• Journal of Korean Society of Coastal and Ocean Engineers
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• v.22 no.3
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• pp.156-162
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• 2010

When eccentric or inclined load acts on foundation of the port & harbor structures, partial safety factors of bearing capacity limit state were estimated using reliability analysis. Current Korean technical standards of port and harbor structures recommend to estimate the geotechnical bearing capacity using the simplified Bishop method. In practice, however, simple method of comparing ground reaction resistance with allowable bearing capacity has been mostly used by design engineers. While the simple method gives just one number fixed but somewhat convenient, it could not consider the uncertainty of soil properties depending on site by site. Thus, in this paper, partial safety factors for each design variable were determined so that designers do perform reliability-based level 1 design for bearing capacity limit state. For these, reliability index and their sensitivities were gained throughout the first order reliability method(FORM), and the variability of the random variables was also considered. In order to verify partial safety factors determined here, a comparison with foreign design codes was carried out and were found to be reasonable in practical design.

• Journal of Environmental Health Sciences
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• v.44 no.1
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• pp.63-75
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• 2018

Objectives: The aim of this research is to explore the total heavy metals from a coal-fired power plant burning bituminous coal with wood pellets due to the implementation of the Renewable Portfolio Standard policy (RPS, 10% of electricity from renewable energy resources by 2023). Methods: The research was carried out by collecting archival data and using the USEPA's AP-42 & EMEP/EEA compilation of emission factors for use in calculating emissions. The Monte Carlo method was also applied for carrying out the calculations of measurement uncertainty. Results: In this paper, the results are listed as follows. Sb was measured at 110 kg (2015) and calculated as 165 kg (2019) and 201 kg (2023). Cr was measured at 1,597 kg (2015) and calculated as 1,687 kg (2019) and 1,728 kg (2023). Cu was measured at 2,888 kg (2015) and calculated as 3,133 kg (2019) and 3,264 kg (2023). Pb was measured at 2,580 kg (2015) and calculated as 2,831 kg (2019) and 2,969 kg (2023). Mn was measured at 3,011 kg (2015) and calculated as 15,034 kg (2019) and 23,014 kg (2023). Hg was measured at 510 kg (2015) and calculated as 513 kg (2019) and 537 kg (2023). Ni was measured at 1,720 kg (2015) and calculated as 1,895 kg (2019) and 1,991 kg (2023). Zn was measured at 7,054 kg (2015) and calculated as 9,938 kg (2019) and 11,778 kg (2023). Se was measured at 7,988 kg (2015) and calculated as 7,663 kg (2019) and 7,351 kg (2023). Conclusion: This shows that most heavy metals would increase steadily from 2015 to 2023. However, Se would decrease by 7.9%. This analysis was conducted with EMEP/EEA's emission factors due to the limited emission factors in South Korea. Co-firewood pellets in coal-fired power plants cause the emission of heavy metals. For this reason, emission factors at air pollution control facilities would be presented and the replacement of wood pellets would be needed.

• Asia pacific journal of information systems
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• v.17 no.3
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• pp.1-24
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• 2007

With the development of information technology (IT), various information systems (IS) such as Web-based systems and mobile systems have appeared utilizing different technologies. However, recent studies on IS use and user satisfaction rarely account for technological differences among IS and environmental characteristics where IS are intended to be used. The purpose of this research is to investigate the determinants of the use of Web-based ticketing systems for cultural activities and to empirically validate their relationships. Environmental psychology suggests that human beings respond to external stimuli from environments with their emotions, and their emotional states influence human actions, e.g., IS use in this research. Applying environmental psychology to the use of Web-based systems in the culture and entertainment industry, we propose that web site characteristics first influence a user's internal state of mind (i.e., flow) and then the flow state influences the IS use. Studies related to the state of flow collectively affirm the key role played by the flow construct in shaping individual attitudes and behaviors toward IS. Users' flow states are captured by their shopping enjoyment, perceived behavioral control, and the level of concentration on the IS use. Referring to social presence theory, we have included such web site characteristics as content quality, context of web site, and community quality. In our research model, a second order construct is utilized to represent web site quality, because flow theory suggests that holistic experiences with web-based systems (rather than individual characteristics of the web site) are important in explaining the IS use. Further, we have included trust as another important factor influencing the IS use since business transactions on the web encompass higher uncertainty comparing to offline transactions. In order to test our hypotheses, we have conducted an online survey which results in 1,141 valid responses in the final sample. The data were collected from respondents who have experiences in Internet ticketing systems. Although it was a convenient sample, the sample represents a wide variety of user demographics. Validity and reliability of the research instrument were tested and research hypotheses were examined using PLS Graph 3.0. The results indicate that web site characteristics significantly influence the level of user concentration, user's enjoyment in shopping, and perceived behavioral control. Further, the use of Internet ticketing systems is influenced by users' flow states and trust in the web channel. User satisfaction is turned out to be affected by the use of Internet ticketing systems. Unlike extant research on the relationship between web site characteristics and its use, our study has found that, in the culture and entertainment industry, the impact of web site characteristics on IS use is mediated by a user's flow state. This finding has a practical implication that web site design should include as many features that enhance shopping enjoyment and concentration. Other practical implications of these findings and future research implications are also discussed.

• Journal of Climate Change Research
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• v.2 no.3
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• pp.203-219
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• 2011

Greenhouse gas(GHG) inventories were reported recently in various fields. It, however, has been rarely to mention about the accuracy and reliability of the GHG inventory results. Some reliable assessment methods were introduced to judge the accuracy of the GHG inventory results. It is, hence, critical to develop an evaluation methodology. This project was designed 1) to develop evaluation methodology for reliability of inventory results by GHG-CAPSS, 2) to check the feasibility of the developed evaluation methodology as a result of applying this methodology to two emission sources: liquid fossil fuel and landfill, and 3) to construct the technical roadmap for future role of GHG-CAPSS. Qualitative and quantitative assessment methodologies were developed to check the reliability and accuracy of the inventory results. Qualitative assessment methodology was designed to evaluate the accuracy and reliability of estimation methods of GHG emissions from emission and sink sources, activity data, emission factor, and quality management schemes of inventory results. On the other hand, quantitative assessment methodology was based on the uncertainty assessment of emission results. According to the results of applying the above evaluation methodologies to two emission sources, those seem to be working properly. However, it is necessary to develop source-specific rating systems because emission and sink sources exhibit source-specific characteristics of GHG emissions and sinks.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.2
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• pp.76-84
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• 2021

The quality assurance activities can detect the factors that affect the quality based on risk identification in the course of mass production. Risk identification is conducted with risk analysis, and the risk analysis method for the rotorcraft landing system is selected by failure mode effects analysis (FMEA). FMEA is a method that detects the factors that can affect the product quality by combining severity, occurrence, and detectability. The results of FMEA were prioritized using the risk priority number. On the other hand, these methods have certain shortcomings because the severity, occurrence, detectability are weighted equally. Dempster-Shafer evidence theory can conduct uncertainty analysis for the opinions with personal reflections and subjectivity. Based on the theory, the belief function and the plausibility function can be formed. Moreover, the functions can be utilized to evaluate the belief rate and credibility. The system is exposed to impact during take-off and landing. Therefore, experts should manage failure modes in the course of mass production. In this paper, FMEA based on the Dempster-Shafer evidence theory is discussed to perform risk analysis regarding the failure mode of the rotorcraft landing system. The failure priority was evaluated depending on the factor values. The results were derived using belief and plausibility function graphs.

• Journal of Korea Entertainment Industry Association
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• v.15 no.3
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• pp.289-295
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• 2021

Today, the most important factor affecting the quality of human life is thought to be due to the environment. The importance of environmental monitoring systems to improve human life and improve welfare as the magnitude of the damage increases year by year due to the rapid increase in the frequency of hail, typhoons, collapse of incisions, landslides, etc. Is increasing day by day. Among environmental problems, problems caused by water quality have a very high proportion, and as there is a growing concern that the scale of damage will increase when water pollution accidents occur due to urbanization and industrialization, the demand for social water safety nets is increasing. have. In the last 5 years, 259 cases of water pollution (Han River 99, Nakdong River 31, Geum River 25, Seomjin River and Yeongsan River 19, and 85 others) have occurred in the four major river basins. Caused damage. Therefore, it is required to establish a water quality environment management strategy system based on big data that can minimize the uncertainty of the water quality environment by expanding the target of water quality management from the current water quality management system centered on the four major rivers to small and medium-sized rivers, tributaries/branches, and reservoirs. In this paper, we intend to construct and analyze a water quality monitoring system based on big data that can present useful water quality environment information by analyzing the water quality information accumulated for a long time.

• Journal of the Korean Society of Safety
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• v.37 no.1
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• pp.64-69
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• 2022

The study measured a subway construction worker's Macpa stress by Heart Rate Variability measuring instrument and conducted a survey of Korean job stress from subway construction workers. Also, the study analyzed the relationship between Macpa stress index and Korean job stress result and suggested managing stress method for each item. According to National Statistical Office data, the first line subway in Seoul was started to open in 1974. The extended total length is 996 kilometers until 2019. Many aged workers are currently working at subway construction sites due to the avoidance of young workers since the past until now. It means that the elderly has a substantial portion among subway construction workers. The productivity has been adversely affected by health problems due to the aging of workers, job stress due to heavy work, and personal health problems. So, the regulation and policies on job stress health management are being strengthened. The data were measured Macpa stress by machine measuring heart rate variability and conducted Korean job stress survey(shortened) from Sa-sang to Ha-dan line Busan subway construction workers for analyzing the relationship. Independent variable were age, job duration, job position, employment type, working type in this study. Macpa's dependent variable was stress index and Korean job stress survey(shortened)'s dependent variables were job requirements, job autonomy, relationship conflict, job instability, organizational structure, inappropriate compensation, working place culture, and total score. SPSS 12.0 K Statistics Program was used for statistical analysis. Kruskal-wallis test, a nonparametric statistical analysis, was used because the data are difficult to be assumed as normal distribution. As a result, the paper indicated the significant correlation between Macpa stress index and Korean job stress(short version). The elderly workers presented higher Macpa index and higher job stress due to aging and heavy-duty work. The majority workers were daily workers who had unstable working condition and uncertainty about the future. The study suggested a manual that could reduce job stress for subway construction workers and future study deriving management tool through analyzing job stress factor is necessary.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.1
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• pp.192-207
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• 2023

Commercialization of level-4 (Lv.4) autonomous driving applications requires the definition of a safe road environment under which autonomous vehicles can operate safely. Thus, a risk assessment model is required to determine whether the operation of autonomous vehicles can provide safety to is sufficiently prepared for future real-life traffic problems. Although the risk factors of autonomous vehicles were selected and graded, the decision-making method was applied as qualitative data using a survey of experts in the field of autonomous driving due to the cause of the accident and difficulty in obtaining autonomous driving data. The fuzzy linguistic representation of decision-makers and the fuzzy analytic hierarchy process (AHP), which converts uncertainty into quantitative figures, were implemented to compensate for the AHP shortcomings of the multi-standard decision-making technique. Through the process of deriving the weights of the upper and lower attributes, the road alignment, which is a physical infrastructure, was analyzed as the most important risk factor in the operation risk of autonomous vehicles. In addition, the operation risk of autonomous vehicles was derived through the example of the risk of operating autonomous vehicles for the 5 areas to be evaluated.

• Journal of the Korean Geotechnical Society
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• v.26 no.7
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• pp.161-170
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• 2010

For the development of load and resistance factor design, reliability analysis is required to calibrate resistance factors in the framework of reliability theory. The distribution of measured-to-predicted pile resistance ratio was obrained based on only the results of load tests conducted to failure for the assessment of uncertainty regarding pile resistance and used in the conventional reliability analysis. In other words, successful pile load test (piles resisted twice their design loads without failure) results were discarded, and therefore, were not reflected in the reliability analysis. In this paper, a new systematic method based on Bayesian theory is used to update reliability indices of driven steel pipe piles by adding more proof pile load test results, even not conducted to failure, to the prior distribution of pile resistance ratio. Fifty seven static pile load tests performed to failure in Korea were compiled for the construction of prior distribution of pile resistance ratio. The empirical method proposed by Meyerhof is used to calculate the predicted pile resistance. Reliability analyses were performed using the updated distribution of pile resistance ratio. The challenge of this study is that the distribution updates of pile resistance ratio are possible using the load test results even not conducted to failure, and that Bayesian updates are most effective when limited data are available for reliability analysis.

• The Journal of Bigdata
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• v.9 no.1
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• pp.31-47
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• 2024

With the advancement of artificial intelligence, the travel and hospitality industry is also adopting AI and machine learning technologies for various purposes. In the tourism industry, demand forecasting is recognized as a very important factor, as it directly impacts service efficiency and revenue maximization. Demand forecasting requires the consideration of time-varying data flows, which is why statistical techniques and machine learning models are used. In recent years, variations and integration of existing models have been studied to account for the diversity of demand forecasting data and the complexity of the natural world, which have been reported to improve forecasting performance concerning uncertainty and variability. This study also proposes a new model that integrates various machine-learning approaches to improve the accuracy of hotel sales demand forecasting. Specifically, this study proposes a new time series forecasting model based on XGBoost that selectively utilizes a local model by clustering with DTW K-means and a global model using the entire data to improve forecasting performance. The hotel demand forecasting model that selectively utilizes global and regional models proposed in this study is expected to impact the growth of the hotel and travel industry positively and can be applied to forecasting in other business fields in the future.