subset of distinguishing points, referred to as landmarks, is proposed as a solution. This study proposes a new robust and controllable landmark selection method based on the maximum volume of the simplex spanned by landmarks. The experiments are conducted to compare classification accuracies with standard deviation according to sampling methods, the number of landmarks, and processing time. The proposed method could employ both classification accuracy and computational efficiency.