• Fire Science and Engineering
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• v.32 no.2
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• pp.110-117
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• 2018

This study aims to overcome the problems of existing fire fighting drills and build a practical and effective fire fighting drill system to enhance emergency response capabilities. The unexpected scenarios fire fighting drill is to conduct drills with no scenarios and draw conclusions with quantified outcomes in real time, which provides the object evaluation system. The unexpected scenarios fire fighting drill is based on the IoT sensor-based drill evaluation system to suit individual requirement of drilling spots. This study also includes drill field test conducted to examine the applicability of the evaluation system for quantified outcomes. It is considered that the evaluation system of this paper will contribute to systematization and quantification of fire fighting drill, raise trainees' safety consciousness, and ultimately increase the actual fire fighting response capabilities.

• 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 Energy Engineering
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• v.23 no.4
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• pp.73-88
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• 2014

Various studies on the critical flow models for sub-cooled and/or saturated water were reviewed, especially on Fauske, Moody, and Henry for basic theoretical models; Zaloudek for insight into physical phenomena for a critical flow in an orifice type flow path; Sozzi & Sutherland for a critical flow test of saturated and sub-cooled water at high pressure for orifice and nozzles; and a Marviken test on a full-scale critical flow test. In addition, critical flow tests of sub-cooled water for the break simulators in integral effect test (IET) facilities were also investigated, and a hybrid concept using Moody's and Fauske's models was considered by the authors. In the comparison of the models for the selected test data, discussions of the effect of the diameters, predictions of the critical flow models, and design aspects of break simulator for SBLOCA scenarios in the IET facilities were presented. In the effect of diameter on the critical flow rate with respect to all dimensional scales, it was concluded that the effect of diameter was found irrespective of diameter sizes. In addition, the diameter effect on slip ratio affecting the critical flow rate was suggested. From a comparison of the critical flow models and selected test data, the Henry-Fauske model of the MARS-KS code was found to be the best model predicting the critical flow rate for the selected test data under study.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.7
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• pp.2476-2495
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• 2021

Model-based software architecture verification and test scenarios generation are becoming more and more important in the software industry. Based on the existing temporal graph grammar, this paper proposes a new formalization method of the context-sensitive graph grammar for aiming at UML activity diagrams, which is called the UML Activity Graph Grammar, or UAGG. In the UAGG, there are new definitions and parsing algorithms. The proposed mechanisms are able to not only check the structural correctness of the UML activity diagram but also automatically generate the test scenario according to user constraints. Finally, a case study is discussed to illustrate how the UAGG and its algorithms work.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.2
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• pp.114-128
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• 2019

Recently, the interest in the safety of autonomous vehicles has globally been increasing. Also, there is controversy over the reliability and safety about autonomous vehicle. In Korea, the K-City which is a test-bed for testing autonomous vehicles has been constructing. There is a need for test scenarios for autonomous vehicle test in terms of safety. The purpose of this study is to develop the evaluation scenario for autonomous vehicle at community roads in K-City by using crash data collected by the Korea National Police Agency and a text-mining technique. As a result, 24 scenarios were developed in order to test autonomous vehicle in community roads. Finally, the logical and concrete scenario forms were derived based on the Pegasus 5-layer format.

• Journal of KIISE
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• v.44 no.6
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• pp.595-600
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• 2017

Android applications are composed of one or more components. The components within an application or several applications may interact with each other primarily through intents. Such interactions may cause security and reliability issues such as broadcast theft, activity hijacking, and intent spoofing. These problems need to be resolved through testing techniques using various interaction test scenarios before an application gets launched. However, with the existing test scenario generation approach, some infeasible test scenarios may be generated since they do not consider the re-execution order based on activity setting when pressing the back button. This paper proposes a test case generation technique which removes infeasible interaction paths by utilizing the activity stack information.

• Journal of KIISE:Software and Applications
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• v.36 no.1
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• pp.45-53
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• 2009

In these days GUI components are recognized as the important driving elements to the successful software development. Thus they must be verified. In practice, however, GUI testing for verifying the GUI components needs lots of time and high costs. Test automation for GUI testing is a promising solution to save those expenses. In this paper, we discuss some issues considered to perform GUI testing and suggest a new method that improve the GUI test case generation method based on our previous 'record & playback' approach. For this, we suggest the event generation method using the 'spy' technique and the scenario generation method that generates effectively a lot of scenarios with the generated events. In turn we describe how to create GUI test cases from the generated scenarios.

• Journal of Drive and Control
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• v.19 no.4
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• pp.110-116
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• 2022

Recently, various studies have been conducted to apply deep learning and AI to various fields of autonomous driving, such as recognition, sensor processing, decision-making, and control. This paper proposes a controller applicable to path following, static obstacle avoidance, and pedestrian avoidance situations by utilizing reinforcement learning in autonomous vehicles. For repetitive driving simulation, a reinforcement learning environment was constructed using virtual environments. After learning path following scenarios, we compared control performance with Pure-Pursuit controllers and Stanley controllers, which are widely used due to their good performance and simplicity. Based on the test case of the KNCAP test and assessment protocol, autonomous emergency steering scenarios and autonomous emergency braking scenarios were created and used for learning. Experimental results from zero collisions demonstrated that the reinforcement learning controller was successful in the stationary obstacle avoidance scenario and pedestrian collision scenario under a given condition.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.1
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• pp.457-467
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• 2020

Increasing environmental concerns have prompted countries around the world to tighten regulations on greenhouse gases and fuel efficiency. Research is being done using advanced driver assistance systems to improve fuel economy and for the convenience of drivers. Research on systems such as adaptive cruise control (ACC), LKAS, and AEB is active. The purpose of ACC is to control the longitudinal speed and distance of the vehicle and minimize the driver's load, which is considered useful for accident prevention. From this point of view, research has used a mathematical method of safety evaluation as a function of distances and scenarios while considering domestic road environments. A vehicle is tested with a simulation in a proposed scenario. The purpose of the analysis is to verify the functional safety of ACC by comparing the theoretical calculations using theoretical equations, the relative distances in the simulation, and an actual vehicle test. These methods are expected to enable many companies to use scenarios, formulas, and simulations as safety verification methods in the development of ACC.

• Proceedings of the KSR Conference
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• 2011.10a
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• pp.3092-3098
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• 2011

This paper deals with analysis of measuring power dissipation when Maglev is running. With the various running scenarios for Maglev, power dissipation was measured and a comparative analysis of it and wheel-on rails were carried out. The purpose of this paper is to confirm the efficiency and economics on operation of Maglev and reflect detail design later. When the running scenarios of Maglev are the status of landing on and levitation, running at rated acceleration and deceleration and according to changes of velocity, the power dissipation was measured. The measured results are analyzed considering with apparent electric power and active power, reactive power and power factor etc. Due to the limited test track condition, it is very limited to compare and analyze Maglev and general trains. Nevertheless, It is a task of great significance to identify the efficiency and economics on operating Maglev through the results of measuring power dissipation. In the future, measuring power dissipation through more various scenarios will be carried out, and the results will be reflected the design.