Mo, Hyoung-ho;Kang, Ju Wan;Cho, Kijong;Bae, Yeon Jae;Lee, Mi-Gyung;Park, Jung-Joon
Korean Journal of Environmental Biology
/
v.34
no.1
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pp.56-62
/
2016
Pest population density models are very important to monitor the initial occurrence and to understand the continuous fluctuation pattern of pest in pest management. This is one of the major issues in agriculture because these predictions make pesticides more effective and environmental impact of pesticides less. In this study, we combined and predicted the mortality change of pest caused by pesticides with temperature change and population dynamic model. Sensitive strain of two-spotted spider mite (Tetranychus urticae Koch) with kidney bean leaf as host was exposed to mixed acaricide, Acrinathrin-Spiromesifen and organotin acaricide, Azocyclotin, at 20, 25, 30, and $35^{\circ}C$, respectively. There was significant difference in mortality of T. urticae among pesticides and temperatures. We used DYMEX to simulate population density of T. urticae and predicted that the initial management time and number of chemical control would be changed in the future with climate change. There would be implications for strategies for pest management and selection process of pesticide in the future corresponding climate change.
Korean Journal of Construction Engineering and Management
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v.6
no.3
s.25
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pp.144-155
/
2005
Since 1950s, the Korean housing market has continually experienced the chronicle lack of housing stock because of lower housing investment in comparison with a population explosion, prompt urbanization and rapid restructuring of family. The Korean housing market have thus been driven not by the pricing model by housing demand-supply chain but by the Korean housing policies focusing on the increase of housing supply and the living stability of the middle or low-income bracket. After all, repetitive economic vicious circle of housing price and the increase of unsold apartments aggravated the malfunction of the Korean housing market. Meanwhile, the Korean construction firms have exacerbated their profitability. Such terrible situations are mainly triggered by the Korean construction firms that weighed on the short-term profits and quick response of the government policy alterations rather than the prospect of housing market Therefore, this research focusing on the dynamics of housing market identified and classified the demand and supply elements that consist not only of housing system structures but also of the environmental elements that affect the structures. Based on the system thinking and traditional theory of consumer's choice, the interactions of these elements were constructed as a causal loop diagram that explains the mutual influences among housing subsystems with feedback loops. This paper describes and discusses about the causes of the dynamic changes in the Korean housing market. This study would help housing suppliers, including housing developers, construction firms, etc., to form a more comprehensive understanding on the fundamental issues that constitute the Korean housing market and thereby increasing their long term as well as minimizing the risk involved in the housing supply businesses.
A system dynamic model was developed to predict food grain production under the dynamic consideration of the production circumstance and inputs such as farm population, investment on agriculture, arable land, extensive technology and weather. By using the model, the variation of the food grain production from 1978 to 2008 was examined. The results of the model output says it is desirable that the persistent and long-term program should be studied to get necessary food grain production under the variational inputs and circumstances.
Kim, Eunjung;Park, Changmin;Na, Mijeong;Park, Hyeon;Kim, Bogsoon
Journal of Korean Society on Water Environment
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v.34
no.4
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pp.363-374
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2018
The Han River serves as an important water resource for the city of Seoul, Korea and in the neighboring metropolitan areas. From the Paldang dam to the Jamsil submerged weir, the 4 water intake stations that are located for the Seoul metropolitan population were under review in this study. Therefore the water quality management in this section is very important to monitor, analyze and review to rule out any safety concerns. In this study, a 3-D hydrodynamic model, EFDC (Environmental Fluid Dynamics Code), was applied to the downstream of the Paldang Dam in the Han River, which is about 23 km in length, to determine issues related to water resource management. The 3-D grid was composed of 2,168 horizontal grids and three vertical layers. In this case, the hydrodynamic model was calibrated and verified with an observed average daily water surface elevation, water temperature and flow rate data for 3 years (2013~2015). The developed EFDC model proved to reproduce the hydrodynamics of the Han River well. The composition ratios of the noted incoming flows at the monitored intake stations for 3 years and their flow patterns in the river were analyzed using the validated model. It was found that the flow of the Wangsuk Stream depended on the Paldnag dam discharge, and it was noted that the composition ratios of the stream at the intake stations changed accordingly. In a word, the Wangsuk Stream moved mainly along the right bank of the Han River under the condition of a normal dam flow. As can be seen, when the dam discharge rate was low, the incidence of lateral mixing was often seen. The scenario analyses were also conducted to predict the transport of conservative pollutants as in the case of a chemical spill accident. Generally speaking, when scenarios were applied, the arrival time and concentration of pollutants at each intake station was thus predicted.
Recently, it is continuously rising to concern about the health risk being induced by microorganisms in food such as Escherichia coli O157:H7 and Listeria monocytogenes. Various organizations and regulatory agencies including U.S.FPA, U.S.DA and FAO/WHO are preparing the methodology building to apply microbial quantitative risk assessment to risk-based food safety program. Microbial risks are primarily the result of single exposure and its health impacts are immediate and serious. Therefore, the methodology of risk assessment differs from that of chemical risk assessment. Microbial quantitative risk assessment consists of tow steps; hazard identification, exposure assessment, dose-response assessment and risk characterization. Hazard identification is accomplished by observing and defining the types of adverse health effects in humans associated with exposure to foodborne agents. Epidemiological evidence which links the various disease with the particular exposure route is an important component of this identification. Exposure assessment includes the quantification of microbial exposure regarding the dynamics of microbial growth in food processing, transport, packaging and specific time-temperature conditions at various points from animal production to consumption. Dose-response assessment is the process characterizing dose-response correlation between microbial exposure and disease incidence. Unlike chemical carcinogens, the dose-response assessment for microbial pathogens has not focused on animal models for extrapolation to humans. Risk characterization links the exposure assessment and dose-response assessment and involve uncertainty analysis. The methodology of microbial dose-response assessment is classified as nonthreshold and thresh-old approach. The nonthreshold model have assumption that one organism is capable of producing an infection if it arrives at an appropriate site and organism have independence. Recently, the Exponential, Beta-poission, Gompertz, and Gamma-weibull models are using as nonthreshold model. The Log-normal and Log-logistic models are using as threshold model. The threshold has the assumption that a toxicant is produce by interaction of organisms. In this study, it was reviewed detailed process including risk value using model parameter and microbial exposure dose. Also this study suggested model application methodology in field of exposure assessment using assumed food microbial data(NaCl, water activity, temperature, pH, etc.) and the commercially used Food MicroModel. We recognized that human volunteer data to the healthy man are preferred rather than epidemiological data fur obtaining exact dose-response data. But, the foreign agencies are studying the characterization of correlation between human and animal. For the comparison of differences to the population sensitivity: it must be executed domestic study such as the establishment of dose-response data to the Korean volunteer by each microbial and microbial exposure assessment in food.
Journal of Family Resource Management and Policy Review
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v.15
no.3
/
pp.131-151
/
2011
This study attempted to estimate the level of perceived lack of time in Korean society, to link it to time management and to identify the possible association that accounts for time shortage. I employed the gender perspective in order to reveal the dynamics and complexity of the perception of a lack of time in the population. The sample for the study was drawn from the 1999 and 2009 Korean time diary data collected by the Korean National Statistical Office. From the original data, I selected a sample of second shift families(men and women who are presently working and raising children) living in metropolitan areas(including Seoul and six major urban areas in Korea). The dependent variable was time pressure measured by a single-item question on a four-point likert scale. The results of the study showed that working mothers perceived a greater time shortage as compared to working fathers. The time use pattern showed change during the periods, indicating that people worked fewer hours in paid labor and enjoyed more leisure hours and personal care hours. However, on average, people seemed to have experienced a greater time lack in 2009 as compared to 1999. The results from the ordered logistic regression model revealed that even though there were similarities in the impact of relevant factors, men's perception of a lack of time was more closely linked with their work role and social status, while for women, this perception was influenced by work and family duties. This indicates that Korean working mothers and fathers are facing a double jeopardy of time shortage in terms of combining their work and family roles. As a result, the level of time pressure by gender is converging toward a "never enough" phase. These findings generated policy implications and detailed suggestions.
International Journal of Control, Automation, and Systems
/
v.2
no.4
/
pp.463-474
/
2004
Game theory is a method of mathematical analysis developed to study the decision making process. In 1928, Von Neumann mathematically proved that every two-person, zero-sum game with many pure finite strategies for each player is deterministic. In the early 50's, Nash presented another concept as the basis for a generalization of Von Neumann's theorem. Another central achievement of game theory is the introduction of evolutionary game theory, by which agents can play optimal strategies in the absence of rationality. Through the process of Darwinian selection, a population of agents can evolve to an Evolutionary Stable Strategy (ESS) as introduced by Maynard Smith in 1982. Keeping pace with these game theoretical studies, the first computer simulation of coevolution was tried out by Hillis. Moreover, Kauffman proposed the NK model to analyze coevolutionary dynamics between different species. He showed how coevolutionary phenomenon reaches static states and that these states are either Nash equilibrium or ESS in game theory. Since studies concerning coevolutionary phenomenon were initiated, there have been numerous other researchers who have developed coevolutionary algorithms. In this paper we propose a new coevolutionary algorithm named Game theory based Coevolutionary Algorithm (GCEA) and we confirm that this algorithm can be a solution of evolutionary problems by searching the ESS. To evaluate this newly designed approach, we solve several test Multiobjective Optimization Problems (MOPs). From the results of these evaluations, we confirm that evolutionary game can be embodied by the coevolutionary algorithm and analyze the optimization performance of our algorithm by comparing the performance of our algorithm with that of other evolutionary optimization algorithms.
Proceedings of the Korea Water Resources Association Conference
/
2019.05a
/
pp.407-407
/
2019
According to Asian Development Bank report Pakistan is among water scarce countries. Climate scenario on the basis IPCC fifth assessment report (AR5) revealed that annual mean temperature of Pakistan from year 2010-2019 was $17C^o$ which will rise up to $21C^o$ at the end of this century, similarly almost 10% decrease of annual rainfall is expected at the end of the century. It is a changing task in underdeveloped countries like Pakistan to meet the water demands of rapidly increasing population in a changing climate. While many studies have tackled scarcity and stream flow forecasting of the Upper Indus Basin (UIB) Pakistan, very few of them are related to socio-economic and climate change impact on sustainable water management of UIB. This study investigates the pattern of current and future surface water availability for various demand sites (e.g. domestic, agriculture and industrial) under different socio-economic and climate change scenarios in Upper Indus Basin (UIB) Pakistan for a period of 2010 to 2050. A state-of-the-art planning tool Water Evaluation and Planning (WEAP) is used to analyze the dynamics of current and future water demand. The stream flow data of five sub catchment (Astore, Gilgit, Hunza, Shigar and Shoyke) and entire UIB were calibrated and validated for the year of 2006 to 2011 using WEAP. The Nash Sutcliffe coefficient and coefficient of determination is achieved ranging from 0.63 to 0.92. The results indicate that unmet water demand is likely to increase severe threshold and the external driving forces e.g. socio-economic and climate change will create a gap between supply and demand of water.
Journal of Korean Society of Industrial and Systems Engineering
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v.44
no.2
/
pp.1-14
/
2021
It is highly challenging to measure the efficiency of electric vehicle charging stations (EVCSs) because factors affecting operational characteristics of EVCSs are time-varying in practice. For the efficiency measurement, environmental factors around the EVCSs can be considered because such factors affect charging behaviors of electric vehicle drivers, resulting in variations of accessibility and attractiveness for the EVCSs. Considering dynamics of the factors, this paper examines the technical efficiency of 622 electric vehicle charging stations in Seoul using data envelopment analysis (DEA). The DEA is formulated as a multi-period output-oriented constant return to scale model. Five inputs including floating population, number of nearby EVCSs, average distance of nearby EVCSs, traffic volume and traffic congestion are considered and the charging frequency of EVCSs is used as the output. The result of efficiency measurement shows that not many EVCSs has most of charging demand at certain periods of time, while the others are facing with anemic charging demand. Tobit regression analyses show that the traffic congestion negatively affects the efficiency of EVCSs, while the traffic volume and the number of nearby EVCSs are positive factors improving the efficiency around EVCSs. We draw some notable characteristics of efficient EVCSs by comparing means of the inputs related to the groups classified by K-means clustering algorithm. This analysis presents that efficient EVCSs can be generally characterized with the high number of nearby EVCSs and low level of the traffic congestion.
Journal of the Korean Institute of Intelligent Systems
/
v.14
no.3
/
pp.253-261
/
2004
Game theory is mathematical analysis developed to study involved in making decisions. In 1928, Von Neumann proved that every two-person, zero-sum game with finitely many pure strategies for each player is deterministic. As well, in the early 50's, Nash presented another concept as the basis for a generalization of Von Neumann's theorem. Another central achievement of game theory is the introduction of evolutionary game theory, by which agents can play optimal strategies in the absence of rationality. Not the rationality but through the process of Darwinian selection, a population of agents can evolve to an Evolutionary Stable Strategy (ESS) introduced by Maynard Smith. Keeping pace with these game theoretical studies, the first computer simulation of co-evolution was tried out by Hillis in 1991. Moreover, Kauffman proposed NK model to analyze co-evolutionary dynamics between different species. He showed how co-evolutionary phenomenon reaches static states and that these states are Nash equilibrium or ESS introduced in game theory. Since the studies about co-evolutionary phenomenon were started, however many other researchers have developed co-evolutionary algorithms, in this paper we propose Game theory based Co-Evolutionary Algorithm (GCEA) and confirm that this algorithm can be a solution of evolutionary problems by searching the ESS.To evaluate newly designed GCEA approach, we solve several test Multi-objective Optimization Problems (MOPs). From the results of these evaluations, we confirm that evolutionary game can be embodied by co-evolutionary algorithm and analyze optimization performance of GCEA by comparing experimental results using GCEA with the results using other evolutionary optimization algorithms.
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