• Korean Journal of Remote Sensing
• /
• v.39 no.6_2
• /
• pp.1565-1576
• /
• 2023

An atmospheric correction algorithm based on the radiative transfer model is required to obtain remote-sensing reflectance (R_rs) from the Geostationary Ocean Color Imager-II (GOCI-II) observed at the top-of-atmosphere. This R_rs derived from the atmospheric correction is utilized to estimate various marine environmental parameters such as chlorophyll-a concentration, total suspended materials concentration, and absorption of dissolved organic matter. Therefore, an atmospheric correction is a fundamental algorithm as it significantly impacts the reliability of all other color products. However, in clear waters, for example, atmospheric path radiance exceeds more than ten times higher than the water-leaving radiance in the blue wavelengths. This implies atmospheric correction is a highly error-sensitive process with a 1% error in estimating atmospheric radiance in the atmospheric correction process can cause more than 10% errors. Therefore, the quality assessment of R_rs after the atmospheric correction is essential for ensuring reliable ocean environment analysis using ocean color satellite data. In this study, a Quality Assurance (QA) algorithm based on in-situ R_rs data, which has been archived into a database using Sea-viewing Wide Field-of-view Sensor (SeaWiFS) Bio-optical Archive and Storage System (SeaBASS), was applied and modified to consider the different spectral characteristics of GOCI-II. This method is officially employed in the National Oceanic and Atmospheric Administration (NOAA)'s ocean color satellite data processing system. It provides quality analysis scores for R_rs ranging from 0 to 1 and classifies the water types into 23 categories. When the QA algorithm is applied to the initial phase of GOCI-II data with less calibration, it shows the highest frequency at a relatively low score of 0.625. However, when the algorithm is applied to the improved GOCI-II atmospheric correction results with updated calibrations, it shows the highest frequency at a higher score of 0.875 compared to the previous results. The water types analysis using the QA algorithm indicated that parts of the East Sea, South Sea, and the Northwest Pacific Ocean are primarily characterized as relatively clear case-I waters, while the coastal areas of the Yellow Sea and the East China Sea are mainly classified as highly turbid case-II waters. We expect that the QA algorithm will support GOCI-II users in terms of not only statistically identifying R_rs resulted with significant errors but also more reliable calibration with quality assured data. The algorithm will be included in the level-2 flag data provided with GOCI-II atmospheric correction.

• Journal of the Korean Regional Science Association
• /
• v.34 no.2
• /
• pp.3-19
• /
• 2018

The objective of this study is to observe the efficiency of clinical performance on the supply and demand of medical resources in Korea. For the empirical analysis, we constructed the dataset on age standardized mortality rate, the number of physician, specialist, surgery, medical institution, ratio of general hospitals of 16 provinces in Korea from 2006 to 2013. The panel probability frontier model is employed as an analysis method and considered heteroscedasticity and autocorrelation of the error in panel data. In addition, the demographic and socioeconomic characteristics of the 16 provinces, unemployment rate, elderly population ratio, GRDP per capita, and ratio of hospitals in comparison to the general hospitals are used to find the effect on the technical efficiency of clinical performance on supply and demand of medical resources. The results are as follows. First, for the clinical performance, the supply side of human resources such as doctors and specialists and the demand side factors such as chronic illness clinic per unit population have a significant influence, respectively. Second, the technical efficiency of clinical performance on the supply and demand of medical resources of each input component was 59-70% in terms of clinical efficiency in each region. Third. estimates of technical efficiency of inputs that affect clinical performance showed a slight increase in all regions during the analysis period, but the increase trend decreased slightly. Fourth, the ratio of the elderly population and GRDP per capita have a positive influence on the technical efficiency of clinical performance on the supply and demand of medical resources. The difference of each efficiency by region is due to the regional differences of the input medical resources and the combination of them and the demographic and socioeconomic characteristics of the region. It is understood that the differences in technological efficiency due to the complexity of supply and demand of medical resources, demographic structure and economic difference affecting clinical performance by region are different.

• Journal of the Korean Society of Radiology
• /
• v.6 no.6
• /
• pp.455-464
• /
• 2012

This study suggested evaluation of approximately exposure to low-dose ionization radiation from medical images using a computed radiography (CR) system in standard X-ray examination and experimental model can compare diagnostic reference level (DRL) will suggest on optimization condition of guard about medical radiation of low dose space. Entrance surface dose (ESD) cross-measuring by standard dosimeter and optically stimulated luminescence dosimeters (OSLDs) in experiment condition about tube voltage and current of X-ray generator. Also, Hounsfield unit (HU) scale measured about each experiment condition in CR system and after character relationship table and graph tabulate about ESD and HU scale, approximately radiation dose about head, neck, thoracic, abdomen, and pelvis draw a measurement. In result measuring head, neck, thoracic, abdomen, and pelvis, average of ESD is 2.10, 2.01, 1.13, 2.97, and 1.95 mGy, respectively. HU scale is $3,276{\pm}3.72$, $3,217{\pm}2.93$, $2,768{\pm}3.13$, $3,782{\pm}5.19$, and $2,318{\pm}4.64$, respectively, in CR image. At this moment, using characteristic relationship table and graph, ESD measured approximately 2.16, 2.06, 1.19, 3.05, and 2.07 mGy, respectively. Average error of measuring value and ESD measured approximately smaller than 3%, this have credibility cover all the bases radiology area of measurement 5%. In its final analysis, this study suggest new experimental model approximately can assess radiation dose of patient in standard X-ray examination and can apply to CR examination, digital radiography and even film-cassette system.

• Journal of dental hygiene science
• /
• v.13 no.4
• /
• pp.471-479
• /
• 2013

This study is trying to grasp the stress of the male high school students and the correlation between the stress according to the academic and economic level and oral parafunctional habits, emphasizing the need for the education of oral parafunctional habits, providing the basic data in order to accomplish correctly until the oral health of the oral maxillofacial region. From May 2013 till July 2013, a self administered survey was conducted by the selected by convenience sampling from subjects of 1, 2 grade of two high school located in Chungnam, Korea. The study results were as follow: 1) Among five areas of stress, the stress of school life was the highest as 2.11 points and the stress of home problem was the lowest as 1.51 points; 2) the stress by class showed that grade 2 was higher than grade 1 in all areas. The stress of the school life (2.21) (p<0.01), interpersonal relationship (p<0.01), and own problem (p<0.05) showed the significant difference; 3) The significance analysis results between the five areas of stress according to the stress of latent variable and the oral parafunctional habits all showed the significant difference (p<0.001). The correlation between the stress and the oral parafunctional habits showed a weak negative correlation as -0.30, and the stress of the school life, own problem, environment problem, and interpersonal relationship showed very strong correlations more than 0.7; 4) Fit measures test result of stress, academic level, and family economic level model all showed more than 0.9 in good of fit index, adjusted goodness of fit index, normed fit index and root mean square residual and root mean square error of approximation values is all estimated less than 0.1, so it showed good model. From this study, it can be concluded that there is the correlation between stress and oral parafunctional habits.

• Journal of Global Scholars of Marketing Science
• /
• v.18 no.4
• /
• pp.1-32
• /
• 2008

Brown and Dacin (1997) have investigated the relationship between corporate associations and product evaluations. Their study focused on the effects of associations with a company's corporate ability (CA) and its corporate social responsibility (CSR) on consumers' product evaluations. Their study has found that both of CA and CSR influenced product evaluation but CA association has a stronger effect than CSR associations. Brown and Dacin (1997) have, however, claimed that there are few researches on how corporate association impacts product responses. Accordingly, some of researchers have found the variables to moderate or to mediate the relationship between the corporate association and the product responses. In particular, there has been existed a few of studies that tested the influence of the reputation on the product-relevant perceived risk, but the effects of two types of the corporate association on the product-relevant perceived risk were not identified so far. The primary goal of this article is to identify and empirically examine some variables to moderate the effects of CA association and CSR association on the perceived risk of the product. In this articles, we take the concept of the corporate associations that Brown and Dacin (1997) had proposed. CA association is those association related to the company's expertise in producing and delivering its outputs and CSR association reflected the organization's status and activities with respect to its perceived societal obligations. Also, this study defines the risk, which is the uncertainty or loss of the product and corporate that consumers have taken in a particular purchase decision or after having purchased. The risk is classified into product-relevant performance risk and financial risk. Performance risk is the possibility or the consequence of a product not functioning at some expected level and financial risk is the monetary loss one perceives to be incurring if a product does not function at some expected level. In relation to consumer's knowledge, expert consumers have much of the experiences or knowledge of the product in consumer position and novice consumers does not. The model tested in this article are shown in Figure 1. The model indicates that both of CA association and CSR association influence on performance risk and financial risk. In addition, the effects of CA and CSR are moderated by product category knowledge (product knowledge) and product category involvement (product involvement). In this study, the relationships between the corporate association and product-relevant perceived risk are hypothesized as the following form. For example, Hypothesis 1a($H_{1a}$) is represented that CA association has a positive influence on the performance risk of consumer. Also, the hypotheses that identified some variables to moderate the effects of two types of corporate association on the perceived risk of the product are laid down. One of the hypotheses of the interaction effect is Hypothesis 3a($H_{3a}$), it is described that consumer's knowledges of the product moderates the negative relationship between CA association and product-relevant performance risk. A field experiment was conducted in order to examine our model. The company tested was not real but imagined to meet the internal validity. Water purifiers were used for our study. Four scenarios have been developed and described as the imaginary company: Type A with both of superior CA and CSR, Type B with superior CSR and inferior CA, Type C with superior CA and inferior CSR, and Type D with both inferior of CA and CSR. The respondents of this study were classified into four groups. One type of four scenarios (Type A, B, C, or D) in its questionnaire was given to the respondent who filled out questions. Data were collected by means of a self-administered questionnaire to the respondents, chosen in convenience. A total of 300 respondents filled out the questionnaire but 207 were used for further analysis. Table 1 indicates that the scales in this study are reliable because the range of coefficients of Cronbach's $\alpha$ are from 0.85 to 0.92. The composite reliability is in the range of 0,85 to 0,92 and average variance extracted is in 0.72-0.98 range that is higher than the base level of 0.6. As shown in Table 2, the values for CFI, NNFI, root-mean-square error approximation (RMSEA), and standardized root-mean-square residual (SRMR) are acceptably close to the standards suggested by Hu and Bentler (1999):.95 for CFI and NNFI,.06 for RMSEA, and.08 for SRMR. We also tested discriminant validity provided by Fornell and Larcker (1981). As shown in Table 2, we found strong evidence for discriminant validity between each possible pair of latent constructs in all samples. Given that these batteries of overall goodness-of-fit indices were accurate and that the model was developed on theoretical bases, and given the high level of consistency across samples, this enables us to proceed the previously defined scales. We used the moderated hierarchical regression analysis to test the influence of the corporate association(CA and CSR associations) on product-relevant perceived risk(performance and financial risks) and to identify the variables moderating the relationship between the corporate association and product-relevant performance risk. In this study, dependent variables are performance and financial risk. CA and CSR associations are described the independent variables. The moderating variables are product category knowledge and product category involvement. The results are, as expected, found that CA association has statistically a significant influence on the perceived risk of the product, but CSR association does not. Product category knowledge and involvement moderate the relationship between the CA association and the perceived risk of the product. However, the effect of CSR association on the perceived risk of the product is not moderated by the consumers' knowledge and involvement. For this result, it is necessary for a corporate to inform its customers CA association more than CSR association so that they could be felt to be the reduction of the perceived risk. The important theoretical contribution of this research is the meanings that two types of corporate association that Brown and Dacin(1997), and Brown(1998) have proposed replicated the difference of the effects on product evaluation. According to Hunter(2001), it was an important affair to accomplish the validity of a particular study and we had to take about ten studies to deduce a strict study. Next, there is the contribution of the this study to find that the effects of corporate association on the perceived risk of the product are varied by the moderator variables. In particular, the moderating effect of knowledge on the relationship between corporate association and product-relevant perceived risk has not been tested in Korea. In the managerial implications of this research, we suggest the necessity to stress the ability that corporate manufactures the product well(CA association) than the accomplishment of corporate's social obligation(CSR association). This study suffers from various limitations that imply future research directions. The moderating effects of product category knowledge and involvement on the relationship between corporate association and perceived risk need to be replicated. Next, future research could explore whether the mediated effects of the perceived risk has the relationship between corporate association and consumer's product purchase. In addition, to ensure the external validity of the study will be needed to use realistic company, not artificial.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.17 no.4
• /
• pp.384-398
• /
• 2015

In this paper, the high-resolution Weather Research and Forecasting/Noah-MultiParameterization (WRF/Noah-MP) modeling system is configured for the Cheongmicheon Farmland site in Korea (CFK), and its performance in land and atmospheric simulation is evaluated using the observed data at CFK during the 2014 special observation period (21 August-10 September). In order to explore the usefulness of turning on Noah-MP dynamic vegetation in midterm simulations of surface and atmospheric variables, two numerical experiments are conducted without dynamic vegetation and with dynamic vegetation (referred to as CTL and DVG experiments, respectively). The main results are as following. 1) CTL showed a tendency of overestimating daytime net shortwave radiation, thereby surface heat fluxes and Bowen ratio. The CTL experiment showed reasonable magnitudes and timing of air temperature at 2 m and 10 m; especially the small error in simulating minimum air temperature showed high potential for predicting frost and leaf wetness duration. The CTL experiment overestimated 10-m wind and precipitation, but the beginning and ending time of precipitation were well captured. 2) When the dynamic vegetation was turned on, the WRF/Noah-MP system showed more realistic values of leaf area index (LAI), net shortwave radiation, surface heat fluxes, Bowen ratio, air temperature, wind and precipitation. The DVG experiment, where LAI is a prognostic variable, produced larger LAI than CTL, and the larger LAI showed better agreement with the observed. The simulated Bowen ratio got closer to the observed ratio, indicating reasonable surface energy partition. The DVG experiment showed patterns similar to CTL, with differences for maximum air temperature. Both experiments showed faster rising of 10-m air temperature during the morning growth hours, presumably due to the rapid growth of daytime mixed layers in the Yonsei University (YSU) boundary layer scheme. The DVG experiment decreased errors in simulating 10-m wind and precipitation. 3) As horizontal resolution increases, the models did not show practical improvement in simulation performance for surface fluxes, air temperature, wind and precipitation, and required three-dimensional observation for more agricultural land spots as well as consistency in model topography and land cover data.

• Journal of dental hygiene science
• /
• v.14 no.2
• /
• pp.158-166
• /
• 2014

This study is trying to grasp the stress of the male high school students and the correlation between the stress according to the oral health important cognitive and self-rated oral health status and number of brushing, emphasizing the need for the education of oral health important, providing the basic data in order to accomplish correctly until the enhance of oral health-related quality of the oral health correct behavior. From May to July 2013, a self administered survey was conducted by the selected by convenience sampling from subjects of two high school located in Chungcheongnam-do 1, 2 grade. The SPSS PASW Statistics 18.0 and Amos 5.0 program had been used for the statistical data analysis. The study results were as follow: 1) Among five areas of stress, the stress of school life was the highest as 2.11 points and the stress of home problem was the lowest as 1.51 points; 2) The significance analysis results between the five areas of stress according to the stress of latent variable and the oral health-related quality of life all showed the significant difference (p<0.001). 3) Oral health-related quality of life was higher as oral health important and self-rated oral health status positive. Furthermore oral health-related quality of life was higher as number of brushing increased; 4) Fit Measures test result of stress, academic level, and family economic level model all showed more than 0.9 in goodness of fit index (GFI), adjusted GFI, normed fit index and root mean square residual and root mean square error of approximation values is all estimated less than 0.1, so it showed good model. From this study, it can be concluded that there is the correlation between stress and oral health-related quality of life.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.12 no.1
• /
• pp.36-44
• /
• 2010

In order to rehabilitate forest sites damaged by wildfire via natural or artificial restoration, it is important to determine right tree species, which can acclimate to biogeoclimatic environment at the sites. The objectives of this study were to develop site index equation of different tree species for estimating forest productivity and to provide information on species selection for post-wildfire restoration. Site index equation was developed based on environmental information from wildfire damaged areas in Gangneung, Goseong, Donghae, and Samcheok, where were located in east coastal areas of South Korea. Despite the small numbers (4~5) of environmental variables used for the development of the site index equations, statistical analysis (e.g. mean difference, standard deviation of difference, and standard error of difference) showed relatively low bias and variation, suggesting that those equations can provide relatively high capability of estimation and practical applicability with high effectiveness. The small numbers of the variables enabled the model to be applied in a wide range of usages including determination of appropriate tree species for post-wildfire restoration. The estimation of forest site productivity showed the possibility of large distribution in east coastal region as the best site for Korean ash (Fraxinus rhynchophylla) and original oak (Quercus variabilis) that can be used for firebreak in the region. These results imply that damages by forest fire can be reduced significantly by replacing existing pure coniferous forests in the area with ones dominated by broad-leaved deciduous stands, which can play an important role as fire break and/or prevent a transition from surface fire to crown fire.

• Journal of Intelligence and Information Systems
• /
• v.19 no.3
• /
• pp.57-71
• /
• 2013

Over a billion people in the world generate new news minute by minute. People forecasts some news but most news are from unexpected events such as natural disasters, accidents, crimes. People spend much time to watch a huge amount of news delivered from many media because they want to understand what is happening now, to predict what might happen in the near future, and to share and discuss on the news. People make better daily decisions through watching and obtaining useful information from news they saw. However, it is difficult that people choose news suitable to them and obtain useful information from the news because there are so many news media such as portal sites, broadcasters, and most news articles consist of gossipy news and breaking news. User interest changes over time and many people have no interest in outdated news. From this fact, applying users' recent interest to personalized news service is also required in news service. It means that personalized news service should dynamically manage user profiles. In this paper, a content-based news recommendation system is proposed to provide the personalized news service. For a personalized service, user's personal information is requisitely required. Social network service is used to extract user information for personalization service. The proposed system constructs dynamic user profile based on recent user information of Facebook, which is one of social network services. User information contains personal information, recent articles, and Facebook Page information. Facebook Pages are used for businesses, organizations and brands to share their contents and connect with people. Facebook users can add Facebook Page to specify their interest in the Page. The proposed system uses this Page information to create user profile, and to match user preferences to news topics. However, some Pages are not directly matched to news topic because Page deals with individual objects and do not provide topic information suitable to news. Freebase, which is a large collaborative database of well-known people, places, things, is used to match Page to news topic by using hierarchy information of its objects. By using recent Page information and articles of Facebook users, the proposed systems can own dynamic user profile. The generated user profile is used to measure user preferences on news. To generate news profile, news category predefined by news media is used and keywords of news articles are extracted after analysis of news contents including title, category, and scripts. TF-IDF technique, which reflects how important a word is to a document in a corpus, is used to identify keywords of each news article. For user profile and news profile, same format is used to efficiently measure similarity between user preferences and news. The proposed system calculates all similarity values between user profiles and news profiles. Existing methods of similarity calculation in vector space model do not cover synonym, hypernym and hyponym because they only handle given words in vector space model. The proposed system applies WordNet to similarity calculation to overcome the limitation. Top-N news articles, which have high similarity value for a target user, are recommended to the user. To evaluate the proposed news recommendation system, user profiles are generated using Facebook account with participants consent, and we implement a Web crawler to extract news information from PBS, which is non-profit public broadcasting television network in the United States, and construct news profiles. We compare the performance of the proposed method with that of benchmark algorithms. One is a traditional method based on TF-IDF. Another is 6Sub-Vectors method that divides the points to get keywords into six parts. Experimental results demonstrate that the proposed system provide useful news to users by applying user's social network information and WordNet functions, in terms of prediction error of recommended news.

• Journal of Intelligence and Information Systems
• /
• v.24 no.2
• /
• pp.85-109
• /
• 2018

Recommender system recommends the items expected to be purchased by a customer in the future according to his or her previous purchase behaviors. It has been served as a tool for realizing one-to-one personalization for an e-commerce service company. Traditional recommender systems, especially the recommender systems based on collaborative filtering (CF), which is the most popular recommendation algorithm in both academy and industry, are designed to generate the items list for recommendation by using 'overall rating' - a single criterion. However, it has critical limitations in understanding the customers' preferences in detail. Recently, to mitigate these limitations, some leading e-commerce companies have begun to get feedback from their customers in a form of 'multicritera ratings'. Multicriteria ratings enable the companies to understand their customers' preferences from the multidimensional viewpoints. Moreover, it is easy to handle and analyze the multidimensional ratings because they are quantitative. But, the recommendation using multicritera ratings also has limitation that it may omit detail information on a user's preference because it only considers three-to-five predetermined criteria in most cases. Under this background, this study proposes a novel hybrid recommendation system, which selectively uses the results from 'traditional CF' and 'CF using multicriteria ratings'. Our proposed system is based on the premise that some people have holistic preference scheme, whereas others have composite preference scheme. Thus, our system is designed to use traditional CF using overall rating for the users with holistic preference, and to use CF using multicriteria ratings for the users with composite preference. To validate the usefulness of the proposed system, we applied it to a real-world dataset regarding the recommendation for POI (point-of-interests). Providing personalized POI recommendation is getting more attentions as the popularity of the location-based services such as Yelp and Foursquare increases. The dataset was collected from university students via a Web-based online survey system. Using the survey system, we collected the overall ratings as well as the ratings for each criterion for 48 POIs that are located near K university in Seoul, South Korea. The criteria include 'food or taste', 'price' and 'service or mood'. As a result, we obtain 2,878 valid ratings from 112 users. Among 48 items, 38 items (80%) are used as training dataset, and the remaining 10 items (20%) are used as validation dataset. To examine the effectiveness of the proposed system (i.e. hybrid selective model), we compared its performance to the performances of two comparison models - the traditional CF and the CF with multicriteria ratings. The performances of recommender systems were evaluated by using two metrics - average MAE(mean absolute error) and precision-in-top-N. Precision-in-top-N represents the percentage of truly high overall ratings among those that the model predicted would be the N most relevant items for each user. The experimental system was developed using Microsoft Visual Basic for Applications (VBA). The experimental results showed that our proposed system (avg. MAE = 0.584) outperformed traditional CF (avg. MAE = 0.591) as well as multicriteria CF (avg. AVE = 0.608). We also found that multicriteria CF showed worse performance compared to traditional CF in our data set, which is contradictory to the results in the most previous studies. This result supports the premise of our study that people have two different types of preference schemes - holistic and composite. Besides MAE, the proposed system outperformed all the comparison models in precision-in-top-3, precision-in-top-5, and precision-in-top-7. The results from the paired samples t-test presented that our proposed system outperformed traditional CF with 10% statistical significance level, and multicriteria CF with 1% statistical significance level from the perspective of average MAE. The proposed system sheds light on how to understand and utilize user's preference schemes in recommender systems domain.