Purpose. The purpose of this study was to evaluate the performance efficiency of two different drill combinations according to the heat generated and drilling time. Materials and methods. In this study, cow ribs were used as research materials. To test the specimen, cow bones were rid of fascia and muscles, and a temperature sensor was mounted around the drilling area. The experimental group was divided into a group using a guide drill and a group using a Lindmann drill according to the drill used before the initial drilling. The drilling sequence of the guide drilling group is as follows; guide drill (ø 2.25), initial drill (ø 2.25), twist drill (ø 2.80), and twist drill (ø 3.20). The drilling sequence of the Lindmann drilling group is as follows; Lindmann drill (ø 2.10), initial drill (ø 2.25), twist drill (ø 2.80), and twist drill (ø 3.20). The temperature was measured after drilling. For statistical analysis, the difference between the groups was analyzed using the Mann-Whitney U test and the Friedman test was used (α = .05). Results. The average performance efficiency for each specimen of guide drilling group ranged from 0.3861 to 1.1385 mm3/s and that of Lindmann drilling group ranged from 0.1700 to 0.4199 mm3/s. The two drill combinations contained a guide drill and Lindmann drill as their first drills. The combination using the guide drill demonstrated excellent performance efficiency when calculated using the drilling time (P < .001). Conclusion. Since the guide drill group showed better performance efficiency than the Lindmann drill group, the use of the guide drill was more suitable for the primary drilling process.
Journal of the Korean Association of Geographic Information Studies
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v.24
no.4
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pp.41-54
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2021
It is very essential to estimate the water body area using remote exploration for water resource management, analysis and prediction of water disaster damage. Hydrophysical detection using satellites has been mainly performed on large satellites equipped with optical and SAR sensors. However, due to the long repeat cycle, there is a limitation that timely utilization is impossible in the event of a disaster/disaster. With the recent active development of Micro satellites, it has served as an opportunity to overcome the limitations of time resolution centered on existing large satellites. The Micro satellites currently in active operation are ICEYE in Finland and Capella satellites in the United States, and are operated in the form of clusters for earth observation purposes. Due to clustering operation, it has a short revisit cycle and high resolution and has the advantage of being able to observe regardless of weather or day and night with the SAR sensor mounted. In this study, the operation status and characteristics of micro satellites were described, and the water area estimation technology optimized for micro SAR satellite images was applied to the Daecheong Dam basin on the Korean Peninsula. In addition, accuracy verification was performed based on the reference value of the water generated from the optical satellite Sentinel-2 satellite as a reference. In the case of the Capella satellite, the smallest difference in area was shown, and it was confirmed that all three images showed high correlation. Through the results of this study, it was confirmed that despite the low NESZ of Micro satellites, it is possible to estimate the water area, and it is believed that the limitations of water resource/water disaster monitoring using existing large SAR satellites can be overcome.
Han, Seok Gi;Joo, Ji Yong;Lee, Jun Ho;Park, Sang Yeong;Kim, Young Soo;Jung, Yong Suk;Jung, Do Hwan;Huh, Joon;Lee, Kihun
Korean Journal of Optics and Photonics
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v.33
no.4
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pp.167-176
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2022
Adaptive optics (AO) systems compensate for atmospheric disturbance, especially phase distortion, by introducing counter-wavefront deformation calculated from real-time wavefront sensing or prediction. Because AO system implementations are time-consuming and costly, it is highly desirable to estimate the system's performance during the development of the AO system or its parts. Among several techniques, we mostly apply statistical analysis, computational simulation, and optical-bench tests. Statistical analysis estimates performance based on the sum of performance variances due to all design parameters, but ignores any correlation between them. Computational simulation models every part of an adaptive optics system, including atmospheric disturbance and a closed loop between wavefront sensor and deformable mirror, as close as possible to reality, but there are still some differences between simulation models and reality. The optical-bench test implements an almost identical AO system on an optical bench, to confirm the predictions of the previous methods. We are currently developing an AO system for a 1.6-m ground telescope using a deformable mirror that was recently developed in South Korea. This paper reports the results of the statistical analysis and computer simulation for the system's design and confirmation. For the analysis, we apply the Strehl ratio as the performance criterion, and the median seeing conditions at the Bohyun observatory in Korea. The statistical analysis predicts a Strehl ratio of 0.31. The simulation method similarly reports a slightly larger value of 0.32. During the study, the simulation method exhibits run-to-run variation due to the random nature of atmospheric disturbance, which converges when the simulation time is longer than 0.9 seconds, i.e., approximately 240 times the critical time constant of the applied atmospheric disturbance.
Kwak, Tae-Soo;Kim, Won-Seok;Lee, Sun Ho;Kwak, Ihn-Sil
Korean Journal of Ecology and Environment
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v.54
no.4
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pp.272-279
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2021
A pump-type eDNA filtering system that can control voltage and hydraulic pressure respectively has been developed, and applied a filter case that can filter out without damaging the filter. The filtering performance of the developed system was evaluated by comparing the eDNA concentration with the conventional vacuum-pressured filtering method at the catchment conduit intake reservoir. The developed system was divided into a voltage control (manual pump system) method and a pressure control (automatic pump system) method, and the pressure was measured during filtering and the pressure change of each system was compared. The voltage control method started with 65 [KPa] at the beginning of the filtering, and as the filtering time elapsed, the amount of filtrate accumulated in the filter increased, so the pressure gradually increased. As a result of controlling the pressure control method to maintain a constant pressure according to the designed algorithm, there was a difference in the width of the hydraulic pressure fluctuation during the filtering process according to the feedback time of the hydraulic pressure sensor, and it was confirmed that the pressure was converged to the target pressure. The filtering performance of the developed system was confirmed by measuring the eDNA concentration and comparing the voltage control method and the hydraulic control method with the control group. The voltage control method obtained similar results to the control group, but the hydraulic control method showed lower results than the control group. It is considered that the low eDNA concentration in the hydraulic control method is due to the large pressure deviation during filtering and maintaining a constant pressure during the filtering process. Therefore, rather than maintaining a constant pressure during filtering, it was confirmed that a voltage control method in which the pressure is gradually increased as the filtrate increases with the lapse of filtering time is suitable for collecting eDNA. As a result of comparing the average concentration of eDNA in lentic zone and lotic zone as a control group, it was found to be 96.2 [ng µL-1] and 88.4 [ng µL-1l], respectively. The result of comparing the average concentration of eDNA by the pump method was also high in the lentic zone sample as 90.7 [ng µL-1] and 74.8 [ng µL-1] in the lentic zone and the lotic zone, respectively. The high eDNA concentration in the lentic zone is thought to be due to the influence of microorganisms including the remaining eDNA.
Kim, Hee-Young;Park, Kyung-Ae;Kwak, Byeong-Dae;Joo, Hui-Tae;Lee, Joon-Soo
Journal of the Korean earth science society
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v.43
no.5
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pp.604-617
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2022
Sea surface temperature (SST) is a key variable that can be used to understand ocean-atmosphere phenomena and predict climate change. Satellite microwave remote sensing enables the measurement of SST despite the presence of clouds and precipitation in the sensor path. Therefore, considering the high utilization of microwave SST, it is necessary to continuously verify its accuracy and analyze its error characteristics. In this study, the validation of the microwave global precision measurement (GPM)/GPM microwave imager (GMI) SST around the Northwest Pacific and Korean Peninsula was conducted using surface drifter temperature data for approximately eight years from March 2014 to December 2021. The GMI SST showed a bias of 0.09K and an average root mean square error of 0.97K compared to the actual SST, which was slightly higher than that observed in previous studies. In addition, the error characteristics of the GMI SST were related to environmental factors, such as latitude, distance from the coast, sea wind, and water vapor volume. Errors tended to increase in areas close to coastal areas within 300 km of land and in high-latitude areas. In addition, relatively high errors were found in the range of weak wind speeds (<6 m s-1) during the day and strong wind speeds (>10 m s-1) at night. Atmospheric water vapor contributed to high SST differences in very low ranges of <30 mm and in very high ranges of >60 mm. These errors are consistent with those observed in previous studies, in which GMI data were less accurate at low SST and were estimated to be due to differences in land and ocean radiation, wind-induced changes in sea surface roughness, and absorption of water vapor into the microwave atmosphere. These results suggest that the characteristics of the GMI SST differences should be clarified for more extensive use of microwave satellite SST calculations in the seas around the Korean Peninsula, including a part of the Northwest Pacific.
Automatic Target Recognition (ATR) technology is emerging as a core technology of Future Combat Systems (FCS). Conventional ATR is performed based on IMINT (image information) collected from the SAR sensor, and various image-based deep learning models are used. However, with the development of IT and sensing technology, even though data/information related to ATR is expanding to HUMINT (human information) and SIGINT (signal information), ATR still contains image oriented IMINT data only is being used. In complex and diversified battlefield situations, it is difficult to guarantee high-level ATR accuracy and generalization performance with image data alone. Therefore, we propose a knowledge graph-based ATR method that can utilize image and text data simultaneously in this paper. The main idea of the knowledge graph and deep model-based ATR method is to convert the ATR image and text into graphs according to the characteristics of each data, align it to the knowledge graph, and connect the heterogeneous ATR data through the knowledge graph. In order to convert the ATR image into a graph, an object-tag graph consisting of object tags as nodes is generated from the image by using the pre-trained image object recognition model and the vocabulary of the knowledge graph. On the other hand, the ATR text uses the pre-trained language model, TF-IDF, co-occurrence word graph, and the vocabulary of knowledge graph to generate a word graph composed of nodes with key vocabulary for the ATR. The generated two types of graphs are connected to the knowledge graph using the entity alignment model for improvement of the ATR performance from images and texts. To prove the superiority of the proposed method, 227 documents from web documents and 61,714 RDF triples from dbpedia were collected, and comparison experiments were performed on precision, recall, and f1-score in a perspective of the entity alignment..
Agricultural reservoirs are essential structures for water supplies during dry period in the Korean peninsula, where water resources are temporally unequally distributed. For efficient water management, systematic and effective monitoring of medium-small reservoirs is required. Synthetic Aperture Radar (SAR) provides a way for continuous monitoring of those, with its capability of all-weather observation. This study aims to evaluate the applicability of SAR in monitoring medium-small reservoirs using Sentinel-1 (10 m resolution) and Capella X-SAR (1 m resolution), at Chari (CR), Galjeon (GJ), Dwitgol (DG) reservoirs located in Ulsan, Korea. Water detected results applying Z fuzzy function-based threshold (Z-thresh) and Chan-vese (CV), an object detection-based segmentation algorithm, are quantitatively evaluated using UAV-detected water boundary (UWB). Accuracy metrics from Z-thresh were 0.87, 0.89, 0.77 (at CR, GJ, DG, respectively) using Sentinel-1 and 0.78, 0.72, 0.81 using Capella, and improvements were observed when CV was applied (Sentinel-1: 0.94, 0.89, 0.84, Capella: 0.92, 0.89, 0.93). Boundaries of the waterbody detected from Capella agreed relatively well with UWB; however, false- and un-detections occurred from speckle noises, due to its high resolution. When masked with optical sensor-based supplementary images, improvements up to 13% were observed. More effective water resource management is expected to be possible with continuous monitoring of available water quantity, when more accurate and precise SAR-based water detection technique is developed.
Choi, Gyeong Lee;Lim, Mi Young;Kim, So Hui;Rho, Mi Young
Journal of Bio-Environment Control
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v.31
no.4
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pp.444-451
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2022
Recently, long-term cultivation is becoming more common with the increase in tomato hydroponics. In hydroponics, it is very important to supply an appropriate nutrient solution considering the nutrient and moisture requirements of crops, in terms of productivity, resource use, and environmental conservation. Since seasonal environmental changes appear severely in long-term cultivation, it is so critical to manage irrigation control considering these changes. Therefore, this study was carried out to investigate the effect of irrigation volume on growth and yield in tomato long-term cultivation using coir substrate. The irrigation volume was adjusted at 4 levels (high, medium high, medium low and low) by different irrigation frequency. Irrigation scheduling (frequency) was controlled based on solar radiation which measured by radiation sensor installed outside the greenhouse and performed whenever accumulated solar radiation energy reached set value. Set value of integrated solar radiation was changed by the growing season. The results revealed that the higher irrigation volume caused the higher drainage rate, which could prevent the EC of drainage from rising excessively. As the cultivation period elapsed, the EC of the drainage increased. And the lower irrigation volume supplied, the more the increase in EC of the drainage. Plant length was shorter in the low irrigation volume treatment compared to the other treatments. But irrigation volume did not affect the number of nodes and fruit clusters. The number of fruit settings was not significantly affected by the irrigation volume in general, but high irrigation volume significantly decreased fruit setting and yield of the 12-15th cluster developed during low temperature period. Blossom-end rot occurred early with a high incidence rate in the low irrigation volume treatment group. The highest weight fruits was obtained from the high irrigation treatment group, while the medium high treatment group had the highest total yield. As a result of the experiment, it could be confirmed the effect of irrigation amount on the nutrient and moisture stabilization in the root zone and yield, in addition to the importance of proper irrigation control when cultivating tomato plants hydroponically using coir substrate. Therefore, it is necessary to continue the research on this topic, as it is judged that the precise irrigation control algorithm based on root zone-information applied to the integrated environmental control system, will contribute to the improvement of crop productivity as well as the development of hydroponics control techniques.
Analysis Ready Data (ARD) for optical satellite images represents a pre-processed product by applying spectral characteristics and viewing parameters for each sensor. The atmospheric correction is one of the fundamental and complicated topics, which helps to produce Top-of-Atmosphere (TOA) and Top-of-Canopy (TOC) reflectance from multi-spectral image sets. Most remote sensing software provides algorithms or processing schemes dedicated to those corrections of the Landsat-8 OLI sensors. Furthermore, Google Earth Engine (GEE), provides direct access to Landsat reflectance products, USGS-based ARD (USGS-ARD), on the cloud environment. We implemented the Orfeo ToolBox (OTB) atmospheric correction extension, an open-source remote sensing software for manipulating and analyzing high-resolution satellite images. This is the first tool because OTB has not provided calibration modules for any Landsat sensors. Using this extension software, we conducted the absolute atmospheric correction on the Landsat-8 OLI images of Railroad Valley, United States (RVUS) to validate their reflectance products using reflectance data sets of RVUS in the RadCalNet portal. The results showed that the reflectance products using the OTB extension for Landsat revealed a difference by less than 5% compared to RadCalNet RVUS data. In addition, we performed a comparative analysis with reflectance products obtained from other open-source tools such as a QGIS semi-automatic classification plugin and SAGA, besides USGS-ARD products. The reflectance products by the OTB extension showed a high consistency to those of USGS-ARD within the acceptable level in the measurement data range of the RadCalNet RVUS, compared to those of the other two open-source tools. In this study, the verification of the atmospheric calibration processor in OTB extension was carried out, and it proved the application possibility for other satellite sensors in the Compact Advanced Satellite (CAS)-500 or new optical satellites.
Journal of the Korea Institute of Building Construction
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v.22
no.6
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pp.651-662
/
2022
The electrochemical impedance spectroscopy(EIS) method was used to evaluate the concrete deterioration process related to chloride-induced steel corrosion with various corrosion levels(initiation, rust propagation and acceleration periods). The impressed current technique, with four total current levels of 0C, 13C, 65C and 130C, was used to accelerate steel corrosion in concrete cylinder samples with w/c ratio of 0.4, 0.5, and 0.6, immersed in a 0.5M NaCl solution. A series of EIS measurements was performed to monitor concrete deterioration during the accelerated corrosion test in this study. Some critical parameters of the equivalent circuit were obtained through the EIS analysis. It was observed that the charge transfer resistance(Rc) dropped sharply as the impressed current increased from 0C to 13C, indicating a value of approximately 10kΩcm2. However, the sensitivity of Rc significantly decreased when the impressed current was further increased from 13C to 130C after corrosion of steel had been initiated. Meanwhile, the double-layer capacitance value(Cdl) linearly increased from 50×10-6μF/cm2 to 250×10-6μF/cm2 as the impressed current in creased from 0C to 130C. The results in this study showed that monitoring Cdl is an effective measurement parameter for evaluating the progress of internal concrete damages(de-bonding between steel and concrete, micro-cracks, and surface-breaking cracks) induced by steel corrosion. The findings of this study provide a fundamental basis for developing an embedded sensor and signal interpretation method for monitoring concrete deterioration due to steel corrosion at various corrosion levels.
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