• Journal of Korea Water Resources Association
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• v.39 no.10 s.171
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• pp.867-880
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• 2006

Hydrological models with many parameters and complex model structures require a powerful and detailed model calibration/validation scheme. In this study, we proposed a multi-variable and multi-site calibration and validation framework for the Soil Water Assessment Tool (SWAT) model applied in the Gap-cheon catchment located downstream of the Geum river basin. The sensitivity analysis conducted before main calibration helped understand various hydrological processes and the characteristics of subcatchments by identifying sensitive parameters in the model. In addition, the model's parameters were estimated based on existing data prior to calibration in order to increase the validity of model. The Nash-Sutcliffe coefficients and correlation coefficient were used to estimate compare model output with the observed streamflow data: $R_{eff}\;and\;R^2$ ranged 0.41-0.84 and 0.5-0.86, respectively, at the Heuduck station. Model reproduced baseflow estimated using recursive digital filter except for 2-5% overestimation at the Sindae and Boksu stations. Model also reproduced the temporal variability and fluctuation magnitude of observed groundwater levels with $R^2$ of 0.71 except for certain periods. Therefore, it was concluded that the use of multi-variable and multi-site method provided high confidence for the structure and estimated parameter values of the model.

• Journal of Biosystems Engineering
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• v.35 no.2
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• pp.132-137
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• 2010

Site-specific N application for corn is one of the precision crop management. To implement the site-specific N application, various nitrogen stress sensing methods, including aerial image, tissue analysis, soil sampling analysis, and SPAD meter readings, have been used. Use of side-dressing, an efficient nitrogen application method than a uniform application in either late fall or early spring, relies mainly on the capability of nitrogen deficiency detection. This paper presents map-based variable rate nitrogen application based using a multi-spectral corn nitrogen deficiency(CND) sensor. This sensor assess the nitrogen stress by means of the estimated SPAD reading calculated from the corn leave reflectance. The estimated SPAD value from the CND sensor system and location information form DGPS of each field block was combined into the field map using a ArcView program. Then this map was converted into a raster file for a map-based variable rate application software. The relative SPAD (RSPAD = SPAD over reference SPAD) was investigated 2 weeks after the treatments. The results showed that the map-based variable rate application system was feasible.

• Journal of Korea Water Resources Association
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• v.53 no.12
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• pp.1143-1157
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• 2020

In this study, a criteria for the SWAT model calibration method in SWAT-CUP which considers multi-site and multi-variable observations was presented. For its application, the SWAT model was simulated using long-term observed flow, soil moisture, and evapotranspiration data in Yongdam study watershed, investigating the hydrological runoff characteristics and water balance in the water cycle analysis. The model was calibrated with different parameter values for each sub-watershed in order to reflect the characteristics of multiple observations through one-by-one calibration, appropriate settings of model simulation run/iteration number (1,000 simulation runs in the first iteration and then 500 simulation runs for the following iterations), and executions of partial and all run in SWAT-CUP. The flow simulation results of watershed outlet point, ENS 0.85, R2 0.87, and PBIAS -7.6%, were compared with the analysis results (ENS 0.52, R2 0.54, and PBIAS -22.4%) applied in the other batch (i.e., non one-by-one) calibration approach and showed better performances of proposed method. From the simulation results of a total of 15 years, it was found that the total runoff (streamflow) and evapotranspiration rates from precipitation are 53 and 39%, and the ratio of surface runoff and baseflow (i.e., sum of lateral and return flow, and recharge deep aquifer) are 35 and 65%, respectively, in Yongdam watershed. In addition, the analytical amount of available water (i.e., water yield), including the total annual streamflow (daily average 21.8 m3/sec) is 6.96 billion m3 per year (about 540 to 900 mm for sub-watersheds).

• Journal of Korea Water Resources Association
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• v.50 no.3
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• pp.191-200
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• 2017

A robust parameter set (ROPS) selection framework for an unsteady flow model was developed by combining Pareto optimums obtained by outcomes of model calibration using multi-site observations with the minimax regret approach (MRA). The multi-site calibration problem which is a multi-objective problem was solved by using an aggregation approach which aggregates the weighted criteria related to different sites into one measure, and then performs a large number of individual optimization runs with different weight combinations to obtain Pareto solutions. Roughness parameter structure which can describe the variation of Manning's n with discharges and sub-reaches was proposed and the related coefficients were optimized as model parameters. By applying the MRA which is a decision criterion, the Pareto solutions were ranked based on the obtained regrets related to each Pareto solution, and the top-rated one due to the lowest aggregated regrets of both calibration and validation was determined as the only ROPS. It was found that the determination of variable roughness and the corresponding standardized RMSEs at the two gauging stations varies considerably depending on the combinations of weights on the two sites. This method can provide the robust parameter set for the multi-site calibration problems in hydrologic and hydraulic models.

• International Journal of High-Rise Buildings
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• v.12 no.3
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• pp.225-234
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• 2023

Even at this point in the era of digital transformation, we are still facing many problems in the safety sector that cannot prevent the occurrence or spread of human casualties. When you are in an unexpected emergency, it is often difficult to respond only with human physical ability. Human casualties continue to occur at construction sites, manufacturing plants, and multi-use facilities used by many people in everyday life. If you encounter a situation where normal judgment is impossible in the event of an emergency at a life site where there are still many safety blind spots, it is difficult to cope with the existing manual guidance method. New variable guidance technology, which combines artificial intelligence and digital twin, can make it possible to prevent casualties by processing large amounts of data needed to derive appropriate countermeasures in real time beyond identifying what safety accidents occurred in unexpected crisis situations. When a simple control method that divides and monitors several CCTVs is digitally converted and combined with artificial intelligence and 3D digital twin control technology, intelligence augmentation (IA) effect can be achieved that strengthens the safety decision-making ability required in real time. With the enforcement of the Serious Disaster Enterprise Punishment Act, the importance of distributing a smart location guidance system that urgently solves the decision-making delay that occurs in safety accidents at various industrial sites and strengthens the real-time decision-making ability of field workers and managers is highlighted. The smart location guidance system that combines artificial intelligence and digital twin consists of AIoT HW equipment, wireless communication NW equipment, and intelligent SW platform. The intelligent SW platform consists of Builder that supports digital twin modeling, Watch that meets real-time control based on synchronization between real objects and digital twin models, and Simulator that supports the development and verification of various safety management scenarios using intelligent agents. The smart location guidance system provides on-site monitoring using IoT equipment, CCTV-linked intelligent image analysis, intelligent operating procedures that support workflow modeling to immediately reflect the needs of the site, situational location guidance, and digital twin virtual fencing access control technology. This paper examines the limitations of traditional fixed passive guidance methods, analyzes global technology development trends to overcome them, identifies the digital transformation properties required to switch to intelligent variable smart location guidance methods, explains the characteristics and components of AI-based public facility smart fire safety integrated system (ISFS).

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.23-45
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• 2020

Big data is creating in a wide variety of fields such as medical care, manufacturing, logistics, sales site, SNS, and the dataset characteristics are also diverse. In order to secure the competitiveness of companies, it is necessary to improve decision-making capacity using a classification algorithm. However, most of them do not have sufficient knowledge on what kind of classification algorithm is appropriate for a specific problem area. In other words, determining which classification algorithm is appropriate depending on the characteristics of the dataset was has been a task that required expertise and effort. This is because the relationship between the characteristics of datasets (called meta-features) and the performance of classification algorithms has not been fully understood. Moreover, there has been little research on meta-features reflecting the characteristics of multi-class. Therefore, the purpose of this study is to empirically analyze whether meta-features of multi-class datasets have a significant effect on the performance of classification algorithms. In this study, meta-features of multi-class datasets were identified into two factors, (the data structure and the data complexity,) and seven representative meta-features were selected. Among those, we included the Herfindahl-Hirschman Index (HHI), originally a market concentration measurement index, in the meta-features to replace IR(Imbalanced Ratio). Also, we developed a new index called Reverse ReLU Silhouette Score into the meta-feature set. Among the UCI Machine Learning Repository data, six representative datasets (Balance Scale, PageBlocks, Car Evaluation, User Knowledge-Modeling, Wine Quality(red), Contraceptive Method Choice) were selected. The class of each dataset was classified by using the classification algorithms (KNN, Logistic Regression, Nave Bayes, Random Forest, and SVM) selected in the study. For each dataset, we applied 10-fold cross validation method. 10% to 100% oversampling method is applied for each fold and meta-features of the dataset is measured. The meta-features selected are HHI, Number of Classes, Number of Features, Entropy, Reverse ReLU Silhouette Score, Nonlinearity of Linear Classifier, Hub Score. F1-score was selected as the dependent variable. As a result, the results of this study showed that the six meta-features including Reverse ReLU Silhouette Score and HHI proposed in this study have a significant effect on the classification performance. (1) The meta-features HHI proposed in this study was significant in the classification performance. (2) The number of variables has a significant effect on the classification performance, unlike the number of classes, but it has a positive effect. (3) The number of classes has a negative effect on the performance of classification. (4) Entropy has a significant effect on the performance of classification. (5) The Reverse ReLU Silhouette Score also significantly affects the classification performance at a significant level of 0.01. (6) The nonlinearity of linear classifiers has a significant negative effect on classification performance. In addition, the results of the analysis by the classification algorithms were also consistent. In the regression analysis by classification algorithm, Naïve Bayes algorithm does not have a significant effect on the number of variables unlike other classification algorithms. This study has two theoretical contributions: (1) two new meta-features (HHI, Reverse ReLU Silhouette score) was proved to be significant. (2) The effects of data characteristics on the performance of classification were investigated using meta-features. The practical contribution points (1) can be utilized in the development of classification algorithm recommendation system according to the characteristics of datasets. (2) Many data scientists are often testing by adjusting the parameters of the algorithm to find the optimal algorithm for the situation because the characteristics of the data are different. In this process, excessive waste of resources occurs due to hardware, cost, time, and manpower. This study is expected to be useful for machine learning, data mining researchers, practitioners, and machine learning-based system developers. The composition of this study consists of introduction, related research, research model, experiment, conclusion and discussion.

• Applied Chemistry for Engineering
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• v.10 no.3
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• pp.343-348
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• 1999

The iron silicide films were prepared by chemical vapor deposition method using rf-plasma in variations of substrate temperature. rf-power, and ratio of $SiH_4$ and Fe-precursor. While iron silicide films are generally grown by ion beam synthesis (IBS) method of multi-step process, it is confirmed that iron silicide or $\beta$-phase consolidated $Fe_aSi_bC_cH_d$ was formed by one-step process in this study. The characteristics of films is variable because the different amounts of carbon and hydrogen was involved in the films as a function of dilute ratio of Fe-precursors and silane. It was shown that the different characteristics of films in carbon and hydrogen following the ratio of Fe-precursor and silane. The optical gap energy of films fabricated according to substrate temperature was invariant because active site brought in desorption of hydrogen was limiled. When rf-power was above 240 watt, the optical gap energy turned out to have high values because of dangling bonds increased by etching.

• Journal of the Korean earth science society
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• v.27 no.6
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• pp.670-676
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• 2006

We present a B and V band time-series CCD photometry of ${\delta}$ Scuti type variable star HR 2707. The observation was carried out for 45 nights between November 13, 2001 and February 20, 2002 with a 40 cm telescope equipped with a 1K CCD camera at the Korea National University of Education Optical Astronomy Observatory. Through the time-series CCD photometry we obtained 3011 V band and 6562 B band CCD frames. In some of these data, the V band data obtained for seven nights in January of 2002, had been used as a part of a multi-site campaign by Lopez de Coca et al. (2003). To detect pulsational frequencies, we used Discrete Fourier Transformation (DFT) and linear least square method. We have detected eight resonable pulsational frequencies and compare to previous studies we determine $f_1,\;f_2,\;f_3,\;f_4,\;f_5$ of Lopez do Coca et al. (2003) and $f_4$ for derived from this study are real pulsational frequencies of HR 2707.

• Journal of the Korean association of regional geographers
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• v.4 no.2
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• pp.165-182
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• 1998

When tour site is being used by people for the destination of tour, it has a life, or it will lose its life as a tour site. Therefore this paper aims to, based on Butler's theory, has chosen 46 hot spring spots in Korea which are legally assigned and presently running, and tried to analyze the life cycles, the stage of dispositional characteristics, and visitors' favoritism, and to try to find activating method which is not decline. Out of 46 spots, 29 Places were found on the stage of development, which took high percentage, 4 were on the growing stage, 5 were on the mature stage, 5 were on the stagnation or decline stage and the rest 3 were on the stage of rejuvenation. Geographically, Korean hot springs were located on the plain or mountainous areas mostly, and less of them were on hills and coast lines. In water quality, most of places had simple water while the places with salt and sulfur contained water were marked low rate. The temperatures of hot spring water were variable between $25^{\circ}C{\sim}78^{\circ}C$, but the older hot springs were hotter than new ones. After observing the relationship between disposition characteristics and life cycles, the geographical locations and the matter of approach were found as majour influential factors to the life cycles of them. The type of mountainous areas were observed slow progress in life cycle, due to traffic problem, until the road expansion or pavement work were done. Meanwhile, the suburban ones adjacent to big cities were favored by hot spring tourists due to their easy approach and easy traffic. The new born hot springs with such conditions have shown the fast growth. As studied above, since the hot springs were supposed to be for recuperation and vacational, a hot spring with better recreational and accommodational facilities was more favored by tourists than the one with pretty interior decorations. It was because the tour purpose of people has been switched from single purpose to multi one. Thus, the suggestion for activating a declining hot spring and bringing people in them is to develop new and attractive tour resources, expanding the related area, maintaining good quality of water, developing a complex site for long-term tour, developed traffic routs, hot spring festivals, utilizing adjacent tour resources, preparing public water supply system, and assigning as special tour zone.

• Asia Marketing Journal
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• v.14 no.2
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• pp.65-96
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• 2012

Brand has received much attention from considerable marketing research. When consumers consume product or services, they are exposed to a lot of brand related stimuli. These contain brand personality, brand experience, brand identity, brand communications and so on. A special kind of new crisis occasionally confronting companies' brand management today is the brand related rumor. An important influence on consumers' purchase decision making is the word-of-mouth spread by other consumers and most decisions are influenced by other's recommendations. In light of this influence, firms have reasonable reason to study and understand consumer-to-consumer communication such as brand rumor. The importance of brand rumor to marketers is increasing as the number of internet user and SNS(social network service) site grows. Due to the development of internet technology, people can spread rumors without the limitation of time, space and place. However relatively few studies have been published in marketing journals and little is known about brand rumors in the marketplace. The study of rumor has a long history in all major social science. But very few studies have dealt with the antecedents and consequences of any kind of brand rumor. Rumor has been generally described as a story or statement in general circulation without proper confirmation or certainty as to fact. And it also can be defined as an unconfirmed proposition, passed along from people to people. Rosnow(1991) claimed that rumors were transmitted because people needed to explain ambiguous and uncertain events and talking about them reduced associated anxiety. Especially negative rumors are believed to have the potential to devastate a company's reputation and relations with customers. From the perspective of marketer, negative rumors are considered harmful and extremely difficult to control in general. It is becoming a threat to a company's sustainability and sometimes leads to negative brand image and loss of customers. Thus there is a growing concern that these negative rumors can damage brands' reputations and lead them to financial disaster too. In this study we aimed to distinguish antecedents of brand rumor transmission and investigate the effects of brand rumor characteristics on rumor spread intention. We also found key components in personal acceptance of brand rumor. In contextualist perspective, we tried to unify the traditional psychological and sociological views. In this unified research approach we defined brand rumor's characteristics based on five major variables that had been found to influence the process of rumor spread intention. The five factors of usefulness, source credibility, message credibility, worry, and vividness, encompass multi level elements of brand rumor. We also selected product involvement as a control variable. To perform the empirical research, imaginary Korean 'Kimch' brand and related contamination rumor was created and proposed. Questionnaires were collected from 178 Korean samples. Data were collected from college students who have been experienced the focal product. College students were regarded as good subjects because they have a tendency to express their opinions in detail. PLS(partial least square) method was adopted to analyze the relations between variables in the equation model. The most widely adopted causal modeling method is LISREL. However it is poorly suited to deal with relatively small data samples and can yield not proper solutions in some cases. PLS has been developed to avoid some of these limitations and provide more reliable results. To test the reliability using SPSS 16 s/w, Cronbach alpha was examined and all the values were appropriate showing alpha values between .802 and .953. Subsequently, confirmatory factor analysis was conducted successfully. And structural equation modeling has been used to analyze the research model using smartPLS(ver. 2.0) s/w. Overall, R² of adoption of rumor is .476 and R² of intention of rumor transmission is .218. The overall model showed a satisfactory fit. The empirical results can be summarized as follows. According to the results, the variables of brand rumor characteristic such as source credibility, message credibility, worry, and vividness affect argument strength of rumor. And argument strength of rumor also affects rumor intention. On the other hand, the relationship between perceived usefulness and argument strength of rumor is not significant. The moderating effect of product involvement on the relations between argument strength of rumor and rumor W.O.M intention is not supported neither. Consequently this study suggests some managerial and academic implications. We consider some implications for corporate crisis management planning, PR and brand management. This results show marketers that rumor is a critical factor for managing strong brand assets. Also for researchers, brand rumor should become an important thesis of their interests to understand the relationship between consumer and brand. Recently many brand managers and marketers have focused on the short-term view. They just focused on strengthen the positive brand image. According to this study we suggested that effective brand management requires managing negative brand rumors with a long-term view of marketing decisions.