• Journal of Astronomy and Space Sciences
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• v.39 no.3
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• pp.117-126
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• 2022

The Ionospheric Anomaly Monitoring by Magnetometer And Plasma-probe (IAMMAP) is one of the scientific instruments for the Compact Advanced Satellite 500-3 (CAS 500-3) which is planned to be launched by Korean Space Launch Vehicle in 2024. The main scientific objective of IAMMAP is to understand the complicated correlation between the equatorial electro-jet (EEJ) and the equatorial ionization anomaly (EIA) which play important roles in the dynamics of the ionospheric plasma in the dayside equator region. IAMMAP consists of an impedance probe (IP) for precise plasma measurement and magnetometers for EEJ current estimation. The designated sun-synchronous orbit along the quasi-meridional plane makes the instrument suitable for studying the EIA and EEJ. The newly-devised IP is expected to obtain the electron density of the ionosphere with unprecedented precision by measuring the upper-hybrid frequency (f_UHR) of the ionospheric plasma, which is not affected by the satellite geometry, the spacecraft potential, or contamination unlike conventional Langmuir probes. A set of temperature-tolerant precision fluxgate magnetometers, called Adaptive In-phase MAGnetometer, is employed also for studying the complicated current system in the ionosphere and magnetosphere, which is particularly related with the EEJ caused by the potential difference along the zonal direction.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.353-353
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• 2022

본 연구에서는 CMIP5(The fifth phase of the Couple Model Intercomparison Project) 미래기후시나리오와 LSTM(Long Short-Term Memory) 모형 기반의 딥러닝 기법을 이용하여 하천유량 예측을 위한 최적 학습 기간을 제시하였다. 연구지역으로는 진안군(성산리) 지점을 선정하였다. 보정(2000~2002/2014~2015) 및 검증(2003~2005/2016~2017) 기간을 설정하여 연구지역의 실측 유량 자료와 LSTM 기반 모의유량을 비교한 결과, 전체적으로 모의값이 실측값을 잘 반영하는 것으로 나타났다. 또한, LSTM 모형의 장기간 예측 성능을 평가하기 위하여 LSTM 모형 기반 유량을 보정(2000~2015) 및 검증(2016~2019) 기간의 SWAT 기반 유량에 비교하였다. 비록 모의결과에일부 오차가 발생하였으나, LSTM 모형이 장기간의 하천유량을 잘 산정하는 것으로 나타났다. 검증 결과를 기반으로 2011년~2100년의 CMIP5 미래기후시나리오 기상자료를 이용하여 SWAT 기반 유량을 모의하였으며, 모의한 하천유량을 LSTM 모형의 학습자료로 사용하였다. 다양한 학습 시나리오을 적용하여 LSTM 및 SWAT 모형 기반의 하천유량을 모의하였으며, 최적 학습 기간을 제시하기 위하여 학습 시나리오별 LSTM/SWAT 기반 하천유량의 상관성 및 불확실성을 비교하였다. 비교 결과 학습 기간이 최소 30년 이상일때, 실측유량과 비교하여 LSTM 모형 기반 하천유량의 불확실성이 낮은 것으로 나타났다. 따라서 CMIP5 미래기후시나리오와 딥러닝 기반 LSTM 모형을 연계하여 미래 장기간의 일별 유량을 모의할 경우, 신뢰성 있는 LSTM 모형 기반 하천유량을 모의하기 위해서는 최소 30년 이상의 학습 기간이 필요할 것으로 판단된다.

• The Journal of the Convergence on Culture Technology
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• v.9 no.1
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• pp.531-537
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• 2023

Interior construction is required to estimate the quantity of material and the cost expected from 2D drawing in design phase and look for the reasonable method of work. Therefore, exact estimation for quantity and budgeting are very important processes, as a measure of judging the profitability of interior construction. These processes are mostly based on 2D drawing, so time and experienced staff are required. Error and omission can occur because the experienced staff also calculates the area using 2D based drawing. Interior market is currently based on 3D modeling from planning to final design. Accordingly, estimating quantity based on 3D modeling is emerging as a way of reducing error and omission. This paper will present the methodology on calculating area, the basic element of estimating quantity based on 3D Modeling in interior field.

• Journal of the Korea Society of Computer and Information
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• v.14 no.8
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• pp.1-9
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• 2009

In this paper, make a study decision problem called an optimal release policies after testing a software system in development phase and transfer it to the user. When correcting or modifying the software, because of the possibility of introducing new faults when correcting or modifying the software, infinite failure non-homogeneous Poisson process models presented and propose an optimal release policies of the life distribution applied fixed shape parameter distribution which can capture the increasing/decreasing nature of the failure occurrence rate per fault. In this paper, discuss optimal software release policies which minimize a total average software cost of development and maintenance under the constraint of satisfying a software reliability requirement. In a numerical example, after trend test applied and estimated the parameters using maximum likelihood estimation of inter-failure time data, make out estimating software optimal release time

• The Journal of Economics, Marketing and Management
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• v.6 no.4
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• pp.1-16
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• 2018

Purpose - This study will investigate and identify the relationship between brand image, brand attitude and intent to purchase based on subjects that have remembered or watched more than one storytelling marketing ad related to airlines. The purpose of the project is to secure market competitiveness by presenting the basis for and use of the marketing strategy using storytelling, which can capture the goodwill of the aerospace competition market in the future. Research, design, data, and methodology - Prior to the research model and hypothesis testing phase, a verification factor analysis was conducted to assess internal consistency among each measurement item and to ensure reliability and validity of the measurement tool. Further, the organization was assessed for validity by calculating the mean variance estimation (AVE) and the construction concept reliability (CCR) through a positive factor analysis. Hypothesis verification was analyzed through a structural equation model, and each concept set in the hypothesis was entered as a potential variable, and each measurement item was entered as an observation variable. Results - Airline's storytelling marketing has a significant impact on the brand image and two emotional and cognitive responses have been shown to influence the brand image. In addition, airline storytelling marketing has a significant impact on brand attitudes and airline storytelling marketing derived from factor analysis has shown two emotional and cognitive responses to brand attitudes. Conclusions - The parts derived based on the research results show that storytelling marketing has a strong influence on the airline's brand image and attitude, and that it is necessary for airlines to have a brand image and attitude. Also, forming a favorable brand image has a significant impact on brand attitudes. We believe that by presenting basic data to the aviation industry in future research on airline storytelling, we will be able to increase understanding and contribution to development of storytelling marketing in aviation.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.305-305
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• 2022

A better approach for assessing meteorological drought occurrences is increasingly important in mitigating and adapting to the impacts of climate change, as well as strategies for developing early warning systems. The present study defines meteorological droughts as a period with an abnormal precipitation deficit based on monthly precipitation data of 18 gauging stations for the Han River watershed in the past (1974-2015). This study utilizes a Bayesian parameter estimation approach to analyze the effects of climate change on future drought (2025-2065) in the Han River Basin using the Coupled Model Intercomparison Project Phase 6 (CMIP6) with four bias-corrected general circulation models (GCMs) under the Shared Socioeconomic Pathway (SSP)2-4.5 scenario. Given that drought is defined by several dependent variables, the evaluation of this phenomenon should be based on multivariate analysis. Two main characteristics of drought (severity and duration) were extracted from precipitation anomalies in the past and near-future periods using the copula function. Three parameters of the Archimedean family copulas, Frank, Clayton, and Gumbel copula, were selected to fit with drought severity and duration. The results reveal that the lower parts and middle of the Han River basin have faced severe drought conditions in the near future. Also, the bivariate analysis using copula showed that, according to both indicators, the study area would experience droughts with greater severity and duration in the future as compared with the historical period.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.6
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• pp.499-508
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• 2023

In this paper, we propose a technique to estimate the coordinates of feature points existing on a 2D planar object in the three dimensional space. The proposed method detects multiple 3D features from the image, and excludes those which are not located on the plane. The proposed technique estimates the planar homography between the planar object in the 3D space and the camera image plane, and computes back-projection error of each feature point on the planar object. Then any feature points which have large error is considered as off-plane points and are excluded from the feature estimation phase. The proposed method is archived on the basis of the planar homography without any additional sensors or optimization algorithms. In the expretiments, it was confirmed that the speed of the proposed method is more than 40 frames per second. In addition, compared to the RGB-D camera, there was no significant difference in processing speed, and it was verified that the frame rate was unaffected even in the situation that the number of detected feature points continuously increased.

• Geomechanics and Engineering
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• v.37 no.4
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• pp.307-321
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• 2024

This paper delves into the critical assessment of predicting sidewall displacement in underground caverns through the application of nine distinct machine learning techniques. The accurate prediction of sidewall displacement is essential for ensuring the structural safety and stability of underground caverns, which are prone to various geological challenges. The dataset utilized in this study comprises a total of 310 data points, each containing 13 relevant parameters extracted from 10 underground cavern projects located in Iran and other regions. To facilitate a comprehensive evaluation, the dataset is evenly divided into training and testing subset. The study employs a diverse array of machine learning models, including recurrent neural network, back-propagation neural network, K-nearest neighbors, normalized and ordinary radial basis function, support vector machine, weight estimation, feed-forward stepwise regression, and fuzzy inference system. These models are leveraged to develop predictive models that can accurately forecast sidewall displacement in underground caverns. The training phase involves utilizing 80% of the dataset (248 data points) to train the models, while the remaining 20% (62 data points) are used for testing and validation purposes. The findings of the study highlight the back-propagation neural network (BPNN) model as the most effective in providing accurate predictions. The BPNN model demonstrates a remarkably high correlation coefficient (R2 = 0.99) and a low error rate (RMSE = 4.27E-05), indicating its superior performance in predicting sidewall displacement in underground caverns. This research contributes valuable insights into the application of machine learning techniques for enhancing the safety and stability of underground structures.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.27 no.7
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• pp.380-394
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• 2015

This article reviews the papers published in the Korean Journal of Air-Conditioning and Refrigeration Engineering during 2014. It is intended to understand the status of current research in the areas of heating, cooling, ventilation, sanitation, and indoor environments of buildings and plant facilities. Conclusions are as follows. (1) The research works on the thermal and fluid engineering have been reviewed as groups of heat and mass transfer, cooling and heating, and air-conditioning, the flow inside building rooms, and smoke control on fire. Research issues dealing with duct and pipe were reduced, but flows inside building rooms, and smoke controls were newly added in thermal and fluid engineering research area. (2) Research works on heat transfer area have been reviewed in the categories of heat transfer characteristics, pool boiling and condensing heat transfer and industrial heat exchangers. Researches on heat transfer characteristics included the results for thermal contact resistance measurement of metal interface, a fan coil with an oval-type heat exchanger, fouling characteristics of plate heat exchangers, effect of rib pitch in a two wall divergent channel, semi-empirical analysis in vertical mesoscale tubes, an integrated drying machine, microscale surface wrinkles, brazed plate heat exchangers, numerical analysis in printed circuit heat exchanger. In the area of pool boiling and condensing, non-uniform air flow, PCM applied thermal storage wall system, a new wavy cylindrical shape capsule, and HFC32/HFC152a mixtures on enhanced tubes, were actively studied. In the area of industrial heat exchangers, researches on solar water storage tank, effective design on the inserting part of refrigerator door gasket, impact of different boundary conditions in generating g-function, various construction of SCW type ground heat exchanger and a heat pump for closed cooling water heat recovery were performed. (3) In the field of refrigeration, various studies were carried out in the categories of refrigeration cycle, alternative refrigeration and modelling and controls including energy recoveries from industrial boilers and vehicles, improvement of dehumidification systems, novel defrost systems, fault diagnosis and optimum controls for heat pump systems. It is particularly notable that a substantial number of studies were dedicated for the development of air-conditioning and power recovery systems for electric vehicles in this year. (4) In building mechanical system research fields, seventeen studies were reported for achieving effective design of the mechanical systems, and also for maximizing the energy efficiency of buildings. The topics of the studies included energy performance, HVAC system, ventilation, and renewable energies, piping in the buildings. Proposed designs, performance performance tests using numerical methods and experiments provide useful information and key data which can improve the energy efficiency of the buildings. (5) The field of architectural environment was mostly focused on indoor environment and building energy. The main researches of indoor environment were related to the evaluation of work noise in tunnel construction and the simulation and development of a light-shelf system. The subjects of building energy were worked on the energy saving of office building applied with window blind and phase change material(PCM), a method of existing building energy simulation using energy audit data, the estimation of thermal consumption unit of apartment building and its case studies, dynamic window performance, a writing method of energy consumption report and energy estimation of apartment building using district heating system. The remained studies were related to the improvement of architectural engineering education system for plant engineering industry, estimating cooling and heating degree days for variable base temperature, a prediction method of underground temperature, the comfort control algorithm of car air conditioner, the smoke control performance evaluation of high-rise building, evaluation of thermal energy systems of bio safety laboratory and a development of measuring device of solar heat gain coefficient of fenestration system.

• Korean Journal of Mineralogy and Petrology
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• v.35 no.1
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• pp.65-73
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• 2022

The proper estimation of physical and chemical properties of Earth materials and their structures at high pressure and high temperature conditions is key to the full understanding of diverse geological processes in Earth and planetary interiors. Multi-anvil press - high-pressure generating device - provides unique information of Earth materials under compression, mainly relevant to Earth's upper mantle. The quantitative estimation of the relationship between the oil load within press and the actual pressure conditions within the sample needs to be established to infer the planetary processes. Such pressure-load calibration has often been based on the phase transitions of crystalline earth materials with known pressure conditions; however, unlike at high temperature conditions, phase transitions at low (or room) temperatures can be sluggish, making the calibration at such conditions challenging. In this study, we explored the changes in Al coordination environments of permanently densified pyrope glasses upon the cold compression using the high-resolution ²⁷Al MAS and 3QMAS NMR. The fractions of highly coordinated Al in the cold compressed pyrope glasses increase with increasing oil load and thus, the peak pressure condition. Based on known relationship between the peak pressure and the Al coordination environment in the compressed pyrope glasses at room temperature, we established a room temperature pressure-load calibration of the 14/8 HT assembly in 1,100-ton multi-anvil press. The current results highlight the first pressure-load calibration of any high pressure device using high-resolution NMR. Irreversible structural densification upon cold compression observed for the pyrope glasses provides insights into the deformation and densification mechanisms of amorphous earth materials at low temperature and high pressure conditions within the subducting slabs.