• ETRI Journal
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• v.45 no.2
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• pp.254-266
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• 2023

This paper investigates the effect of hardware impairments (HIs) and imperfect channel state information (ICSI) on a SWIPT-assisted adaptive nonorthogonal multiple access (NOMA)/orthogonal multiple access (OMA) system over independent and nonidentical Rayleigh fading channels. In the NOMA mode, the energy-constrained near users act as a relay to improve the performance for the far users. The OMA transmission mode is adopted to avoid a complete outage when NOMA is infeasible. The best user selection scheme is considered to maximize the energy harvested and avoid error propagation. To characterize the performance of the proposed systems, closed-form and asymptotic expressions of the outage probability for both near and far users are studied. Moreover, exact and approximate expressions of the ergodic rate for near and far users are investigated. Simulation results are provided to verify our theoretical analysis and confirm the superiority of the proposed NOMA/OMA scheme in comparison with the conventional NOMA and OMA protocol with/without HIs and ICSI.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.134-134
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• 2021

Precipitation is a crucial component of water cycle and play a key role in hydrological processes. Traditionally, gauge-based precipitation is the main method to achieve high accuracy of rainfall estimation, but its distribution is sparsely in mountainous areas. Recently, satellite-based precipitation products (SPPs) provide grid-based precipitation with spatio-temporal variability, but SPPs contain a lot of uncertainty in estimated precipitation, and the spatial resolution quite coarse. To overcome these limitations, this study aims to generate new grid-based daily precipitation using Automatic weather system (AWS) in Korea and multiple SPPs(i.e. CHIRPSv2, CMORPH, GSMaP, TRMMv7) during the period of 2003-2017. And this study used a machine learning based Random Forest (RF) model for generating new merging precipitation. In addition, several statistical linear merging methods are used to compare with the results of the RF model. In order to investigate the efficiency of RF, observed data from 64 observed Automated Synoptic Observation System (ASOS) were collected to evaluate the accuracy of the products through Kling-Gupta efficiency (KGE), probability of detection (POD), false alarm rate (FAR), and critical success index (CSI). As a result, the new precipitation generated through the random forest model showed higher accuracy than each satellite rainfall product and spatio-temporal variability was better reflected than other statistical merging methods. Therefore, a random forest-based ensemble satellite precipitation product can be efficiently used for hydrological simulations in ungauged basins such as the Mekong River.

• The Bulletin of The Korean Astronomical Society
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• v.45 no.1
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• pp.39.3-40
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• 2020

For the space weather research, KASI (Korea Astronomy and Space Science Institute) is developing the SNIPE (Small-scale magNetospheric and Ionospheric Plasma Experiment) mission, which consists of four 6U CubeSats of ~10 kg. Besides of space weather research, the SNIPE mission has another astrophysical objective, detecting Gamma-Ray Bursts(GRB). By cross-correlating the light curves of the detected GRBs, the fleet shall be able to determine the time difference of the arriving signal between the satellites and thus determine the position of bright short bursts with an accuracy ~100'. To demonstrate the technology of the GRB observation, CSI gamma-ray detectors combined with GPS and IRIDIUM communication modules are placed on each SNIPE CubeSat. The time of each spacecraft is synchronized and when the GRB is detected, the light curve will be transferred to the Mission Operation Center (MOC) by IRIDIUM communication module. By measuring time difference of each GRB signals, the technology for localization of GRB will be proved. If the results show some possibilities, we can challenge the new astrophysical mission for investigating the origin of GRB.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.128-128
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• 2022

최근 호우의 빈도와 규모는 증가하는 추세이며 이에 따른 홍수 피해는 많은 피해를 야기하고 있다. 이러한 관점에서 홍수 피해에 대한 선제적 대응을 위한 요소로써 초단시간 강우예측 정보의 중요성은 매우 높다. 특히, 레이더 자료 기반의 강우예측은 수치예보모델과 비교하여 3시간 이내의 짧은 선행시간 이내의 높은 정확도를 갖고 있어 홍수예보에 다수 활용되고 있다. 최근에는 강우자료의 복잡한 관계와 특징을 고려하기 위해 딥러닝 기반의 강우예측 활용 사례가 증가하고 있으나 국내 적용 사례는 적어 관련 연구가 요구되는 실정이다. 본 연구에서는 레이더 강우를 활용한 딥러닝 기반의 강우예측 기법을 제안하고 이에 대한 적용성을 평가하고자 한다. 2차원 레이더 강우자료의 특징과 시계열 특성을 고려하기 위한 심층신경망 구조를 제안하였으며 기존 딥러닝 모형과의 비교를 통해 활용 가능성을 제시하고자 하였다. 적용 대상지역은 한강 유역으로 선정하였다. 정성적 평가를 위해 임계성공지수(CSI)를 활용하여 예측 강우에 대한 정확도를 평가하였으며 정량적 평가를 위해 예측 강우와 관측 강우의 상관관계를 분석하였다. 평가 결과, 제안하는 방법이 기존 모형과 비교하여 예측오차의 범위가 적고 강우의 위치 변화를 잘 반영하는 것으로 나타났다. 본 연구결과는 초단기간 강우예측 자료를 활용하는 홍수예보의 정확도 향상에 기여할 것으로 기대된다.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.143-143
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• 2022

Precipitation plays an essential role in water resources management and disaster prevention. Therefore, the understanding related to spatiotemporal characteristics of rainfall is necessary. Nowadays, highly accurate precipitation is mainly obtained from gauge observation systems. However, the density of gauge stations is a sparse and uneven distribution in mountainous areas. With the proliferation of technology, satellite-based precipitation sources are becoming increasingly common and can provide rainfall information in regions with complex topography. Nevertheless, satellite-based data is that it still remains uncertain. To overcome the above limitation, this study aims to take the strengthens of machine learning to generate a new reanalysis of precipitation data by fusion of multiple satellite precipitation products (SPPs) with gauge observation data. Several machine learning algorithms (i.e., Random Forest, Support Vector Regression, and Artificial Neural Network) have been adopted. To investigate the robustness of the new reanalysis product, observed data were collected to evaluate the accuracy of the products through Kling-Gupta efficiency (KGE), probability of detection (POD), false alarm rate (FAR), and critical success index (CSI). As a result, the new precipitation generated through the machine learning model showed higher accuracy than original satellite rainfall products, and its spatiotemporal variability was better reflected than others. Thus, reanalysis of satellite precipitation product based on machine learning can be useful source input data for hydrological simulations in ungauged river basins.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2023.05a
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• pp.367-368
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• 2023

Kiscon, Seumteo, KONEPS and CSI are representative construction-related DBs. All four DBs are operated by the public. However, the characteristics of data are different depending on the purpose. Therefore, it is difficult to utilize integrated data and it is only used sparingly. Creating and sharing a unique key that can identify a construction site will enable integrated accumulation and management of construction-related data for various purposes. At this point, it is most efficient to assign a unique key based on KISCON. KISCOn data conforms to the construction site definition and covers most of the public, private, architectural and civil works. In addition, there is an advantage in that DB construction is performed in the construction situation, which is a relatively preceding process. In the future, it is necessary to create a practical construction site integrated DB through the production of an integrated key table containing linkage information of unique keys for site management, performance indicators, and statistics production.

• Journal of the Korea Safety Management & Science
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• v.25 no.3
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• pp.63-71
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• 2023

The construction industry stands out for its higher incidence of accidents in comparison to other sectors. A causal analysis of the accidents is necessary for effective prevention. In this study, we propose a data-driven causal analysis to find significant factors of fatal construction accidents. We collected 14,318 cases of structured and text data of construction accidents from the Construction Safety Management Integrated Information (CSI). For the variables in the collected dataset, we first analyze their patterns and correlations with fatal construction accidents by statistical analysis. In addition, machine learning algorithms are employed to develop a classification model for fatal accidents. The integration of SHAP (SHapley Additive exPlanations) allows for the identification of root causes driving fatal incidents. As a result, the outcome reveals the significant factors and keywords wielding notable influence over fatal accidents within construction contexts.

• Proceedings of the Korean Society of Disaster Information Conference
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• 2023.11a
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• pp.93-94
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• 2023

해체공사는 작업의 특성상 단기간에 이루어지며, 해체공사 현장에 투입되는 근로자는 일용직 근로자가 대부분으로 안전사고의 비율이 높다. 사업장 위험성 평가에 관한 지침에는 위험성 평가시 근로자를 참여토록 하고 있으나 해체현장의 특성상 근로자가 참여한다고 하여도 위험요소를 파악할 역량이 부족할 따름이다. 또한 기존의 해체공사 안전관리 매뉴얼은 구조안전성 확보를 위한 매뉴얼로 해체 근로자의 안전을 위한 매뉴얼은 없는 실정으로, 근로자의 안전을 확보하기 위한 위험성 평가 매뉴얼이 요구되고 있다. 이에 본 연구에서는 건설공사 안전관리 종합정보망(CSI)의 해체 및 철거공사의 사고사례를 분석하였으며, 해체 및 철거 사고시 발생한 주요 위험요소를 도출하여 작업 공종별로 유해·위험요인의 파악을 손 쉽게 할 수 있도록 하였다. 또한 해체 현장 규모에 따라 대규모 현장은 빈도·강도법, 중·소규모 현장은 체크리스트법을 활용하여 위험성을 결정하고 감소대책을 수립할 수 있도록 매뉴얼을 구성하였다. 잔여 위험에 대해서는 관리카드를 만들어 해체공사 완료시까지 관리하도록 하였다.

• Radiation Oncology Journal
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• v.22 no.3
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• pp.165-176
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• 2004

Purpose: Firstly, to analyze facto in terms of radiation treatment that might potentially cause subfrontal relapse in two patients who had been treated by craniospinal irradiation (CSI) for medulloblastoma, Secondly, to explore an effective salvage treatment for these relapses. Materials and Methods: Two patients who had high-risk disease (T3bMl, T3bM3) were treated with combined chemoradiotherapy CT-simulation based radiation-treatment planning (RTP) was peformed. One patient who experienced relapse at 16 months after CSI was treated with salvage surgery followed by a 30.6 Gy IMRT (intensity modulated radiotherapy). The other patient whose tumor relapsed at 12 months after CSI was treated by surgery alone for the recurrence. To investigate factors that might potentially cause subfrontal relapse, we evaluated thoroughly the charts and treatment planning process including portal films, and tried to find out a method to give help for placing blocks appropriately between subfrotal-cribrifrom plate region and both eyes. To salvage subfrontal relapse in a patient, re-irradiation was planned after subtotal tumor removal. We have decided to treat this patient with IMRT because of the proximity of critical normal tissues and large burden of re-irradiation. With seven beam directions, the prescribed mean dose to PTV was 30.6 Gy (1.8 Gy fraction) and the doses to the optic nerves and eyes were limited to 25 Gy and 10 Gy, respectively. Results: Review of radiotherapy Portals clearly indicated that the subfrontal-cribriform plate region was excluded from the therapy beam by eye blocks in both cases, resulting in cold spot within the target volume, When the whole brain was rendered in 3-D after organ drawing in each slice, it was easier to judge appropriateness of the blocks in port film. IMRT planning showed excellent dose distributions (Mean doses to PTV, right and left optic nerves, right and left eyes: 31.1 Gy, 14.7 Gy, 13.9 Gy, 6.9 Gy, and 5.5 Gy, respectively. Maximum dose to PTV: 36 Gy). The patient who received IMRT is still alive with no evidence of recurrence and any neurologic complications for 1 year. Conclusion: To prevent recurrence of medulloblastoma in subfrontal-cribriform plate region, we need to pay close attention to the placement of eye blocks during the treatment. Once subfrontal recurrence has happened, IMRT may be a good choice for re-irradiation as a salvage treatment to maximize the differences of dose distributions between the normal tissues and target volume.

• Molecules and Cells
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• v.26 no.2
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• pp.206-211
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• 2008

HI0381 of Haemophilus influenzae was investigated by circular dichroism (CD) and nuclear magnetic resonance (NMR) spectroscopy. HI0381 is a 153-residue peptidoglycan-associated outer membrane lipoprotein, and a part of the larger Tol/Pal network. Here, we report its backbone $^1H$, $^{15}N$, and $^{13}C$ resonance assignments, and secondary structure predictions. About 97% of all of the $^1HN$, $^{15}N$, $^{13}CO$, $^{13}C{\alpha}$, and $^{13}C{\beta}$ resonances covering 131 non-proline residues of the 134 residue, mature protein, were clarified by sequential and specific assignments. CSI and TALOS analyses revealed that HI0381 contains five ${\alpha}$-helices and five ${\beta}$-strands. To characterize the structure of HI0381, the effects of pH and salt concentration were investigated by CD. In addition, the structural changes occurring when HI0381 was in a membranous environment were investigated by comparing its HSQC spectra and CD data in buffer and in DPC micelles; the results showed that helix ${\alpha}4$ and strand ${\beta}4$ became aligned with the membrane. We conclude that the conformation of HI0381 is affected by the membrane environment, implying that its folded state is directly related to its function.