• The Korean Journal of Nuclear Medicine
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• v.34 no.5
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• pp.418-425
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• 2000

Purpose: There is no established formula for estimating renal depths in Korean. As a result, we undertook this study to develop a new formula, and to apply this formula in the calculation of glomerular filtration rate (GFR). Materials and Methods: We measured the renal depth (RD) on the abdominal CT obtained in 300 adults (M:F: 167:133, mean age 50.9 years) without known renal diseases. The RDs measured by CT were compared with the estimated RDs based on the Tonnesen and Taylor equations. New formulas were derived from the measured RDs in 200 out of 300 patients based on several variables such as sex, age, weight, and height by multiple regression analysis. The RDs estimated from the new formulas were compared with the measured RDs in the remaining 100 patients as a control. In 48 patients who underwent Tc-99m DTPA renal scintigraphy, GFR was measured with three equations (new formula, Tonnesen and Taylor equations), respectively, and compared with each other. Results: The mean values of the RDs measured from CT were 6.9 cm for right kidney of the men (MRK), 6.7 cm for left kidney of the men (MLK), 6.7 cm for right kidney of the women (WRK), and 6.6 cm for left kidney of the women (WLK). The RDs estimated from Tonnesen equation were shorter than the ones measured from CT significantly. The newly derived formulas were 12.813 (weight/height)+0.002 (age)+ 2.264 for MRK, 15.344 (weight/height)+0.011 (age)+0.557 for MLK, 12.936 (weight/height)+ 0.014 (age)+1.462 for WRK and 13.488 (weight/height)+0.019 (age)+0.762 for WLK. The correlation coefficients of the RD measured from CT and estimated from the new formula were 0.529 in MRK, 0.729 in MLK, 0.601 in WRK, and 0.724 in WLK, respectively. The GFRs from the new formula were significantly higher than those from the Tonnesen equation significantly, which was the most similar to normal GFR values. Conclusion: We generated new formulas for estimating RD in Korean from the data by CT. By adopting these formulas, we expect that GFR can be measured by the Gates method accurately in Korean.

• Journal of Chest Surgery
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• v.39 no.4 s.261
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• pp.269-274
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• 2006

Background: Tetralogy of Fallot (TOF) with pulmonary atresia and major aortopulmonary collateral arteries (MAPCAS) is complex lesion with marked heterogeneity of pulmonary blood supply and arborization anomalies. Patients with TOF with PA and MAPCAS have traditionally required multiple staged unifocalization of pulmonary blood supply before undergoing complete repair. In this report, we describe recent change of strategy and the results in our institution. Material and Method: We established surgical stratagies: early correction, central mediastinal approach, initial RV-PA conduit interposition, and aggressive intervention. Between July 1998 and August 2004, 23 patients were surgically treated at our institution. We divided them into 3 groups by initial operation method; group I: one stage total correction, group II: RV-PA conduit and unifocalization, group III: RV-PA conduit interposition only. Result: Mean ages at initial operation in each group were $13.9{\pm}16.0$ months (group 1), $10.4{\pm}15.6$ months (group II), and $7.9{\pm}7.7$ months (group III). True pulmonary arteries were not present in f patient and the pulmonary arteries were confluent in 22 patients. The balloon angioplasty was done in average 1.3 times (range: $1{\sim}6$). There were 4 early deaths relating initial operation, and 1 late death due to incracranial hemorrhage after definitive repair. The operative mortalities of initial procedures in each group were 25.0% (1/4: group I), 20.0% (2/10: group II), and 12.2% (1/9: group III). The causes of operative mortality were hypoxia (2), low cardiac output (1) and sudden cardiac arrest (1). Definitive repair rates in each group were 75% (3/4) in group I, 20% (2/10, fenestration: 2) in group II, and 55.0% (5/9, fenestration: 1) in group III. Conclusion: In patients of TOF with PA and MAPCAS, RV-PA connection as a initial procedure could be performed with relatively low risk, and high rate of definitive repair can be obtained in the help of balloon pulmonary angioplasty. One stage RV-PA connection and unifocalization appeared to be successful in selected patients.

• Radiation Oncology Journal
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• v.16 no.1
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• pp.35-41
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• 1998

Purpose : To investigate the role of adjuvant chemoradiotherapy in adenocarcinoma of the rectum, we retrospectively compared the treatment results between postoperative adjuvant radiotherapy alone and combined chemoradiotherapy. Material and Methods : From October 1989 to May 1994, 141 patients with rectal carcinoma were treated by postoperative adjuvant therapy in Yonsei Cancer Center. Sixty eight patients were treated by radiation therapy alone. Seventy three patients were treated by combined chemoradiotherapy. Radiation therapy was delivered with 10 MV linear accelerator, 180cGy fraction/5 days per week. Total radiation doses were 5400cGy in the postoperative radiotherapy alone group. Three to twelve cycles of Fluorouracil(mean dose $393.9mg/m^2$) with Leucovorin($20mg/m^2$) and 5040cGy of radiation were delivered in the combined chemoradiotherapy group. Third and 4th cycle of chemotherapy were administrated during the radiation treatment in the combined group. The median follow up was 38 months with a range of 3 to 81 months. Results : The 5 year overall survival rate of radiation alone group and combined group were $60.1\%$ and $66.3\%$, respectively. The 5 year disease free survival rate of radiation aione group and combined group were $54.2\%$ and $65.5\%$, respectively There was no significant difference of overall survival and disease free survival between RT alone group and combined group(p<0.05). But the 5 year Local failure free survival rate of combined group was significantly better than radiotherapy alone group($05.8\%\;vs.\;50.3\%.\;p=0.04$). Conclusion : There was no significant difference in overall survival, disease free survival, and distant metastasis free survival between postoperative adjuvant radiotheray alone group and combinded chemoradiotherapy group. Only the Local failure free survival rate was superior in the combined treatment group. These results confirm the radiosensitizing effect of the chemotherapeutic agent in the combined chemoradiotherapy treatment.

• Korean Journal of Soil Science and Fertilizer
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• v.42 no.1
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• pp.46-52
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• 2009

Deposition of atmospheric N that is depleted in $^{15}N$ has shown to decrease N isotope ratio ($^{15}N/^{14}N$,expressed as ${\delta}^{15}N$) of forest samples such as tree rings, foliage, and total soil-N. However, its effect on ${\delta}^{15}N$ of mineral soil-N which is biologically active N pool has never been tested. In this study, ${\delta}^{15}N$ of mineral N($NH{_4}^+$ and $NO_3{^-}$) in forest soils from organic and two depths of mineral soil layers (0 to 20 cm and 20 to 40cm depth) of Pinus densiflora stands located at two distinct areas (rural and industrial areas) in southern Korea was analyzed to investigate if there is any difference in ${\delta}^{15}N$ of mineral N between these areas. We also evaluated potential N loss of the study sites using ${\delta}^{15}N$ of mineral N. Across the soil layers, the ${\delta}^{15}N$ of $NH{_4}^+$ ranged from +8.9 to +24.8‰ in the rural area and from +4.4 to +13.8‰ in the industrial area. Soils from organic layer (+4.4‰) and mineral layer between 0 and 20 cm (+13.8‰) of industrial area showed significantly lower ${\delta}^{15}N$ of $NH{_4}^+$ than those of rural area (+8.9 and +24.3‰, respectively), probably indicating the greater contribution of $^{15}N$-depleted $NH{_4}^+$ from atmospheric deposition to forest in the industrial area than in the rural area. Meanwhile, ${\delta}^{15}N$ of $NO_3{^-}$ was not different between the rural and industrial areas, probably because ${\delta}^{15}N$ of $NO_3{^-}$ is more likely to be altered by the N loss that causes $^{15}N$ enrichment of the remaining soil N pool. Compared with the ${\delta}^{15}N$ of soil mineral N reported by other studies (from -10.9 to +15.6‰ for $NH{_4}^+$ and -14.8 to +5.6‰ for $NO_3{^-}$), the ${\delta}^{15}N$ observed in our study was substantially high, suggesting that the study sites are more subject to the N loss. It was concluded that $NH{_4}^+$ rather than $NO_3{^-}$ can conserve the ${\delta}^{15}N$ signature of atmospheric N deposition in forest ecosystems.

• Journal of Intelligence and Information Systems
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• v.24 no.4
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• pp.111-136
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• 2018

In this paper, we propose a methodology to extract answer information about queries from various types of unstructured documents collected from multi-sources existing on web in order to expand knowledge base. The proposed methodology is divided into the following steps. 1) Collect relevant documents from Wikipedia, Naver encyclopedia, and Naver news sources for "subject-predicate" separated queries and classify the proper documents. 2) Determine whether the sentence is suitable for extracting information and derive the confidence. 3) Based on the predicate feature, extract the information in the proper sentence and derive the overall confidence of the information extraction result. In order to evaluate the performance of the information extraction system, we selected 400 queries from the artificial intelligence speaker of SK-Telecom. Compared with the baseline model, it is confirmed that it shows higher performance index than the existing model. The contribution of this study is that we develop a sequence tagging model based on bi-directional LSTM-CRF using the predicate feature of the query, with this we developed a robust model that can maintain high recall performance even in various types of unstructured documents collected from multiple sources. The problem of information extraction for knowledge base extension should take into account heterogeneous characteristics of source-specific document types. The proposed methodology proved to extract information effectively from various types of unstructured documents compared to the baseline model. There is a limitation in previous research that the performance is poor when extracting information about the document type that is different from the training data. In addition, this study can prevent unnecessary information extraction attempts from the documents that do not include the answer information through the process for predicting the suitability of information extraction of documents and sentences before the information extraction step. It is meaningful that we provided a method that precision performance can be maintained even in actual web environment. The information extraction problem for the knowledge base expansion has the characteristic that it can not guarantee whether the document includes the correct answer because it is aimed at the unstructured document existing in the real web. When the question answering is performed on a real web, previous machine reading comprehension studies has a limitation that it shows a low level of precision because it frequently attempts to extract an answer even in a document in which there is no correct answer. The policy that predicts the suitability of document and sentence information extraction is meaningful in that it contributes to maintaining the performance of information extraction even in real web environment. The limitations of this study and future research directions are as follows. First, it is a problem related to data preprocessing. In this study, the unit of knowledge extraction is classified through the morphological analysis based on the open source Konlpy python package, and the information extraction result can be improperly performed because morphological analysis is not performed properly. To enhance the performance of information extraction results, it is necessary to develop an advanced morpheme analyzer. Second, it is a problem of entity ambiguity. The information extraction system of this study can not distinguish the same name that has different intention. If several people with the same name appear in the news, the system may not extract information about the intended query. In future research, it is necessary to take measures to identify the person with the same name. Third, it is a problem of evaluation query data. In this study, we selected 400 of user queries collected from SK Telecom 's interactive artificial intelligent speaker to evaluate the performance of the information extraction system. n this study, we developed evaluation data set using 800 documents (400 questions * 7 articles per question (1 Wikipedia, 3 Naver encyclopedia, 3 Naver news) by judging whether a correct answer is included or not. To ensure the external validity of the study, it is desirable to use more queries to determine the performance of the system. This is a costly activity that must be done manually. Future research needs to evaluate the system for more queries. It is also necessary to develop a Korean benchmark data set of information extraction system for queries from multi-source web documents to build an environment that can evaluate the results more objectively.

• The Journal of Korean Society for Radiation Therapy
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• v.31 no.1
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• pp.51-56
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• 2019

Purpose: The usefulness of using single-electron radiation for secondary radiotherapy of breast cancer patients after surgery is assessed and the use of a combine of different energy. Methods and materials : In this study, 40 patients (group A) using energy 6 MeV and 9 MeV, and 19 patients (group B) using a combine of 9 MeV and 12 MeV were studied among 59 patients who performed secondary care using combine electronic radiation. Each patient in each group, 6 MeV, 9 MeV, Combine(6 MeV / 9 MeV) and 9 MeV, 12 MeV, Combine (9 MeV / 12 MeV) were developed in different ways, and the maximum doses delivered to the original hospital, D95, D5, and $V_3$, $V_5$, $V_{10}$ were compared. Result: The D95 mean value of Group A treatment plan was $785.33{\pm}225.37cGy$, $1121.79{\pm}87.02cGy$ at 9 MeV, and $1010.98{\pm}111.17cGy$ at 6 MeV / 9 MeV, and the mean value at 6 MeV / 9 MeV was most appropriate for the dose. The mean values of the low dose area $V_3$ and $V_5$ in the lung of the breast direction being treated were $3.24{\pm}3.49%$ and $0.72{\pm}1.55%$ at 6 MeV, the highest 9 MeV at $7.25{\pm}4.59%$, $3.07{\pm}2.64%$, the lowest at 6 MeV. Maximum and average lung dose was $727.78{\pm}137.27cGy$ at 6 MeV / 9 MeV, $49.16{\pm}24.44cGy$, highest 9 MeV at $998.97{\pm}114.35cGy$, $85.33{\pm}41.18cGy$, and lowest 6 MeV at $387.78{\pm}208.88cGy$, $9.27{\pm}6.60cGy$. The value of $V_{10}$ was all close to zero. Group B appeared in the pattern of Group A. Conclusion: Relative differences in low-dose areas of the lungs $V_3$ and $V_5$ were seen and were most effective in the dose transfer of tumor bed in the application of combined energy. It is thought that the method of using electronic energy in further radiation treatments for breast cancer is a more effective way to use the energy effect of limiting energy resources, and that if you think about it again, it could be a little more beneficial radiation treatment for patients.

• Journal of Intelligence and Information Systems
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• v.26 no.4
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• pp.111-126
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• 2020

Most industries have recently become aware of the importance of customer lifetime value as they are exposed to a competitive environment. As a result, preventing customers from churn is becoming a more important business issue than securing new customers. This is because maintaining churn customers is far more economical than securing new customers, and in fact, the acquisition cost of new customers is known to be five to six times higher than the maintenance cost of churn customers. Also, Companies that effectively prevent customer churn and improve customer retention rates are known to have a positive effect on not only increasing the company's profitability but also improving its brand image by improving customer satisfaction. Predicting customer churn, which had been conducted as a sub-research area for CRM, has recently become more important as a big data-based performance marketing theme due to the development of business machine learning technology. Until now, research on customer churn prediction has been carried out actively in such sectors as the mobile telecommunication industry, the financial industry, the distribution industry, and the game industry, which are highly competitive and urgent to manage churn. In addition, These churn prediction studies were focused on improving the performance of the churn prediction model itself, such as simply comparing the performance of various models, exploring features that are effective in forecasting departures, or developing new ensemble techniques, and were limited in terms of practical utilization because most studies considered the entire customer group as a group and developed a predictive model. As such, the main purpose of the existing related research was to improve the performance of the predictive model itself, and there was a relatively lack of research to improve the overall customer churn prediction process. In fact, customers in the business have different behavior characteristics due to heterogeneous transaction patterns, and the resulting churn rate is different, so it is unreasonable to assume the entire customer as a single customer group. Therefore, it is desirable to segment customers according to customer classification criteria, such as loyalty, and to operate an appropriate churn prediction model individually, in order to carry out effective customer churn predictions in heterogeneous industries. Of course, in some studies, there are studies in which customers are subdivided using clustering techniques and applied a churn prediction model for individual customer groups. Although this process of predicting churn can produce better predictions than a single predict model for the entire customer population, there is still room for improvement in that clustering is a mechanical, exploratory grouping technique that calculates distances based on inputs and does not reflect the strategic intent of an entity such as loyalties. This study proposes a segment-based customer departure prediction process (CCP/2DL: Customer Churn Prediction based on Two-Dimensional Loyalty segmentation) based on two-dimensional customer loyalty, assuming that successful customer churn management can be better done through improvements in the overall process than through the performance of the model itself. CCP/2DL is a series of churn prediction processes that segment two-way, quantitative and qualitative loyalty-based customer, conduct secondary grouping of customer segments according to churn patterns, and then independently apply heterogeneous churn prediction models for each churn pattern group. Performance comparisons were performed with the most commonly applied the General churn prediction process and the Clustering-based churn prediction process to assess the relative excellence of the proposed churn prediction process. The General churn prediction process used in this study refers to the process of predicting a single group of customers simply intended to be predicted as a machine learning model, using the most commonly used churn predicting method. And the Clustering-based churn prediction process is a method of first using clustering techniques to segment customers and implement a churn prediction model for each individual group. In cooperation with a global NGO, the proposed CCP/2DL performance showed better performance than other methodologies for predicting churn. This churn prediction process is not only effective in predicting churn, but can also be a strategic basis for obtaining a variety of customer observations and carrying out other related performance marketing activities.

• Asia Marketing Journal
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• v.14 no.1
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• pp.83-98
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• 2012

In a market where new and used cars are competing with each other, we would run the risk of obtaining biased estimates of cross elasticity between them if we focus on only new cars or on only used cars. Unfortunately, most of previous studies on the automobile industry have focused on only new car models without taking into account the effect of used cars' pricing policy on new cars' market shares and vice versa, resulting in inadequate prediction of reactive pricing in response to competitors' rebate or price discount. However, there are some exceptions. Purohit (1992) and Sullivan (1990) looked into both new and used car markets at the same time to examine the effect of new car model launching on the used car prices. But their studies have some limitations in that they employed the average used car prices reported in NADA Used Car Guide instead of actual transaction prices. Some of the conflicting results may be due to this problem in the data. Park (1998) recognized this problem and used the actual prices in his study. His work is notable in that he investigated the qualitative effect of new car model launching on the pricing policy of the used car in terms of reinforcement of brand equity. The current work also used the actual price like Park (1998) but the quantitative aspect of competitive price promotion between new and used cars of the same model was explored. In this study, I develop a model that assumes that the cross elasticity between new and used cars of the same model is higher than those amongst new cars and used cars of the different model. Specifically, I apply the nested logit model that assumes the car model choice at the first stage and the choice between new and used cars at the second stage. This proposed model is compared to the IIA (Independence of Irrelevant Alternatives) model that assumes that there is no decision hierarchy but that new and used cars of the different model are all substitutable at the first stage. The data for this study are drawn from Power Information Network (PIN), an affiliate of J.D. Power and Associates. PIN collects sales transaction data from a sample of dealerships in the major metropolitan areas in the U.S. These are retail transactions, i.e., sales or leases to final consumers, excluding fleet sales and including both new car and used car sales. Each observation in the PIN database contains the transaction date, the manufacturer, model year, make, model, trim and other car information, the transaction price, consumer rebates, the interest rate, term, amount financed (when the vehicle is financed or leased), etc. I used data for the compact cars sold during the period January 2009- June 2009. The new and used cars of the top nine selling models are included in the study: Mazda 3, Honda Civic, Chevrolet Cobalt, Toyota Corolla, Hyundai Elantra, Ford Focus, Volkswagen Jetta, Nissan Sentra, and Kia Spectra. These models in the study accounted for 87% of category unit sales. Empirical application of the nested logit model showed that the proposed model outperformed the IIA (Independence of Irrelevant Alternatives) model in both calibration and holdout samples. The other comparison model that assumes choice between new and used cars at the first stage and car model choice at the second stage turned out to be mis-specfied since the dissimilarity parameter (i.e., inclusive or categroy value parameter) was estimated to be greater than 1. Post hoc analysis based on estimated parameters was conducted employing the modified Lanczo's iterative method. This method is intuitively appealing. For example, suppose a new car offers a certain amount of rebate and gains market share at first. In response to this rebate, a used car of the same model keeps decreasing price until it regains the lost market share to maintain the status quo. The new car settle down to a lowered market share due to the used car's reaction. The method enables us to find the amount of price discount to main the status quo and equilibrium market shares of the new and used cars. In the first simulation, I used Jetta as a focal brand to see how its new and used cars set prices, rebates or APR interactively assuming that reactive cars respond to price promotion to maintain the status quo. The simulation results showed that the IIA model underestimates cross elasticities, resulting in suggesting less aggressive used car price discount in response to new cars' rebate than the proposed nested logit model. In the second simulation, I used Elantra to reconfirm the result for Jetta and came to the same conclusion. In the third simulation, I had Corolla offer $1,000 rebate to see what could be the best response for Elantra's new and used cars. Interestingly, Elantra's used car could maintain the status quo by offering lower price discount ($160) than the new car ($205). In the future research, we might want to explore the plausibility of the alternative nested logit model. For example, the NUB model that assumes choice between new and used cars at the first stage and brand choice at the second stage could be a possibility even though it was rejected in the current study because of mis-specification (A dissimilarity parameter turned out to be higher than 1). The NUB model may have been rejected due to true mis-specification or data structure transmitted from a typical car dealership. In a typical car dealership, both new and used cars of the same model are displayed. Because of this fact, the BNU model that assumes brand choice at the first stage and choice between new and used cars at the second stage may have been favored in the current study since customers first choose a dealership (brand) then choose between new and used cars given this market environment. However, suppose there are dealerships that carry both new and used cars of various models, then the NUB model might fit the data as well as the BNU model. Which model is a better description of the data is an empirical question. In addition, it would be interesting to test a probabilistic mixture model of the BNU and NUB on a new data set.

• Journal of Sasang Constitutional Medicine
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• v.11 no.2
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• pp.119-150
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• 1999

In spite of recent remarkable recent development in both western and oriental medical sciences, there is still only a shallow understanding of individual differences for various prognoses of incurable diseases and immunopathy diseases. Nevertheless, the care, cure and prevention methods of Sasang Constitutional Medicine are broadly used as an effective treatment of incurable diseases like immunopathy diseases and stress-related diseases and diseases due to aging. In this sense, the establishment of classification norms is urgent and essential for the worldwide application of Sasang Constitutional Medicine(SCM). This study began with the confirmation process of whether Sasang Constitutional types exist in Americans. To accomodate for cultural differences, the distinguishing tool was readjusted so that Sasang Constitutional Types in Americans could be determined. Hence, the selected tool is the new QSCCII+, which is a newly revised English version of the QSCCII. QSCCII was made and standardized by Dept. of SCM in Kyung Hee Medical Center and Dr. Kim7). The evaluation methods of the old version were improved in the new QSCCII+ through necessary statistical manipulation. The original QSCCII was officially authorized by the Korean Society of Sasang Constitutional Medicine as the only computerized version of Sasang diagnostics. This study is the first attempt to design a new diagnostic tool for the classification of Sasang Constitutional types in North Americans with the revision of QSCCII. The subjects of this study were selected from the cooperative people among the students and staffs of the University of Bridgeport and the patients who visited the Clinic in the Health Science Center. This study takes for about 1 year from 1998. 8 to 1999. 8 The conclusions of the study can be summarized as follows: 1. Sasang constitutional types also exist in Americans. It can also naturally be inferred that Sasang Constitutional types exist in all human beings, for there are many different human races in America. 2. There are more So-Yang In's than any other types in American white people. This result confirms the hypothesis that there also exist Sasang Constitutional types in westerners. 3. The result of repetitive tests suggests that the new QSCCII+ is an effective diagnostic tool for westerners when we consider the constant diagnostic results of the QSCCII+. 4. Sasang Constitutional types exit in the sample group regardless of racial difference. 5. The question items that were not often checked by Americans need to be modified into more understandable expressions. 6. The standardization of diagnosis for Americans should be established by use of the QSCCII+ 7. It can be guessed that there are many Tae-yang In's among the 71 persons who could not be clearly classified by the QSCCII+. Due to the scarcity of Tae-yang-In in general, it is important to improve upon the discernability of the QSCC II+. 8. The results of the Sasang Constitutional distribution in North Americans are as follows: The percentage of So-yang In distribution in the sample group is 36.25%(87persons), that of Tae-eum In is 13.75%(33persons), and that of So-eum In is 20.41%(49persons).

• Journal of Global Scholars of Marketing Science
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• v.17 no.4
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• pp.51-89
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• 2007

INTRODUCTION Due to the high broadband internet penetration rate and its group-oriented culture, various types of online communities operate in Korea. This study use 'Uses and Gratification Approach, and argue that members' usage-needs satisfaction with brand community is an important factor for promoting community commitment. Based on previous studies identifying the effect of brand image on consumers' responses to various marketing stimuli, this study hypothesizes that brand image can be a moderate variable affecting the relationship between usage-needs satisfaction with brand community and members' commitment to brand community. This study analyzes the influence of usage-needs satisfaction on brand community commitment and how apparel brand image affects the relationships between usage-needs satisfactions and community commitments. The hypotheses of this study are proposed as follows. H1-3: The usage-needs satisfaction of apparel brand community (interest, transaction, relationship needs) influences emotional (H1), continuous (H2), and normative (H3) commitments to apparel brand communities. H4-6: Apparel brand image has a moderating effect on the relationship between usage-needs satisfaction and emotional (H4), continuous (H5), and normative (H6) commitments to apparel brand communities. METHODS Brand communities founded by non-company affiliates were excluded and emphasis was placed instead on communities created by apparel brand companies. Among casual apparel brands registered in 6 Korean portal sites in August 2003, a total of 9 casual apparel brand online communities were chosen, depending on the level of community activity and apparel brand image. Data from 317 community members were analyzed by exploratory factor analysis, moderated regression analysis, ANOVA, and scheffe test. Among 317 respondents answered an online html-type questionnaire, 80.5% were between 16 to 25 years old. There were a total of 150 respondents from apparel brand communities(n=3) recording higher-than-average brand image scores (Mean > 3.75) and a total of 162 respondents from apparel brand communities(n=6) recording lower-than-average brand image scores(Mean < 3.75). In this study, brand community commitment was measured by a 5-point Likert scale: emotional, continuous and normative commitment. The degree of usage-needs satisfaction (interest, transaction, relationship needs) was measured on a 5-point Likert scale. The level of brand image was measured by a 5-point Likert scale: strength, favorability, and uniqueness of brand associations. RESULTS In the results of exploratory factor analysis, the three usage-needs satisfactions with brand community were classified as interest, transaction, and relationship needs. Brand community commitment was also divided into the multi-dimensional factors: emotional, continuous, and normative commitments. The regression analysis (using a stepwise method) was used to test the influence of 3 independent variables (interest-needs satisfaction, transaction-needs, and relationship-needs satisfactions) on the 3 dependent variables (emotional, continuous and normative commitments). The three types of usage-needs satisfactions are positively associated with the three types of commitments to apparel brand communities. Therefore, hypothesis 1, 2, and 3 were significantly supported. Moderating effects of apparel brand image on the relationship between usage-needs satisfaction and brand community commitments were tested by moderated regression analysis. The statistics result showed that the influence of transaction-needs on emotional commitment was significantly moderated by apparel brand image. In addition, apparel brand image had moderating effects on the relationship between relationship-needs satisfaction and emotional, continuous and normative commitments to apparel brand communities. However, there were not significant moderate effects of apparel brand image on the relationships between interest-needs satisfaction and 3 types of commitments (emotional, continuous and normative commitments) to apparel brand communities. In addition, the influences of transaction-needs satisfaction on 2 types of commitments (continuous and normative commitments) were not significantly moderated by apparel brand image. Therefore, hypothesis 4, 5 and 6 were partially supported. To explain the moderating effects of apparel brand image, four cross-tabulated groups were made by averages of usage-needs satisfaction (interest-needs satisfaction avg. M=3.09, transaction-needs satisfaction avg. M=3.46, relationship-needs satisfaction M=1.62) and the average apparel brand image (M=3.75). The average scores of commitments in each classified group are presented in Tables and Figures. There were significant differences among four groups. As can be seen from the results of scheffe test on the tables, emotional commitment in community group with high brand image was higher than one in community group with low brand image when transaction-needs satisfaction was high. However, when transaction-needs satisfaction was low, there was not any difference between the community group with high brand image and community group with low brand image regarding emotional commitment to apparel brand communities. It means that emotional commitment didn't increase significantly without high satisfaction of transaction-needs, despite the high apparel brand image. In addition, when apparel brand image was low, increase in transaction-needs did not lead to the increase in emotional commitment. Therefore, the significant relationship between transaction-needs satisfaction and emotional commitment was found in only brand communities with high apparel brand image, and the moderating effect of apparel brand image on this relationship between two variables was found in the communities with high satisfaction of transaction-needs only. Statistics results showed that the level of emotional commitment is related to the satisfaction level of transaction-needs, while overall response is related to the level of apparel brand image. We also found that the role of apparel brand image as a moderating factor was limited by the level of transaction-needs satisfaction. In addition, relationship-needs satisfaction brought significant increase in emotional commitment in both community groups (high and low levels of brand image), and the effect of apparel brand image on emotional commitment was significant in both community groups (high and low levels of relationship-needs satisfaction). Especially, the effect of brand image was greater when the level of relationship-needs satisfaction was high. in contrast, increase in emotional commitment responding to increase in relationship-needs satisfaction was greater when apparel brand image is high. The significant influences of relationship-needs satisfaction on community commitments (continuous and normative commitments) were found regardless of apparel brand image(in both community groups with low and high brand image). However, the effects of apparel brand image on continuous and normative commitments were found in only community group with high satisfaction level of relationship-needs. In the case of communities with low satisfaction levels of relationship needs, apparel brand image marginally increases continuous and normative commitments. Therefore, we could not find the moderating effect of apparel brand image on the relationship between relationship-needs satisfaction and continuous and normative commitments in community groups with low satisfaction levels of relationship needs, CONCLUSIONS AND IMPLICATIONS From the results of this study, we draw several conclusions; First, the increases in usage-needs satisfactions through apparel brand communities result in the increases in commitments to apparel brand communities, wheres the degrees of such relationship depends on the level of apparel brand image. That is, apparel brand image is a moderating factor strengthening the relationship between usage-needs satisfaction and commitment to apparel brand communities. In addition, the effect of apparel brand image differs, depending on the level and types of community usage-needs satisfactions. Therefore, marketers of apparel brand companies must determine the appropriate usage-needs, depending on the type of commitment they wish to increase and the level of their apparel brand image, to promote member's commitments to apparel brand communities. Especially, relationship-needs satisfaction was very important factor for increasing emotional, continuous and normative commitments to communities. However the level of relationship-needs satisfaction was lower than interest-needs and transaction-needs. satisfaction. According to previous study on apparel brand communities, relationship-need satisfaction was strongly related to member's intention of participation in their communities. Therefore, marketers need to develope various strategies in order to increase the relationship- needs as well as interest and transaction needs. In addition, despite continuous commitment was higher than emotional and normative commitments, all types of commitments to apparel brand communities had scores lower than 3.0 that was mid point in 5-point scale. A Korean study reported that the level of members' commitment to apparel brand community influenced customers' identification with a brand and brand purchasing behavior. Therefore, marketers should try to increase members' usage-needs satisfaction and apparel brand image as the necessary conditions for bringing about community commitments. Second, marketers should understand that they should keep in mind that increasing the level of community usage needs (transaction and relationship) is most effective in raising commitment when the level of apparel brand image is high, and that increasing usage needs (transaction needs) satisfaction in communities with low brand image might not be as effective as anticipated. Therefore, apparel companies with desirable brand image such as luxury designer goods firms need to create formal online brand communities (as opposed to informal communities with rudimentary online contents) to satisfy transaction and relationship needs systematically. It will create brand equity through consumers' increased emotional, continuous and normative commitments. Even though apparel brand is very famous, emotional commitment to apparel brand communities cannot be easily increased without transaction-needs satisfaction. Therefore famous fashion brand companies should focus on developing various marketing strategies to increase transaction-needs satisfaction.