• Ocean Systems Engineering
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• v.6 no.2
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• pp.191-201
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• 2016

Stern bearing is a key component of marine propulsion plant. Its environment is diverse, working condition changeable, and condition severe, so that stern bearing load is of strong time variability, which directly affects the safety and reliability of the system and the normal navigation of ships. In this paper, three affecting factors of the stern bearing load such as hull deformation, propeller hydrodynamic vertical force and bearing wear are calculated and characterized by random theory. The uncertainty mathematical model of stern bearing load is established to research the relationships between factors and uncertainty load of stern bearing. The validity of calculation mathematical model and results is verified by examples and experiment yet. Therefore, the research on the uncertainty load of stern bearing has important theoretical significance and engineering practical value.

• Journal of Soil and Groundwater Environment
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• v.18 no.1
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• pp.94-101
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• 2013

It is well known that uncertainty associated with soil sampling is bigger than that with analysis. In this research, uncertainties for soil sampling when assessing TPH and BTEX concentration in soils were quantified based on actual field data. It is almost impossible to assess exact contamination of the site regardless how carefully devised for sampling. Uncertainties associated with sample reduction for further chemical analysis were quantified approximately 10 times larger than those associated with core sampling on site. Bigger uncertainties occur when contamination level is low, sample quantity is small, and soil particle is coarse. To minimize the uncertainties on field, homogenization of soil sample is necessary and its procedures are proposed in this research as well.

• The Journal of Korea Robotics Society
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• v.5 no.1
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• pp.23-31
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• 2010

This paper suggests a multiple robot simulator which considers the uncertainties in robot motion and sensing. A mobile robot moves with errors due to some kinds of uncertainties from actuators, wheels, electrical components, environments. In addition, sensors attached to a mobile robot can't make accurate output information because of uncertainties of the sensor itself and environment. Uncertainties in robot motion and sensing leads researchers find difficulty in building mobile robot navigation algorithms. Generally, a robot algorithm without considering unexpected uncertainties fails to control its action in a real working environment and it leads to some troubles and damages. Thus, the authors propose a simulator model which includes robot motion and sensing uncertainties to help making robust algorithms. Sensor uncertainties are applied in range sensors which are widely used in mobile robot localization, obstacle detection, and map building. The paper shows performances of the proposed simulator by comparing it with a simulator without any uncertainty.

• Journal of Applied Tourism Food and Beverage Management and Research
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• v.12 no.1
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• pp.111-122
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• 2001

This study analyzed the relationships among perceptions of uncertainty, environmental characteristics and strategy maker\`s actual decision such as resource allocation in different organizational subunits by focusing on the hotel general managers in two different countries Korea and Japan. The results show that managerial perceptions of the environment would vary across organizations within an industry but it was surprising to fad that managerial perceptions did not vary more substantially across countries. General managers in both countries perceived government regulator\`s actions to be the most uncertain environmental factor. Hotels in Japan were more geared toward external effectiveness than were hotels in Korea. The findings of this study also suggest that when the organization faces high environmental uncertainty, it places greater emphasis on extemally oriented functions such as market research and product development.

• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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• 2005.04a
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• pp.316-319
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• 2005

Contaminated area should be identified for designing polluted groundwater cleanup plan. A methodology was suggested to identify a contaminant plume distribution geostatistically. James & Gorelick (1994) suggested a methodology to evaluate data worth as expected reducing remediation cost. In this study, their methodology was modified to evaluate data worth as expected reducing uncertainty of the contaminant plume distribution. In suggested methodology, the source identification model by Mahar & Datta (2001) using a forward solute transport model is integrated. Suggested methodology was assessed by two simple example problems and its result represented reducing uncertainties of contaminant plume distribution successfully.

• Journal of Korean Society for Atmospheric Environment
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• v.34 no.4
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• pp.610-615
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• 2018

A filter-based optical technique is one of the representative ways for the measurement and quantification of black carbon (BC). Since the filter-based technique adopts a simple principle, it is easy to put into practical use and instrumental products have already been commercialized. In this study, however, the absorption coefficients of BC after the correction process was estimated to be approximately 3 times lower than those before the correction process. In addition, the difference between before and after corrections was also evident for the trend of increasing and decreasing absorption coefficient. When BC concentration is low, uncertainty may increase regardless of corrections due to the artifacts of filter. In this sense, techniques without using a filter are required, and uncertainties will be minimized if these techniques are used to further complement the filter-based black carbon measurements. Finally, this study is believed to help understand the uncertainty and correction of filter-based black carbon measurements.

• The Journal of Korea Robotics Society
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• v.16 no.2
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• pp.122-129
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• 2021

For the Simultaneous Localization and Mapping (SLAM) problem, a different path results in different SLAM results. Usually, SLAM follows a trail of input data. Active SLAM, which determines where to sense for the next step, can suggest a better path for a better SLAM result during the data acquisition step. In this paper, we will use reinforcement learning to find where to perceive. By assigning entire target area coverage to a goal and uncertainty as a negative reward, the reinforcement learning network finds an optimal path to minimize trajectory uncertainty and maximize map coverage. However, most active SLAM researches are performed in indoor or aerial environments where robots can move in every direction. In the urban environment, vehicles only can move following road structure and traffic rules. Graph structure can efficiently express road environment, considering crossroads and streets as nodes and edges, respectively. In this paper, we propose a novel method to find optimal SLAM path using graph structure and reinforcement learning technique.

• Journal of Korea Society of Industrial Information Systems
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• v.27 no.1
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• pp.135-146
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• 2022

A safe working environment is an important and crucial factor in the operation of a firm, and is also essential for logistics companies in supply chain management. This study confirmed that the safety climate and safety prevention activities have a positive relationship with safety behavior from the perspective of domestic small and medium-sized logistics companies that continue their business relationships by signing contracts with large logistics companies. In addition, the moderating role of regulatory uncertainty and competition uncertainty in the previous positive relationship was empirically examined.

• Proceedings of the Korea Society of Information Technology Applications Conference
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• 2002.06a
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• pp.123-135
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• 2002

Being in era of the digital economy, the influence of IT that effects on our economy is getting greater. Along with this effect, IT becomes origin of predominance of competition in every category of industry. Regarding new trends in industry, how companies mutate their IT skill become important factor. Every industry has their own color and environment of IT and uncertainty is different. For a company, It is most important to plan own strategy with strategic view on industrial environment. The idea of this study is to find the difference of Skill Requirement and Job Requirement in every category of industry by find what are the most important jobs and skills of IT in every industry and to analyze the results. The second idea is to find what kinds of skill are required in every sector of job. Base on the analyzed data, we classified the uncertainty in every industry by Duncan′s "classification of environment", and extracted some pattern within the skill and job in industry that found in our study by applying OIP model. We set skills by categorized curriculum of specialized IT education center, then with IT specialist, checked and retouched the results and surveyed with IT people in every industry on skill set and job of IT. The summery of this study is as follow : 1. Importance of IT skill is differentiated in each industry. It shows that IT skills, which requested in a field are differentiated by uncertainty of environment that comes from the character of industry. 2. Importance of IT job differs by the fields of industry. It shows as IT skills are differentiated, the importance of job that apply these skills is differentiated. 3. As the character of each job that work on is diversified, the importance of skills are diversified in each field of jobs. The Result of this study can give the idea to who designs curriculum and builds educational contentsthat would fulfill the need of fields. Also this study would be meaningful that it opens the field of study of skill requirement in Korea.

• Journal of Climate Change Research
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• v.9 no.1
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• pp.103-115
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• 2018

The uncertainty of climate scenarios, as initial information, is one of the significant factors among uncertainties of climate change impacts and vulnerability assessments. In this sense, the quantification of the uncertainty of climate scenarios is essential to understanding these assessments of impacts and vulnerability for adaptation to climate change. Here we quantified the precision of surface temperature of ensemble scenarios (high resolution (1km) RCP4.5 and 8.5) provided by Korea Meteorological Administration, with spatiotemporal variation of the standard deviation of them. From 2021 to 2050, the annual increase rate of RCP8.5 was higher than that of RCP4.5 while the annual variation of RCP8.5 was lower than that of RCP4.5. The standard deviations of ensemble scenarios are higher in summer and winter, particularly in July and January, when the extreme weather events could occur. In general, the uncertainty of ensemble scenarios in summer were lower than those in winter. In spatial distribution, the standard deviation of ensemble scenarios in Seoul Metropolitan Area is relatively higher than other provinces, while that of Yeongnam area is lower than other provinces. In winter, the standard deviations of ensemble scenarios of RCP4.5 and 8.5 in January are higher than those of December. Especially, the standard deviation of ensemble scenarios is higher in the central regions including Gyeonggi, and Gangwon, where the mean surface temperature is lower than southern regions along with Chungbuk. Such differences in precisions of climate ensemble scenarios imply that those uncertainty information should be taken into account for the implementation of national climate change policy.