• Journal of the Korea Institute of Building Construction
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• v.19 no.1
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• pp.77-86
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• 2019

Due to the increasing demand for and complexity of plant construction projects, unpredictable risk factors are on the consequent increase. For that reason, the quantitative risk analysis is being called for, in order for the development of a risk assessment model using risk indicators for the plant construction projects. This study used the claim payout data collected at a global insurance company to reflect the actual financial losses in plant construction projects as dependent variables in the risk assessment model. In terms of independent variables, the geographic information, i. e., landform, and the construction information including test-run, schedule rate, total cost and duration are adopted. In addition, this study suggests that the regression model containing such independent variables that are statistically significant can be applied to as a foundational guideline for the plant construction project risk analysis during the phase of construction and commissioning.

• Journal of Satellite, Information and Communications
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• v.8 no.3
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• pp.52-57
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• 2013

This paper describes the color comparison analysis of flame in each standard color model in order to propose the optimal color model for image processing based flame detection algorithm. Histogram intersection values were used to analyze the separation characteristics between color of flame and color of non-flame in each standard color model which are RGB, YCbCr, CIE Lab, HSV. Histogram intersection value in each color model and components is evaluated for objective comparison. The analyzed result shows that YCbCr color model is the most suitable for flame detection by average HI value of 0.0575. Among the 12 components of standard color models, each Cb, R, Cr component has respectively HI value of 0.0433, 0.0526, 0.0567 and they have shown the best flame separation characteristics.

• Information Systems Review
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• v.23 no.3
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• pp.51-75
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• 2021

Global e-commerce websites offer personalized recommendation services to gain sustainable competitiveness. Existing studies have offered personalized recommendation services using quantitative preferences such as ratings. However, offering personalized recommendation services using only quantitative data has raised the problem of decreasing recommendation performance. For example, a user gave a five-star rating but wrote a review that the user was unsatisfied with hotel service and cleanliness. In such cases, has problems where quantitative and qualitative preferences are inconsistent. Recently, a growing number of studies have considered review data simultaneously to improve the limitations of existing personalized recommendation service studies. Therefore, in this study, we identify review and rating mismatches and build a new user profile to offer personalized recommendation services. To this end, we use deep learning algorithms such as CNN, LSTM, CNN + LSTM, which have been widely used in sentiment analysis studies. And extract sentiment features from reviews and compare with quantitative preferences. To evaluate the performance of the proposed methodology in this study, we collect user preference information using real-world hotel data from the world's largest travel platform TripAdvisor. Experiments show that the proposed methodology in this study outperforms the existing other methodologies, using only existing quantitative preferences.

• Journal of the Korea Concrete Institute
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• v.22 no.2
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• pp.209-217
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• 2010

Recently, some mathematical models for the prediction on progress of carbonation of concrete were reported. These models take account for $CO_2$ diffusion and chemical reaction between $Ca(OH)_2$ and $CO_2$. Based on the assumption that $CO_2$ diffuses in the carbonation zone and reacts with $Ca(OH)_2$ at the outer face of carbonation zone and non-carbonation zone. In this study, a mathematical model to predict the progress of carbonation of concrete has been established based on the reducing concentration of $Ca(OH)_2$ in the carbonation progress zone, where $Ca(OH)_2$ reacts with $CO_2$ and $Ca(OH)_2$ and $CaCO_3$ coexist. Also, the prediction model of carbonation progress rate of concrete using the air permeability coefficient regarding to $CO_2$ diffusion is developed. As a result of this study, an expression, the model equation is obtained for the prediction of carbonation based on the time and interaction velocity between $CO_2$ and Ca(OH)$_2$ dependent air permeability coefficient. The prediction by the model satisfied the experimental data of the accelerated carbonation for painted concrete. Consequently, the model can predict the rate of carbonation and the potential service life of concrete structure exposed to atmosphere.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.28 no.6
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• pp.1427-1437
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• 2018

While biometric authentication system has been in general use, research is ongoing to apply biometric data to public key infrastructure. It is a significant task to generate a cryptographic key from biometrics in setting up a public key of Bio-PKI. Methods for generating the key by quantization of feature vector can cause data loss and degrade the performance of key extraction. In this paper, we suggest a new method for generating a cryptographic key from classification results of biometric data using multiple classifying models. Our proposal does not cause data loss of feature vector so it showed better performance in key extraction. Also, it uses the multiple models to generate key blocks which produce sufficient length of the key.

• Korean Journal of Food Science and Technology
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• v.37 no.6
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• pp.1012-1017
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• 2005

Predictive growth model of putrefactive bacteria of surimi-based imitation crab in the modified surimi-based imitation crab (MIC) broth was investigated. The growth curves of putrefactive bacteria were obtained by measuring cell number in MIC broth under different conditions (Initial cell number, $1.0{\times}10^2,\;1.0{\times}10^3$ and $1.0{\times}10^4$ colony forming unit (CFU)/mL; temperature, $15^{\circ}C,\;20^{\circ}C\;and\;25^{\circ}C$) and applied them to Gompertz model. The microbial growth indicators, maximum specific growth rate constant (k), lag time (LT) and generation time (GT), were calculated from Gompertz model. Maximum specific growth rate (k) of putrefactive bacteria was become fast with rising temperature and fastest at $25^{\circ}C$. LT and GT were become short with rising temperature and shortest at $25^{\circ}C$. There were not significant differences in k, LT and GT by initial cell number (p>0.05). Polynomial model, $k=-0.2160+0.0241T-0.0199A_0$, and square root model, $\sqrt{k}=0.02669$ (T-3.5689), were developed to express the combination effects of temperature and initial cell number, The relative coefficient of experimental k and predicted k of polynomial model was 0.87 from response surface model. The relative coefficient of experimental k and predicted k of square root model was 0.88. From above results, we found that the growth of putrefactive bacteria was mainly affected by temperature and the square root model was more credible than the polynomial model for the prediction of the growth of putrefactive bacteria.

• Journal of Energy Engineering
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• v.16 no.3
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• pp.93-102
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• 2007

This paper presents a scenario evaluation model of the AHP (Analytic Hierarchy Process) to evaluate dismantling scenarios considering quantitative and qualitative considerations. And decommissioning information producing modules which can obtain a dismantling schedule, quantify radioactive waste, visualize a radioactive inventory, estimate a decommissioning cost, and estimate a worker's exposure was developed to assess qualitatively decommissioning information. The digital mock-up (DMU) system was developed to verify dismantling processes and find error of scenarios in virtual space. It combines and manages the decommissioning information producing modules, the decommissioning DB, and the dismantling evaluation module synthetically. By using AHP model and DMU system, the thermal column in KRR-1 was evaluated on plasma arc cutting scenario and nibbler cutting scenario using the developed decommissioning DMU system.

• Economic and Environmental Geology
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• v.38 no.4 s.173
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• pp.369-380
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• 2005

This study describes image-based approach for efficient and objective evaluation method of the rock slope stability. Three-dimensional rock slope model was reconstructed by processing stereo digital images. The model provided fundamental information for geospatial analysis of the rock slope. Methods to extract three-dimensional information about discontinuity on the rock slope and to estimate roughness of the rock surfaces were suggested. The results show that stereo digital images have potential to provide information for both quantitative and qualitative analysis of rock slope. In addition, visualization of the results increases efficiency and benefit in evaluating rock slope stability.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.80-80
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• 2016

GPS로 대표되는 위성항법시스템(GNSS : Global Navigation Satellite System)은 지구 주위를 돌면서 연속적으로 항법신호를 보내고 있다. 그 중 지구표면으로부터 반사되는 항법신호를 수신하고 해석함으로써 지구표면에 관한 정보를 취득할 수가 있다. GPS로 대표되는 항법신호는 L밴드를 사용하기 때문에 토양수분의 변화 등에 대한 반사강도의 감도가 비교적 높다고 알려져 있으며, 토양수분 측정 등에 사용할 수 있다. 뿐만 아니라 경량화, 소형화하기 쉬운 점, 능동적 마이크로웨이브 리모트센싱시스템(Active Microwave Remote Sensing System)과 달리 스스로 신호를 발사하지 않기 때문에 관측의 스텔스성(Stealth)dl 뛰어난 점 등의 장점을 가지고 있다. 또한 향후 10년 이내에 준천정위성(QZSS), Galileo, COMPAS, IRNSS 등 많은 위성항법시스템이 본격 운용되어 GPS와 함께 120기 정도의 항법위성이 항법신호를 송신할 예정이므로 이용 가능성은 크게 늘어날 것으로 기대된다.한편, 항법위성을 이용한 바이스테이틱 리모트센싱은 반사파의 강도가 상당히 미약하기 때문에 정량적 계측모델의 구축은 미미한 상태이다. 즉, 지상 타워에서의 관측, 항공기에서의 관측, 소형 위성에서의 관측 등이 수행되고 있으나, 타워관측과 같이 지상의 거의 동일한 장소를 계속적으로 관측하는 경우를 제외한 기존의 연구에서는 토지의 피복상황이나 토양수분 등의 상관관계를 제시하는 수준으로써 정량적인 계측방법은 아직 확립되어 있지 않다. 이러한 관점에서 본 연구에서는 GPS위성으로부터의 항법신호를 이용하여 지구표면에 관한 정보를 얻는 바이스테이틱 리모트센싱(Bi-static Remote Sensing) 기술을 바탕으로 육지면과 해면의 판별에 신호특성이 어떻게 유효한가를 실험적으로 밝혔다. 이러한 기술은 토양수분 측정 등 수자 원인자를 추출하는데 유용할 뿐만 아니라 수면의 고도 측정, 해상풍 산출 등에도 응용 가능하다.

• Journal of the Korea Society for Simulation
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• v.5 no.1
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• pp.43-50
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• 1996

2-propanol/acetone/hydrogen 반응계로 구성된 화학적 열펌프 시스템은 낮은 온도(82.5~$90^{\circ}C$)에서의 2-propanol의 탈수소화 반응과 높은 온도(약 $200^{\circ}C$ 부근)에서의 acetone의 수소화반응을 이용하여 열을 고품위화 시키는 장치이다. 본 연구에서는 이 시스템의 해석 및 설계를 목적으로 이 시스템에 대한 수치적인 모델들을 세우고 Sequential modular approach를 이용하여 시스템의 모사를 수행하였다. 또한 에너지 효율을 최대화하기 위하여 열펌프 시스템에서의 환류비의 영향을 규명하였다. 모사결과 이 시스템의 scale up을 위한 정량적인 정상상태 운전조건들을 구할수 있었으며 두 반응의 반응 전화율이 다르더라도 반응물의 유량의 차이를 통하여 두 반응열이 거의 같아지는 것을 알수 있었다. 아울러 주어진 운전조건에서 증류의 환류비는 최소환류비 근처의 최적값이 존재함을 알수 있었다.