Service-Oriented Architecture (SOA) is emerging as an effective approach for developing applications by dynamically discovering and composing reusable services. Generally, the benefits of SOA are known as low-development cost, high agility, high scalability, business level reuse, etc. However, a representative problem for widely applying SOA is the performance problem. This is caused by the nature of SOA such as service deployment and execution in distributed environment, heterogeneity of service platforms, use of a standard message format, etc. Therefore, performance problem has to be overcome to effectively apply SOA, and service performance has to be measured precisely to analyze where and why the problem has occurred. Prerequisite for this is a definition of a quality model to effectively measure service performance. However, current works on service performance lacks in defining a practical and precise quality model for measuring performance which adequately addresses the execution environment and features of SOA. Hence, in this paper, we define a quality model which includes a set of practical metrics for measuring service performance and an effective technique to measure the value of the proposed metrics. In addition, we apply the metrics for Hotel Reservation Service System (HRSS) to show the practicability and usefulness of the proposed metrics.
Kim, Nam Won;Lee, Jeong Eun;Lee, Jeongwoo;Jung, Yong
Journal of Korea Water Resources Association
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v.49
no.5
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pp.439-450
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2016
For the design of infrastructures controlling the flood events at ungauged basins, this study tries to find the regional flood frequencies using peak flow data generated by the spatial extension of flood records. The Chungju Dam watershed is selected to validate the possibility of regional flood frequency analysis using the spatially extended flood data. Firstly, based on the index flood method, the flood event data from the spatial extension method is evaluated for 22 mid/smaller sub-basins at the Chungju Dam watershed. The homogeneity of the Chungju dam watershed was assessed in terms of the different size of watershed conditions such as accumulated and individual sub-basins. Based on the result of homogeneity analysis, this watershed is heterogeneous with respect to individual sub-basins because of the heterogeneity of rainfall distribution. To decide the regional probability distribution, goodness-of fit measure and weighted moving averages method from flood frequency analysis were adopted. Finally, GEV distribution was selected as a representative distribution and regional quantile were estimated. This research is one step further method to estimate regional flood frequency for ungauged basins.
In this study, we conducted the study of the merits and demerits of the laser flash and the divided-bar methods for measuring the thermal conductivity of rocks and investigated applicability of the divided-bar apparatus which was developed by KIGAM. The laser flash method can measure thermal diffusivity, specific heat capacity, and thermal conductivity of rocks with even small thickness (< ~3 mm) in the high temperature range($25-200^{\circ}C$) in non-contact mode. For the laser flash method, samples must be uniform and homogeneous. In the case of the divided-bar method, the apparatus measures only thermal conductivity of rock samples at the room temperature. We measured thermal conductivities of 12 rock samples with low density and high porosity using two methods. In the laser flash method, there exist potential errors caused by the effect of pulse dispersion and reflection by various minerals and porosity in rock samples; the difference in thermal conductivity values measured on the front surface and the opposite surface ranges from 0.001 to 0.140 W/mK with the standard deviation of 0.003~0.089 W/mK, which seems to be caused by heterogeneity of rock samples. On the contrary, the divided-bar apparatus shows stable thermal conductivity measurements and relatively small measurement errors; the difference in thermal conductivity values, just as we applied to the laser frash method, is 0.001~0.016 W/mK with the standard deviation 0.001~0.034 W/mK. In turn, the divided-bar method can be applied to more thick samples that are more representative of bulk thermal conductivity.
Journal of Family Resource Management and Policy Review
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v.26
no.3
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pp.1-17
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2022
This study focused on the heterogeneity of groups in single-person households, to identify how middle-aged single-person households is categorized by sub-groups and to come up with policy measures to overcome social exclusion by examining predictive factors for the type of social exclusion. Potential class analysis and multinomial logistic regression analysis were conducted on a total of 361 middle-aged single-person households using the 14th Korea Replication Panel data. The social exclusion index of these households was measured consisting of 10 six-dimensional indicators. The results showed that middle-aged single-person households had five different types: "non-exclusion"(29.6%), "health restriction"(14.3%), "interact restriction and middle-risk multiple-exclusion" (12.0%), "income and health exclusion"(14.1%), and "high-risk multiple-exclusion"(30.0%). More than 70% of the respondents experienced social exclusion, and most of the exclusion types were multiple exclusion. When examining the factors affecting each exclusion type, the 'subjective health level' was a common major predictor, and family interact, age and leisure activity satisfaction variables were significant predictors of the 'high-risk multiple exclusion type' and 'the interact restriction and middle-risk multiple-exclusion type'. Based on these results, a multidimensional intervention strategy is an effective measure to solve the social exclusion problem of middle-aged single-person households, and practical measures should be considered by strengthening 'health' and exchanges.
This study investigated the relationship of self-esteem, academic stress, social support, and parenting attitudes with depression of Korean children and adolescents using a meta-analysis. A total of 86 studies, both published and unpublished manuscripts, were included. The results showed that depression of children and adolescents were positively associated with self-esteem, social support, and functional parenting attitudes, and negatively related to academic stress. The largest effect size was found in the relationship with self-esteem, followed by the relationships with academic stress, social support, and functional parenting attitudes, all in the range between moderate and large effect size. As the analysis indicated the heterogeneity of the results, subsequent analyses were performed to test the moderating effects of instrument and age. The significant moderators were the types of instruments used to measure self-esteem, academic stress, parenting attitudes, and depression. Age was also a significant moderator.
This study was conducted to measure methane ($CH_4$) and nitrous oxide ($N_2O$) emissions from the 6 month old litter stockpile used for korean native cattle (Hanwoo) from August 3, 2007 to October 4, 2007. Daily mean $CH_4$ emissions was peaked to 273.013 ${\mu}g\;m^{-2}\;s^{-1}$ (SE : ${\pm}1.047{\mu}g\;m^{-2}\;s^{-1}$) on first day and then gradually decreased to 2.309 ${\mu}g\;m^{-2}\;s^{-1}$ (SE : ${\pm}0.061{\mu}g\;m^{-2}\;s^{-1}$) at the end of this experiment. Daily mean $N_2O$ emissions was as little as 0.269 ${\mu}g\;m^{-2}\;s^{-1}$ (SE : ${\pm}0.018{\mu}g\;m^{-2}\;s^{-1}$) on first day, but exponentially increased up to 3.569 ${\mu}g\;m^{-2}\;s^{-1}$ (SE : ${\pm}0.454{\mu}g\;m^{-2}\;s^{-1}$) on 43rd day and then slowly decreased to 1.888 ${\mu}g\;m^{-2}\;s^{-1}$ (SE : ${\pm}0.012{\mu}g\;m^{-2}\;s^{-1}$) at the end of this experiment. Carbon dioxide equivalent ($CO_2$-eq), calculated by global warming potentials of $CH_4$ or $N_2O$, of $CH_4$ on first day occupied approximately 99% of sum of $CO_2$-eq of $CH_4$ and $N_2O$. Methane emissions decreased and $N_2O$ emissions increased so that $CO_2$-eq ratio of $CH_4$ to $N_2O$ was 50:50 on 34th day. The effect of $N_2O$ on the ratio was increase thereafter. The ratio of daily mean $CH_4$ and $N_2O$ emissions to daily error of the mean was calculated to find daily fluctuation of $CH_4$ and $N_2O$ emissions. The ratio of $CH_4$ was less than 1.0% till 11th day but increased to 10.9% on 57th day. The ratio of $N_2O$ (0.4%~51.0%) was higher than that of $CH_4$, showing high in early stage and then gradually decrease, which was different from the pattern of $CH_4$. The ratio of daily mean emissions to daily error of the mean was little in case of active $CH_4$ or $N_2O$ generation period, which would be caused by the temporal and spatial heterogeneity of composting process. Hence more air supply on early stage to decrease $CH_4$ generation and proper turning to reduce spatial heterogeneity are needed to mitigate greenhouse gas emissions.
Near surface air temperature data which are one of the essential factors in hydrology, meteorology and climatology, have drawn a substantial amount of attention from various academic domains and societies. Meteorological observations, however, have high spatio-temporal constraints with the limits in the number and distribution over the earth surface. To overcome such limits, many studies have sought to estimate the near surface air temperature from satellite image data at a regional or continental scale with simple regression methods. Alternatively, we applied various Kriging methods such as ordinary Kriging, universal Kriging, Cokriging, Regression Kriging in search of an optimal estimation method based on near surface air temperature data observed from automatic weather stations (AWS) in South Korea throughout 2010 (365 days) and MODIS land surface temperature (LST) data (MOD11A1, 365 images). Due to high spatial heterogeneity, auxiliary data have been also analyzed such as land cover, DEM (digital elevation model) to consider factors that can affect near surface air temperature. Prior to the main estimation, we calculated root mean square error (RMSE) of temperature differences from the 365-days LST and AWS data by season and landcover. The results show that the coefficient of variation (CV) of RMSE by season is 0.86, but the equivalent value of CV by landcover is 0.00746. Seasonal differences between LST and AWS data were greater than that those by landcover. Seasonal RMSE was the lowest in winter (3.72). The results from a linear regression analysis for examining the relationship among AWS, LST, and auxiliary data show that the coefficient of determination was the highest in winter (0.818) but the lowest in summer (0.078), thereby indicating a significant level of seasonal variation. Based on these results, we utilized a variety of Kriging techniques to estimate the surface temperature. The results of cross-validation in each Kriging model show that the measure of model accuracy was 1.71, 1.71, 1.848, and 1.630 for universal Kriging, ordinary Kriging, cokriging, and regression Kriging, respectively. The estimates from regression Kriging thus proved to be the most accurate among the Kriging methods compared.
Purpose : Since the mid cranial fossa is composed of various thickness of bone, the tissue inhomogeneity caused by bone would produce dose attenuation in cobalt-60 gamma knife irradiation. The correction factor for bone attenuation of cobalt-60 which is used for gamma knife source is -3.5$\%$. More importantly, nearly all the radiosurgery treatment planning systems assume a treatment volume of unit density: any perturbation due to tissue inhomogeneity is neglected, This study was performed to confirm the bone attenuation in mid cranial fossa using gamma knife. Materials and Methods : Computed tomography was performed after Leksell stereotactic frame had been liked to the Alderson Rando Phantom (human phantom) skull area. Kodak X-omat V film was inserted into two sites of pituitary adenoma point and acoustic neurinoma point, and irradiated by gamma knife with 14mm and 18mm collimator. An automatic scanning densitometer with a 1mm aperture is used to measure the dose profile along the x and y axis. Results : Isodose curve constriction in mid cranial fossa is observed with various ranges. Pituitary tumor point is greater than acoustic neurinoma point (0.2-3.0 mm vs 0.1-1.3 mm) and generally 14 mm collimator is greater than 18mm collimator (0.4-3.0 mm vs. 0.2-2.2 mm) Even though the isodose constriction is found, constriction of 50$\%$ isodose curve which is used for treatment reference line does not exceed 1 mm. This range is too small to influence the treatment planning and treatment results. Conclusion : Radiosurgery planning system of gamma knife does not show significant error to be corrected without consideration of bone attenuation.
Journal of the Korean Association of Geographic Information Studies
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v.25
no.1
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pp.120-132
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2022
Recently, the rapid increase in vacant houses in urban areas has caused various problems such as worsening urban landscape, causing safety accidents, crime accidents, and hygiene problems. According to the Statistics Korea Future Population Estimation results, the growth rate of Korean population and households is expected to continue to decrease, which is likely to lead to an increase in the occurrence of vacant houses. If the problem caused by the occurrence of vacant houses is neglected, it causes not only a physical decline such as a deterioration of the residential environment but also a social and economic decline. In order to solve this problem, it is necessary to grasp the spatial distribution characteristics of vacant houses at the local level considering the existence of regional characteristics and spatial influence. Therefore, in this study, in order to measure global spatial autocorrelation, the analysis was conducted centering on the old downtown area of Busan, where there are many vacant houses through Moran's I and Geographically Weighted Regression(GWR). In addition, the distribution of vacant houses in different spatial units in Eup_Myeon_Dong and Census was analyzed to evaluate the possibility of Modifiable Areal Unit Problem(MAUP), which differ in the results of spatial analysis as the spatial analysis units change. As a result of the analysis, the occurrence of vacant houses by Eup_Myeon_Dong in the old downtown area of Busan had spatial heterogeneity, and the spatial analysis results of vacant houses were different as the spatial analysis units were different. Accordingly, in order to understand the exact distribution characteristics of vacant house occurrence, spatial dimensions using the GWR model should be considered, and it is suggested that consideration of the MAUP is necessary.
Brand switching data frequently used in market structure analysis is adequate to analyze non- durable goods, because it can capture competition between specific two brands. But brand switching data sometimes can not be used to analyze goods like automobiles having long term duration because one of main assumptions that consumer preference toward brand attributes is not changed against time can be violated. Therefore a new type of data which can precisely capture competition among durable goods is needed. Another problem of using brand switching data collected from actual purchase behavior is short of explanation why consumers consider different set of brands. Considering above problems, main purpose of this study is to analyze market structure for durable goods with consideration set. The author uses exploratory approach and latent class clustering to identify market structure based on heterogeneous consideration set among consumers. Then the relationship between some factors and consideration set formation is analyzed. Some benefits and two demographic variables - age and income - are selected as factors based on consumer behavior theory. The author analyzed USA automotive market with top 11 brands using exploratory approach and latent class clustering. 2,500 respondents are randomly selected from the total sample and used for analysis. Six models concerning market structure are established to test. Model 1 means non-structured market and model 6 means market structure composed of six sub-markets. It is exploratory approach because any hypothetical market structure is not defined. The result showed that model 1 is insufficient to fit data. It implies that USA automotive market is a structured market. Model 3 with three market structures is significant and identified as the optimal market structure in USA automotive market. Three sub markets are named as USA brands, Asian Brands, and European Brands. And it implies that country of origin effect may exist in USA automotive market. Comparison between modal classification by derived market structures and probabilistic classification by research model was conducted to test how model 3 can correctly classify respondents. The model classify 97% of respondents exactly. The result of this study is different from those of previous research. Previous research used confirmatory approach. Car type and price were chosen as criteria for market structuring and car type-price structure was revealed as the optimal structure for USA automotive market. But this research used exploratory approach without hypothetical market structures. It is not concluded yet which approach is superior. For confirmatory approach, hypothetical market structures should be established exhaustively, because the optimal market structure is selected among hypothetical structures. On the other hand, exploratory approach has a potential problem that validity for derived optimal market structure is somewhat difficult to verify. There also exist market boundary difference between this research and previous research. While previous research analyzed seven car brands, this research analyzed eleven car brands. Both researches seemed to represent entire car market, because cumulative market shares for analyzed brands exceeds 50%. But market boundary difference might affect the different results. Though both researches showed different results, it is obvious that country of origin effect among brands should be considered as important criteria to analyze USA automotive market structure. This research tried to explain heterogeneity of consideration sets among consumers using benefits and two demographic factors, sex and income. Benefit works as a key variable for consumer decision process, and also works as an important criterion in market segmentation. Three factors - trust/safety, image/fun to drive, and economy - are identified among nine benefit related measure. Then the relationship between market structures and independent variables is analyzed using multinomial regression. Independent variables are three benefit factors and two demographic factors. The result showed that all independent variables can be used to explain why there exist different market structures in USA automotive market. For example, a male consumer who perceives all benefits important and has lower income tends to consider domestic brands more than European brands. And the result also showed benefits, sex, and income have an effect to consideration set formation. Though it is generally perceived that a consumer who has higher income is likely to purchase a high priced car, it is notable that American consumers perceived benefits of domestic brands much positive regardless of income. Male consumers especially showed higher loyalty for domestic brands. Managerial implications of this research are as follow. Though implication may be confined to the USA automotive market, the effect of sex on automotive buying behavior should be analyzed. The automotive market is traditionally conceived as male consumers oriented market. But the proportion of female consumers has grown over the years in the automotive market. It is natural outcome that Volvo and Hyundai motors recently developed new cars which are targeted for women market. Secondly, the model used in this research can be applied easier than that of previous researches. Exploratory approach has many advantages except difficulty to apply for practice, because it tends to accompany with complicated model and to require various types of data. The data needed for the model in this research are a few items such as purchased brands, consideration set, some benefits, and some demographic factors and easy to collect from consumers.
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