• Journal of Broadcast Engineering
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• v.26 no.4
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• pp.429-440
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• 2021

With the recent development of deep convolutional neural network learning, deep learning techniques applied to single image super-resolution are showing good results. One of the existing deep learning-based super-resolution techniques is RDN(Residual Dense Network), in which the initial feature information is transmitted to the last layer using residual dense blocks, and subsequent layers are restored using input information of previous layers. However, if all hierarchical features are connected and learned and a large number of residual dense blocks are stacked, despite good performance, a large number of parameters and huge computational load are needed, so it takes a lot of time to learn a network and a slow processing speed, and it is not applicable to a mobile system. In this paper, we use the residual dense structure, which is a continuous memory structure that reuses previous information, and the residual dense channel attention block using the channel attention method that determines the importance according to the feature map of the image. We propose a method that can increase the depth to obtain a large receptive field and maintain a concise model at the same time. As a result of the experiment, the proposed network obtained PSNR as low as 0.205dB on average at 4× magnification compared to RDN, but about 1.8 times faster processing speed, about 10 times less number of parameters and about 1.74 times less computation.

• Journal of the Korea Institute of Building Construction
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• v.21 no.3
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• pp.203-211
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• 2021

Recently, the insulaton design standards for reducing the energy use of buildings have been strengthened. Althoug insulation work is the most cost-effective method for reducing the primary energy consumption per unit area of a building, there are no evaluation criteria for insulation performance at the time of construction and completion inspection. The purpose of this study is to provide objective data by establishing a standard for an analysis method and a method for easily experimenting with the exterior wall thermal transmittance of an apartment house using a thermal transmittance measuring device(TESTO 435). For the exterior wall of the test subject, the specific heat per unit area exceeded 20kJ/(m²·K), and the data at the end point suitable for ISO 9869-1 were analyzed by the average method. The measured values of the thermal transmittance for 3 consecutive days converged within +5% of the desing value, and the standard deviation of the thermal transmittance by day decreased in the order of 1-Day > 3-Day > 2-Day. The standard deviation of the thermal transmittance by time period decreased in the order of 00:00~24:00 < 19:00~07:00 < 00:00~07:00. The measured value of the thermal transmittance for the time perion of 00:00 to 07:00 per day almost coincided with an error of -3% to + 2% compare to the desing value.

• Tunnel and Underground Space
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• v.32 no.6
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• pp.451-463
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• 2022

Whenever a mineshaft accidentally collapses, speedy risk assessment is both required and crucial. But onsite safety diagnosis by humans is reportedly difficult considering the additional risk of collapse of the unstable mineshaft. Generally, drones equipped with high-speed lidar sensors can be used for such inspection. However, the drone technology is restrictively applicable at very shallow depth, failing in mineshafts with depths of hundreds of meters because of the limit of wireless communication and turbulence inside the mineshaft. In previous study, a three-dimensional (3D) scanning system with a single channel lidar was fabricated and operated using towed cable in a mineshaft to a depth of 200 m. The rotation and pendulum movement errors of the measuring unit were compensated for by applying the data of inertial measuring unit and comparing the similarity between the scan data of the adjacent depths (Kim et al., 2020). However, the errors grew with scan depth. In this paper, a multi-channel lidar sensor to obtain a continuous cross-sectional image of the mineshaft from a winch system pulled from bottom upward. In this new approach, within overlapped region viewed by the multi-channel lidar, rotation error was compensated for by comparing the similarity between the scan data at the same depth. The fabricated system was applied to scan 0-165 m depth of the mineshaft with 180 m depth. The reconstructed image was depicted in a 3D graph for interpretation.

• The Journal of Engineering Geology
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• v.33 no.1
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• pp.39-49
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• 2023

Soil contaminants measured and managed in Korea include those of geologic origin such as arsenic, cadmium, copper, lead, zinc, nickel, mercury, and fluoride. This study identifies the distribution of these contaminants using GIS modeling to analyze the spatial probability of soil contamination originating from geology. The modeling found that cadmium, copper, lead, nickel, and mercury often exceed the regulated standard by <1%. Concentrations of arsenic and zinc greatly exceeded the standard in the vicinity of mines and industrial complexes: mining and industry seemed to have substantial effects on the concentrations of these metals. Although fluoride was sampled at the lowest number of points, its frequency of exceeding the standard was the highest. No obvious source of artificial contamination has been identified, and fluoride's distribution characteristics showed continuity over a wide area, suggesting a strong correlation between geological characteristics and fluoride concentration. The highest frequencies of fluoride exceeding the standard were in Jurassic granite (40.00%) and Precambrian banded gneiss (34.12%). As these rocks contributed to the formation of soil through their weathering, high fluoride concentrations can be expected in soil in areas where these rocks are distributed.

• Journal of Intelligence and Information Systems
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• v.29 no.3
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• pp.267-286
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• 2023

The conversational agents such as AI speakers utilize voice conversation for human-computer interaction. Voice recognition errors often occur in conversational situations. Recognition errors in user utterance records can be categorized into two types. The first type is misrecognition errors, where the agent fails to recognize the user's speech entirely. The second type is misinterpretation errors, where the user's speech is recognized and services are provided, but the interpretation differs from the user's intention. Among these, misinterpretation errors require separate error detection as they are recorded as successful service interactions. In this study, various text separation methods were applied to detect misinterpretation. For each of these text separation methods, the similarity of consecutive speech pairs using word embedding and document embedding techniques, which convert words and documents into vectors. This approach goes beyond simple word-based similarity calculation to explore a new method for detecting misinterpretation errors. The research method involved utilizing real user utterance records to train and develop a detection model by applying patterns of misinterpretation error causes. The results revealed that the most significant analysis result was obtained through initial consonant extraction for detecting misinterpretation errors caused by the use of unregistered neologisms. Through comparison with other separation methods, different error types could be observed. This study has two main implications. First, for misinterpretation errors that are difficult to detect due to lack of recognition, the study proposed diverse text separation methods and found a novel method that improved performance remarkably. Second, if this is applied to conversational agents or voice recognition services requiring neologism detection, patterns of errors occurring from the voice recognition stage can be specified. The study proposed and verified that even if not categorized as errors, services can be provided according to user-desired results.

• Korean Journal of Environmental Biology
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• v.40 no.3
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• pp.247-254
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• 2022

To investigate the tolerance limit and critical thermal maximum (CTM), behavioral responses of wild goldeye rockfish Sebastes thompsoni according to exposure to high water temperature were observed using a continuous behavior tracking system. As a result, behavioral index (BI) of S. thompsoni in each temperature (20.0, 25.0, and 30.0℃) showed a significant difference (p<0.05) when compared with the value measured in a stable condition of 15.0℃. The activity level of S. thompsoni exposed to 25.0℃ decreased sharply after 20 hours. Their rest time at the bottom of experiment chamber increased, and their normal swimming and metabolic activities were disturbed. In addition, at a high water temperature of 30.0℃, S. thompsoni reached the limit of resistance and showed a sub-lethal reaction of swimming behavior, with energy consumption in the body increased and all test organisms died. In conclusion, the eco-physiological response of S. thompsoni to water temperature varied greatly depending on the fluctuation range of the exposed temperature and the exposure time. In addition, the tolerance limit of S. thompsoni to high water temperature was predicted to be 25.0-30.0℃. The maximum critical thermal that had a great influence on the survival of this species was found to be around 30.0℃.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.5C
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• pp.293-301
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• 2008

Soil profiling is one of the most important work among geotehnical engineering practice. Generally, soil profile is estimated from the observation of soil samples during subsurface exploration but such estimation also includes some experiencing aspects such as flushed water from the borehole, slime colour, boring speed and so on. In addition, since the capacity of hydraulic drill rig is significantly increased, thin layers might be easily missed. So, continuous soil profile is almost impossible over all depth to be bored from conventional subsurface exploration. While CPT or CPTu can serve continuous soil profile information over all depth generally in 5cm interval. Many charts or methods for soil profile from CPT result have been proposed during last several decades over the world. However they have not been verified in local ground condition in Korea. In this research, CPT results and soil classification results based on USCS were compiled from 17 sites over the Korea. Soil classification results by using 7 CPT soil classification charts were compared with those of USCS for the compiled database. Most proper CPT soil classification chart for Korean soil characteristics was evaluated and effective parameters for the soil classification from CPT were discussed. Finally interrelationship between CPT soil classification chart and USCS soil classification was evaluated.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.121-121
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• 2022

한국과 미국은 2018년 8월에 발표한 메콩우호국(Friends of the Lower Mekong, FLM) "메콩지역 수자원 데이터 관리 및 정보공유 강화에 관한 공동성명"을 계기로 메콩유역의 실시간 수자원 변동 모니터링 및 분석과 수자원 데이터 공동활용 역량을 강화하여 효율적이고 과학적인 수자원관리 지원과 함께 한국의 신남방정책과 미국의 인도-태평양 전략 시너지효과를 극대화하고자 메콩 주변국 재해경감 및 수자원 데이터 활용 역량강화를 위한 글로벌 위성기반 수문자료의 생산·활용 및 홍수·가뭄 등의 수재해 분석기술을 개발하고 있다. 여기에는 한국 K-water의 물관리 기술과 미국 NASA, USACE의 위성활용 및 수자원분석 기술을 접목하여 메콩지역의 체계적인 물관리 및 재해로부터 안전성 확보 기여에 목표를 두고 연구를 진행 중에 있다. 본 연구에서는 전 세계적으로 광범위하게 활용되고 있는 미공병단(USACE, U.S. Army Corps of Engineers)의 HEC software 프로그램을 메콩 시범지역(pilot area)에 적용하여 수리/수문모델 구축을 진행하고 있다. 구축되는 모형은 유역 상류 댐의 연계 모의운영 및 하류 홍수분석이 동시 가능한 HEC-RTS(Real-Time Simulation)로 이는 HEC-HMS, -ResSim, -RAS와 -FIA 모형이 순차적으로 결합된 수리/수문 모델링 시스템이다. 모형의 시범적용 지역은 현지 메콩위원회(MRC, Mekong River Comission)의 의견 등을 반영, 메콩강 하류지역(Lower Mekong) 본류 유역에 위성자료 활용 및 준실시간(near real-time)으로 댐 모의운영 등을 고려할 수 있는 JingHong댐(중국 란창강 최하류)에서 라오스 Xayaburi댐(메콩강 최상류)까지의 구간을 선정하였으며, 전년도에는HEC-RTS 중 HMS(Hydrologic Modeling System) 모형 적용을 중심으로 가용한 위성자료(GPM IMERG)를 활용하여 과거 홍수사상에 대한 모의를 고려한 강우-유출모형의 구축을 완료하였다. 이에 연속하여 금년도에는 동일유역 내 하천 단면 등이 확보된 Chiang Saen 지점에서 Xayaburi 댐까지의 구간에 대해 RAS(River Analysis System)을 구축할 예정으로 구축된 RAS 모형은 HEC-RTS에 포함되어 메콩 시범지역의 종합적 수리/수문분석에 적용될 예정이다.

• Journal of the Korean Geotechnical Society
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• v.39 no.11
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• pp.7-22
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• 2023

In January 2022, a new legislation was enforced to enhance the safety of underground construction. Consequently, a comprehensive assessment of underground safety is now an integral part of the planning process, including an evaluation of its impact. Ensuring the stability of temporary retaining walls during underground excavation has become paramount, prompting a heightened focus on the assessment of underground safety. This study delves into the analysis of the Multi-axis Flat Continuous Soil Cement Wall retaining wall (MFS) construction method. This method facilitates the expansion of wall thickness in the ground and provides flexibility in selecting and spacing H-piles. Through laboratory model tests, we scrutinized the load-displacement behavior of the wall, varying the H-pile installation intervals using the MFS method. Additionally, a 3-dimensional numerical analysis was conducted to explore the influence of H-pile installation intervals and sizes on the load for different thicknesses of the MFS retaining wall. The displacement analysis yielded the calculation of the height of the arching effect acting on the wall. To further our understanding, a design method was introduced, quantitatively analyzing the results of axial force and shear force acting on the wall. This involved applying the maximum arching height, calculated by the MFS method, to the existing member force review method. The axial force and shear force, contingent on the H-pile installation interval and size applied to the MFS retaining wall, demonstrated a reduction effect ranging from 24.6% to 62.9%.

• Korean Journal of Remote Sensing
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• v.39 no.6_2
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• pp.1541-1551
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• 2023

Radiometric calibration is a fundamental step in ocean color remote sensing since the step to derive solar radiance spectrum in visible to near-infrared wavelengths from the sensor-observed electromagnetic signals. Generally, satellite sensor suffers from degradation over the mission period, which results in biases/uncertainties in radiometric calibration and the final ocean products such as water-leaving radiance, chlorophyll-a concentration, and colored dissolved organic matter. Therefore, the importance of radiometric calibration for the continuity of ocean color satellites has been emphasized internationally. This study introduces an approach to improve the radiometric calibration algorithm for the visible bands of the Geostationary Ocean Color Imager-II (GOCI-II) satellite with a focus on stability. Solar Diffuser (SD) measurements were employed as an on-orbit radiometric calibration reference, to obtain the continuous monitoring of absolute gain values. Time series analysis of GOCI-II absolute gains revealed seasonal variations depending on the azimuth angle, as well as long-term trends by possible sensor degradation effects. To resolve the complexities in gain variability, an azimuth angle correction model was developed to eliminate seasonal periodicity, and a sensor degradation correction model was applied to estimate nonlinear trends in the absolute gain parameters. The results demonstrate the effects of the azimuth angle correction and sensor degradation correction model on the spectrum of Top of Atmosphere (TOA) radiance, confirming the capability for improving the long-term stability of GOCI-II data.