Kim, Dae-Ha;Bahk, Jang-Jun;Lee, Jin-Heuck;Ryu, Byong-Jae;Kim, Ji-Hoon;Chun, Jong-Hwa;Torres, Marta E.;Chang, Chan-Dong
Economic and Environmental Geology
/
v.45
no.4
/
pp.397-406
/
2012
During the 2nd Ulleung Basin Gas Hydrate Drilling Expedition (UBGH2) in 2010, gas-hydrate-bearing sediment cores were recovered at 10 drill sites. Base, on Infrared (IR) thermal image and grain-size analysis of the cores, three distinct types of gas hydrate are classified: Type I (fracture-filling in mud layers), Type II (disseminated in mud layers), and Type III (pore-filling in sand layers). Types I and II gas hydrates occur in mud as discrete veins, nodules or disseminated particles. Type III fills the pore spaces of the sand layers encased in mud layers. In this case, the sand content of hosting sediments shows a general linear relationship with gas hydrate saturation. The degrees of temperature anomalies (${\Delta}T$) from IR images generally increase with gas hydrate saturation regardless of gas hydrate occurrence types. Type I is dominantly found in the sites where seismic profiles delineate chimney structures, whereas Type II where the drill cores are composed almost of mud layers. Type III was mainly recovered from the sites where hemipelagic muds are frequently intercalated with turbidite sand layers. Our results indicate that gas hydrate occurrence is closely related to sedimentological characteristic of gas hydrate-bearing sediments, that is, grain size distribution.
Kim, Jong-uk;Choi, Sung-yong;Jin, Kyong-son;Hwang, Woo-jun;Min, Sang-jun;Lee, Sun-ho;Lee, Sang-ryong
Journal of Acupuncture Research
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v.21
no.1
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pp.226-239
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2004
Objective: Purpose of this study was to examine the effect of electroacupuncture(EA) at Xingjian(LR2) as 'Fire(火)' point of The Leg Absolute Um Liver Meridan(足厥陰肝經 : Chok-Kworum-Kan-Kyong) on the facial thermal change. Methods: Subjects of this study were 15 patients with upperpart(includes head and facial part) fever of human body and two examinations were carried out in each other day. We divided cases of two examinations into two groups. One is experimental group(N=15) that was carried out electroacupuncture stimulation at Xingjian(LR2), the other is control group(N=15) which was carried out electroacupuncture stimulation at optional point(in space between 1st and 2nd fingers) except acupuncture points of 12 meridians. We took the temperature of fixed areas on face by digital infrared thermal image(D.I.T.I.) before and after electroacupuncture stimulation. Those fixed areas on face that was taken temperature are Jingming(BL1), Sibai(ST2), Dicang(ST4), Indang, Shuigou(GV26), Chengjiang(CV24) areas. In cases of temperature of Jingming(BL1), Sibai(ST2), Dicang(ST4) areas, we applied each mean of left and right temperature to statical analysis. Results: In the group of electroacupuncture stimulation at Xingjian(LR2), temperature of every fixed areas on face fell: Jingming(BL1) area's ${\Delta}T=-0.7007{\pm}0.78642$, Sibai(ST2) area's ${\Delta}T=-0.6280{\pm}0.56439$, Dicang(ST4) area's ${\Delta}T=-0.5940{\pm}0.60179$, Indang area's ${\Delta}T=-0.7200{\pm}0.64515$, Shuigou(GV26) area's ${\Delta}T=-0.6160{\pm}0.80487$, Chengjiang(CV24) area's ${\Delta}T=-0.5627{\pm}0.72615$. In Xingjian(LR2) electroacupuncture group, each temperature of Jingming(BL1), Sibai(ST2), Indang areas showed a drop significantly in comparison with control group (p<0.05). But each temperature of Dicang(ST4), Shuigou(GV26), Chengjiang(CV24) areas did not showed a drop significantly in comparison with control group(p>0.05). Conclusions: The results mentioned above showed that electroacupuncture stimulation at Xingjian(LR2) significantly decreased the temperature on face of patients with upperpart fever of human body. In Xingjian(LR2) electroacupuncture group, especially temperature of upper part of face includes eye, cheekbone, forehead regions showed a drop significantly in comparison with control group.
Journal of the Korean Association of Geographic Information Studies
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v.23
no.2
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pp.21-35
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2020
Vegetation information is a very important factor used in various fields such as urban planning, landscaping, water resources, and the environment. Vegetation varies according to canopy density or chlorophyll content, but vegetation vitality is not considered when classifying vegetation areas in previous studies. In this study, in order to satisfy various applied studies, a study was conducted to set a threshold value of vegetation index considering vegetation vitality. First, an eBee fixed-wing drone was equipped with a multi-spectral camera to construct optical and near-infrared orthomosaic images. Then, GIS calculation was performed for each orthomosaic image to calculate the NDVI, GNDVI, SAVI, and MSAVI vegetation index. In addition, the vegetation position of the target site was investigated through VRS survey, and the accuracy of each vegetation index was evaluated using vegetation vitality. As a result, the scenario in which the vegetation vitality point was selected as the vegetation area was higher in the classification accuracy of the vegetation index than the scenario in which the vegetation vitality point was slightly insufficient. In addition, the Kappa coefficient for each vegetation index calculated by overlapping with each site survey point was used to select the best threshold value of vegetation index for classifying vegetation by scenario. Therefore, the evaluation of vegetation index accuracy considering the vegetation vitality suggested in this study is expected to provide useful information for decision-making support in various business fields such as city planning in the future.
In this study, the experiment of the measuring of four different types of flooring materials' thermal characteristics was conducted and examined during the summer. The experimental materials were arranged on the existing slab of the roof, and then its thermal characteristics were examined from the point of view of thermal radiation analysis. The aim of this study is ultimately to draw the fundamental data for improvements in a building's thermal function and reduce the urban heat island phenomena through optimizing the thermal characteristics of the surface covering materials of a building. The results from this study are as follows; 1) Each experimental material's albedo was calculated as 0.83 on the aluminum panel, 0.40 on the rock block, 0.37 on the wood deck and 0.21 on the concrete. It shows that the concrete material, which has the lowest short wave reflective rate, absorbed the most radiation energy and the aluminium panel has absorbed the lowest radiation energy. 2) From the each experimental object's value of the long wave radiation, the concrete material measured the highest, at $628W/m^2$, and the aluminium panel measured the lowest at $412W/m^2$. Therefore, it verifies that the experimental objects' own radiation rate determines the amount of the long wave radiation. 3) The degree of energy absorbency of a building's surface covering materials is greatly influenced by its own albedo and radiation rate, Therefore, it needs to be considered for the improvements in a building's thermal function and reducing the urban heat island phenomena. 4) According to the evaluation result of the each experimental object's overall heat transmission screening function on the roof of a building, the wooden deck is proven to be an excellent material for excluding the outside temperature differences effectively with its characteristic of low heat capacity and conduction. Also its surface temperature on the roof slab and the temperature difference during the day were both measured at low.
This report does studied for making the method of conserving bracket murals in Daeungjeon of Jikjisa Temple, through the scientific way. Results of evaluated the conservation status at the braket mural paintings, most serious damage is structural damage like cracks, breakage, and delamination. After optical investigation, a characteristic point wasn't found such as underdrawing or traces of a coat of paint. The ultrasonic examination speed by each wall painting was measured from about 195.8 m/s to 392.7 m/s, according to the location of the surface, and it was able to compare the surface properties according to the location. In Infrared-thermal image measurement shows that wall layer separation and paint layer delamination are closely detected, therefore it was able to judge of damage on the objective way. Material analysis revealed that the walls were made by sand and weathering soil. The wall layer combined sand with less than fine sand size by nearly 5:5, and the finishing layer was found to have mixed medium sand and fine sand at approximately 6:4 rates. However, In case of finishing layer, mixing ratios of sizes less than very fine sand were found to be significantly lower than wall. Therefore, it is estimated that the plysical damage such as the separation between the layers of the walls created in the braket mural paintings, is continuously caused by changes in the internal stresses and volume ratio caused by the density differences between the wall and the finishing layers.
The goal of this study is to implement a communication system that can monitor the status of the nacelle using the power cable itself, without the dedicated communication lines such as an UTP cable and optical fiber for the offshore wind turbine. An inductive coupling powerline communication system for a MW class offshore wind turbine was proposed and its communication performance was demonstrated. The inductive couplers was designed for operation at up to 500 A using a ferrite composite materials. Field test was carried out on the wind farms of Jeju island. Using the iperf communication test program, we have obtained more than 15 Mbps data transmission rate through the 100 m power cable that was installed between the nacelle and the bottom of the power converter. In the data transmission stability test for a week, there was no failure ever. The minimum transmission rate was 15 Mbps and the average data rate was about 20 Mbps. Next, we have installed an infrared camera inside the nacelle in order to measure the temperature distribution and variation of the nacelle. The real-time thermal image taken by the camera was successfully sent to the monitoring system without error.
The Journal of The Korea Institute of Intelligent Transport Systems
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v.2
no.1
s.2
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pp.25-40
/
2003
The purpose of this thesis is development of detection algorithm for stop-line detector. Detail detection area is set in basing detection area($1.8{\times}4.0m$) and traffic information(volume, occupancy, nonoccupancy) is collected by passive infrared detector at designing detection area. The basis detection area($1.8{\times}4.0m$) is named existing PIR and detection area applied on development algorithm is named proposal PIR. The proposal PIR is collected data such volume, occupancy, nonoccupancy, speed and lane change, but this thesis is limited to evaluate for volume, occupancy and nonoccupancy The procedure and each step of being developed algorithm is described in the next (1) The detection area of proposal PIR is made up of 2 of $1.8{\times}0.6m$ size(the detection area is named 1 and 3) and 1 of $1.8{\times}1.78m$ size(the detection area is named 2) (2) The image detection area is set on monitor to analyze outdoor photographing data then video frame analysis has been done by analyzer. (3) The occupancy, nonoccupancy and speed data of vehicle have been collected with the detection area 1 and 3 and lane change has been collected with combination of detection area 1, 2 and 3 The MAD and MAPE have been utilized to being compared with volume, occupancy and nonoccupancy for the field application and evaluation of a algorithm As the result, the proposal PIR data have been identified superior to the existing PIR data and the effect has been improved its information(volume, occupancy and nonoccupancy)
In line with the trend of industrial innovation, IoT technology utilized in a variety of fields is emerging as a key element in creation of new business models and the provision of user-friendly services through the combination of big data. The accumulated data from devices with the Internet-of-Things (IoT) is being used in many ways to build a convenience-based smart system as it can provide customized intelligent systems through user environment and pattern analysis. Recently, it has been applied to innovation in the public domain and has been using it for smart city and smart transportation, such as solving traffic and crime problems using CCTV. In particular, it is necessary to comprehensively consider the easiness of securing real-time service data and the stability of security when planning underground services or establishing movement amount control information system to enhance citizens' or commuters' convenience in circumstances with the congestion of public transportation such as subways, urban railways, etc. However, previous studies that utilize image data have limitations in reducing the performance of object detection under private issue and abnormal conditions. The IoT device-based sensor data used in this study is free from private issue because it does not require identification for individuals, and can be effectively utilized to build intelligent public services for unspecified people. Especially, sensor data stored by the IoT device need not be identified to an individual, and can be effectively utilized for constructing intelligent public services for many and unspecified people as data free form private issue. We utilize the IoT-based infrared sensor devices for an intelligent pedestrian tracking system in metro service which many people use on a daily basis and temperature data measured by sensors are therein transmitted in real time. The experimental environment for collecting data detected in real time from sensors was established for the equally-spaced midpoints of 4×4 upper parts in the ceiling of subway entrances where the actual movement amount of passengers is high, and it measured the temperature change for objects entering and leaving the detection spots. The measured data have gone through a preprocessing in which the reference values for 16 different areas are set and the difference values between the temperatures in 16 distinct areas and their reference values per unit of time are calculated. This corresponds to the methodology that maximizes movement within the detection area. In addition, the size of the data was increased by 10 times in order to more sensitively reflect the difference in temperature by area. For example, if the temperature data collected from the sensor at a given time were 28.5℃, the data analysis was conducted by changing the value to 285. As above, the data collected from sensors have the characteristics of time series data and image data with 4×4 resolution. Reflecting the characteristics of the measured, preprocessed data, we finally propose a hybrid algorithm that combines CNN in superior performance for image classification and LSTM, especially suitable for analyzing time series data, as referred to CNN-LSTM (Convolutional Neural Network-Long Short Term Memory). In the study, the CNN-LSTM algorithm is used to predict the number of passing persons in one of 4×4 detection areas. We verified the validation of the proposed model by taking performance comparison with other artificial intelligence algorithms such as Multi-Layer Perceptron (MLP), Long Short Term Memory (LSTM) and RNN-LSTM (Recurrent Neural Network-Long Short Term Memory). As a result of the experiment, proposed CNN-LSTM hybrid model compared to MLP, LSTM and RNN-LSTM has the best predictive performance. By utilizing the proposed devices and models, it is expected various metro services will be provided with no illegal issue about the personal information such as real-time monitoring of public transport facilities and emergency situation response services on the basis of congestion. However, the data have been collected by selecting one side of the entrances as the subject of analysis, and the data collected for a short period of time have been applied to the prediction. There exists the limitation that the verification of application in other environments needs to be carried out. In the future, it is expected that more reliability will be provided for the proposed model if experimental data is sufficiently collected in various environments or if learning data is further configured by measuring data in other sensors.
Cloud detection means determining the presence or absence of clouds in a pixel in a satellite image, and acts as an important factor affecting the utility and accuracy of the satellite image. In this study, among the satellites of various advanced organizations that provide cloud detection data, we intend to perform quantitative and qualitative comparative analysis on the difference between the cloud detection data of GK-2A/AMI, Terra/MODIS, and Suomi-NPP/VIIRS. As a result of quantitative comparison, the Proportion Correct (PC) index values in January were 74.16% for GK-2A & MODIS, 75.39% for GK-2A & VIIRS, and 87.35% for GK-2A & MODIS in April, and GK-2A & VIIRS showed that 87.71% of clouds were detected in April compared to January without much difference by satellite. As for the qualitative comparison results, when compared with RGB images, it was confirmed that the results corresponding to April rather than January detected clouds better than the previous quantitative results. However, if thin clouds or snow cover exist, each satellite were some differences in the cloud detection results.
Normalized Difference Vegetation Index (NDVI) is the most widely used remote sensing data in the agricultural field and is currently provided by most optical satellites. In particular, as high-resolution optical satellite images become available, the selection of optimal optical satellite images according to agricultural applications has become a very important issue. In this study, we aim to define the most optimal optical satellite image when monitoring NDVI in rice fields in Korea and derive the resolution-related requirements necessary for this. For this purpose, we compared and analyzed the spatial distribution and time series patterns of the Dangjin rice paddy in Korea from 2019 to 2022 using NDVI images from MOD13, Landsat-8, Sentinel-2A/B, and PlanetScope satellites, which are widely used around the world. Each data is provided with a spatial resolution of 3 m to 250 m and various periods, and the area of the spectral band used to calculate NDVI also has slight differences. As a result of the analysis, Landsat-8 showed the lowest NDVI value and had very low spatial variation. In comparison, the MOD13 NDVI image showed similar spatial distribution and time series patterns as the PlanetScope data but was affected by the area surrounding the rice field due to low spatial resolution. Sentinel-2A/B showed relatively low NDVI values due to the wide near-infrared band area, and this feature was especially noticeable in the early stages of growth. PlanetScope's NDVI provides detailed spatial variation and stable time series patterns, but considering its high purchase price, it is considered to be more useful in small field areas than in spatially uniform rice paddy. Accordingly, for rice field areas, 250 m MOD13 NDVI or 10 m Sentinel-2A/B are considered to be the most efficient, but high-resolution satellite images can be used to estimate detailed physical quantities of individual crops.
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