• Proceedings of the Korea Water Resources Association Conference
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• 2011.05a
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• pp.18-18
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• 2011

Climate change is impacting and will increasingly impact both the quantity and quality of the world's water resources in a variety of ways. In some areas warming climate results in increased rainfall, surface runoff, and groundwater recharge while in others there may be declines in all of these. Water quality is described by a number of variables. Some are directly impacted by climate change. Temperature is an obvious example. Notably, increased atmospheric concentrations of $CO_2$ triggering climate change increase the $CO_2$ dissolving into water. This has manifold consequences including decreased pH and increased alkalinity, with resultant increases in dissolved concentrations of the minerals in geologic materials contacted by such water. Climate change is also expected to increase the number and intensity of extreme climate events, with related hydrologic changes. A simple framework has been developed in New Zealand for assessing and predicting climate change impacts on water resources. Assessment is largely based on trend analysis of historic data using the non-parametric Mann-Kendall method. Trend analysis requires long-term, regular monitoring data for both climate and hydrologic variables. Data quality is of primary importance and data gaps must be avoided. Quantitative prediction of climate change impacts on the quantity of water resources can be accomplished by computer modelling. This requires the serial coupling of various models. For example, regional downscaling of results from a world-wide general circulation model (GCM) can be used to forecast temperatures and precipitation for various emissions scenarios in specific catchments. Mechanistic or artificial intelligence modelling can then be used with these inputs to simulate climate change impacts over time, such as changes in streamflow, groundwater-surface water interactions, and changes in groundwater levels. The Waimea Plains catchment in New Zealand was selected for a test application of these assessment and prediction methods. This catchment is predicted to undergo relatively minor impacts due to climate change. All available climate and hydrologic databases were obtained and analyzed. These included climate (temperature, precipitation, solar radiation and sunshine hours, evapotranspiration, humidity, and cloud cover) and hydrologic (streamflow and quality and groundwater levels and quality) records. Results varied but there were indications of atmospheric temperature increasing, rainfall decreasing, streamflow decreasing, and groundwater level decreasing trends. Artificial intelligence modelling was applied to predict water usage, rainfall recharge of groundwater, and upstream flow for two regionally downscaled climate change scenarios (A1B and A2). The AI methods used were multi-layer perceptron (MLP) with extended Kalman filtering (EKF), genetic programming (GP), and a dynamic neuro-fuzzy local modelling system (DNFLMS), respectively. These were then used as inputs to a mechanistic groundwater flow-surface water interaction model (MODFLOW). A DNFLMS was also used to simulate downstream flow and groundwater levels for comparison with MODFLOW outputs. MODFLOW and DNFLMS outputs were consistent. They indicated declines in streamflow on the order of 21 to 23% for MODFLOW and DNFLMS (A1B scenario), respectively, and 27% in both cases for the A2 scenario under severe drought conditions by 2058-2059, with little if any change in groundwater levels.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.1C
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• pp.21-35
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• 2002

Nowadays, in accordance with increasing expectations of multimedia stream service on the internet, a lot of distributed applications are being required and developed. But the models of the existing systems have the problems that cannot support the extensibility and the reusability, when the QoS relating functions are being developed as an integrated modules which are suited on the centralized controlled specific-purpose application services. To cope with these problems, it is suggested in this paper to a distributed QoS management system on CORBA, an object-oriented middleware compliance. This systems we suggested can provides not only for efficient control of resources, various service QoS, and QoS control functions as the existing functions, but also QoS control real-time negotiation and dynamic adaptation in addition. This system consists of QoS Control Management Module(QoS CMM) in client side and QoS Management Module(QoS MM) in server side, respectively. These distributed modules are interfacing with each other via CORBA on different systems for distributed QoS management while serving distributed streaming applications. In phase of design of our system, we use UML(Unified Modeling Language) for designing each component in modules, their method calls and various detailed functions for controlling QoS of stream services. For implementation of our system, we used OrbixWeb 3.1c following CORBA specification on Solaris 2.5/2.7, Java language, Java Media Framework API 2.0 beta2, Mini-SQL 1.0.16 and the multimedia equipments, such as SunVideoPlus/Sun Video capture board and Sun Camera. Finally, we showed a numerical data controlled by real-time negotiation and adaptation procedures based on QoS map information to GUIs on client and server dynamically, while our distributed QoS management system is executing a given streaming service.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.4
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• pp.538-545
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• 2020

This study measured the economic impact (from 2012 through the end of 2017) of the KOR-USA FTA (Free Trade Agreement) on the Korean citrus industry according to importing orange from the USA after the implementation of the KOR-USA FTA. Citrus fruits were divided into field citrus grown in open fields, house citrus grown in green houses, and late-maturing citrus (including winter season citrus) based on the cultivation methods and the varieties of citrus. We specified the structural and dynamic recursive demand-supply equilibrium models of three citrus fruits to analyze policy simulations. The results showed that for field citrus, due to the impact of some amounts of TRQ, the annual average of the real gross revenue dropped by 2.39 billion KRW between 2012 and 2017. As for house citrus, due to the impact of oranges and cherries, the annual average of the real gross revenue declined by 3.01 billion KRW between 2012 and 2017, and for late-maturing citrus (including winter season citrus), the annual average of the real gross revenue fell by 15.11 billion KRW between 2012 and 2017. This paper also suggests several policy implications.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.7
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• pp.846-851
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• 2005

In this paper, we propose Genetic Algorithms(GAs)-based Optimized Polynomial Neural Networks(PNN). The proposed algorithm is based on Group Method of Data Handling(GMDH) method and its structure is similar to feedforward Neural Networks. But the structure of PNN is not fixed like in conventional neural networks and can be generated in a dynamic manner. As each node of PNN structure, we use several types of high-order polynomial such as linear, quadratic and modified quadratic, and it is connected as various kinds of multi-variable inputs. The conventional PNN depends on the experience of a designer that select the number of input variables, input variable and polynomial type. Therefore it is very difficult to organize optimized network. The proposed algorithm leads to identify and select the number of input variables, input variable and polynomial type by using Genetic Algorithms(GAs). The aggregate performance index with weighting factor is proposed as well. The study is illustrated with tile NOx omission process data of gas turbine power plant for application to nonlinear process. In the sequel the proposed model shows not only superb predictability but also high accuracy in comparison to the existing intelligent models.

• Korean Journal of Environmental Biology
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• v.34 no.1
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• pp.56-62
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• 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.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.36 no.12
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• pp.1683-1688
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• 2012

Topology optimization is applied for the lightweight design of three main parts of a vertical articulated robot: a base frame, a lower and a upper frame. Design domains for optimization are set as large solid regions that completely embrace the original parts, which are discretized by using three-dimensional solid elements. Design variables are parameterized one-to-one to the material properties of each element by using the SIMP method. The objective of optimization is set as the multi-objective form combining the natural frequencies and mean compliances of a structure for which load steps of interest are selected from the multibody dynamics analysis of a robot. The obtained results of topology optimization are post-processed to designs favorable to manufacturability for casting process. The final optimized results are 11.0% (base frame), 12.0% (lower frame) and 10.0% (upper frame) lighter with similar or even higher static and dynamic stiffnesses than the original models.

• Molecules and Cells
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• v.42 no.12
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• pp.893-905
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• 2019

Mitochondria are highly dynamic organelles that constantly undergo fission and fusion processes that closely related to their function. Disruption of mitochondrial dynamics has been demonstrated in acute kidney injury (AKI), which could eventually result in cell injury and death. Previously, we reported that augmenter of liver regeneration (ALR) alleviates renal tubular epithelial cell injury. Here, we gained further insights into whether the renoprotective roles of ALR are associated with mitochondrial dynamics. Changes in mitochondrial dynamics were examined in experimental models of renal ischemia-reperfusion (IR). In a model of hypoxia-reoxygenation (HR) injury in vitro, dynamin-related protein 1 (Drp1) and mitochondrial fission process protein 1 (MTFP1), two key proteins of mitochondrial fission, were downregulated in the Lv-ALR + HR group. ALR overexpression additionally had an impact on phosphorylation of Drp1 Ser637 during AKI. The inner membrane fusion protein, Optic Atrophy 1 (OPA1), was significantly increased whereas levels of outer membrane fusion proteins Mitofusin-1 and -2 (Mfn1, Mfn2) were not affected in the Lv-ALR + HR group, compared with the control group. Furthermore, the mTOR/4E-BP1 signaling pathway was highly activated in the Lv-ALR + HR group. ALR overexpression led to suppression of HR-induced apoptosis. Our collective findings indicate that ALR gene transfection alleviates mitochondrial injury, possibly through inhibiting fission and promoting fusion of the mitochondrial inner membrane, both of which contribute to reduction of HK-2 cell apoptosis. Additionally, fission processes are potentially mediated by promoting tubular cell survival through activating the mTOR/4E-BP1 signaling pathway.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.2 no.3
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• pp.181-188
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• 2004

The contaminative influence of beef due to the inhalation of air and the ingestion of soil of livestock, both of which are dealt with as minor contaminative pathways in most radioecological models but may not be neglected, was comprehensively investigated with the improvement of the Korean food chain model DYNACON. As the results, it was found that both pathways can not be neglected at all in the contamination of beef in the case of an accidental release during the non-grazing period of livestock. The ingestion of soil was more influential in the contamination of beef than the inhalation of air over most time following an release. If precipitation is encountered during an accidental release, contaminative influence due to the ingestion of soil was far greater compared with the cases of no precipitation. This fact was more distinct for a long-lived radionuclide $^{l37}Cs$ than a short-lived radionuclide $^{131}I$ (elemental iodine). Compared with the results for milk performed prior to this study, the contaminative pathways due to the inhalation of air and the ingestion of soil were more important in beef because of longer biological half-lives. On the other hand, in the case of an accidental release during the grazing period of livestock, radioactive contamination due to the ingestion of pasture was dominant irrespective of the existence of precipitation during an accidental release. It means that contaminative influence due to the inhalation of air and the ingestion of soil is negligible, like the cases of milk.

• Journal of Korean Society of Transportation
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• v.21 no.1
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• pp.91-102
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• 2003

There are two goals in this paper. The one is development of existing CA(Cellular Automata) model to explain more realistic deceleration process to stop. The other is the application of the updated CA model to forecasting simulation to predict short term link travel time that takes a key rule in finding the shortest path of route guidance system of ITS. Car following theory of CA models don't makes not response to leading vehicle's velocity but gap or distance between leading vehicles and following vehicles. So a following vehicle running at free flow speed must meet steeply sudden deceleration to avoid back collision within unrealistic braking distance. To tackle above unrealistic deceleration rule, “Slow-to-stop” rule is integrated into NaSch model. For application to interrupted traffic flow, this paper applies “Slow-to-stop” rule to both normal traffic light and random traffic light. And vehicle packet method is used to simulate a large-scale network on the desktop. Generally, time series data analysis methods such as neural network, ARIMA, and Kalman filtering are used for short term link travel time prediction that is crucial to find an optimal dynamic shortest path. But those methods have time-lag problems and are hard to capture traffic flow mechanism such as spill over and spill back etc. To address above problems. the CA model built in this study is used for forecasting simulation to predict short term link travel time in Kangnam district network And it's turned out that short term prediction simulation method generates novel results, taking a crack of time lag problems and considering interrupted traffic flow mechanism.

• Journal of Korean Society of Transportation
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• v.34 no.2
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• pp.180-190
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• 2016

Atmospheric pollutants such as Nitrogen Oxides(NOx), Carbon Monoxide(CO), Carbon Dioxide($CO_2$), Particulate Matter(PM) and Hydrocarbons(HC) come from vehicle exhaust gases. Emission curves based on average travel speeds have been employed for estimating on-road emissions as well as evaluating environmental impacts of transportation plans and policies in Korea. Recently, there is a growing interest in estimation methods of vehicle emissions considering relationship between vehicle dynamic driving characteristics and emissions, and incorporating such emission estimators into traffic simulation models. MOVES Lite, a simplified version of MOVES, is one of the estimation methods. In this study, the authors performed a study to develop an adaptable version of MOVES Lite for Korea, called MOVES Lite-K. Vehicle types, driving characteristics, emission rates, and emission standards of Korea were reflected in MOVES Lite-K. The characteristics of emission calculation of MOVES Lite-K and NIER emission curves were compared and the adaptability of MOVES Lite-K were examined.