• The Journal of Fisheries Business Administration
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• v.54 no.1
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• pp.37-49
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• 2023

Climate change is a major global problem. Oysters, one of the most representative farmed fish in Korea, are attracting attention as candidates for blue carbon, an alternative to carbon neutrality. This study is analyzed by the SSP scenarios to determine the impact of oyster aquaculture production according to climate change. Based on the analysis, future productions of oysters are predicted by the SSP scenario. Significant differences by the SSP scenario are confirmed through predictive power tests among scenarios. Regression analysis was conducted from January 2001 to December 2014. As a result of the analysis, water temperature, water temperature quadratic term, salinity, salinity quadratic term, and month × water temperature cross term were estimated as significant variables. Oyster production which is predicted by the SSP scenario based on the significant variables from 2015 to 2022 was compared with actual production. The model with the highest predictive power was selected by RMSE and MAPE criteria. The predictive power was compared with the MDM test to determine which model was superior. As a result, based on RMSE and MAPE, the SSP1-2.6 scenario was selected as the best model and the SSP1-2.6, SSP2-4.5, and SSP3-7.0 scenarios all showed the same predictive power based on the MDM test. In conculusion, this study predicted oyster aquaculture production by 2030, not the distant future, due to the short duration of the analytical model. This study was found that oyster aquaculture production increased in all scenarios and there was no significant difference in predictive power by the SSP scenario.

• Journal of the Korea Convergence Society
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• v.8 no.11
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• pp.77-83
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• 2017

For efficient predictive analysis, self-healing research is needed that enables the system to recover autonomously by self-cognition and diagnosing system problems. However, software development does not provide formal contextual information analysis and appropriate presentation structure according to external situation. In this paper, we propose a prediction analysis method based on the change contents by applying the extraction rule to the functions that can act, data, and transaction based on the new Goal-scenario. We also evaluated how well the predictive analysis met through the performance indicators for achieving the requirements goal. Compared with the existing methods, the proposed method has a maximum 32.8% higher matching result through performance measurement, resulting in a 28.9% error rate and a 45.8% reduction in the change code. This shows that it can be processed into a serviceable form through rules, and it shows that performance can be expanded through predictive analysis of changes.

• Journal of Auto-vehicle Safety Association
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• v.7 no.2
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• pp.44-49
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• 2015

This paper presents an evaluation scenario of safety performance for extraordinary service permission of autonomous vehicle driving on a motorway. Based on advanced driver assistance system (ADAS) which is already mass-production, an autonomous vehicle driving on motorway is tested on the public roads and also getting close to mass-production. Before the autonomous vehicle tested, the safety of autonomous driving system should be evaluated based on a proper test scenario. Prior to develop the test scenario, this paper reviews the licensing standards for an autonomous vehicle in California and Nevada, and the international regulations of each ADAS. To develop the scenario, the driving conditions of motorway are categorized into five modes and fundamental evaluation requirements of elements of autonomous driving system are derived. An evaluation scenario, which represents the real driving conditions, has been developed to assess the safety of autonomous vehicle. This scenario has validated by computer simulation using model predictive control (MPC) based autonomous driving algorithm.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2023.11a
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• pp.247-248
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• 2023

As carbon neutrality becomes an issue around the world, research is actively being conducted to achieve reduction targets for each industry by declaring 2050 carbon neutrality in Korea and implementing the greenhouse gas target management system and emission trading system. The construction industry quantitatively predicts and evaluates carbon emissions by stages through the evaluation of the entire building process, but research on this is insufficient in the case of the construction process. Therefore, as part of the research on predicting and reducing carbon emissions generated at construction sites, data from actual construction sites were collected to analyze the facilities and characteristics of each energy source, and a scenario was proposed to quantitatively predict the use of each energy source.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.27 no.3
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• pp.95-99
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• 2013

The maximum power analysis simulator took advantage of the facilities and power consumption reduction simulator test scenario development and testing of improvement in the scenario. As a maximum demand power controller, Maximum power analysis simulator performs control and disperasion of maximum demand power by calculating base power, load forecast, and present power which are based on signal of watt-hour meter to keep the electricity under the target. In addition, various algorithms to select appropriate control methode on each of the light installations through the peak demand power is configured to management. The simulation shows the success of control power for the specified target controlled by five sequential lighting installations.

• Journal of the Korean Society of Safety
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• v.32 no.5
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• pp.32-40
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• 2017

The current status of Performance-Based Design (PBD) implemented in 4 wide areas (Seoul, Gyeonggi, Incheon and Busan) over the past 5 years was reviewed with regard to the number of PBD implementation and target buildings. Then, detailed status related to fire scenarios, input information for fire simulation, and grid size were analyzed with the pre-review for the PBD. As a result, the domestic PBD was mainly applied to the mixed occupancy. In the fire simulations performed on the identical fire scenario and fire space, the maximum heat release rate (HRR) varied significantly depending on the PBD designer. Various combustibles were also considered for the identical fire source, and their combustion properties also showed considerable uncertainty. In addition, the applicability of accurate input information for predictive models of heat and smoke detectors was examined. Finally, the average grid size for the fire simulation using Fire Dynamics Simulator (FDS) was analyzed, and the improvement of PBD to minimize designer dependency was proposed.

• Journal of Drive and Control
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• v.14 no.2
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• pp.9-15
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• 2017

The steering systems of all-terrain cranes have been developed with various control strategies for the stability and drivability. To optimally control the input steering angle, an accurate mathematical model that represents the actual crane dynamics is required. The derivation of an accurate mathematical model to optimally control the steering angle, however, is difficult since the steering-control strategy generally varies with the magnitude of the crane's longitudinal velocity, and the postures of the crane's working parts vary while it is being driven. To address this problem, this paper proposes an automatic steering-control algorithm that is based on the MPC (model predictive control) with a disturbance observer for all-terrain cranes. The designed disturbance observer of this study was used to estimate the error between the base steering model and the actual crane. A model predictive controller was used for the computation of the optimal steering angle, along with the use of the base steering model with an estimated uncertainty. Performance evaluations of the designed control algorithms were conducted based on a curved-path scenario in the Matlab/Simulink environment. The performance-evaluation results show a sound reference-path-tracking performance despite the large uncertainties.

• Journal of Climate Change Research
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• v.6 no.1
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• pp.1-10
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• 2015

Climate change lead to environmental pollution caused by the radical economic growth and development of industry. The amount of damage from abnormal climate is increasing rapidly for this reason in Korea. In particular, the cities is a lot of carbon emission quantity from the radical growth. Thus the government present "low carbon green growth" for eco-friendly city planning. As one of the important factors effecting climate change, active researches on land use change is performed. In this study, we knew land use change of each scenarios using land use equilibrium model which is kind of predictive model of land use in Japan. First, we selected study area to Jeju lsland. For this study, indicators for input data were selected and spatial data for input data were established using GIS program. Second, we established future scenarios based in 2040s. There are 2 future scenarios: dispersion scenario, compact scenario. Third, we compared with residential area of current and residential area for future scenarios. Results showed that residential area of the difference between current and dispersion scenario were 1,230 ha and residential area of the difference between current and compact scenario were 1,515 ha. Finally, for comparing carbon dioxide absorption volume between dispersion scenarios and compact scenarios, we calculated carbon dioxide absorption volume according to residential area decreased of each future scenarios. Results showed that carbon dioxide absorption volume in dispersion scenario was 477,878 ton and carbon dioxide absorption volume in compact scenario was 588,606 ton. Therefore, the study showed that land use equilibrium model is expected to put to use for future enhancement in creating data for climate change stabilization. And it is also expected to be utilized for city planning research in Korea.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.38 no.1
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• pp.35-41
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• 2010

In developing modern aircraft, the reconfiguration control that can improve the safety and the survivability against the unexpected failure by partitioning control surfaces into several parts has been actively studied. This paper deals with the reconfiguration control using model predictive control method considering the saturation of control surfaces under the control surface failure. Linearized aircraft model at trim condition is used as the internal model of model predictive control. We propose the controller that performs optimization using LMI (linear matrix inequalities) based semi-definite programming in case that control surface saturation occurs, otherwise, uses analytic solution of the model predictive control. The performance of the proposed control method is evaluated by nonlinear simulation under the flight scenario of control surface failure.

• Transactions of the Korean Society of Automotive Engineers
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• v.17 no.3
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• pp.54-61
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• 2009

Lane keeping assistant system (LKAS) could save thousands of lives each year by maintaining lane position and is regarded as a promising active safety system. The LKAS is expected to reduce the driver workload and to assist the driver during driving. This paper proposes a model based predictive controller for the LKAS which requires cooperative driving between the driver and the assistance system. A Hardware-In-the-Loop-Simulator (HILS) is constructed for its evaluation and includes Carsim, Matlab Simulink and a lane detection algorithm. The single camera is mounted with the HILS to acquire the monitor images and to detect the lane markers. The simulation is conducted to validate the LKAS control performance in various road scenario.