• Archives of Plastic Surgery
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• 제47권2호
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• pp.178-181
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• 2020

In this report, we present a case in which good results were achieved by treatment using a free jejunal patch graft with virtual endoscopy (VE) assistance in a patient whose swallowing had failed to improve for 40 years after he mistakenly swallowed sulfuric acid, despite pectoralis major myocutaneous flap grafting and frequent balloon dilatation surgery. During the last 20 years, virtual computed tomography imaging has improved remarkably and continues to be used to address new challenges. For reconstructive surgeons, the greatest advantage of VE is that it is a noninvasive modality capable of visualizing areas inaccessible to a flexible endoscope. Using VE findings, we were able to visualize the 3-dimensional shape beyond the stenosis. VE can also help predict the area of the defect after contracture release.

• Smart Structures and Systems
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• 제5권4호
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• pp.317-328
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• 2009

Current maintenance operations and integrity checks on a wide array of structures require personnel entry into normally-inaccessible or hazardous areas to perform necessary nondestructive inspections. To gain access for these inspections, structure must be disassembled and removed or personnel must be transported to remote locations. The use of in-situ sensors, coupled with remote interrogation, can be employed to overcome a myriad of inspection impediments stemming from accessibility limitations, complex geometries, the location and depth of hidden damage, and the isolated location of the structure. Furthermore, prevention of unexpected flaw growth and structural failure could be improved if on-board health monitoring systems were used to more regularly assess structural integrity. A research program has been completed to develop and validate Comparative Vacuum Monitoring (CVM) Sensors for surface crack detection. Statistical methods using one-sided tolerance intervals were employed to derive Probability of Detection (POD) levels for a wide array of application scenarios. Multi-year field tests were also conducted to study the deployment and long-term operation of CVM sensors on aircraft. This paper presents the quantitative crack detection capabilities of the CVM sensor, its performance in actual flight environments, and the prospects for structural health monitoring applications on aircraft and other civil structures.

• Journal of Information Processing Systems
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• 제16권3호
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• pp.733-741
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• 2020

A smart dust monitoring system is useful for obtaining information on rough terrain that is difficult for humans to access. One of ways to deploy sensors to gather information in smart dust environment is to use an aircraft in the Amazon rainforest to scatter an enormous amount of small and cheap sensors (or smart dust devices), or to use an unmanned spacecraft to throw the sensors on the moon's surface. However, scattering an enormous amount of smart dust devices creates the difficulty of managing such devices as they can be scattered into inaccessible areas, and also causes problems such as bottlenecks, device failure, and high/low density of devices. Of the various problems that may occur in the smart dust environment, this paper is focused on solving the bottleneck problem. To address this, we propose and construct a three-layered hierarchical smart dust monitoring system that includes relay dust devices (RDDs). An RDD is a smart dust device with relatively higher computing/communicating power than a normal smart dust device. RDDs play a crucial role in reducing traffic load for the system. To validate the proposed system, we use climate data obtained from authorized portals to compare the system with other systems (i.e., non-hierarchical system and simple hierarchical system). Through this comparison, we determined that the transmission processing time is reduced by 49%-50% compared to other systems, and the maximum number of connectable devices can be increased by 16-32 times without compromising the system's operations.

• 한국측량학회지
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• 제40권5호
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• pp.439-448
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• 2022

MV (Moving Vehicle) detection using satellite imagery is important for traffic monitoring and provides a wide range of observations. Specifically, MV detection methods utilizing the time lag in single-pass optical satellite images have been studied for detecting MVs from a single set of images. Because of limitations in detecting MVs outside of roads, most previous studies required road information to limit the moving object to cars on the road. However, it is difficult to obtain road information from inaccessible areas. Therefore, this study proposed a new method for detecting MVs regardless of their locations from single-pass optical satellite images without using additional data. WV-3 (Worldview-3) satellite images were used, and a spatial correlation coefficient map was proposed to detect spatial displacement which denotes MVs across two WV-3 MS images. Finally, evaluation was performed through quantitative metrics and visual inspection. The evaluation results revealed that the proposed method can detect MV movements from the single-pass satellite images. On the contrary, misdetected or undetected MVs due to radiometric differences between the images could be identified by visual inspection. The performance of the proposed method can be improved by minimizing radiometric variations and adding conditions that are robust to radiometric differences between the images.

• Advances in Energy Research
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• 제8권4호
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• pp.203-211
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• 2022

The aim of this paper is to analyze the performance of commercial fuel cell (rated capacity 1000W) with the help of resistive load and output power variation with change in H₂ flow rate and calculate the maximum power point (MPP) of the proton exchange membrane (PEM) while changing AC and DC load respectively. The factors influencing the output power of a fuel cell are hydrogen flow rate, cell temperature, and membrane water content. The results show that when the H₂ flow rate is changed from 11, 13, and 15 Lpm, MPP is increased from lower to higher flow rate. The power of the fuel cell is increased at the rate of 29% by increasing the flow rate from 11 to 15 lpm. This study will allow small-scale industries and residential buildings (in remote or inaccessible areas) to characterize the performance of PEMFC. Furthermore, fuel cell helps in reducing emission in the environment compared to fossil fuels. Also, fuel cells are ecofriendly as well as cost effective and can be the best alternative way to convert energy.

• 대한원격탐사학회지
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• 제40권2호
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• pp.123-139
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• 2024

Forest vertical structure is vital for comprehending ecosystems and biodiversity, in addition to fundamental forest information. Currently, the forest vertical structure is predominantly assessed via an in-situ method, which is not only difficult to apply to inaccessible locations or large areas but also costly and requires substantial human resources. Therefore, mapping systems based on remote sensing data have been actively explored. Recently, research on analyzing and classifying images using machine learning techniques has been actively conducted and applied to map the vertical structure of forests accurately. In this study, Sentinel-2 and digital surface model images were obtained on two different dates separated by approximately one month, and the spectral index and tree height maps were generated separately. Furthermore, according to the acquisition time, the input data were separated into cases 1 and 2, which were then combined to generate case 3. Using these data, forest vetical structure mapping models based on random forest, support vector machine, and extreme gradient boost(XGBoost)were generated. Consequently, nine models were generated, with the XGBoost model in Case 3 performing the best, with an average precision of 0.99 and an F1 score of 0.91. We confirmed that generating a forest vertical structure mapping model utilizing bi-seasonal data and an appropriate model can result in an accuracy of 90% or higher.

• Earthquakes and Structures
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• 제20권2호
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• pp.149-160
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• 2021

Buildings made using the locally available clay materials are amongst the least expensive forms of construction in many developing countries, and therefore, widely popular in remote areas. It is despite the fact that these low-strength masonry structures are vulnerable to seismic forces. Since transporting imported materials like cement and steel in areas inaccessible by motorable roads is challenging and financially unviable. This paper presents, and experimentally investigates, adobe masonry structures that utilize the abundantly available local clay materials with moderate use of imported materials like cement, aggregates, and steel. Shake-table tests were performed on two 1:3 reduce-scaled adobe masonry models for experimental seismic testing and verification. The model AM1 was confined with vertical lightly reinforced concrete columns provided at all corners and reinforced concrete horizontal bands (i.e., tie beams) provided at sill, lintel, and eave levels. The model AM2 was confined only with the horizontal bands provided at sill, lintel, and eave levels. The models were subjected to sinusoidal base motions for studying the damage evolution and response of the model under dynamic lateral loading. The lateral forcedeformation capacity curves for both models were developed and bi-linearized to compute the seismic response parameters: stiffness, strength, ductility, and response modification factor R. Seismic performance levels, story-drift, base shear coefficient, and the expected structural damages, were defined for both the models. Seismic performance assessment of the selected models was carried out using the lateral seismic force procedure to evaluate their safety in different seismic zones. The use of vertical columns in AM1 has shown a considerable increase in the lateral strength of the model in comparison to AM2. Although an R factor equal to 2.0 is recommended for both the models, AM1 has exhibited better seismic performance in all seismic zones due to its relatively high lateral strength in comparison to AM2.

• 대한토목학회논문집
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• 제41권3호
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• pp.317-325
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• 2021

1988년 부산에서 처음 발병된 소나무재선충병(Pine Wilt Disease, PWD)은 우리나라 소나무에 막대한 피해를 주고 있는 심각한 질병이다. 정부에서는 2005년 소나무재선충병 방제특별법을 제정하고 피해지역의 소나무 이동 금지와 방제를 시행하고 있다. 하지만, 기존의 예찰 및 방제방법은 산악지형에서 동시다발적이고 급진적으로 발생하는 소나무재선충병을 줄이기에는 물리적, 경제적 어려움이 있다. 따라서 본 연구에서는 소나무재선충병 감염의심목을 효율적으로 탐지하기 위해 무인항공기를 이용한 영상자료를 바탕으로 딥러닝 객체인식 예찰 방법의 활용가능성을 제시하고자 한다. 소나무재선충병 피해목을 관측하기 위해서 항공촬영을 통해 영상 데이터를 획득하고 정사영상을 제작하였다. 그 결과 198개의 피해목이 확인되었으며, 이를 검증하기 위해서 접근이 불가한 급경사지나 절벽과 같은 곳을 제외하고 현장 조사를 진행하여 84개의 피해목을 확인할 수 있었다. 검증된 데이터를 가지고 분할방법인 SegNet과 검출방법인 YOLOv2를 이용하여 분석한 결과 성능은 각각 0.57, 0.77로 나타났다.

• 한국측량학회지
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• 제39권6호
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• pp.533-540
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• 2021

고해상도 위성영상은 극지 내륙 지역과 같이 접근이 어려운 지역에 대해서도 공간 정보를 획득할 수 있는 탁월한 접근성을 가진다. 고해상도 위성영상으로부터 도출되는 공간정보의 위치 정확도를 향상시키기 위해서는 기준점을 활용하는데, 이러한 접근 불가 지역에 대해서는 기준점 획득이 쉽지 않기 때문에 여러 보조 데이터를 쓰기도 하나, 그러한 보조 데이터 마저 획득이 어려운 지역이 존재한다. 따라서 본 논문에서는 완전한 무기준점 기반으로 위치 정확도를 향상시키기 위한 방법으로 멀티 영상의 번들조정을 기반으로 정확도 향상의 정도를 평가하였다. 멀티 영상 조정을 위해 영상 간의 매칭점를 추출하여 활용하였고, 개별 영상 또는 스테레오 영상의 조정이 아닌 전체 영상의 통합 센서 모델링을 구현하여 정확도 향상 정도를 평가하였다. 실험으로 아리랑 3A 영상을 활용하였으며, 실험결과 RMSE (Root Mean Square Error) 오차의 현격한 향상은 도출하기 어려웠으나, 최대오차를 감소시키는 효과가 있었으며, 특히 표고 방향으로의 과대오차를 감소시키는데 효과적임을 알 수 있었다.

• 한국지형학회지
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• 제28권1호
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• pp.83-99
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• 2021

Burn severity analysis using satellite imagery has high capabilities for research and management in inaccessible areas. We extracted the forest fire area of the DMZ (Demilitarized Zone) in the western Imjin Estuary which is restricted to access due to the confrontation between South and North Korea. Then we analyzed the forest fire severity and recoverability using atmospheric corrected Surface Reflectance Level-2 data collected from Landsat-8 OLI (Operational Land Imagery) / TIRS (Thermal Infrared Sensor). Normalized Burn Ratio (NBR), differenced NBR (dNBR), and Relative dNBR (RdNBR) were analyzed based on changes in the spectral pattern of satellite images to estimate burn severity area and intensity. Also, we evaluated the recoverability after a forest fire using a land cover map which is constructed from the NBR, dNBR, and RdNBR analyzed results. The results of dNBR and RdNBR analysis for the six years (during May 30, 2014 - May 30, 2020) showed that the intensity of monthly burn severity was affected by seasonal changes after the outbreak and the intensity of annual burn severity gradually decreased after the fire events. The regrowth of vegetation was detected in most of the affected areas for three years (until May 2020) after the forest fire reoccurred in May 2017. The monthly recoverability (from April 2014 to December 2015) of forests and grass fields was increased and decreased per month depending on the vegetation growth rate of each season. In the case of annual recoverability, the growth of forest and grass field was reset caused by the recurrence of a forest fire in 2017, then gradually recovered with grass fields from 2017 to 2020. We confirmed that remote sensing was effectively applied to research of the burn severity and recoverability in the DMZ. This study would also provide implications for the management and construction statistics database of the forest fire in the DMZ.