• Korean Journal of Heritage: History & Science
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• v.51 no.2
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• pp.22-37
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• 2018

Unmanned aerial vehicles (UAV) have attracted considerable attention both at home and abroad. The UAV is equipped with a camera that shoots images, which is advantageous for access to areas where archaeological investigations are not possible. Moreover, it is possible to acquire three-dimensional spatial image information by modeling the terrain through aerial photographing, and it is possible to specify the interpretation of the terrain of the survey area. In addition, if we understand the change of the terrain through comparison with past aerial photographs, it will be very helpful to grasp the existence of the ruins. The terrain modeling for searching these remains can be divided into two parts. First, we acquire the aerial photographs of the current terrain using the drone. Then, using image registration and post-processing, we complete the image-joining and terrain-modeling using past aerial photographs. The completed modeled terrain can be used to derive several analytical results. In the present terrain modeling, terrain analysis such as DSM, DTM, and altitude analysis can be performed to roughly grasp the characteristics of the change in the form, quality, and micro-topography. Past terrain modeling of aerial photographs allows us to understand the shape of landforms and micro-topography in wetlands. When verified with actual findings and overlapping data on the modelling of each terrain, it is believed that changes in hill shapes and buried Microform can be identified as helpful when used in low-flying applications. Thus, modeling data using aerial photographs is useful for identifying the reasons for the inability to carry out archaeological surveys, the existence of terrain and ruins in a wide area, and to discuss the preservation process of the ruins. Furthermore, it is possible to provide various themes, such as cadastral maps and land use maps, through comparison of past and present topographical data. However, it is certain that it will function as a new investigation methodology for the exploration of ruins in order to discover archaeological cultural properties.

• Korean Journal of Heritage: History & Science
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• v.43 no.2
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• pp.40-59
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• 2010

Anssolim is the unique technique which standing columns lean in a inward direction of buildings in traditional architecture, which has not been thoroughly investigated to this day. With a dearth of previous studies, the anssolim technique can only be examined through detailed three-dimensional surveys. The main halls of Korean palaces can be seen as buildings that were built with the regulations of the day in mind, making them excellent research subjects when studying the anssolim technique. The findings can be summarized as follows. 1. In the main halls that were studied, anssolim was applied most to main space (eokan) columns, then lessened for peripheral columns. 2. The largest second-floor cheoma columns were placed inward in the eokan, then became smaller as with the peripheral columns. In the case of the eokan, the columns were arranged according to the size of the anssolim. 3. The second-floor cheoma column anssolim in the middle-floor main hall were generally a third or a quarter of the size of those on the first floor. As on the first floor, the largest anssolim were applied to the eokan columns, then became gradually smaller towards the periphery columns. 4. In the palace main halls, the largest anssolim were used for the eokan columns, and became smaller with the peripheral columns. This unique structure can be seen to be a Korean technique that deviates from the Chinese "Yingzaofashi(營造法式)" techniques. Although this study is limited in that it only studies the main hall of Korean palaces, it is significant in that it shed new light on the technological implications of the anssolim technique, and can be used as important data for research into the history of technology. Although this type of data is difficult to extrapolate, it has been made as accurate as possible by minimizing the margin of error in the data for the palaces that were actually studied.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.3
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• pp.82-98
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• 2019

The importance of spatial information is rapidly rising. In particular, 3D spatial information construction and modeling for Real World Objects, such as smart cities and digital twins, has become an important core technology. The constructed 3D spatial information is used in various fields such as land management, landscape analysis, environment and welfare service. Three-dimensional modeling with image has the hig visibility and reality of objects by generating texturing. However, some texturing might have occlusion area inevitably generated due to physical deposits such as roadside trees, adjacent objects, vehicles, banners, etc. at the time of acquiring image Such occlusion area is a major cause of the deterioration of reality and accuracy of the constructed 3D modeling. Various studies have been conducted to solve the occlusion area. Recently the researches of deep learning algorithm have been conducted for detecting and resolving the occlusion area. For deep learning algorithm, sufficient training data is required, and the collected training data quality directly affects the performance and the result of the deep learning. Therefore, this study analyzed the ability of detecting the occlusion area of the image using various image quality to verify the performance and the result of deep learning according to the quality of the learning data. An image containing an object that causes occlusion is generated for each artificial and quantified image quality and applied to the implemented deep learning algorithm. The study found that the image quality for adjusting brightness was lower at 0.56 detection ratio for brighter images and that the image quality for pixel size and artificial noise control decreased rapidly from images adjusted from the main image to the middle level. In the F-measure performance evaluation method, the change in noise-controlled image resolution was the highest at 0.53 points. The ability to detect occlusion zones by image quality will be used as a valuable criterion for actual application of deep learning in the future. In the acquiring image, it is expected to contribute a lot to the practical application of deep learning by providing a certain level of image acquisition.

• Journal of Environmental Impact Assessment
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• v.30 no.5
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• pp.271-296
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• 2021

Since the thermal stratification in a reservoir inhibits the vertical mixing of the upper and lower layers and causes the formation of a hypoxia layer and the enhancement of nutrients release from the sediment, changes in the stratification structure of the reservoir according to future climate change are very important in terms of water quality and aquatic ecology management. This study was aimed to develop a data-driven inflow water temperature prediction model for Daecheong Reservoir (DR), and to predict future inflow water temperature and the stratification structure of DR considering future climate scenarios of Representative Concentration Pathways (RCP). The random forest (RF)regression model (NSE 0.97, RMSE 1.86℃, MAPE 9.45%) developed to predict the inflow temperature of DR adequately reproduced the statistics and variability of the observed water temperature. Future meteorological data for each RCP scenario predicted by the regional climate model (HadGEM3-RA) was input into RF model to predict the inflow water temperature, and a three-dimensional hydrodynamic model (AEM3D) was used to predict the change in the future (2018~2037, 2038~2057, 2058~2077, 2078~2097) stratification structure of DR due to climate change. As a result, the rates of increase in air temperature and inflow water temperature was 0.14~0.48℃/10year and 0.21~0.41℃/10year,respectively. As a result of seasonal analysis, in all scenarios except spring and winter in the RCP 2.6, the increase in inflow water temperature was statistically significant, and the increase rate was higher as the carbon reduction effort was weaker. The increase rate of the surface water temperature of the reservoir was in the range of 0.04~0.38℃/10year, and the stratification period was gradually increased in all scenarios. In particular, when the RCP 8.5 scenario is applied, the number of stratification days is expected to increase by about 24 days. These results were consistent with the results of previous studies that climate change strengthens the stratification intensity of lakes and reservoirs and prolonged the stratification period, and suggested that prolonged water temperature stratification could cause changes in the aquatic ecosystem, such as spatial expansion of the low-oxygen layer, an increase in sediment nutrient release, and changed in the dominant species of algae in the water body.

• Korean Journal of Remote Sensing
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• v.38 no.5_3
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• pp.939-951
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• 2022

The most important factor in designing autonomous driving systems is to recognize the exact location of the vehicle within the surrounding environment. To date, various sensors and navigation systems have been used for autonomous driving systems; however, all have limitations. Therefore, the need for high-definition (HD) maps that provide high-precision infrastructure information for safe and convenient autonomous driving is increasing. HD maps are drawn using three-dimensional point cloud data acquired through a mobile mapping system (MMS). However, this process requires manual work due to the large numbers of points and drawing layers, increasing the cost and effort associated with HD mapping. The objective of this study was to improve the efficiency of HD mapping by segmenting semantic information in an MMS point cloud into six classes: roads, curbs, sidewalks, medians, lanes, and other elements. Segmentation was performed using various machine learning techniques including random forest (RF), support vector machine (SVM), k-nearest neighbor (KNN), and gradient-boosting machine (GBM), and 11 variables including geometry, color, intensity, and other road design features. MMS point cloud data for a 130-m section of a five-lane road near Minam Station in Busan, were used to evaluate the segmentation models; the average F1 scores of the models were 95.43% for RF, 92.1% for SVM, 91.05% for GBM, and 82.63% for KNN. The RF model showed the best segmentation performance, with F1 scores of 99.3%, 95.5%, 94.5%, 93.5%, and 90.1% for roads, sidewalks, curbs, medians, and lanes, respectively. The variable importance results of the RF model showed high mean decrease accuracy and mean decrease gini for XY dist. and Z dist. variables related to road design, respectively. Thus, variables related to road design contributed significantly to the segmentation of semantic information. The results of this study demonstrate the applicability of segmentation of MMS point cloud data based on machine learning, and will help to reduce the cost and effort associated with HD mapping.

• The korean journal of orthodontics
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• v.27 no.5 s.64
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• pp.815-824
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• 1997

The purpose of this study is to develop the basic algorithm for the finite element method modeling of individual malocclusions. Usually, a great deal of time is spent in preprocessing. To reduce the time required, we developed a standardized procedure for measuring the position of each tooth and a program to automatically preprocess. The following procedures were carried to complete this study. 1. Twenty-eight teeth morphologies were constructed three-dimensionally for the finite element analysis and saved as separate files. 2. Standard brackets were attached so that the FA points coincide with the center of the brackets. 3. The study model of a patient was made. 4. Using the study model, the crown inclination, angulation, and the vertical distance from the tip of a tooth was measured by using specially designed tools. 5. The arch form was determined from a picture of the model with an image processing technique. 6. The measured data were input as a rotational matrix. 7. The program provides an output file containing the necessary information about the three-dimensional position of teeth, which is applicable to several finite element programs commonly used. The program for a basic algorithm was made with Turbo-C and the subsequent outfile was applied to ANSYS. This standardized model measuring procedure and the program reduce the time required, especially for preprocessing and can be applied to other malocclusions easily.

• Journal of the Korean Association of Geographic Information Studies
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• v.14 no.3
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• pp.78-95
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• 2011

This study has developed various DEMs with different spatial resolutions using many different interpolation methods with the aid of a 1:5,000 digital map. In addition, this study has evaluated the vertical accuracy of various DEMs constructed by check point data obtained from the network RTK GPS survey. The obtained results suggest that a DEM developed from the TIN-based Terrain method performs well in evaluating height restriction of buildings in a flying safety area considering general RMSE values, land-type RMSE values and profile evaluation results, etc. And, it has been found that three meters is the right spatial resolution for a DEM in evaluating height restriction of buildings in a flying safety area. Meanwhile, elevation values obtained by the DEM are not point estimation values but interval estimation values. This can be used to check whether the height of buildings in the vicinity of an airfield violates height limitation values of the area. To check whether the height of buildings measured in interval estimation values violates height limitation values of the area, this study has adopted three steps: 1) high probability of violation, 2) low probability of violation, 3) inconclusiveness about the violation. The obtained results will provide an important basis for developing a GIS related to the evaluation of height restriction of buildings in the vicinity of an airfield. Furthermore, although results are limited to the study area, the vertical accuracy values of the DEM constructed from a two-dimensional digital map may provide useful information to researchers who try to use DEMs.

• Journal of the Korean Society of Clothing and Textiles
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• v.29 no.12 s.148
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• pp.1595-1607
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• 2005

Three-dimensional(3-D) body scanners used to capture anthropometric measurements are now becoming a common research tool far apparel. This study had two goals, to test the accuracy and reliability of 3-D measurements of dynamic postures, and !o analyze the change in upper body surface measurements between the standard anthropometric position and various dynamic positions. A comparison of body surface measurements using two different measuring methods, 3-D scan measurements using virtual tools on the computer screen and traditional manual measurements for a standard anthropometric posture and for a posture with shoulder flexion were $-2\~20mm$. Girth items showed some disagreement of values between the two methods. None of the measurements were significantly different except f3r the neckbase girth for any of the measuring methods or postures. Scan measurements of the upper body items showed significant linear surface change in the dynamic postures. Shoulder length, interscye front and back, and biacromion length were the items most affected in the dynamic postures. Changes of linear body surface were very similar for the two measuring methods within the same posture. The repeatability of data taken from the 3-D scans using virtual tools showed satisfactory results. Three times repeated scan measurements f3r the scapula protraction and scapula elevation posture were proven to be statistically the same for all measurement items. Measurements from automatic measuring software that measured the 3-D scan with no manual intervention were compared with the measurements using virtual tools. Many measurements from the automatic program were larger and showed quite different values.

• Korean Journal of Applied Biomechanics
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• v.12 no.2
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• pp.17-32
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• 2002

The purpose of this study was to find the rational method to analyze golf swing with specific property of club shaft. Three subjects were filmed by two high speed digital cameras with 500 fps. The phase analyzed was downswing of each subject. The three-dimensional coordinates of the anatomical landmarks were obtained with motion analysis system Kwon3d 3.0 version and smoothed by lowpass digital filter with cutoff frequency 6Hz. From these data, kinematic and kinetic variables were calculated using Matlab(ver 5.0) The variables for this study were angular velocity and accelerations, which were calculated and following conclusions have been made : 1) Golf swing time of stiff club is faster than that of regular club. 2) In shoulder joint motion of swing with the stiff club, x-stiff showed mort rapid negative acceleration than that of regular club. 3) In regular club, the velocity of club head would be more effective velocity, which was increasing, than those of other clubs before impact. 4) In wrist joint motion of swing with stiff club, x-stiff club showed faster than regular club in the downswing and impact more rapid negative acceleration.

• Korean Journal of Biological Psychiatry
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• v.5 no.1
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• pp.95-101
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• 1998

The changes of electroencephalogram(EEG) in patients with dementia of Alzheimer's type are most commonly studied by analyzing power or magnitude in traditionally defined frequency bands. However because of the absence of an identified metric which quantifies the complex amount of information, there are many limitations in using such a linear method. According to the chaos theory, irregular signals of EEG can be also resulted from low dimensional deterministic chaos. Chaotic nonlinear dynamics in the EEG can be studied by calculating the largest Lyapunov exponent($L_1$). The authors have analyzed EEG epochs from three patients with dementia of Alzheimer's type and three matched control subjects. The largest $L_1$ is calculated from EEG epochs consisting of 16,384 data points per channel in 15 channels. The results showed that patients with dementia of Alzheimer's type had significantly lower $L_1$ than non-demented controls on 8 channels. Topographic analysis showed that the $L_1$ were significantly lower in patients with Alzheimer's disease on all the frontal, temporal, central, and occipital head regions. These results show that brains of patients with dementia of Alzheimer's type have a decreased chaotic quality of electrophysiological behavior. We conclude that the nonlinear analysis such as calculating the $L_1$ can be a promising tool for detecting relative changes in the complexity of brain dynamics.