• Journal of the Ergonomics Society of Korea
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• v.36 no.2
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• pp.87-108
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• 2017

Objective: The purpose of this study was to precede the acceptance study based on automation steps and user experience that was lacked in the past study on the core technology of autonomous vehicle, ADAS. The first objective was to construct the acceptance model of ADAS technology that is the core technology, and draw factors that affect behavioral intention through user experience-based evaluation by applying driving simulator. The second one was to see the change of factors on automation step of autonomous vehicle through the UX/UA score. Background: The number of vehicles with the introduction of ADAS is increasing, and it caused change of interaction between vehicle and driver as automation is being developed on the particular drive factor. For this reason, it is becoming important to study the technology acceptance on how driver can actively accept giving up some parts of automated drive operation and handing over the authority to vehicle. Method: We organized the study model and items through literature investigation and the scenario according to the 4 stages of automation of autonomous vehicle, and preceded acceptance assessment using driving simulator. Total 68 men and woman were participated in this experiment. Results: We drew results of Performance Expectancy (PE), Social Influence (SI), Perceived Safety (PS), Anxiety (AX), Trust (T) and Affective Satisfaction (AS) as the factors that affect Behavioral Intention (BI). Also the drawn factors shows that UX/UA score has a significant difference statistically according to the automation steps of autonomous vehicle, and UX/UA tends to move up until the stage 2 of automation, and at stage 3 it goes down to the lowest level, and it increases a little or stays steady at stage 4. Conclusion and Application: First, we presented the acceptance model of ADAS that is the core technology of autonomous vehicle, and it could be the basis of the future acceptance study of the ADAS technology as it verifies through user experience-based assessment using driving simulator. Second, it could be helpful to the appropriate ADAS development in the future as drawing the change of factors and predicting the acceptance level according to the automation stages of autonomous vehicle through UX/UA score, and it could also grasp and avoid the problem that affect the acceptance level. It is possible to use these study results as tools to test validity of function before ADAS offering company launches the products. Also it will help to prevent the problems that could be caused when applying the autonomous vehicle technology, and to establish technology that is easily acceptable for drivers, so it will improve safety and convenience of drivers.

• Journal of Climate Change Research
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• v.2 no.1
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• pp.55-68
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• 2011

The Intergovernmental Panel on Climate Change(IPCC) has identified the causes of climate change and come up with measures to address it at the global level. Its key component of the work involves developing and assessing future climate change scenarios. The IPCC Expert Meeting in September 2007 identified a new greenhouse gas concentration scenario "Representative Concentration Pathway(RCP)" and established the framework and development schedules for Climate Modeling (CM), Integrated Assessment Modeling(IAM), Impact Adaptation Vulnerability(IAV) community for the fifth IPCC Assessment Reports while 130 researchers and users took part in. The CM community at the IPCC Expert Meeting in September 2008, agreed on a new set of coordinated climate model experiments, the phase five of the Coupled Model Intercomparison Project(CMIP5), which consists of more than 30 standardized experiment protocols for the shortterm and long-term time scales, in order to enhance understanding on climate change for the IPCC AR5 and to develop climate change scenarios and to address major issues raised at the IPCC AR4. Since early 2009, fourteen countries including the Korea have been carrying out CMIP5-related projects. Withe increasing interest on climate change, in 2009 the COdinated Regional Downscaling EXperiment(CORDEX) has been launched to generate regional and local level information on climate change. The National Institute of Meteorological Research(NIMR) under the Korea Meteorological Administration (KMA) has contributed to the IPCC AR4 by developing climate change scenarios based on IPCC SRES using ECHO-G and embarked on crafting national scenarios for climate change as well as RCP-based global ones by engaging in international projects such as CMIP5 and CORDEX. NIMR/KMA will make a contribution to drawing the IPCC AR5 and will develop national climate change scenarios reflecting geographical factors, local climate characteristics and user needs and provide them to national IAV and IAM communites to assess future regional climate impacts and take action.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.4B
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• pp.354-361
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• 2011

Increasing interest and technological advances in smart home has led to active research on context-awareness service and prediction algorithms such as Bayesian Networks, Tree-Dimensional Structures and Genetic prediction algorithms. Context-awareness service presents that providing automatic customized service regarding individual user's pattern surely helps users improve the quality of life. However, it is difficult to implement context-awareness service because the problems are that handling coincidence with context information and exceptional cases have to consider. To overcome this problem, we proposes an Intelligent Sequential Matching Algorithm(ISMA), models context-awareness service using Timed Petri-net(TPN) which is petri-net to have time factor. The example scenario illustrates the effectiveness of the Timed Petri-net model and our proposed algorithm improves average 4~6% than traditional in the accuracy and reliability of prediction.

• Journal of the Society of Naval Architects of Korea
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• v.53 no.2
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• pp.135-143
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• 2016

In this study, an embedded system composed of equipment setting, block importing, scenario setting and output reporting is developed in multi-body dynamics program, ADAMS, for conducting dynamic structural analysis of block lifting process. First, equipment used for block lifting process is set in the simulation environment and the shapes and functions of two lifting beams, and six block loaders are provided as the equipment. Second, the modal analysis result of the lifting block is imported from the static structural analysis system, NASTRAN. Third, the lifting scenarios, such as hoisting, waiting, trolley moving, and wire connecting, are set in the system. Finally, output results in the forms of plots, texts and tables, are reported after the dynamic structural analysis. The test examples conducted in a shipyard are applied into the developed system in various condition and scenarios. The loads at the lug points, the stress contours, and the hot spot tables of the developed system are compared with the result of the static analysis system.

• Nuclear Engineering and Technology
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• v.55 no.7
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• pp.2656-2661
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• 2023

The project of China initiative Accelerator Driven Subcritical (CiADS) system has been started to construct in southeast China's Guangdong province since 2019, which is expected to be checked and accepted in the year 2025. In order to make the students in University of Chinese Academy of Sciences (UCAS) better understand the main characteristic and the operation condition in the subcritical nuclear facility, the training platform for CiADS has been developed based on the Cave Automatic Virtual Environment (CAVE) in the Institute of Modern Physics Chinese Academy of Sciences (IMPCAS). The CAVE platform is a kind of non-head mounted virtual reality display system, which can provide the immersive experience and the alternative training platform to substitute the dangerous operation experiments with strong radioactivity. In this paper, the CAVE platform for the training scenarios in CiADS system has been presented with real-time simulation feature, where the required devices to generate the auditory and visual senses with the interactive mode have been detailed. Moreover, the three dimensional modeling database has been created for the different operation conditions, which can bring more freedom for the teachers to generate the appropriate training courses for the students. All the user-friendly features will offer a deep realistic impression to the students for the purpose of getting the required knowledge and experience without the large costs in the traditional experimental nuclear reactor.

• Journal of Climate Change Research
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• v.9 no.1
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• pp.13-29
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• 2018

This study presented evaluation procedure for selecting appropriate GCMs and downscaling method by focusing on the climate extreme indices suitable for climate change adaptation. The procedure includes six stages of processes as follows: 1) exclusion of unsuitable GCM through raw GCM analysis before bias correction; 2) calculation of the climate extreme indices and selection of downscaling method by evaluating reproducibility for the past and distortion rate for the future period; 3) selection of downscaling method based on evaluation of reproducibility of spatial correlation among weather stations; and 4) MME calculation using weight factors and evaluation of uncertainty range depending on number of GCMs. The presented procedure was applied to 60 weather stations where there are observed data for the past 30 year period on Korea Peninsula. First, 22 GCMs were selected through the evaluation of the spatio-temporal reproducibility of 29 GCMs. Between Simple Quantile Mapping (SQM) and Spatial Disaggregation Quantile Delta Mapping (SDQDM) methods, SQM was selected based on the reproducibility of 27 climate extreme indices for the past and reproducibility evaluation of spatial correlation in precipitation and temperature. Total precipitation (prcptot) and annual 1-day maximum precipitation (rx1day), which is respectively related to water supply and floods, were selected and MME-based future projections were estimated for near-future (2010-2039), the mid-future (2040-2069), and the far-future (2070-2099) based on the weight factors by GCM. The prcptot and rx1day increased as time goes farther from the near-future to the far-future and RCP 8.5 showed a higher rate of increase in both indices compared to RCP 4.5 scenario. It was also found that use of 20 GCM out of 22 explains 80% of the overall variation in all combinations of RCP scenarios and future periods. The result of this study is an example of an application in Korea Peninsula and APCC Integrated Modeling Solution (AIMS) can be utilized in various areas and fields if users want to apply the proposed procedure directly to a target area.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.41 no.10
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• pp.1-9
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• 2004

User-Perceived application-level performance is a key to the adoption and success of CDMA 2000. To predict this performance in advance, a detailed end-to-end simulation model of a CDMA network was built to include application traffic characteristics, network architecture, network element details, and protocol features. We assess the user application performance when a Radio Access Network (RAN) and a Core Network (CN) adopt different transport architectures such as ATM and If. For voice Performance, we found that the vocoder bypass scenario shows 8% performance improvement over the others. For data packet performance, we found that HTTP v.1.1 shows better performance than that of HTTP v.1.0 due to the pipelining and TCP persistent connection. We also found that If transport technology is better solution for higher FER environment since the IP packet overhead is smaller than that of ATM for web browsing data traffic, while it shows opposite effect to small size voice packet in RAN architecture. Though simulation results we showed that the 3G-lX EV system gives much better packet delay performance than 3G-lX RTT, the main conclusion is that end-to-end application-level performance is affected by various elements and layers of the network and thus it must be considered in all phases of the technology evolution process.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.3
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• pp.147-154
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• 2018

This paper focuses on the development of a support system that can rapidly generate the design data of a hot-form die with cooling channels, commonly known as hot stamping technology. We propose a new process for designing hot-form dies based on our (automated) system, whose main features are derived from the analysis of the design requirements and design process in the current industry. Our design support system consists of two modules, which allow for the generation of a 3D geometry model and its 2D drawings. The module for 3D modeling automation is implemented as a type of CATIA template model based on CATIA V5 Knowledgeware. This module automatically creates a 3D model of a hot-form die, including the cooling channels, that depends on the shape of the forming surface and the number of STEELs (subsets of die product) and cooling channels. It also allows for both the editing of the positions and orientations of the cooling channels and testing for the purpose of satisfying the constraints on the distance between the forming surface and cooling channels. Another module for the auto-generation of the 2D drawings is being developed as a plug-in using CAA (CATIA SDK) and Visual C++. Our system was evaluated using the S/W test based on a user defined scenario. As a result, it was shown that it can generate a 3D model of a hot form die and its 2D drawings with hole tables about 29 times faster than the conventional manual method without any design errors.

• Journal of Food Hygiene and Safety
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• v.32 no.1
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• pp.8-13
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• 2017

This study was conducted to develop an agent-based computing platform enabling simulation of on-farm produce contamination by enteric foodborne pathogens, which is herein called PPMCS (Preharvest Produce Microbial Contamination Simulator). Also, fecal contamination of preharvest produce was simulated using PPMCS. Although Agent-based Modeling and Simulation, the tool applied in this study, is rather popular in where socio-economical human behaviors or ecological fate of animals in their niche are to be predicted, the incidence of on-farm produce contamination which are thought to be sporadic has never been simulated using this tool. The agents in PPMCS including crop, animal as a source of fecal contamination, and fly as a vector spreading the fecal contamination are given their intrinsic behaviors that are set to be executed at certain probability. Once all these agents are on-set following the intrinsic behavioral rules, consequences as the sum of all the behaviors in the system can be monitored real-time. When fecal contamination of preharvest produce was simulated in PPMCS as numbers of animals, flies, and initially contaminated plants change, the number of animals intruding cropping area affected most on the number of contaminated plants at harvest. For further application, the behaviors and variables of the agents are adjustable depending on user's own scenario of interest. This feature allows PPMCS to be utilized in where different simulating conditions are tested.

• Korean Journal of Agricultural and Forest Meteorology
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• v.24 no.4
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• pp.337-345
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• 2022

For data such as rainfall and soil moisture, it is important to obtain the values of all points required as geostatistical data. Spatial interpolation is generally performed in this process, and commercial software such as ArcGIS is often used. However, commercial software has fatal drawbacks due to its high expertise and cost. In this study, R, an open source-based environment with ArcGIS, a commercial software, was used to compare the differences according to the processing environment when performing spatial interpolation. The data for spatial interpolation was weather forecast data calculated through Land-Atmosphere Modeling Package (LAMP)-WRF model, and soil moisture data calculated for each cumulative rainfall scenario. There was no difference in the output value in the two environments, but there was a difference in user interface and calculation time. The results of spatial interpolation work in the test bed showed that the average time required for R was 5 hours and 1 minute, and for ArcGIS, the average time required was 4 hours and 40 minutes, respectively, showing a difference of 7.5%. The results of this study are meaningful in that researchers can derive the same results in a commercial software environment and an open source-based environment, and can choose according to the researcher's environment and level.