• Journal of the Korea Academia-Industrial cooperation Society
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• 제21권10호
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• pp.361-371
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• 2020

Since the implementation of the sunset law in 2020, concerns have been raised over the reckless development of long-term non-executed urban parks. In this study, the FSDAF method and CASA-NPP model were used to evaluate the annual average NPP of long-term non-executed urban parks in Seoul. Based on this, the carbon loss and economic value were assessed under five development scenarios. The total NPP value of long-term non-executed urban parks, except for the greenbelt area in Seoul, was 4,892.18 t C. In the first scenario, the NPP and cost were 4,892.18 t C of vegetation carbon and 1.18 billion won, 2,548.55 t C of vegetation carbon and 615 million won in the second scenario, 238.94 t C of vegetation carbon and 58 million won in the third scenario, 848.38 t C of vegetation carbon and 205 million won in the fourth scenario, and 1,596.00 t C of vegetation carbon and 385 million won in the fifth scenario. These results are meaningful for evaluating vegetation carbon and economic value loss according to five different development scenarios. The results of this study are expected to be useful for the preparation of measures to minimize the impact of the development of long-term non-executed urban parks.

• KSCE Journal of Civil and Environmental Engineering Research
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• 제26권5C호
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• pp.359-368
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• 2006

After construction, time-variant seepage and long-term underground motion are representative factors to understand the abnormal behavior of tunnels. In this study, numerical models have been developed to analyze the behavior of tunnels associated with seepage and long-term underground motion. Possible scenarios have been investigated to establish causes-and-results mechanisms. Various parameters such as permeability of tunnel filter, seepage condition, water table, long-term rock mass load, size of damaged zone due to excessive blasting have been investigated. These are divided into two sub-parts depending on the tunnel type and major loading mechanisms depending on the types. For the soft ground tunnels, the behavior associated with seepage conditions has been studied and the effect of permeability change in tunnel-filter and the effect of water-table change which are seldom measurable are investigated in detail. For the rock mass tunnels, tunnel behavior associated with the visco-plastic behavior of rock mass has been studied and the long-term rock mass loads as a result of relaxation and creep have been considered.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제8권6호
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• pp.2139-2151
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• 2014

Embedded system testing, especially long-term reliability testing, of flash memory solutions such as embedded multi-media card, secure digital card and solid-state drive involves strategic decision making related to test sample size to achieve high test coverage. The test sample size is the number of flash memory devices used in a test. Earlier, there were physical limitations on the testing period and the number of test devices that could be used. Hence, decisions regarding the sample size depended on the experience of human testers owing to the absence of well-defined standards. Moreover, a lack of understanding of the importance of the sample size resulted in field defects due to unexpected user scenarios. In worst cases, users finally detected these defects after several years. In this paper, we propose that a large number of potential field defects can be detected if an adequately large test sample size is used to target weak features during long-term reliability testing of flash memory solutions. In general, a larger test sample size yields better results. However, owing to the limited availability of physical resources, there is a limit on the test sample size that can be used. In this paper, we address this problem by proposing a self-adaptive reliability testing scheme to decide the sample size for effective long-term reliability testing.

• Korean Management Science Review
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• 제30권1호
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• pp.139-148
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• 2013

A nuclear energy has been one of the most important sources to securely supply electricity in South Korea. Its weight in the national electricity supply has kept increasing since the first nuclear reactor was built in 1978. The country relies on the nuclear approximately 31.4% in 2012 and it is expected to increase to 48.5% in 2024 based on the long-term electricity supply plan announced by the Korean government. However, Fukushima disaster due to 9.0 magnitude earthquake followed by the tsunami has raised deep concerns on the security of the nuclear power plants. The policy makers of the country are much interested in analyzing the cost structure of the power supply in the case that the nuclear is diminished from the current supply portion. This research uses a stochastic model that aims to evaluate the long-term power supply plan and provides an extensive cost analysis on the changes of the nuclear power supply. To evaluate a power supply plan, the research develops a few plausible energy mix scenarios by changing the installed capacities of energy sources from the long-term electricity supply plan. The analyses show that the nuclear is still the most attractive energy source since its fuel cost is very much stable compared to the other sources. Also the results demonstrate that a large amount of financial expenditure is additionally required every year if Koreans agree on the reduction of nuclear to increase national security against a nuclear disaster.

• Proceedings of the Safety Management and Science Conference
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• 대한안전경영과학회 2000년도 춘계학술대회
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• pp.339-349
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• 2000

Inchon Port is the second largest import-export port of Korea, and has the point at issue such as the excessive logistics cost because of the limits of handling capacity and the chronic demurrage. There are few research activities on the analysis and improvement of the whole port operation, because Inchon Port not only has the dual dock system and various facilities but also handles a various kind of cargo. The purpose of this paper is to develop the simulation program as a long-term strategic support tool, considering the dual dock system and the TU(Terminal Operation Company) system executed since March, 1997 in Inchon Port. The basic input parameters such as arrival intervals, cargo tons, service rates are analyzed and the probability density functions for these parameters are estimated. The main mechanism of simulation model is the discrete event-driven simulation and the next-event time advancing. The program is executed based on the knowledge base and database. From the simulation model, it is possible to estimate the demurrage status through analyzing various scenarios and to establish the long-term port strategic plan.

• Journal of Information Technology Applications and Management
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• 제24권2호
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• pp.81-96
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• 2017

Forecasting long-term mobile service demand is inevitable to establish an effective frequency management policy despite the lack of reliability of forecast results. The statistical forecasting method has limitations in analyzing how the forecasting result changes when the scenario for various drivers such as consumer usage pattern or market structure for mobile communication service is changed. In this study, we propose a dynamic model of the mobile communication service market using system dynamics technique and forecast the future demand for long-term mobile communication subscriber based on the dynamic model, and also experiment on the change pattern of subscriber demand under various scenarios.

• Journal of the Korea Safety Management & Science
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• 제2권2호
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• pp.127-137
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• 2000

Inchon Port is the second largest import-export port of Korea, and has the point at issue such as the excessive logistics cost because of the limits of handling capacity and the chronic demurrage. The purpose of this paper is to develop the simulation program as a long-term strategic support tool, considering the dual dock system and the TOC(Terminal Operation Company) system executed since March, 1997 in Inchon Port. The basic input parameters such as arrival intervals, cargo tons, service rates are analyzed and the probability density functions for these parameters are estimated. From the simulation model, it is possible to estimate the demurrage status through analyzing various scenarios and to establish the long-term port strategic plan.

• ETRI Journal
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• 제41권5호
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• pp.560-573
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• 2019

Two supervised learning algorithms, a basic neural network and a long short-term memory recurrent neural network, are applied to traffic including DDoS attacks. The joint effects of preprocessing methods and hyperparameters for machine learning on performance are investigated. Values representing attack characteristics are extracted from datasets and preprocessed by two methods. Binary classification and two optimizers are used. Some hyperparameters are obtained exhaustively for fast and accurate detection, while others are fixed with constants to account for performance and data characteristics. An experiment is performed via TensorFlow on three traffic datasets. Three scenarios are considered to investigate the effects of learning former traffic on sequential traffic analysis and the effects of learning one dataset on application to another dataset, and determine whether the algorithms can be used for recent attack traffic. Experimental results show that the used preprocessing methods, neural network architectures and hyperparameters, and the optimizers are appropriate for DDoS attack detection. The obtained results provide a criterion for the detection accuracy of attacks.

• Journal of Korean Society for Atmospheric Environment
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• 제28권5호
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• pp.556-570
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• 2012

The Low Carbon Path Calculator is an excel-based model to project greenhouse gas emissions from 2009 to 2050, which is based on the 2050 Pathways Calculator developed by the UK Department of Energy and Climate Change (DECC). Scenarios are developed to reduce GHG emissions in Korea at 50% based on 2005 levels by 2050 using a Low Carbon Path Calculator. They were classified in four different cases, which are high renewable, high nuclear, high CCS and mixed option scenarios. The objectives of this study are to compare scenarios in terms of GHG emissions, final energy, primary energy and electricity generation and examine the usefulness of that model in terms of identifying pathways towards a low carbon emission society. This model will enhance the understanding of the pathways toward a low carbon society and the level of the climate change policy for policy makers, stakeholders, and the public. This study can be considered as a reference for developing strategies in reducing GHG emissions in the long term.

• Journal of Climate Change Research
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• 제5권3호
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• pp.267-275
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• 2014

A key driver for climate change caused by global average temperature rise is greenhouse gas cumulative emissions that stay for long term in the atmosphere. Although at the moment there is no GHG emission, global warming will continue owing to GHG cumulative emission. In this study, scenarios are developed based on two types of optimistic and conservative diffusion goal. There were a total of 6 alternatives scenarios. The objective of this study are to compare scenarios in terms of GHG cumulative emissions and alternative fuels. An object of analysis is the residential buildings and time frame of scenarios is set up by 2030. And this study uses the LEAP model that is a bottom-up energy model. In conclusion, It is important to set specific diffusion pathway for mitigating climate change virtually.