• Bulletin of the Korean Space Science Society
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• 2003.10a
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• pp.43-43
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• 2003

본 연구에서는 정지궤도 위성을 이용한 표준시각 동기 서비스에 실시간 궤도결정 기술을 적용하는 방안을 고려하였다. 정지궤도 위성을 이용하여 표준시각 동기신호를 전파하는 연구는 여러 나라에서 진행되고 있는데 3지역에서의 측정(Trilateration)과 미분 보정(Differential Correction) 방식이 일반적인 방법으로 채택되고 있다. 본 논고에서는 한국 항공우주연구원에서 진행 중인 표준시각 동기 서비스 연구와 이를 위해 제작중인 실시간 궤도결정 기술을 적용한 실험 소프트웨어에 대해 소개하고자 한다. 실시간 궤도결정 방법을 적용하게 되면 동기신호 전파에 있어서 가장 큰 오차의 원인이 되는 위성궤도 예측 오차를 크게 줄일 수 있을 것으로 판단된다. 본 연구에서는 기존에 궤도 결정을 위해 사용하는 톤 레인징에 의한 위상차 신호와 안테나 각도 대신에 동기신호 자체만을 사용하고 있으며 1개의 수신 데이터만으로 궤도 결정을 수행하는 방안을 강구하였다. 본 논고에서는 실시간 궤도 결정에 의한 시뮬레이션 결과와 한국항공우주연구원에서 준비 중인 실험에 대해서 간략히 소개한다. 그리고 본 연구에서 개발된 기술은 2004년 4월에 무궁화위성 2호를 이용하여 실험을 수행할 예정이다.

• Explosives and Blasting
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• v.21 no.1
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• pp.9-17
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• 2003

본 기술사례는 과학기술부가 주도하는 자연재해방재기술개발 국가중점연구사업 중 기상청주관의 기상지진기술개발사업의 한반도 지각속도 구조연구 과제 중 서산지역과 포항지역을 연결하는 200km 측선에서 2차원 지각구조를 밝히기 위한 지각규모 굴절파탐사의 지진동 source 제공을 위해 발파로 실시하였다. 본 연구를 위하여 국내에서는 거의 실행해 본 경우가 없는 지발당 장약량이 500~1000kg발파를 실시하였다. 200개의 계측지점에 지진동이 전달될 수 있도록 충분한 폭속을 가진 폭약과 외부의 충격과 우수한 기폭력, 시차가 정확한 비전기뇌관을 특수 제작하여 사용하였다. 시추공내로 유출되는 물에 의한 사압을 방지하기 위하여 폭약은 철관용기를 제작하여 벌크형태로 장약을 하여 발파를 하였다. 발파전 용기 밀폐 시험 및 용기제작 후 기폭실험, 수압작용으로 인한 폭약 및 뇌관에 미치는 영향 등을 실험을 통하여 사전 파악을 하였다. 또한 실제 발파 중 진동차를 측정한 결과 보안물건에 대한 진동치값은 미광무국식(USBM)을 이용하여 예측한 진동치보다 평균 180% 정도 높게 나타났다.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.41 no.1
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• pp.85-91
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• 2021

In contrast to standard train tracks, tramlines are often set along public roads, with trams running among pedestrians and other vehicles. In some cities and towns, trams and buses share the same routes and stations. Under the current investment appraisal system, trams are classified into light rail when predicting traffic demand and calculating benefits, but in the case of non-capital areas, it is notable that the origin-destination and transit lines of buses are not provided in the Korea Transport Database distribution data. Due to this problem, it is difficult to reflect proper mode changing behaviors between route buses and trams. This study examines the impact on tramlines of bus routes that are not currently considered in non-capital areas. Following an analysis of the effect of tram projects according to whether bus routes are considered or not, an improvement in methodology is proposed. Through this study, it is expected that the investment appraisal system for the planning of new tramlines will be improved in the future.

• Korean Chemical Engineering Research
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• v.59 no.1
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• pp.68-76
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• 2021

As hazardous chemicals are releasing in process industries such as chemical & petro-chemical plants, the importance of initial responses has been always emphasized. However, little attention of quantitative analysis of the consequence by different initial responses during releasing of the chemicals has been done. The main objective of current paper is to investigate the effects of initial responses for the release accidents of hydrofluoric acid. For this, a simplified equation that can easily calculate the effect distance by varying concentrations of hydrofluoric acid was firstly deduced. In addition, a causal loops for the initial response steps using the system dynamics technique was constructed during release of 50% hydrofluoric acid. The effect distances according to different scenarios of the initial actions were also quantitatively analyzed by applying the simplified equation to the causal map. As a result, the highest reduction rate on the maximum effect distance was obtained with 'start time of action after leak detection' being about 87% while the lowest was 'arrival time of professional response team' being about 50%, as expected. It is expected that the results gained from the current study can be helpful as of basics of the initial response to the workplace, dealing with the hydrofluoric acid.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.27 no.2
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• pp.71-86
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• 2022

The water quality index (WQI) has been widely used to evaluate marine water quality. The WQI in Korea is categorized into five classes by marine environmental standards. But, the WQI calculation on huge datasets is a very complex and time-consuming process. In this regard, the current study proposed machine learning (ML) based models to predict WQI class by using water quality datasets. Sihwa Lake, one of specially-managed coastal zone, was selected as a modeling site. In this study, adaptive boosting (AdaBoost) and tree-based pipeline optimization (TPOT) algorithms were used to train models and each model performance was evaluated by metrics (accuracy, precision, F1, and Log loss) on classification. Before training, the feature importance and sensitivity analysis were conducted to find out the best input combination for each algorithm. The results proved that the bottom dissolved oxygen (DO_Bot) was the most important variable affecting model performance. Conversely, surface dissolved inorganic nitrogen (DIN_Sur) and dissolved inorganic phosphorus (DIP_Sur) had weaker effects on the prediction of WQI class. In addition, the performance varied over features including stations, seasons, and WQI classes by comparing spatio-temporal and class sensitivities of each best model. In conclusion, the modeling results showed that the TPOT algorithm has better performance rather than the AdaBoost algorithm without considering feature selection. Moreover, the WQI class for unknown water quality datasets could be surely predicted using the TPOT model trained with satisfactory training datasets.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.334-334
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• 2019

기후변화에 능동적으로 대처하기 위해서는 기후변화에 따른 수자원가용량의 변화를 정량적으로 평가할 수 있어야 한다. 평가결과의 신뢰도를 높이기 위해서 기후변화 시나리오는 지역기후 및 유역특성에 적합한 결과를 포함하여야 한다. 또한, 기후변화가 유역의 물순환계에 미치는 영향이 있다면, 물순환 개선 기술을 통해 지속가능한 유역 물환경을 구축하는 것이 필요하다. 유역 물순환 개선 기술은 기후변화가 진행 중에 있거나 예상되는 지역에 대하여 강우로부터 발생되는 유출을 지연, 저류, 침투시켜 지속가능한 물순환 체계를 유지하고 회복하도록 하는 기법이라 할 수 있다. 한국건설기술연구원에서는 기후변화에 따른 영향을 평가하고 적응 대책을 수립하기 위한 실무적인 유역 물순환 개선 및 평가 모형인 CAT3(Catchment hydrologic cycle Assessment Tool 3)을 개발하였으며 본 모형은 침투시설, 저류시설, 습지, 빗물저장시설과 같은 물순환 개선시설에 대한 효과를 정량적으로 평가할 수 있다. 본 연구에서는 팔당댐 상류의 경안천 유역을 대상으로 APCC 기후변화 시나리오 통계적 상세화 자료를 활용하여 물순환 개선 기술의 적용성을 평가하였다. 통계적 상세화 자료는 APCC에서 개발된 AIMS(APCC Integrated Modeling Solution) 플랫폼을 이용하였다. AIMS는 다양한 기후정보를 기반으로 사용자 관점에서 상세화를 수행할 수 있는 장점이 있다. 상세화 기법은 SDQDM(Spatial Disaggregation Quantile Delta Mapping) 방법을 이용하였다. 상세화된 기후자료는 과거자료의 재현성 및 미래 기간에 대한 왜곡도를 평가하기 위해 극한기후지수(Climate Index)를 이용하는데 본 연구에서는 장기간에 걸친 수자원가용량의 평가 및 예측을 위해 연강수량(PRCPTOT)을 사용하였으며 증발산량의 평가 및 예측에 영향을 미치는 온도 관련 극한기후지수는 평균기온 개념의 DTR(TMAX&TMIN)을 이용하였다. 통계적 상세화 과정을 통해 최종적으로 HadGEM2-CC, INMCM4, CanESM2 시나리오를 선택하였으며 각 시나리오별 물순환 개선 기술을 적용한 후 미래의 수문학적 변동성을 평가하였다.

• Journal of KIISE:Computer Systems and Theory
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• v.32 no.6
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• pp.306-313
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• 2005

Conditional branch prediction is an important technique for improving processor performance. Branch mispredictions, however, waste a large number of cycles, inhibit out-of-order execution, and waste electric power on mis-speculated instructions. Hence, the branch predictor with higher accuracy is necessary for good processor performance. In global-history-based predictors like gshare and GAg, many mispredictions come from commit update of the history. Some works on this subject have discussed the need for speculative update of the history and recovery mechanisms for branch mispredictions. In this paper, we present a simple mechanism for recovering the branch history after a misprediction. The proposed mechanism adds an age_counter to the original predictor and doubles the size of the branch history register. The age_counter counts the number of outstanding branches and uses it to recover the branch history register. Simulation results on the Simplescalar 3.0/PISA tool set and the SPECINTgS benchmarks show that gshare and GAg with the proposed recovery mechanism improved the average prediction accuracy by 2.14$\%$ and 9.21$\%$, respectively and the average IPC by 8.75$\%$ and 18.08$\%$, respectively over the original predictor.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.7
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• pp.802-811
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• 2023

Marine spatial planning (MSP) is a crucial element for rational allocation and sustainable use of marine areas. Particularly, Fishing Activity Protected Areas constitute essential zones accounting for 45.6% designated for sustainable fishing activities. However, the current assessment of these zones does not adequately consider future demands and potential values, necessitating appropriate evaluation methods and predictive tools for long-term planning. In this study, we selected key fish species (Scomber japonicus, Trichiurus lepturus, Engraulis japonicus, and Larimichthys polyactis) within the Fishing Activity Protected Area to predict their distribution and compare it with the current designated zones for evaluating the ability of the prediction tool. Employing the Intergovernmental Panel on Climate Change (IPCC) 6th Assessment Report scenarios (SSP1-2.6 and SSP5-8.5), we used species distribution models (such as MaxEnt) to assess the movement and distribution changes of these species owing to future variations. The results indicated a 30-50% increase in the distribution area of S. japonicus, T. lepturus, and L. polyactis, whereas the distribution area of E. japonicus decreased by approximately 6-11%. Based on these results, a species richness map for the four key species was created. Within the marine spatial planning boundaries, the overlap between areas rated "high" in species richness and the Fishing Activity Protected Area was approximately 15%, increasing to 21% under the RCP 2.6 scenario and 34% under the RCP 8.5 scenario. These findings can serve as scientific evidence for future evaluations of use zones or changes in reserve areas. The current and predicted distributions of species owing to climate change can address the limitations of current use zone evaluations and contribute to the development of plans for sustainable and beneficial use of marine resources.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.11
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• pp.71-79
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• 2017

In this paper, we implemented the exchange rate forecasting neural network using heterogeneous computing. Exchange rate forecasting requires a large amount of data. We used a neural network that could leverage this data accordingly. Neural networks are largely divided into two processes: learning and verification. Learning took advantage of the CPU. For verification, RTL written in Verilog HDL was run on FPGA. The structure of the neural network has four input neurons, four hidden neurons, and one output neuron. The input neurons used the US $ 1, Japanese 100 Yen, EU 1 Euro, and UK £ 1. The input neurons predicted a Canadian dollar value of $ 1. The order of predicting the exchange rate is input, normalization, fixed-point conversion, neural network forward, floating-point conversion, denormalization, and outputting. As a result of forecasting the exchange rate in November 2016, there was an error amount between 0.9 won and 9.13 won. If we increase the number of neurons by adding data other than the exchange rate, it is expected that more precise exchange rate prediction will be possible.

• Journal of the Korea Institute of Military Science and Technology
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• v.24 no.4
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• pp.426-434
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• 2021

In this paper, three-dimensional unsteady computational fluid dynamic(CFD) analyses based on overset grid technique have been performed for a hand-launched unmanned aerial vehicle(UAV) considering the wake effect generated by a rotating propeller. In addition, the defection of rudder is considered in order to consider to predict the equilibrium condition of yawing moment during cruise flight conditions. It is importantly shown in this paper that the wake interference effect of the propeller is significant to accurately predict the yawing moment of the UAV and the yawing moment coefficient corresponding to a flight speed can be different because of its different amount of wake effect due to the different rotating speed of the propeller.