• Korean Journal of Remote Sensing
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• v.38 no.5_3
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• pp.967-977
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• 2022

The occurrence and intensity of wildfires are increasing with climate change. Emissions from forest fire smoke are recognized as one of the major causes affecting air quality and the greenhouse effect. The use of satellite product and machine learning is essential for detection of forest fire smoke. Until now, research on forest fire smoke detection has had difficulties due to difficulties in cloud identification and vague standards of boundaries. The purpose of this study is to detect forest fire smoke using Level 1 and Level 2 data of Geostationary Environment Monitoring Spectrometer (GEMS), a Korean environmental satellite sensor, and machine learning. In March 2022, the forest fire in Gangwon-do was selected as a case. Smoke pixel classification modeling was performed by producing wildfire smoke label images and inputting GEMS Level 1 and Level 2 data to the random forest model. In the trained model, the importance of input variables is Aerosol Optical Depth (AOD), 380 nm and 340 nm radiance difference, Ultra-Violet Aerosol Index (UVAI), Visible Aerosol Index (VisAI), Single Scattering Albedo (SSA), formaldehyde (HCHO), nitrogen dioxide (NO₂), 380 nm radiance, and 340 nm radiance were shown in that order. In addition, in the estimation of the forest fire smoke probability (0 ≤ p ≤ 1) for 2,704 pixels, Mean Bias Error (MBE) is -0.002, Mean Absolute Error (MAE) is 0.026, Root Mean Square Error (RMSE) is 0.087, and Correlation Coefficient (CC) showed an accuracy of 0.981.

• Progress in Medical Physics
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• v.25 no.3
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• pp.139-142
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• 2014

The purpose of this study was to develop a system of clinical application of reconstructed dose that includes dose reconstruction, reconstructed dose registration between fractions of treatment, and dose-volume-histogram generation and to demonstrate the system on a deformable prostate phantom. To achieve this purpose, a deformable prostate phantom was embedded into a 20 cm-deep and 40 cm-wide water phantom. The phantom was CT scanned and the anatomical models of prostate, seminal vesicles, and rectum were contoured. A coplanar 4-field intensity modulated radiation therapy (IMRT) plan was used for this study. Organ deformation was simulated by inserting a "transrectal" balloon containing 20 ml of water. A new CT scan was obtained and the deformed structures were contoured. Dose responses in phantoms and electronic portal imaging device (EPID) were calculated by using the XVMC Monte Carlo code. The IMRT plan was delivered to the two phantoms and integrated EPID images were respectively acquired. Dose reconstruction was performed on these images using the calculated responses. The deformed phantom was registered to the original phantom using an in-house developed software based on the Demons algorithm. The transfer matrix for each voxel was obtained and used to correlate the two sets of the reconstructed dose to generate a cumulative reconstructed dose on the original phantom. Forwardly calculated planning dose in the original phantom was compared to the cumulative reconstructed dose from EPID in the original phantom. The prescribed 200 cGy isodose lines showed little difference with respect to the "prostate" and "seminal vesicles", but appreciable difference (3%) was observed at the dose level greater than 210 cGy. In the rectum, the reconstructed dose showed lower volume coverage by a few percent than the plan dose in the dose range of 150 to 200 cGy. Through this study, the system of clinical application of reconstructed dose was successfully developed and demonstrated. The organ deformation simulated in this study resulted in small but observable dose changes in the target and critical structure.

• Journal of Internet Computing and Services
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• v.21 no.1
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• pp.169-178
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• 2020

The reductions of troops/human resources, and improvement in combat power have made Korean Department of Defense actively adapt 4th Industrial Revolution technology (Artificial Intelligence, Big Data). The defense information system has been developed in various ways according to the task and the uniqueness of each military. In order to take full advantage of the 4th Industrial Revolution technology, it is necessary to improve the closed defense datamanagement system.However, the establishment and usage of data standards in all information systems for the utilization of defense big data and artificial intelligence has limitations due to security issues, business characteristics of each military, anddifficulty in standardizing large-scale systems. Based on the interworking requirements of each system, data sharing is limited through direct linkage through interoperability agreement between systems. In order to implement smart defense using the 4th Industrial Revolution technology, it is urgent to prepare a system that can share defense data and make good use of it. To technically support the defense, it is critical to develop Multi Repository Meta-Data Management (MRMM) that supports systematic standard management of defense data that manages enterprise standard and standard mapping for each system and promotes data interoperability through linkage between standards which obeys the Defense Interoperability Management Development Guidelines. We introduced MRMM, and implemented by using vocabulary similarity using machine learning and statistical approach. Based on MRMM, We expect to simplify the standardization integration of all military databases using artificial intelligence and bigdata. This will lead to huge reduction of defense budget while increasing combat power for implementing smart defense.

• Korean Journal of Cognitive Science
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• v.17 no.2
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• pp.75-102
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• 2006

Three experiments were conducted using a verification task to examine good and poor readers' generation of causal inferences(with because sentences) and contrastive inferences(with although sentences). The unfamiliar, critical verification statement was either explicitly mentioned or was implied. In Experiment 1, both good and poor readers responded accurately to the critical statement, suggesting that both groups had the linguistic knowledge necessary to the required inferences. Differences were found, however, in the groups' verification latencies. Poor, but not good, readers responded faster to explicit than to implicit verification statements for both because and although sentences. In Experiment 2, poor readers were induced to generate causal inferences for the because experimental sentences by including fillers that were apparently counterfactual unless a causal inference was made. In Experiment 3, poor readers were induced to generate contrastive inferences for the although sentences by including fillers that could only be resolved by making a contrastive inference. Verification latencies for the critical statements showed that poor readers made causal inferences in Experiment 2 and contrastive inferences in Experiment 3 doting comprehension. These results were discussed in terms of context effect: Specific encoding operations performed on anomaly backgrounded in another passage would form part of the context that guides the ongoing activity in processing potentially relevant subsequent text.

• The KIPS Transactions:PartB
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• v.19B no.2
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• pp.123-126
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• 2012

This paper proposed a method to separate a liver into left and right liver lobes for simple and exact volumetry of the river graft at abdominal MDCT(Multi-Detector Computed Tomography) image before the living donor liver transplantation. A medical team can evaluate an accurate river graft with minimized interaction between the team and a system using this algorithm for ensuring donor's and recipient's safe. On the image of segmented liver, 2 points(PMHV: a point in Middle Hepatic Vein and PPV: a point at the beginning of right branch of Portal Vein) are selected to separate a liver into left and right liver lobes. Middle hepatic vein is automatically segmented using PMHV, and the cutting line is decided on the basis of segmented Middle Hepatic Vein. A liver is separated on connecting the cutting line and PPV. The volume and ratio of the river graft are estimated. The volume estimated using 2 points are compared with a manual volume that diagnostic radiologist processed and estimated and the weight measured during surgery to support proof of exact volume. The mean ${\pm}$ standard deviation of the differences between the actual weights and the estimated volumes was $162.38cm^3{\pm}124.39$ in the case of manual segmentation and $107.69cm^3{\pm}97.24$ in the case of 2 points method. The correlation coefficient between the actual weight and the manually estimated volume is 0.79, and the correlation coefficient between the actual weight and the volume estimated using 2 points is 0.87. After selection the 2 points, the time involved in separation a liver into left and right river lobe and volumetry of them is measured for confirmation that the algorithm can be used on real time during surgery. The mean ${\pm}$ standard deviation of the process time is $57.28sec{\pm}32.81$ per 1 data set ($149.17pages{\pm}55.92$).

• Korean Journal of Remote Sensing
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• v.37 no.6_1
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• pp.1657-1667
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• 2021

Anthropogenic activities and natural processes have been causes of land subsidence which is sudden sinking or gradual settlement of the earth's solid surface. Mexico City, the capital of Mexico, is one of the most severe land subsidence areas which are resulted from excessive groundwater extraction. Because groundwater is the primary water resource occupies almost 70% of total water usage in the city. Traditional terrestrial observations like the Global Navigation Satellite System (GNSS) or leveling survey have been preferred to measure land subsidence accurately. Although the GNSS observations have highly accurate information of the surfaces' displacement with a very high temporal resolution, it has often been limited due to its sparse spatial resolution and highly time-consuming and high cost. However, space-based synthetic aperture radar (SAR) interferometry has been widely used as a powerful tool to monitor surfaces' displacement with high spatial resolution and high accuracy from mm to cm-scale, regardless of day-or-night and weather conditions. In this paper, advanced interferometric approaches have been applied to get a time-series of land subsidence of Mexico City using four-year-long twenty ALOS PALSAR L-band observations acquired from Feb-11, 2007 to Feb-22, 2011. We utilized persistent scatterer interferometry (PSI) and small baseline subset (SBAS) techniques to suppress atmospheric artifacts and topography errors. The results show that the maximum subsidence rates of the PSI and SBAS method were -29.5 cm/year and -27.0 cm/year, respectively. In addition, we discuss the different subsidence rates where the study area is discriminated into three districts according to distinctive geotechnical characteristics. The significant subsidence rate occurred in the lacustrine sediments with higher compressibility than harder bedrock.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2005.11a
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• pp.233-237
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• 2005

수화의 인식 및 표현 기술에 대한 관련 연구는 수화 인식을 통한 건청인과의 의사 전달, 가상현실에서의 손동작 인식 등을 대상으로 여러 방면으로의 접근 및 연구 결과를 도출하고 있다. 그러나 이들 연구의 대부분 데스크탑 PC기반의 수신호(Hand signal) 제어 및 수화 - 손 동작 인식에 목적을 두었고 수화 신호의 획득을 위하여 영상장비를 이용하였으며 이를 바탕으로 단어 위주의 수화 인식 및 표현에 중점을 둔 수화 인식 시스템의 구현을 통해 비장애인과의 자유로운 의사소통을 추구하고 있다. 따라서 본 논문에서는 햅틱 장치로부터 사용자의 의미있는 수화 제스처를 획득하기 위한 접근 방식을 차세대 착용형 PC 플랫폼 기반의 유비쿼터스 환경으로 확대, 적용시켜 제스처 데이터 입력 모듈로부터 새로운 정보의 획득에 있어 한계성을 극복하고 사용자의 편의를 도모할 수 있는 효율적인 데이터 획득 방안을 제시한다. 또한 퍼지 알고리즘 및 RDBMS 모듈을 이용하여 언제, 어디에서나 사용자의 의미 있는 문장형 수화 제스처를 실시간으로 인식하고 표현하는 수화 제스처 인식기를 구현하였다. 본 논문에서는 수화 제스처 입력 모듈(5th Data Glove System과 $Fastrak{\circledR}$)과 차세대 착용형 PC 플랫폼(embedded I.MX21 board)간의 이격거리를 반경 10M의 타원 형태로 구성하고 규정된 위치로 수화 제스처 데이터 입력모듈을 이동시키면서 5인의 피실험자에 대하여 연속적으로 20회의 반복 실험을 수행하였으며 사용자의 동적 제스처 인식 실험결과 92.2% 평균 인식률을 도출하였다.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.4
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• pp.81-87
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• 2016

With the rapid growth of the up-to-date smartphone and wireless network technologies, huge and various types of smart applications using these technologies are actively developed recently. Especially, multiplex types of smart applications using smartphone are developed and diffused with the rapid development of the ubiquitous sensor network technology using various sensors and the mobile computing technology that enables us to get network services at any time in any places. In this paper, we design a smart application that can accurately diagnose and process the current state of the local environment, objects, and persons remotely based on the context information such as local ecology, circumstances, medical or healthcare records and realtime sound or motion pictures using up-to-date samrtphone technology on the USN based mobile computing environment.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.46 no.4
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• pp.306-314
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• 2018

A two-axis gimbal-type X-band antenna for CAS(Compact Advanced Satellite) transmits large amount of image data to ground station regardless of satellite attitude and orbital motion. This antenna mounted on the external surface of the satellite is directly exposed to the extreme space with thermal environment during the orbital operation. Therefore, a proper thermal design is needed to maintain the antenna itself as well as other main components within allowable temperature range. In this study, the thermal design effectiveness of two-axis gimbal X-band antenna was verified through the thermal analysis. In addition, required power and duty cycle of heater were estimated through the thermal analysis under conditions of system level thermal vacuum test and on-orbit thermal environment. The thermal analysis results indicated that all the main components of X-band antenna satisfy the allowable temperature requirement.

• Journal of Environmental Science International
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• v.17 no.4
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• pp.461-468
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• 2008

Competitive power of pelagic fishery in Korea has been weakened by the domestic and international problems such as wage increase and exclusive economic zone. To make it worse, fishing fleet spends more than 80% of fishing time on searching fishing grounds. Real-time information on oceanographic data, temperature in particular, are likely to contribute to raise efficiency of fishing. However, available data obtained by satellite remote sensing, fixed buoy and drifting buoy, limited to sea surface or fixed positions. ARGO (Array for Real-time Geostrophic Oceanography), an international program, has delivered vertical profiles of temperature and salinity in the upper 2000m of the world ocean every 10 days using freely moving floats. We have developed real-time oceanographic information system for pelagic fishery based on the Argo data which has the contents of vertical profile, horizontal distribution and vertical section of temperature around fishing grounds and searched data can be download unrestrictedly. Comparison of skipjack catch with sea surface temperature and depth of $20^{\circ}C$ derived from Argo data in the West Equatorial Pacific revealed that Argo data are able to help fishing fleet to find fishing grounds and to increase catch.