• Journal of Korean Society of Coastal and Ocean Engineers
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• v.32 no.5
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• pp.322-330
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• 2020

Modeling for outliers in time series was carried out using the MSL and extreme high, low tide levels (EHL, HLL) data set in the Busan and Mokpo stations. The time-series model is seasonal ARIMA model including the components of the AO (additive outliers) and LS (level shift). The optimal model was selected based on the AIC value and the model parameters were estimated using the 'tso' function (in 'tsoutliers' package of R). The main results by the model application, i.e.. outliers and level shift detections, are as follows. (1) The two AO are detected in the Busan monthly EHL data and the AO magnitudes were estimated to 65.5 cm (by typhoon MAEMI) and 29.5 cm (by typhoon SANBA), respectively. (2) The one level shift in 1983 is detected in Mokpo monthly MSL data, and the LS magnitude was estimated to 21.2 cm by the Youngsan River tidal estuary barrier construction. On the other hand, the RMS errors are computed about 1.95 cm (MSL), 5.11 cm (EHL), and 6.50 cm (ELL) in Busan station, and about 2.10 cm (MSL), 11.80 cm (EHL), and 9.14 cm (ELL) in Mokpo station, respectively.

• Journal of Korean Society of Transportation
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• v.28 no.6
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• pp.133-146
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• 2010

The objective of this study is to develop a supply chain-based freight distribution channel choice model considering shippers' logistics behaviors which will be used for freight demand estimation. For this purpose, this study utilized the distribution channel data of the petrochemical and automobile industries collected by KTDB center. The distribution channel choice models for these industries were developed by including transport mode, time, cost, and shipment size. It was found that the multinomial logit model with transport cost, time and shipment size is the best, and as shipment increases, bigger transport mode is preferred. Generally direct distribution channel with small truck was preferred over the one using distribution center and/or big truck.

• Journal of the Korean Data and Information Science Society
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• v.22 no.6
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• pp.1075-1087
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• 2011

We analyze the tourist satisfaction of the Daegu City Tour which plays a big role in the local tourism boosting through '2011 Visit Daegu Year'. To analyze a causal relation among factors, we proposed a structural equation model consisting of four latent variables of the tour: motivation, expectation, satisfaction, and future behaviors. Using data from the actual tourists of the Daegu City Tour, we found out that tourists' motivation before the tour does not affect tourists' satisfaction after the tour. However those who have higher motivation have positive future behavior and those who have the higher expectation are more satisfied with the tour. Meanwhile, the expectation before the tour does not lead the future behavior but the satisfaction after the tour influences the positive future behavior.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.34 no.1
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• pp.1-10
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• 2022

In this study, the two horizontal shroud tidal current energy converter, which can generate power even under low flow speed conditions, was developed. In order to determine the shape of the shroud system, a three-dimensional numerical simulation test was conducted, and a 1/6 scale down model was made to perform a hydraulic model experiment. The hydraulic model experiment was performed under four flow conditions, and the flow speed, torque, and RPM were measured for each experimental case. As a result of the numerical simulation test, it was found that the flow speeds passing through the nozzle were increased by about 2~3 times in the cylinder, and when the extension ratio was 2:1, the highest flow speed was shown. In addition, it was found that the flow speeds increased 2.8 times when the diameter ratio between the nozzle and the cylinder was 1.5:1. Meanwhile, as a result of the hydraulic model experiment, it was found that when the tip speed ratio was between 1.75 and 2, the power coefficient was 0.32 to 0.34.

• Journal of the Korean Society for information Management
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• v.39 no.4
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• pp.1-21
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• 2022

The aim of this study is to identify the research topics and suggest an information literacy curriculum by analyzing research articles on information literacy. For this purpose, we applied the topic modeling technique to 97 scientific articles and identified the core contents of information literacy education, such as media literacy, information literacy instruction, and the use of information resources. Based on the analysis results, we suggested an information literacy curriculum by considering the Big 6 model, information literacy standards of American Association of School Library, and Association of College and Research Libraries's information literacy competencies. This study is significant in that it considered 'use of information resources' and 'information ethics' to suggest information literacy education.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.26 no.5
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• pp.285-291
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• 2014

The statistical information of the coastal water temperature monitoring data can be biased because of outliers and missing intervals. Though a number of outlier detection methods have been developed, their applications are very limited to the in-situ monitoring data because of the assumptions of the a prior information of the outliers and no-missing condition, and the excessive computational time for some methods. In this study, the practical robust method is developed that can be efficiently and effectively detect the outliers in case of the big-data. This model is composed of these two parts, one part is the construction part of the approximate components of the monitoring data using the robust smoothing and data re-sampling method, and the other part is the main iterative outlier detection part using the detailed components of the data estimated by the approximate components. This model is tested using the two-years 5-minute interval water temperature data in Lake Saemangeum. It can be estimated that the outlier proportion of the data is about 1.6-3.7%. It shows that most of the outliers in the data are detected and removed with satisfaction by the model. In order to effectively detect and remove the outliers, the outlier detection using the long-span smoothing should be applied earlier than that using the short-span smoothing.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.36 no.6
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• pp.1083-1091
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• 2016

This research uses public transportation card data to analyze the inter-regional transfer times, transfer frequencies, and transfer resistance that passengers experience during transit amongst the metropolitan public transportation modes. Currently, mode transfers between bus and rail are recorded up to five times during one transit movement by Trip Chain, facilitating greater comprehension of intermodal movements. However, lack of information on what arises during these transfers poses a problem in that it leads to an underestimation of transfer resistances on the Trip Chain. As such, a path choice model that reflects passenger movements during transit activities is created, which attains explanatory power on transfer resistance through its inclusion of transfer times and frequencies. The methodology adopted in this research is to first conceptualize the idea of metropolitan public transportation transfer, and in the case that mode transfers include the city-rail, to newly conceptualize the idea of transfer resistance using transportation card data. Also, the city-rail path choice model within the Trip Chain is constructed, with transfer time and frequency used to reevaluate transfer resistance. Further, in order to align bus and city-rail station administrative level small-zone coordinates to state and regional level mid-zone coordinates, the big node methdod is utilized. Finally, case studies on trip chains using at least one transfer onto the city-rail is used to determine the validity of the results obtained.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.29 no.6
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• pp.14-26
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• 2015

This study has been conducted so as to analyse user's sensibility on lighting method, correlated color temperature and illumination by composing surface light source, which was projected onto a unit side of interior wall, ceiling and floor. 1) As an analyzed results of the sensibility images, it showed that the "snug & tender" value had got higher when the correlated color temperature got lower. And the "energetic, cheerful" value had got higher when the level of illuminance got lower. Furthermore, the "unusual, unique" showed higher value on the illuminated floor circumstance. Finally, the higher correlated color temperature had been, "energetic, cheerful" value also got higher. 2) As a result of multi-regression analysis, it was found that 3000K and 100lx had the biggest influence on 'snug' image while 5,500K, 500lx had the biggest influence on 'energetic' image. In addition, it was found that the illuminated floor had a big influence on 'unusual' image while 500lx had the biggest influence on 'refined' image.

• Journal of Korean Society of Archives and Records Management
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• v.13 no.3
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• pp.99-125
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• 2013

This study proposes an education program using presidential archives to develop the multiple intelligence of children and the youth based on the multiple intelligence theory and the resource-based learning theory. To accomplish this, we performed a literature review and interviews with an archivist working in the Presidential Archive in Korea. This study compared and analyzed the Presidential Archives' education programs between the U.S. and Korea. This study can be useful and valuable in developing education programs in two areas, with the first area being the fact that the proposed program could help learners improve academic abilities by developing multiple intelligence and the second area being the fact that the program could increase the awareness of the importance of presidential archives. With the proposed program, the utilization of presidential archives can be facilitated.

• Journal of the Korean Data and Information Science Society
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• v.28 no.6
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• pp.1427-1435
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• 2017

The smart farm is a remarkable system because it utilizes information and communication technologies in agriculture to bring high productivity and excellent qualities of crops. It automatically measures the growth environment of the crops and accumulates huge amounts of environmental information in real time growing in smart farms using multi-variable control of environmental factors. The statistical model using the collected big data will be helpful for decision making in order to control optimal growth environment of crops in smart farms. Using data collected from a smart farm of tomato, we carried out multiple regression analysis to determine the relationship between yield and environmental factors and to predict yield of tomato. In this study, appropriate parameter modification was made for environmental factors considering tomato growth. Using these new factors, we fit the model and derived the optimal environmental factors that affect the yields of tomato. Based on this, we could predict the yields of tomato. It is expected that growth environment can be controlled to improve tomato productivities by using statistical model.