• Environmental and Resource Economics Review
• /
• v.26 no.3
• /
• pp.359-398
• /
• 2017

Uncertainty is central to energy and climate policy. A growing number of literature show that almost all components of energy and climate models are, to some extent, uncertain and that the effect of uncertainty on the model outputs, in turn policy recommendations, is significantly large. Most existing energy and climate-economy models developed and used in Korea, however, do not take uncertainty into account explicitly. Rather, many models conduct a deterministic analysis or do a simple (limited) sensitivity analysis. In order to help social planners to make more robust decisions (across various plausible situations) on energy and climate change issues, an uncertainty analysis should be conducted. As a first step, this paper reviews the theory of decision making under uncertainty and the method for addressing uncertainty of existing probabilistic energy and climate-economy models. In addition, the paper proposes a strategy to apply an uncertainty analysis to energy and climate-economy models used in Korea. Applying the uncertainty analysis techniques, this paper revises the FUND model and investigates the impacts of climate change in Korea.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.14 no.1
• /
• pp.85-93
• /
• 2015

Previous studies have estimated crash prediction models with the fixed effect model which assumes the fixed value of coefficients without considering characteristics of each intersections. However the fixed effect model would estimate under estimation of the standard error resulted in over estimation of t-value. In order to overcome these shortcomings, the random effect model can be used with considering heterogeneity of AADT, geometric information and unobserved factors. In this study, data collections from 89 intersections in Daejeon and estimates of crash prediction models were conducted using the random and fixed effect negative binomial regression model for comparison and analysis of two models. As a result of model estimates, AADT, speed limits, number of lanes, exclusive right turn pockets and front traffic signal were found to be significant. For comparing statistical significance of two models, the random effect model could be better statistical significance with -1537.802 of log-likelihood at convergence comparing with -1691.327 for the fixed effect model. Also likelihood ration value was computed as 0.279 for the random effect model and 0.207 for the fixed effect model. This mean that the random effect model can be improved for statistical significance of models comparing with the fixed effect model.

• Journal of Korea Water Resources Association
• /
• v.34 no.4
• /
• pp.347-356
• /
• 2001

Even though the increase of greenhouse gases such as $CO_2$ is thought to be the main cause for global warming, its impact on global climate has not been revealed clearly in rather quantitative manners. However, researches using Genral Circulation Model(GCM) has shown that the accumulation of greenhouse gases increases the global mean temperature, which in turn impacts on the global water circulation pattern. A climate predictive capability is limited by lack of understanding of the different process governing the climate and hydrologic systems. The prediction of the complex responses of the fully coupled climate and hydrologic systems can be achieved only through development of models that adequately describe the relevant process at a wide range of spatial and temporal scales. These models must ultimately couple the atmospheres, oceans, and lad and will involve many submodels that properly represent the individual processes at work within the coupled components of systems. So far, there are no climate and related hydrologic models except local rainfall-runoff models in Korea. The purpose of this research is to predict the change of temperature in Korean Peninsula using regional scale model(IRSHAM96 model) and GCM data obtained from the increasing scenarios of $CO_2$ Korean Peninsula increased by $2.5^{\circ}C$ and the duration of Winter in $lxCO_2$ condition would be shorter the $2xCo_2$ condition due to global warming.

• International journal of advanced smart convergence
• /
• v.12 no.4
• /
• pp.208-216
• /
• 2023

The purpose of our study is to design datasets for Artificial Intelligence learning for cold sea fish farming. Salmon is considered one of the most popular fish species among men and women of all ages, but most supplies depend on imports. Recently, salmon farming, which is rapidly emerging as a specialized industry in Gangwon-do, has attracted attention. Therefore, in order to successfully develop salmon farming, the need to systematically build data related to salmon and salmon farming and use it to develop aquaculture techniques is raised. Meanwhile, the catch of pollack continues to decrease. Efforts should be made to improve the major factors affecting pollack survival based on data, as well as increasing the discharge volume for resource recovery. To this end, it is necessary to systematically collect and analyze data related to pollack catch and ecology to prepare a sustainable resource management strategy. Image data was obtained using CCTV and underwater cameras to establish an intelligent aquaculture strategy for salmon and pollock, which are considered representative fish species in Gangwon-do. Using these data, we built learning data suitable for AI analysis and prediction. Such data construction can be used to develop models for predicting the growth of salmon and pollack, and to develop algorithms for AI services that can predict water temperature, one of the key variables that determine the survival rate of pollack. This in turn will enable intelligent aquaculture and resource management taking into account the ecological characteristics of fish species. These studies look forward to achievements on an important level for sustainable fisheries and fisheries resource management.

• Asian-Australasian Journal of Animal Sciences
• /
• v.28 no.5
• /
• pp.703-715
• /
• 2015

One of the challenges to increase milk production in a large pasture-based herd with an automatic milking system (AMS) is to grow forages within a 1- km radius, as increases in walking distance increases milking interval and reduces yield. The main objective of this study was to explore sustainable forage option technologies that can supply high amount of grazeable forages for AMS herds using the Agricultural Production Systems Simulator (APSIM) model. Three different basic simulation scenarios (with irrigation) were carried out using forage crops (namely maize, soybean and sorghum) for the spring-summer period. Subsequent crops in the three scenarios were forage rape over-sown with ryegrass. Each individual simulation was run using actual climatic records for the period from 1900 to 2010. Simulated highest forage yields in maize, soybean and sorghum- (each followed by forage rape-ryegrass) based rotations were 28.2, 22.9, and 19.3 t dry matter/ha, respectively. The simulations suggested that the irrigation requirement could increase by up to 18%, 16%, and 17% respectively in those rotations in El-Nino years compared to neutral years. On the other hand, irrigation requirement could increase by up to 25%, 23%, and 32% in maize, soybean and sorghum based rotations in El-Nino years compared to La-Nina years. However, irrigation requirement could decrease by up to 8%, 7%, and 13% in maize, soybean and sorghum based rotations in La-Nina years compared to neutral years. The major implication of this study is that APSIM models have potentials in devising preferred forage options to maximise grazeable forage yield which may create the opportunity to grow more forage in small areas around the AMS which in turn will minimise walking distance and milking interval and thus increase milk production. Our analyses also suggest that simulation analysis may provide decision support during climatic uncertainty.

• Structural Engineering and Mechanics
• /
• v.77 no.4
• /
• pp.441-461
• /
• 2021

Reinforced concrete (RC) columns are crucial in building structures and they are of higher vulnerability to terrorist threat than any other structural elements. Thus it is of great interest and necessity to achieve a comprehensive understanding of the possible responses of RC columns when exposed to high intensive blast loads. The primary objective of this study is to derive analytical formulas to assess vulnerability of RC columns using an advanced numerical modelling approach. This investigation is necessary as the effect of blast loads would be minimal to the RC structure if the explosive charge is located at the safe standoff distance from the main columns in the building and therefore minimizes the chance of disastrous collapse of the RC columns. In the current research, finite element model is developed for RC columns using LS-DYNA program that includes a comprehensive discussion of the material models, element formulation, boundary condition and loading methods. Numerical model is validated to aid in the study of RC column testing against the explosion field test results. Residual capacity of RC column is selected as damage criteria. Intensive investigations using Arbitrary Lagrangian Eulerian (ALE) methodology are then implemented to evaluate the influence of scaled distance, column dimension, concrete and steel reinforcement properties and axial load index on the vulnerability of RC columns. The generated empirical formulae can be used by the designers to predict a damage degree of new column design when consider explosive loads. With an extensive knowledge on the vulnerability assessment of RC structures under blast explosion, advancement to the convention design of structural elements can be achieved to improve the column survivability, while reducing the lethality of explosive attack and in turn providing a safer environment for the public.

• Proceedings of the Korean Operations and Management Science Society Conference
• /
• 2001.10a
• /
• pp.25-28
• /
• 2001

Today enterprises are bringing forward the strong needs for the Global Work Space that is able to realize the collaboration of the virtual enterprise in order to achieve the rapid entrance to market, the quality improvement as well as the cost reduction of their new products. Especially, they are building the efficient Product Management Infrastructure in parallel with the real-time knowledge management for the information generated in the course of a product lifecycle and the Process Innovation making the Concurrent Engineering possible. Building a system in the web environment cannot be the entire effort to realize the Global Work Space within an enterprise that is an essential factor for the reduction of a product development period which in turn contributes to Time to Market. Various work models and processes are found in enterprises and many different application programs are developed and utilized to support these. This study proposes a scheme for the optimized Collaborative Workflow System Architecture that is able to take in and apply various application programs accompanied by the product development work process. Through this, we are to examine various limits and problems existing in the real-time collaborative system between enterprises and to reform these.

• Fashion & Textile Research Journal
• /
• v.20 no.1
• /
• pp.34-49
• /
• 2018

Sustainability in fashion pertains to all stages within the product lifecycle, starting with the procurement of raw materials and ending with the disposal of the product. To clarify, the Lifecycle Management (LCM) views the Triple Bottom Line (TBL) from the perspective of a product's lifecycle. Sustainable products are identified based on their lifecycle, causing public attention to turn towards Product Lifecycle Management (PLM). As of now, PLM is largely known to have a strong impact on New Product Development (NPD). As such, the objective of this research is to study how PLM-based sustainable NPD models, when applied to the fashion industry, can produce a wide understanding of sustainable fashion products from a variety of angles. In order to achieve the research objective, this study did a selective case study on 20 sustainable fashion brands; conducted 1:1 in-depth interviews with 24 fashion experts, including both sustainable and non-sustainable experts; and took part in participant observation of 5 sustainable fashion brands. The results of the study indicate that there are specific conditions that must be met at each stage of production for the development of sustainable products by fashion brands. However, due to the lack of technological skills and the dearth of sustainability experts within the organization, management, monitoring and systematic collection of data is not properly implemented - leading to problems with the quantification of crucial data. This study aims to further forward the debate regarding the development of sustainable fashion products and its future implications.

• School Mathematics
• /
• v.15 no.1
• /
• pp.121-136
• /
• 2013

The purpose of study was to develop distance education programs that combine the characteristics of the programs for the math gifted students. To this end, the first is to establish the standards for the development of distance programs for the math gifted students. The second is to develop the distance education programs for the elementary school math gifted students according to the program procedure models for distance education. The third is to apply the programs developed to actual distance education field and analyze the results to verify the validity of the programs. This program can increase high-level mathematical thinking power even though it is the distance education, not the face-to-face education. Second, this program make contributions to active mathematical communication through newsgroup or reflective journals. Third, the use of Diffy Game facilitates the selection of in-depth contents, which will in turn enable the development of intensive programs.

• Journal of Korean Society of Rural Planning
• /
• v.24 no.3
• /
• pp.137-144
• /
• 2018

The purpose of this study is to measure the cost-benefit of a road construction project in Vietnam through international development cooperation, which includes private grants and Official Development Assistance(ODA). In developing countries, it is difficult and costly to use data on markets, the CVM(Contingent Valuation Method) to measure the WTP(Willingness-to-Pay) as the benefits of road construction are used. A total of 232 villagers in 16 villages of Lao Cai Province in Northern Vietnam have been surveyed. It is found that the Benefit-Cost Ratio(B/C) in all 3 models are found to be well over 1.0, ranging from 2.8 to 3.64 with the discount rate of 0.06. These BC ratios imply the road construction project in Lao Cai can be justified. Also, it is found that the shortened travel time is the most relevant factor for WTP among direct benefits and the enhanced academic achievement of the children is the most relevant factor among indirect benefits, due to easier and faster access to schools, which in turn increase the school attendance rate. The result of this study can be used to justify other similar projects in Vietnam, even though the benefits may have to be reassessed in other countries.