• Economic and Environmental Geology
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• v.47 no.1
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• pp.1-15
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• 2014

The Bobonaro m$\acute{e}$lange is one of the youngest syn-collisional m$\acute{e}$langes, located between the Indo-Australian and Eurasian plates. The m$\acute{e}$lange has formed in association with a collision between the Australian continental margin and the Banda arc initiated in Neogene. The Suai area at the southern part of Timor is a good place to examine the genetic relationship between the m$\acute{e}$lange and other rock sequences because various tectonostratigraphic units coexist in the area. In this study, we present the structural characteristics and spatial distribution of the Bobonaro m$\acute{e}$lange investigated as a part of 1:25K scale geologic mapping in the area, and discuss on the origin of the m$\acute{e}$lange. The Bobonaro m$\acute{e}$lange in the Suai area is composed of unmetamorphosed clay matrix and blocks of various lithologies. The clay matrix mainly is reddish brown or greenish gray in colour, and has scaly texture. Most blocks are allochthonous, but mostly derived from nearby formations. Based on the internal structure and relationship with surrounding rocks, the Bobonaro m$\acute{e}$lange is genetically classified into 1) diapiric m$\acute{e}$lange; 2) tectonic m$\acute{e}$lange; and 3) broken formation. The spatial distribution of the Bobonaro m$\acute{e}$lange indicates that it intruded all pre-collisional units including the lower Australian continental margin unit(Gondwana megasequence) and the Banda arc unit. Taking the field evidences and previous genetic models into consideration, the Bobonaro m$\acute{e}$lange is interpreted to be mainly formed as a diapiric m$\acute{e}$lange originated from Gondwana megasequence, consistently effected by faulting events. This study reflects that diapiric m$\acute{e}$lange is a significant component in recent accretionay-collision belts. It suggests that diapiric process should be considered as a main genetic factor even in ancient m$\acute{e}$lange.

• Archives of design research
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• v.19 no.2 s.64
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• pp.241-250
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• 2006

Hangeul as the Korean unique characters were invented according to some character-making principles and based on scholars' exhaustive researches. While most of the characters in the world evolved naturally, Hangeul was invented based on a precise linguistic analysis of the time, and therefore, it is most scientific and reasonable among various characters throughout the world. Nevertheless, Hangeul typeface designs do not seem to inherit the ideology of scientific and reasonable Hangeul correctly. For the square forms have been used intact due to the influences from the Chinese characters which prevailed during the time. If a single set of square characters should be designed, as much as 11,172 fonts should be designed, which suggests that advantages of Mangeul may not well be used fully; Hangeul was invented to visualize every sound with the combinations of 28 vowels and consonants. Problems of such square fonts began to be identified since 1900's when typewriters were introduced first from the West. Since a typewriter is designed with 28 characters laid out on its keyboard by using such combinations, the letters may be easily combined on it. The so-called the flexibility square-format typeface was born as such. Specially, the three-pairs fonts of these can be combined up to 67 letters including vowels and consonants. The three-pairs fonts system can help to solve the problems arising form the conventional square fonts and inherit the original ideology of Hangeul invention. This study aims to review the history of the three-pairs fonts designs facilitated by mechanic encoding of Hangeul and thereupon, suggest some desirable directions for future Hangeul fonts. Since the flexibility square-format typeface is expected to evolve more and more owing to development of the digital technology, they would serve our age of information in terms of both functions and convenience. Just as Hunminjongum tried to be literally independent from the Chinese characters, so the flexibility square-format typeface designs would serve to recover identity of our Hangeul font designs.

• Korean Journal of Soil Science and Fertilizer
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• v.43 no.6
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• pp.828-836
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• 2010

This study was conducted to evaluate soil erosion risk with a standard unit watershed in the upper Han river basin using the spatial soil erosion map according to the change of landuse. The study area is 14,577 $km^2$, which consists of 10 subbasins, 107 standard unit watersheds. Total annual soil loss and soil loss per area estimated were $895{\times}10^4\;Mg\;yr^{-1}$ and 6.1 Mg $ha^{-1}\;yr^{-1}$, respectively. A result of analysis with a subbasin as a unit showed that annual soil losses and soil loss per area in Namhan river basins was more than in Bukhan river ones. Predicted annual soil loss according to the landuse ranked as Forest & Grassland > Upland ${\gg}$ Urban & Fallow area > Paddy field > Orchard. Upland area covered 6.2% of the study area, but the contribution of total annul soil loss was 40.6% and that of Forest & Grassland was 44.2%. As a evaluation of soil erosion risk using the spatial soil erosion map, we could precisely conformed the potential hazardous region of soil erosion in each unit watersheds. The ratio of regions, graded as higher "Moderate" for annual soil loss, were respectively 8.7%, 7.9% and 7.8% in 1001, 1002 and 1003 subbasins in Namhan river basin. Most landuse of these area was upland, and these area is necessary to establish soil conservation practices to reduce soil erosion based on the field observation.

• Journal of the Korean Association of Geographic Information Studies
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• v.24 no.3
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• pp.73-82
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• 2021

Rural roads are the significant infrastructure for developing and managing the rural areas, hence the utilization of the remote sensing datasets for managing the rural roads is necessary for expanding the rural transportation infrastructure and improving the life quality of the rural residents. In this research, the two different methods such as image classification and image segmentation were compared for mapping the rural road based on the given high-resolution satellite image acquired in the rural areas. In the image classification method, the deep learning with the multiple neural networks was employed to the given high-resolution satellite image for generating the object classification map, then the rural roads were mapped by extracting the road objects from the generated object classification map. In the image segmentation method, the multiresolution segmentation was employed to the same satellite image for generating the segment image, then the rural roads were mapped by merging the road objects located on the rural roads on the satellite image. We used the 100 checkpoints for assessing the accuracy of the two rural roads mapped by the different methods and drew the following conclusions. The image segmentation method had the better performance than the image classification method for mapping the rural roads using the give satellite image, because some of the rural roads mapped by the image classification method were not identified due to the miclassification errors occurred in the object classification map, while all of the rural roads mapped by the image segmentation method were identified. However some of the rural roads mapped by the image segmentation method also had the miclassfication errors due to some rural road segments including the non-rural road objects. In future research the object-oriented classification or the convolutional neural networks widely used for detecting the precise objects from the image sources would be used for improving the accuracy of the rural roads using the high-resolution satellite image.

• Journal of Korean Society of Forest Science
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• v.108 no.2
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• pp.177-188
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• 2019

The aim of our study was to identify the changing trends in the composition, structure, and spatial distribution of forest vegetation in Apsan Park, a representative urban forest in Daegu, South Korea. A vegetation survey was conducted in 1997 and 2016 using phytosociological methods, and a detailed vegetation map was created using the physiognomic dominant species. There were 22 vegetation types in both 1997 and 2016, but two of those types increased and two decreased. The total coverage per unit area ($100m^2$) of the component vegetation species increased from 163% in 1997 to 182% in 2016, and natural vegetation tended to be more than twice that of artificial vegetation. The average number of species decreased by seven from 25 in 1997 to 18 in 2016. Species diversity (H') increased only slightly from 1,654 in 1997 to 1,680 in 2016, while species dominance (D) decreased by 9% from 0.304 in 1997 to 0.276 in 2016. The similarity in the composition of the forest vegetation was about 78%, which was nearly the same. The life form spectrums of vascular plants changed from '$G-R_5-D_4-e$' in 1997 to '$MM-R_5-D_4-e$' in 2016 and the central dormancy type changed from geophytes (G) to megaphanerophytes (MM). The spatial distribution of the forest vegetation was reduced by approximately four times that of artificial vegetation. The number of forest landscape elements (patches) increased from 269 in 1997 to 294 in 2016, while the average area decreased by 12% from 5.8 ha in 1997 to 5.1 ha in 2016.

• Korean Journal of Remote Sensing
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• v.39 no.6_2
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• pp.1615-1633
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• 2023

Sargassum horneri is one of the floating algae in the sea, which breeds in large quantities in the Yellow Sea and East China Sea and then flows into the coast of Republic of Korea, causing various problems such as destroying the environment and damaging fish farms. In order to effectively prevent damage and preserve the coastal environment, the development of Sargassum horneri detection algorithms using satellite-based remote sensing technology has been actively developed. However, incorrect detection information causes an increase in the moving distance of ships collecting Sargassum horneri and confusion in the response of related local governments or institutions,so it is very important to minimize false detections when producing Sargassum horneri spatial information. This study applied technology to automatically remove false detection results using the GOCI-II-based Sargassum horneri detection algorithm of the National Ocean Satellite Center (NOSC) of the Korea Hydrographic and Oceanography Agency (KHOA). Based on the results of analyzing the causes of major false detection results, it includes a process of removing linear and sporadic false detections and green algae that occurs in large quantities along the coast of China in spring and summer by considering them as false detections. The technology to automatically remove false detection was applied to the dates when Sargassum horneri occurred from February 24 to June 25, 2022. Visual assessment results were generated using mid-resolution satellite images, qualitative and quantitative evaluations were performed. Linear false detection results were completely removed, and most of the sporadic and green algae false detection results that affected the distribution were removed. Even after the automatic false detection removal process, it was possible to confirm the distribution area of Sargassum horneri compared to the visual assessment results, and the accuracy and precision calculated using the binary classification model averaged 97.73% and 95.4%, respectively. Recall value was very low at 29.03%, which is presumed to be due to the effect of Sargassum horneri movement due to the observation time discrepancy between GOCI-II and mid-resolution satellite images, differences in spatial resolution, location deviation by orthocorrection, and cloud masking. The results of this study's removal of false detections of Sargassum horneri can determine the spatial distribution status in near real-time, but there are limitations in accurately estimating biomass. Therefore, continuous research on upgrading the Sargassum horneri monitoring system must be conducted to use it as data for establishing future Sargassum horneri response plans.

• Korean Journal of Remote Sensing
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• v.40 no.3
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• pp.295-305
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• 2024

This study aims to analyze the micro-sedimentary structures of the Hwangdo tidal flats using ultra-high resolution unmanned aerial vehicle (UAV) data. Tidal flats, located in the transitional area between land and sea, constantly change due to tidal activities and provide a unique environment important for understanding sedimentary processes and environmental conditions. Traditional field observation methods are limited in spatial and temporal coverage, and existing satellite imagery does not provide sufficient resolution to study micro-sedimentary structures. To overcome these limitations, high-resolution images of the Hwangdo tidal flats in Chungcheongnam-do were acquired using UAVs. This area has experienced significant changes in its sedimentary environment due to coastal development projects such as sea wall construction. From May 17 to 18, 2022, sediment samples were collected from 91 points during field surveys and 25 in-situ points were intensively analyzed. UAV data with a spatial resolution of approximately 0.9 mm allowed identifying and extracting parameters related to micro-sedimentary structures. For mud cracks, the length of the major axis of the polygons was extracted, and the wavelength and ripple symmetry index were extracted for ripple marks. The results of the study showed that in areas with mud content above 80%, mud cracks formed at an average major axis length of 37.3 cm. In regions with sand content above 60%, ripples with an average wavelength of 8 cm and a ripple symmetry index of 2.0 were formed. This study demonstrated that micro-sedimentary structures of tidal flats can be effectively analyzed using ultra-high resolution UAV data without field surveys. This highlights the potential of UAV technology as an important tool in environmental monitoring and coastal management and shows its usefulness in the study of sedimentary structures. In addition, the results of this study are expected to serve as baseline data for more accurate sedimentary facies classification.

• Journal of Korean Tunnelling and Underground Space Association
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• v.26 no.2
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• pp.129-152
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• 2024

In the application of deep learning object detection via CCTV in tunnels, a large number of false positive detections occur due to the poor environmental conditions of tunnels, such as low illumination and severe perspective effect. This problem directly impacts the reliability of the tunnel CCTV-based accident detection system reliant on object detection performance. Hence, it is necessary to reduce the number of false positive detections while also enhancing the number of true positive detections. Based on a deep learning object detection model, this paper proposes a false positive data training method that not only reduces false positives but also improves true positive detection performance through retraining of false positive data. This paper's false positive data training method is based on the following steps: initial training of a training dataset - inference of a validation dataset - correction of false positive data and dataset composition - addition to the training dataset and retraining. In this paper, experiments were conducted to verify the performance of this method. First, the optimal hyperparameters of the deep learning object detection model to be applied in this experiment were determined through previous experiments. Then, in this experiment, training image format was determined, and experiments were conducted sequentially to check the long-term performance improvement through retraining of repeated false detection datasets. As a result, in the first experiment, it was found that the inclusion of the background in the inferred image was more advantageous for object detection performance than the removal of the background excluding the object. In the second experiment, it was found that retraining by accumulating false positives from each level of retraining was more advantageous than retraining independently for each level of retraining in terms of continuous improvement of object detection performance. After retraining the false positive data with the method determined in the two experiments, the car object class showed excellent inference performance with an AP value of 0.95 or higher after the first retraining, and by the fifth retraining, the inference performance was improved by about 1.06 times compared to the initial inference. And the person object class continued to improve its inference performance as retraining progressed, and by the 18th retraining, it showed that it could self-improve its inference performance by more than 2.3 times compared to the initial inference.

• The Korean Journal of Nuclear Medicine Technology
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• v.14 no.1
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• pp.67-72
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• 2010

Purpose: In Asan Medical Center we perform myocardial perfusion SPECT to evaluate cardiac event risk level for non-cardiac surgery patients. In case of patients with cancer, we check tumor metastasis using whole body bone scan and whole body PET scan and then perform myocardial perfusion SPECT to reduce unnecessary exam. In case of short term in patients, we perform $^{201}Tl$ myocardial perfusion SPECT after whole body bone scan a minimum 16 hours in order to reduce hospitalization period but it is still the actual condition in which the evaluation about the affect of the crosstalk contamination due to the each other dissimilar isotope administration doesn't properly realize. So in our experiments, we try to evaluate crosstalk contamination influence on $^{201}Tl$ myocardial perfusion SPECT using anthropomorphic torso phantom and patient's data. Materials and Methods: From 2009 August to September, we analyzed 87 patients with $^{201}Tl$ myocardial perfusion SPECT. According to $^{201}Tl$ myocardial perfusion SPECT yesterday whole body bone scan possibility of carrying out, a patient was classified. The image data are obtained by using the dual energy window in $^{201}Tl$ myocardial perfusion SPECT. We analyzed $^{201}Tl$ and $^{99m}Tc$ counts ratio in each patients groups obtained image data. We utilized anthropomorphic torso phantom in our experiment and administrated $^{201}Tl$ 14.8 MBq (0.4 mCi) at myocardium and $^{99m}Tc$ 44.4 MBq (1.2 mCi) at extracardiac region. We obtained image by $^{201}Tl$ myocardial perfusion SPECT without gate method application and analyzed spatial resolution using Xeleris ver 2.0551. Results: In case of $^{201}Tl$ window and the counts rate comparison result yesterday whole body bone scan of being counted in $^{99m}Tc$ window, the difference in which a rate to 24 hours exponential-functionally notes in 1:0.114 with Ventri (GE Healthcare, Wisconsin, USA), 1:0.249 after the bone tracer injection in 12 hours in 1:0.411 with 1:0.79 with Infinia (GE healthcare, Wisconsin, USA) according to a reduction a time-out was shown (Ventri p=0.001, Infinia p=0.001). Moreover, the rate of the case in which it doesn't perform the whole body bone scan showed up as the average 1:$0.067{\pm}0.6$ of Ventri, and 1:$0.063{\pm}0.7$ of Infinia. According to the phantom after experiment spatial resolution measurement result, and an addition or no and time-out of $^{99m}Tc$ administrated, it doesn't note any change of FWHM (p=0.134). Conclusion: Through the experiments using anthropomorphic torso phantom and patients data, we found that $^{201}Tl$ myocardium perfusion SPECT image later carried out after the bone tracer injection with 16 hours this confirmed that it doesn't receive notable influence in spatial resolution by $^{99m}Tc$. But this investigation is only aimed to image quality, so it needs more investigation in patient's radiation dose and exam accuracy and precision. The exact guideline presentation about the exam interval should be made of the validation test which is exact and in which it is standardized about the affect of the crosstalk contamination according to the isotope use in which it is different later on.

• 한국지구물리탐사학회:학술대회논문집
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• 2002.09a
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• pp.139-162
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• 2002

Since weak zones or geological lineaments are likely to be eroded, weak zones may develop beneath rivers, and a careful evaluation of ground condition is important to construct structures passing through a river. Dc resistivity surveys, however, have seldomly applied to the investigation of water-covered area, possibly because of difficulties in data aquisition and interpretation. The data aquisition having high quality may be the most important factor, and is more difficult than that in land survey, due to the water layer overlying the underground structure to be imaged. Through the numerical modeling and the analysis of case histories, we studied the method of resistivity survey at the water-covered area, starting from the characteristics of measured data, via data acquisition method, to the interpretation method. We unfolded our discussion according to the installed locations of electrodes, ie., floating them on the water surface, and installing at the water bottom, since the methods of data acquisition and interpretation vary depending on the electrode location. Through this study, we could confirm that the dc resistivity method can provide the fairly reasonable subsurface images. It was also shown that installing electrodes at the water bottom can give the subsurface image with much higher resolution than floating them on the water surface. Since the data acquired at the water-covered area have much lower sensitivity to the underground structure than those at the land, and can be contaminated by the higher noise, such as streaming potential, it would be very important to select the acquisition method and electrode array being able to provide the higher signal-to-noise ratio data as well as the high resolving power. The method installing electrodes at the water bottom is suitable to the detailed survey because of much higher resolving power, whereas the method floating them, especially streamer dc resistivity survey, is to the reconnaissance survey owing of very high speed of field work.