• Journal of Korea Water Resources Association
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• v.32 no.6
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• pp.627-636
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• 1999

In 60 years when the double $CO_2$concentration is anticipated the average annual rainfall depth is expected to be increased by 5 10% due to global warming. However, in the water resources area the frequency change of meteorological extremes such as droughts and floods attracts more interests than the increase of annual rainfall amount. Even though recent frequent occurrences of this kind of meteorological extremes are assumed as an indirect proof of global warming, the prediction of its overall tendency has not yet been made. Thus, in this research we propose a possible methodology to be used for its prediction. The methodology proposed is based on the frequency distribution of daily rainfall be Todorovie and Woolhiser(1975), and Katz(1977), where the input parameters are modified to consider the change of monthly or annual rainfall depth and, thus, to result in the change of frequency distribution. We adopt two values(10mm, 50mm) as thresholds and investigate the change of occurrence probability due to the change monthly and annual rainfall depth. these changes do not directly indicate the changes of occurrence probability of floods and droughts, but it may still be a very useful information for their prediction. Finally, the changes of occurrence probability were found to be greater when considering the monthly rainfall rather than the annual rainfall, and those in rainy season than those in dry season.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.38 no.6
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• pp.839-850
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• 2018

The flood damage in urban areas due to torrential rain is increasing with urbanization. For this reason, accurate and rapid flooding forecasting and expected inundation maps are needed. Predicting the extent of flooding for certain rainfalls is a very important issue in preparing flood in advance. Recently, government agencies are trying to provide expected inundation maps to the public. However, there is a lack of quantifying the extent of inundation caused by a particular rainfall scenario and the real-time prediction method for flood extent within a short time. Therefore the real-time prediction of flood extent is needed based on rainfall-runoff-inundation analysis. One/two dimensional model are continued to analyize drainage network, manhole overflow and inundation propagation by rainfall condition. By applying the various rainfall scenarios considering rainfall duration/distribution and return periods, the inundation volume and depth can be estimated and stored on a database. The Rainfall-Duration-Flooding Quantity (RDF) relationship curve based on the hydraulic analysis results and the Self-Organizing Map (SOM) that conducts unsupervised learning are applied to predict flooded area with particular rainfall condition. The validity of the proposed methodology was examined by comparing the results of the expected flood map with the 2-dimensional hydraulic model. Based on the result of the study, it is judged that this methodology will be useful to provide an unknown flood map according to medium-sized rainfall or frequency scenario. Furthermore, it will be used as a fundamental data for flood forecast by establishing the RDF curve which the relationship of rainfall-outflow-flood is considered and the database of expected inundation maps.

• Geomechanics and Engineering
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• v.35 no.5
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• pp.539-554
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• 2023

This article is dedicated to the pursuit of establishing a robust empirical relationship that allows for the estimation of in-situ modulus of deformations (E_m and G_m) within sedimentary rock slope masses through the utilization of Q_slope values. To achieve this significant objective, an expansive and thorough methodology is employed, encompassing a comprehensive field survey, meticulous sample collection, and rigorous laboratory testing. The study sources a total of 26 specimens from five distinct locations within the South Pars (known as Assalouyeh) region, ensuring a representative dataset for robust correlations. The results of this extensive analysis reveal compelling empirical connections between E_m, geomechanical characteristics of the rock mass, and the calculated Q_slope values. Specifically, these relationships are expressed as follows: E_m = 2.859 Q_slope + 4.628 (R² = 0.554), and G_m = 1.856 Q_slope + 3.008 (R² = 0.524). Moreover, the study unravels intriguing insights into the interplay between in-situ deformation moduli and the widely utilized Rock Mass Rating (RMR) computations, leading to the formulation of equations that facilitate predictions: RMR = 18.12 E_m0.460 (R² = 0.798) and RMR = 22.09 G_m0.460 (R² = 0.766). Beyond these correlations, the study delves into the intricate relationship between RMR and Rock Quality Designation (RQD) with Qslope values. The findings elucidate the following relationships: RMR = 34.05e^0.33Qslope (R² = 0.712) and RQD = 31.42e^0.549Qslope (R² = 0.902). Furthermore, leveraging the insights garnered from this comprehensive analysis, the study offers an empirically derived support system tailored to the distinct characteristics of discontinuous rock slopes, grounded firmly within the framework of the Q_slope methodology. This holistic approach contributes significantly to advancing the understanding of sedimentary rock slope stability and provides valuable tools for informed engineering decisions.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.23 no.2
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• pp.119-131
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• 2024

Understanding accurate traffic performance is crucial for ensuring efficient highway operation and providing a sustainable mobility environment. On the other hand, an immediate and precise estimation of highway traffic performance faces challenges because of infrastructure and technological constraints, data processing complexities, and limitations in using integrated big data. This paper introduces a framework for estimating traffic performance by analyzing real-time data sourced from toll collection systems and dedicated short-range communications used on highways. In particular, this study addresses the data errors arising from segmented information in data, influencing the individual travel trajectories of vehicles and establishing a more reliable Origin-Destination (OD) framework. The study revealed the necessity of trip linkage for accurate estimations when consecutive segments of individual vehicle travel within the OD occur within a 20-minute window. By linking these trip ODs, the daily average highway traffic performance for South Korea was estimated to be248,624 thousand vehicle kilometers per day. This value shows an increase of approximately 458 thousand vehicle kilometers per day compared to the 248,166 thousand vehicle kilometers per day reported in the highway operations manual. This outcome highlights the potential for supplementing previously omitted traffic performance data through the methodology proposed in this study.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.35 no.6
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• pp.1347-1356
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• 2015

Since 1970 transportation investment has been made rapidly, however the doubt on duplication and overinvestment of transportation facility also has been brought up. Thus the necessity for reasonable estimation of investment scale increases. In this paper various researches related to this subject are reviewed and categorized according to their methodologies, namely, the methodology using international comparison, trend of investment policy and endogenous economy development model. Based on these methodologies, AHP is applied to calculate proper investment scale. The result shows that the budget for satisfying the investment scale is estimated about 19.51~24.49 trillion won. This value is 4.28~9.26 trillion won higher than the proper investment budget established in National Fiscal Management Plan. In the future, it is necessary to establish systematic and efficient transportation investment plan by developing transportation policy model which can assess the economic feasibility, social equity and environmental soundness etc. at the same time.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.5
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• pp.1969-1980
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• 2013

The Traffic congestion is caused by the increasing traffic demand. Thus, economic losses have been increasing every year. To solve these problems, car sharing and rental car systems that are equipped with IT technologies emerge. Car sharing has many advantages-the alleviation of the traffic congestion, the saving of maintenance cost for cars, the reduction of car possessiveness, the solution for the hassle of car ownership, for business and personal duty, and the improvement of connectivity between public transportations-. The goal of the car sharing is to achieve low-carbon and eco-friendly transportation. In this study, we review papers related to the car sharing system and the cost system of traffic systems. We estimate the optimal cost of the cloud traffic system that is one of the car sharing services. We suggest a methodology to estimate operational cost and use cost through the analysis of cost system between similar traffic means. The range of the maximum and minimum cost was determined through the comparison and analysis of similar traffic means. Expected demand and the cost that people are willing to pay were estimated through optimized value pricing. The minimum cost per hour that was compared to the cost of rental car was estimated at 5,333 won and the maximum cost per hour that was compared to taxi cost was estimated at 17,700 won. The cost for users was estimated at 6,930 won. The cost of 50% demands was estimated at 6,550won. Future studies should analyze service hours of users, weather, demand pattern and trend and consider them into the cost estimation.

• Journal of Korean Society of Transportation
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• v.32 no.4
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• pp.303-314
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• 2014

This study develops a $CO_2$ emissions estimation method, which considers different O/D travel patterns and through traffic volumes, in different regions for $CO_2$ emissions management in the field of transportation. In the research, O/D and network data provided by the Korea Transport Database (KTDB) Center are used as basic data. The results show that the total emission was similar to the Metropolitan's total emission which was estimated by KTDB (2009). With the analysis focusing on Gyeonggi-do, the results show that $CO_2$ emission from through traffic volumes was greater than $CO_2$ emissions of the Intra-Regional in southern regions; By contrast, $CO_2$ emissions of the Intra-Regional was greater than that from through traffic volumes in northern regions. Therefore, the $CO_2$ emissions management needs to be segregated into local government and nation with each travel pattern.

• Progress in Medical Physics
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• v.21 no.1
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• pp.93-98
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• 2010

The aim of this work was to establish the methodology for event positioning by measuring depth of interaction (DOI) information and to evaluate the system sensitivity and spatial resolution of the new detector for I-125 and Tc-99m imaging. For this purpose, a Monte Carlo simulation tool, DETECT2000 and GATE were used to model the energy deposition and light distribution in the detector and to validate this approach. Our proposed detector module consists of a monolithic CsI(Tl) crystal with dimensions of $50.0{\times}50.0{\times}3.0\;mm^3$. The results of simulation demonstrated that the resolution is less than 1.5 mm for both I-125 and Tc-99m. The main advantage of the proposed detector module is that by using 3 mm thick CsI(Tl) with maximum-likelihood position-estimation (MLPE) method, high resolution I-125 imaging and high sensitivity Tc-99m imaging are possible. In this paper, we proved that our new detector to be a reliable design as a detector for a multi-energy SPECT.

• Journal of Intelligence and Information Systems
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• v.17 no.3
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• pp.1-23
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• 2011

The contextual subjective well-being (SWB) of context-aware system users can be very helpful in recommending relevant mental health services, especially for those who struggle with mental illness due to a metabolic syndrome or melancholia. Self-surveying measuring or auto-sensing methods have been suggested to monitor users' SWB. However, self-surveying measuring method is not inappropriate for a context-aware service due to requesting personal data in a manual and hence obtrusive manner. Moreover, auto-sensing methods still suffer from accuracy problem to be applied in mental health services. Hence, the purpose of this paper is to propose a contextual SWB estimation method to estimate the user's mental health in unobtrusive and accurate manners. This method is timely in that it acquires context data from the user's literal responses, which expose their temporal feeling. In particular, we developed a measuring method based on exposed feeling verbs and degree adverbs in chat and other text-based communications which show anger or negative feelings. Based on the proposed contextual SWB degree estimation method, we developed an idea of well-being life care recommendation. From the experiment with actual drivers, we demonstrated that the proposed method accurately estimate the user's degree of negative feelings even though it does not require a self-survey.

• Korean Journal of Soil Science and Fertilizer
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• v.44 no.2
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• pp.256-262
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• 2011

Currently among the several methods to estimate an environmental impact of products, Life Cycle Assessment (LCA) technique is mostly used. The Ministry of Environment has been performed the carbon footprint labelling to give the carbon record of product by using this method. But the calculation of carbon footprint in primary agricultural product which is raw material of the processed food cannot be made because there is lack of methodology and LCI DB at agriculture sector. Therefore, LCA carried out to estimate carbon footprint, and established LCI DB for complex fertilizers (21-17-17 1 kg, 17-21-17 1 kg, 15-15-15 1 kg, Unspecified 1 kg) in the production system. The result of LCI DB analysis focussed on the GHG, and it was observed that the values of carbon footprint were $2.42E+00kg\;CO_2-eq.kg^{-1}$ for 21-17-17, $2.10E+00kg\;CO_2-eq.kg^{-1}$ for 17-21-17, $2.23E+00kg\;CO_2-eq.kg^{-1}$ for 15-15-15 and $3.56E+00kg\;CO_2-eq.kg^{-1}$ for Unspecified. For the analysis of LCIA (Life Cycle Impact Assessment) on complex fertilizers in the production system, the carbon footprint from pre-manufacturing phase is contributed to 98.96%, 98.81%, 98.88% and 99.30% on each complex fertilizer with 21-17-17, 17-21-17, 15-15-15, and Unspecified, respectively. These results will be used in basic data for estimation of agricultural greenhouse gas emissions.