• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.105-129
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• 2020

This study uses corporate data from 2012 to 2018 when K-IFRS was applied in earnest to predict default risks. The data used in the analysis totaled 10,545 rows, consisting of 160 columns including 38 in the statement of financial position, 26 in the statement of comprehensive income, 11 in the statement of cash flows, and 76 in the index of financial ratios. Unlike most previous prior studies used the default event as the basis for learning about default risk, this study calculated default risk using the market capitalization and stock price volatility of each company based on the Merton model. Through this, it was able to solve the problem of data imbalance due to the scarcity of default events, which had been pointed out as the limitation of the existing methodology, and the problem of reflecting the difference in default risk that exists within ordinary companies. Because learning was conducted only by using corporate information available to unlisted companies, default risks of unlisted companies without stock price information can be appropriately derived. Through this, it can provide stable default risk assessment services to unlisted companies that are difficult to determine proper default risk with traditional credit rating models such as small and medium-sized companies and startups. Although there has been an active study of predicting corporate default risks using machine learning recently, model bias issues exist because most studies are making predictions based on a single model. Stable and reliable valuation methodology is required for the calculation of default risk, given that the entity's default risk information is very widely utilized in the market and the sensitivity to the difference in default risk is high. Also, Strict standards are also required for methods of calculation. The credit rating method stipulated by the Financial Services Commission in the Financial Investment Regulations calls for the preparation of evaluation methods, including verification of the adequacy of evaluation methods, in consideration of past statistical data and experiences on credit ratings and changes in future market conditions. This study allowed the reduction of individual models' bias by utilizing stacking ensemble techniques that synthesize various machine learning models. This allows us to capture complex nonlinear relationships between default risk and various corporate information and maximize the advantages of machine learning-based default risk prediction models that take less time to calculate. To calculate forecasts by sub model to be used as input data for the Stacking Ensemble model, training data were divided into seven pieces, and sub-models were trained in a divided set to produce forecasts. To compare the predictive power of the Stacking Ensemble model, Random Forest, MLP, and CNN models were trained with full training data, then the predictive power of each model was verified on the test set. The analysis showed that the Stacking Ensemble model exceeded the predictive power of the Random Forest model, which had the best performance on a single model. Next, to check for statistically significant differences between the Stacking Ensemble model and the forecasts for each individual model, the Pair between the Stacking Ensemble model and each individual model was constructed. Because the results of the Shapiro-wilk normality test also showed that all Pair did not follow normality, Using the nonparametric method wilcoxon rank sum test, we checked whether the two model forecasts that make up the Pair showed statistically significant differences. The analysis showed that the forecasts of the Staging Ensemble model showed statistically significant differences from those of the MLP model and CNN model. In addition, this study can provide a methodology that allows existing credit rating agencies to apply machine learning-based bankruptcy risk prediction methodologies, given that traditional credit rating models can also be reflected as sub-models to calculate the final default probability. Also, the Stacking Ensemble techniques proposed in this study can help design to meet the requirements of the Financial Investment Business Regulations through the combination of various sub-models. We hope that this research will be used as a resource to increase practical use by overcoming and improving the limitations of existing machine learning-based models.

• Journal of Intelligence and Information Systems
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• v.18 no.2
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• pp.29-45
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• 2012

Bond rating is regarded as an important event for measuring financial risk of companies and for determining the investment returns of investors. As a result, it has been a popular research topic for researchers to predict companies' credit ratings by applying statistical and machine learning techniques. The statistical techniques, including multiple regression, multiple discriminant analysis (MDA), logistic models (LOGIT), and probit analysis, have been traditionally used in bond rating. However, one major drawback is that it should be based on strict assumptions. Such strict assumptions include linearity, normality, independence among predictor variables and pre-existing functional forms relating the criterion variablesand the predictor variables. Those strict assumptions of traditional statistics have limited their application to the real world. Machine learning techniques also used in bond rating prediction models include decision trees (DT), neural networks (NN), and Support Vector Machine (SVM). Especially, SVM is recognized as a new and promising classification and regression analysis method. SVM learns a separating hyperplane that can maximize the margin between two categories. SVM is simple enough to be analyzed mathematical, and leads to high performance in practical applications. SVM implements the structuralrisk minimization principle and searches to minimize an upper bound of the generalization error. In addition, the solution of SVM may be a global optimum and thus, overfitting is unlikely to occur with SVM. In addition, SVM does not require too many data sample for training since it builds prediction models by only using some representative sample near the boundaries called support vectors. A number of experimental researches have indicated that SVM has been successfully applied in a variety of pattern recognition fields. However, there are three major drawbacks that can be potential causes for degrading SVM's performance. First, SVM is originally proposed for solving binary-class classification problems. Methods for combining SVMs for multi-class classification such as One-Against-One, One-Against-All have been proposed, but they do not improve the performance in multi-class classification problem as much as SVM for binary-class classification. Second, approximation algorithms (e.g. decomposition methods, sequential minimal optimization algorithm) could be used for effective multi-class computation to reduce computation time, but it could deteriorate classification performance. Third, the difficulty in multi-class prediction problems is in data imbalance problem that can occur when the number of instances in one class greatly outnumbers the number of instances in the other class. Such data sets often cause a default classifier to be built due to skewed boundary and thus the reduction in the classification accuracy of such a classifier. SVM ensemble learning is one of machine learning methods to cope with the above drawbacks. Ensemble learning is a method for improving the performance of classification and prediction algorithms. AdaBoost is one of the widely used ensemble learning techniques. It constructs a composite classifier by sequentially training classifiers while increasing weight on the misclassified observations through iterations. The observations that are incorrectly predicted by previous classifiers are chosen more often than examples that are correctly predicted. Thus Boosting attempts to produce new classifiers that are better able to predict examples for which the current ensemble's performance is poor. In this way, it can reinforce the training of the misclassified observations of the minority class. This paper proposes a multiclass Geometric Mean-based Boosting (MGM-Boost) to resolve multiclass prediction problem. Since MGM-Boost introduces the notion of geometric mean into AdaBoost, it can perform learning process considering the geometric mean-based accuracy and errors of multiclass. This study applies MGM-Boost to the real-world bond rating case for Korean companies to examine the feasibility of MGM-Boost. 10-fold cross validations for threetimes with different random seeds are performed in order to ensure that the comparison among three different classifiers does not happen by chance. For each of 10-fold cross validation, the entire data set is first partitioned into tenequal-sized sets, and then each set is in turn used as the test set while the classifier trains on the other nine sets. That is, cross-validated folds have been tested independently of each algorithm. Through these steps, we have obtained the results for classifiers on each of the 30 experiments. In the comparison of arithmetic mean-based prediction accuracy between individual classifiers, MGM-Boost (52.95%) shows higher prediction accuracy than both AdaBoost (51.69%) and SVM (49.47%). MGM-Boost (28.12%) also shows the higher prediction accuracy than AdaBoost (24.65%) and SVM (15.42%)in terms of geometric mean-based prediction accuracy. T-test is used to examine whether the performance of each classifiers for 30 folds is significantly different. The results indicate that performance of MGM-Boost is significantly different from AdaBoost and SVM classifiers at 1% level. These results mean that MGM-Boost can provide robust and stable solutions to multi-classproblems such as bond rating.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.47-73
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• 2020

KTX rolling stocks are a system consisting of several machines, electrical devices, and components. The maintenance of the rolling stocks requires considerable expertise and experience of maintenance workers. In the event of a rolling stock failure, the knowledge and experience of the maintainer will result in a difference in the quality of the time and work to solve the problem. So, the resulting availability of the vehicle will vary. Although problem solving is generally based on fault manuals, experienced and skilled professionals can quickly diagnose and take actions by applying personal know-how. Since this knowledge exists in a tacit form, it is difficult to pass it on completely to a successor, and there have been studies that have developed a case-based rolling stock expert system to turn it into a data-driven one. Nonetheless, research on the most commonly used KTX rolling stock on the main-line or the development of a system that extracts text meanings and searches for similar cases is still lacking. Therefore, this study proposes an intelligence supporting system that provides an action guide for emerging failures by using the know-how of these rolling stocks maintenance experts as an example of problem solving. For this purpose, the case base was constructed by collecting the rolling stocks failure data generated from 2015 to 2017, and the integrated dictionary was constructed separately through the case base to include the essential terminology and failure codes in consideration of the specialty of the railway rolling stock sector. Based on a deployed case base, a new failure was retrieved from past cases and the top three most similar failure cases were extracted to propose the actual actions of these cases as a diagnostic guide. In this study, various dimensionality reduction measures were applied to calculate similarity by taking into account the meaningful relationship of failure details in order to compensate for the limitations of the method of searching cases by keyword matching in rolling stock failure expert system studies using case-based reasoning in the precedent case-based expert system studies, and their usefulness was verified through experiments. Among the various dimensionality reduction techniques, similar cases were retrieved by applying three algorithms: Non-negative Matrix Factorization(NMF), Latent Semantic Analysis(LSA), and Doc2Vec to extract the characteristics of the failure and measure the cosine distance between the vectors. The precision, recall, and F-measure methods were used to assess the performance of the proposed actions. To compare the performance of dimensionality reduction techniques, the analysis of variance confirmed that the performance differences of the five algorithms were statistically significant, with a comparison between the algorithm that randomly extracts failure cases with identical failure codes and the algorithm that applies cosine similarity directly based on words. In addition, optimal techniques were derived for practical application by verifying differences in performance depending on the number of dimensions for dimensionality reduction. The analysis showed that the performance of the cosine similarity was higher than that of the dimension using Non-negative Matrix Factorization(NMF) and Latent Semantic Analysis(LSA) and the performance of algorithm using Doc2Vec was the highest. Furthermore, in terms of dimensionality reduction techniques, the larger the number of dimensions at the appropriate level, the better the performance was found. Through this study, we confirmed the usefulness of effective methods of extracting characteristics of data and converting unstructured data when applying case-based reasoning based on which most of the attributes are texted in the special field of KTX rolling stock. Text mining is a trend where studies are being conducted for use in many areas, but studies using such text data are still lacking in an environment where there are a number of specialized terms and limited access to data, such as the one we want to use in this study. In this regard, it is significant that the study first presented an intelligent diagnostic system that suggested action by searching for a case by applying text mining techniques to extract the characteristics of the failure to complement keyword-based case searches. It is expected that this will provide implications as basic study for developing diagnostic systems that can be used immediately on the site.

• The Korean Society of Law and Medicine
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• v.17 no.1
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• pp.299-346
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• 2016

There were also various decisions made in medical area in 2015. In the case that an inmate in a sanatorium was injured due to the reason which can be attributable to the sanatorium and the social welfare foundation that operates the sanatorium request treatment of the patient, the court set the standard of fixation of a party in medical contract. In the case that the family of the patient who was declared brain dead required withdrawal of meaningless life sustaining treatment but the hospital rejected and continued the treatment, the court made a decision regarding chargeable fee for such treatment. When it comes to the eye brightening operation which received measure of suspension from the Ministry of Health and Welfare for the first time in February, 2011, because of uncertainty of its safety, the court did not accept the illegality of such operation itself, however, ordered compensation of the whole damage based on the violation of liability for explanation, which is the omission of explanation about the fact that the cost-effectiveness is not sure as it is still in clinical test stage. There were numerous cases that courts actively acknowledged malpractices; in the cases of paresis syndrome after back surgery, quite a few malpractices during the surgery were acknowledged by the court and in the case of nosocomial infection, hospital's negligence to cause such nosocomial infection was acknowledged by the court. There was a decision which acknowledged malpractice by distinguishing the duty of installation of emergency equipment according to the Emergency Medical Service Act and duty of emergency measure in emergency situations, and a decision which acknowledged negligence of a hospital if the hospital did not take appropriate measures, although it was a very rare disease. In connection with the scope of compensation for damage, there were decisions which comply with substantive truth such as; a court applied different labor ability loss rate as the labor ability loss rate decreased after result of reappraisal of physical ability in appeal compared to the one in the first trial, and a court acknowledged lower labor ability loss rate than the result of appraisal of physical ability considering the condition of a patient, etc. In the event of any damage caused by malpractice, in regard to whether there is a limitation on liability in fee charge after such medical malpractice, the court rejected the hospital's claim for setoff saying that if the hospital only continued treatments to cure the patient or prevent aggravation of disease, the hospital cannot charge Medical bills to the patient. In regard to the provision of the Medical Law that prohibit medical advertisement which was not reviewed preliminarily and punish the violation of such, a decision of unconstitutionality was made as it is a precensorship by an administrative agency as the deliberative bodies such as Korean Medical Association, etc. cannot be denied to be considered as administrative bodies. When it comes to the issue whether PRP treatment, which is commonly performed clinically, should be considered as legally determined uninsured treatment, the court made it clear that legally determined uninsured treatment should not be decided by theoretical possibility or actual implementation but should be acknowledged its medical safety and effectiveness and included in medical care or legally determined uninsured treatment. Moreover, court acknowledged the illegality of investigation method or process in the administrative litigation regarding evaluation of suitability of sanatorium, however, denied the compensation liability or restitution of unjust enrichment of the Health Insurance Review & Assessment Service and the National Health Insurance Corporation as the evaluation agents did not cause such violation intentionally or negligently. We hope there will be more decisions which are closer to substantive truth through clear legal principles in respect of variously arisen issues in the future.

• Korean Journal of Culture and Social Issue
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• v.12 no.5_spc
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• pp.45-79
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• 2006

The purpose of this paper was to review the results of the subjective well-being(swb) studies performed by Hahn and coworkers in Korean culture. As the correlates of swb, we dealt with demographic/individual difference variables, intrapersonal variables, interpersonal process variables, and Korean cultural variables. We proposed that the components of swb were consisted of quality of life(cognitive swb) and overall happy feelings about one's own life(emotional swb). It was also assumed that a measure of total swb could be calculated by summated mean of cognitive swb and emotional swb measures. The data of the swb studies were analyzed and interpreted according to the above three measures of swb. The results of a nationwide survey(Hahn, 2004) from age of 19 to 75 years ald(n=2,230) showed significant simple correlation coefficients between the following demographic/individual difference variables and swb: Gender difference in swb was found(total swb r=.08, p<.001; life satisfaction r=.10, p<.001; overall emotional swb r=.05, p<.05). Men were happier than women in terms of all three measures of swb. It was also found that women appeared to experience greater positive and negative emotions. Correlation between age and emotional swb(r=.09, p<.001) was significant, but life satisfaction was not significant(r=.04, n.s). Correlations between economic status and swb were also significant(total swb r =.23, p<.001; life satisfaction r=.15 p<.001; overall emotional swb r=.15, p<.001l). Although existence of father was negatively related to emotional swb(r=-.05, p<.05), the existence of mother was not related to any of swb measures. Similarly existence of brothers was related positively to overall emotional swb, but existence of sisters was not. Though existence of son was not related to swb, daughter contributed negatively to swb(total swb -.12, p<.01; life satisfaction -.09, p<.05; emotional swb r=-.12, p<.01). We assumed that family member-in-Iaw also contributed to swb because the extended dose social networks were important in Korean culture. The results showed that the following family member-in-law variables were related to swb: Parents-in-law(total swb r=.11, p<.01; life satisfaction r=.10, p<.01; emotional swb r=.10, p<.01), father-in-law(total swb r=.11, p<.01; life satisfaction r=.11, p<.01; emotional swb r=.06, n.s). The result suggested that especially father-in-law contributed to swb through financial and social support. Correlations between emotional experiences in everyday life and swb were also presented. The range of correlation coefficients between the positive emotion measures and swb were r=.30~.48(p<.001) when the above two measures obtained at same time. But the range decreased to r=.19~32(p<.001) when the swb measure was obtained 9 month later longitudinally. Intercorrelations between positive emotional experience; and life satisfaction were r=.37~58(p<.001) when two measures were obtained at same time. We also examined the effects of the intrapersonal cognitive responses to the most stressful life event upon swb. The results of nationwide survey(n=1,021) showed that self-disclosure(total swb r=.09, p<.010; life satisfaction r=.10, p<.01; emotional swb r=.07, p<.01), rumination(total swb r=-.17, p<.001), thought avoidance(total swb r=.12, p<.001; life satisfaction r=-.08; emotional swb r=-.12, p<.001) and suppression(total swb r=-.13, p<.001; life satisfaction r=-.08, p<.05: emotional swb r=-.13, p<.001) contributed to swb. It was also suggested that mismatch between self-guide and regulatory focus contributed negatively to emotional swb. It was also found that social comparison motives and fulfillment of the motives contributed to swb. The results of a survey research(n=363 college students) revealed that the higher the general social comparison motive, the lower the swb(total swb r=-.15, P<.01: life satisfaction r=-.17. p<.01; emotional swb r=-.10, p<.05). It was also found that satisfaction level of self-evalution motive contributed positively to swb(total swb r=-.14. p<.01: life satisfaction r=-.12, p<.05; emotional swb r=.15, p<.001). Both of self-improvement motive(r=.13, p<.05) and satisfaction level of self-improvement motive(r=.12, p<.05) contributed positively to emotional swb, respectively. The above results suggested that swb was depended upon the interaction effect of social comparison motive; and level of fulfillment of the motives. We also reported the significant multiple predictors of swb in a sample of age from 60years to 89years olds. The results of multiple regression analysis showed that the significant multiple predictors of swb were past illness(β=.174, p<.001), economic status(β=.418, p<.001), marital satisfaction(β=.0841, p<.001), satisfaction of offsprins(β=.065, p<.01), expectation level of social support from offsprings(β=-.049, p<.001), and negative emotions(β=-.454. p<.001) among 16 social psychological factors. It was also found that swb was an important multiple predictors of physical health. This finding was replicated in a longitudinal study. Both of positive and negative emotional experiences were significant multiple predictors of physical health one year later. The results of the discriminant analysis showed both of total swb and positive emotional experiences contributed to discriminate the happy and healthy olds from unhappy and unhealthy olds. We paper also examined the effects of the nonnative social behaviors upon swb in Korean culture. The main hypotheses of the study(Hahn, 2006, in press) was that the important nonnative behaviors would influence on swb through both of the mediation processes of adjustment to social relationships and psychological stress. The survey data were collected from 2,129 adults age of 19 to 75, from 7 regional areas in Korea. The results of the study revealed that almost all of correlation coefficients between 15 normative social behaviors and the above three criteria w-ere significant. The fitness test results of the covariance structural equation model showed that all of the fitness indices were satisfactory (GFI=.974, AGFI=.909, NNFI=.922, NFI=.973, CFI=.974. RMR=.049, RMSEA=.073). The results of the analysis revealed that the following five path coeffi6ents from behaviors to social adjustment were significant; behavior tor family and family members(t=5.87, p<.001), courteous behavior(t=4.39, p<.001), faithful behavior (t=2.15. p<.05). collectivistic behavior(t=8.31, p<.001). Seven path coefficients from the normative behaviors to psychological stress were significant; behavior for family and family members (t=-4.63, p<.001), faithful behavior(t=-3.86, p<.001). suppression of emotional expression(t=3.99, p<.001), trustworthy and dependable behavior(t=-2.21, p<.05), collectivistic behavior(t=3.72, p<.001), effortful and diligent behavior(t=2.94, p<.001), husbandry and saving behavior(t=3.40, p<.001). The above results suggested that four normative behaviors among seven behaviors contributed negatively to psychological stress in current Korean society. The results abo confirmed the hypothesized paths from social adjustment (t=10.40, p<.001) to swb and from psychological stress(t=-19.74, p<.001) to swb. The important results of the study were discussed in terms of the Confucian traditions and recent social changes in Korean culture. Finally limitations of this review paper were discussed and the suggestions for the future study were also proposed.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.34 no.5
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• pp.536-544
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• 2001

Three harmful algal bloom species with similar morphology, Cochlodinium polykrikoides, Gyodinium impudicum and Gymodinium catenatum have damaged to aquatic animals or human health by either making massive blooms or intoxication of shellfishes in a food chain. Eco-physiological and hydrodynamic studies on the harmful algae offer useful informations in the understanding their bloom mechanism by giving promising data for the prediction and modelling of harmful algal blooms event. Thus, we studied the abundance of these species in the coastal area of South Sea of Korea and their effects of temperature, salinity, irradiance and nutrient on the growth for the isolates. The timing for initial appearance of the three species around the coastal area of Namhaedo, Narodo and Wando was between Bate July and late August in 1999 when water temperature ranged from $22.8^{\circ}C\;to\;26.5^{\circ}C$ Vegetative cells of C. polykrikoides and G. impudicum were abundant until late September when water temperature had been dropped to less than $23^{\circ}C$. By contrast, vegetative cell of G. catenatum disappeared before early September, showing shorter period of abundance than the other two species in the South Sea. Both G. impudicum and G. catenatum revealed comparatively low density with a maximal cell density of 3,460 cells/L and 440 cells/L, respectively without making any bloom, while C. polykrikoides made massive blooms with a maximal cell density more than $40\times10^6$cells/L, The three species showed a better growth at the relatively higher water temperature ranging from 22 to $28^{\circ}C$ with their maximal growth rate at $25^{\circ}C$ in culture, which almost corresponded with the water temperature during the outbreak of C. polykrikoides in the coastal area of South Sea. Also, they all showed a relatively higher growth at the salinity from 30 to $35\%$. Specially, G. impudicum showed the euryhalic characteristics among the species, On the other hand, growth rate of G. catenatum decreased sharply with the increase of water temperature at the experimental ranges more than $35\%$. The higher of light intensities showed the better growth rates for the three species, Moreover, C. polykrikoides and G. impudirum continued their exponential growth even at 7,500 lux, the highest level of light intensity in the experiment, Therefore, It is assumed that C. polykrikoides has a physiological capability to adapt and utilize higher irradiance resulting in the higher growth rate without any photo inhibition response at the sea surface where there is usually strong irradiance during its blooming season. Although C. poiykikoides and G. impudicum continued their linear growth with the increase of nitrate ($NO_3^-$) and ammonium ($NH_4^-$) concentrations at less than the $40{\mu}M$, they didn't show any significant differences in growth rates with the increase of nitrate and ammonium concentrations at more than $40{\mu}M$, signifying that the nitrogen critical point for the growth of the two species stands between 13.5 and $40{\mu}M$. Also, even though both of the two species continued their linear growth with the increase of phosphate ($PO_4^{2-}$) concentrations at less than the $4.05{\mu}M$, there were no any significant differences in growth rates with the increase of phosphate concentrations at more than $4.05{\mu}M$, signifying that the phosphate critical point for the growth of the two species stands between 1.35 and $4.05{\mu}M$. On the other hand, C. polykrikoides has made blooms at the oligotrophic environment near Narodo and Namhaedo where the concentration of DIN and DIP are less than 1.2 and $0.3{\mu}M$, respectively. We attributed this phenomenon to its own ecological characteristics of diel vertical migration through which C. polykrikoides could uptake enough nutrients from the deep sea water near bottom during the night time irrespective of the lower nutrient pools in the surface water.

• Korean Journal of Soil Science and Fertilizer
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• v.43 no.3
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• pp.363-373
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• 2010

"Curve number" (CN) indicates the runoff potential of an area. The US Soil Conservation Service (SCS)'s CN method is a simple, widely used, and efficient method for estimating the runoff from a rainfall event in a particular area, especially in ungauged basins. The use of soil maps requested from end-users was dominant up to about 80% of total use for estimating CN based rainfall-runoff. This study introduce the use of soil maps with respect to hydrologic and watershed management focused on hydrologic soil group and a case study resulted in assessing effective rainfall and runoff hydrograph based on SCS-CN method in a small watershed. The ratio of distribution areas for hydrologic soil group based on detailed soil map (1:25,000) of Korea were 42.2% (A), 29.4% (B), 18.5% (C), and 9.9% (D) for HSG 1995, and 35.1% (A), 15.7% (B), 5.5% (C), and 43.7% (D) for HSG 2006, respectively. The ratio of D group in HSG 2006 accounted for 43.7% of the total and 34.1% reclassified from A, B, and C groups of HSG 1995. Similarity between HSG 1995 and 2006 was about 55%. Our study area was located in Sosu-myeon, Goesan-gun including an approx. 44 $km^2$-catchment, Chungchungbuk-do. We used a digital elevation model (DEM) to delineate the catchments. The soils were classified into 4 hydrologic soil groups on the basis of measured infiltration rate and a model of the representative soils of the study area reported by Jung et al. 2006. Digital soil maps (1:5,000) were used for classifying hydrologic soil groups on the basis of soil series unit. Using high resolution satellite images, we delineated the boundary of each field or other parcel on computer screen, then surveyed the land use and cover in each. We calculated CN for each and used those data and a land use and cover map and a hydrologic soil map to estimate runoff. CN values, which are ranged from 0 (no runoff) to 100 (all precipitation runs off), of the catchment were 73 by HSG 1995 and 79 by HSG 2006, respectively. Each runoff response, peak runoff and time-to-peak, was examined using the SCS triangular synthetic unit hydrograph, and the results of HSG 2006 showed better agreement with the field observed data than those with use of HSG 1995.

• The Southeast Asian review
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• v.27 no.2
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• pp.37-76
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• 2017

$Nguy{\tilde{\hat{e}}}n$ Cư Trinh has two faces in the history of territorial expansion of Vietnam into the Mekong delta. One is his heroic contribution to the $Nguy{\tilde{\hat{e}}}n$ family gaining control over the large part of the Mekong delta. The other is his role to make the eyes of readers of Vietnamese history be fixed only to the present territory of Vietnam. To the readers, $Nguy{\tilde{\hat{e}}}n$ Cư Trinh's achievement of territorial expansion was the final stage of the nam $ti{\acute{\hat{e}}n$ of Vietnam. In fact, however, his achievement was partial. This study pays attention to the King $V{\tilde{o}}$ instead of $Nguy{\tilde{\hat{e}}}n$ Cư Trinh in the history of the territorial expansion in the Mekong delta. King's goal was more ambitious. And the ambition was propelled by his dream to build a new world, and its order, in which his new capital, $Ph{\acute{u}}$ $Xu{\hat{a}}n$ was to be the center with his status as an emperor. To improve my assertion, three elements were examined in this article. First is the nature of $V{\tilde{o}}$ Vương's new kingship. Second is the preparation and the background of the military operation in the Mekong Delta. The nature of the new territory is the third element of the discussion. In 1744, six years after this ascending to the throne, $V{\tilde{o}}$ Vương declared he was a king. Author points out this event as the departure of the southern kingdom from the traditional dynasties based on the Red River delta. Besides, the government system, northern custom and way of dressings were abandoned and new southern modes were adopted. $V{\tilde{o}}$ Vương had enough tributary kingdoms such as Cambodia, Champa, Thủy $X{\tilde{a}}$, Hoả $X{\tilde{a}}$, Vạn Tượng, and Nam Chưởng. Compared with the $L{\hat{e}}$ empire, the number of the tributary kingdoms was higher and the number was equivalent to that of the Đại Nam empire of the 19th century. In reality, author claims, the King $V{\tilde{o}}^{\prime}s$ real intention was to become an emperor. Though he failed in using the title of emperor, he distinguished himself by claiming himself as the Heaven King, $Thi{\hat{e}}n$ Vương. Cambodian king's attack on the thousands of Cham ethnics in Cambodian territory was an enough reason to the King $V{\tilde{o}}^{\prime}s$ military intervention. He considered these Cham men and women as his amicable subjects, and he saw them a branch of the Cham communities in his realm. He declared war against Cambodia in 1750. At the same time he sent a lengthy letter to the Siamese king claiming that the Cambodia was his exclusive tributary kingdom. Before he launched a fatal strike on the Mekong delta which had been the southern part of Cambodia, $V{\tilde{o}}$ Vương renovated his capital $Ph{\acute{u}}$ $Xu{\hat{a}}n$ to the level of the new center of power equivalent to that of empire for his sake. Inflation, famine, economic distortion were also the features of this time. But this study pays attention more to the active policy of the King $V{\tilde{o}}$ as an empire builder than to the economic situation that has been told as the main reason for King $V{\tilde{o}}^{\prime}s$ annexation of the large part of the Mekong delta. From the year of 1754, by the initiative of $Nguy{\tilde{\hat{e}}}n$ Cư Trinh, almost whole region of the Mekong delta within the current border line was incorporated into the territory of $V{\tilde{o}}$ Vương within three years, though the intention of the king was to extend his land to the right side of the Mekong Basin beyond the current border such as Kampong Cham, Prey Vieng, and Svai Rieng. The main reason was $V{\tilde{o}}$ Vương's need to expand his territory to be matched with that of his potential empire with the large number of the tributary kingdoms. King $V{\tilde{o}}^{\prime}s$ strategy was the variation of 'silkworm nibbling' and 'to strike barbarians by barbarians.' He ate the land of Lower Cambodia, the region of the Mekong delta step by step as silkworm nibbles mulberry leave(general meaning of $t{\acute{a}}m$ thực), but his final goal was to eat all(another meaning of $t{\acute{a}}m$ thực) the part of the Mekong delta including the three provinces of Cambodia mentioned above. He used Cham to strike Cambodian in the process of getting land from Long An area to $Ch{\hat{a}}u$ Đốc. This is a faithful application of the Dĩ Man $C{\hat{o}}ng$ Man (to strike barbarians by barbarians). In addition he used Chinese refugees led by the Mạc family or their quasi kingdom to gain land in the region of $H{\grave{a}}$ $Ti{\hat{e}}n$ and its environs from the hand of Cambodian king. This is another application of Dĩ Man $C{\hat{o}}ng$ Man. In sum, author claims a new way of looking at the origin of the imperial world order which emerged during the first half of the 19th century. It was not the result of the long history of Đại Việt empires based on the Red River delta, but the succession of the King $V{\tilde{o}}^{\prime}s$ new world based on $Ph{\acute{u}}$ $Xu{\hat{a}}n$. The same ways of Dĩ Man $C{\hat{o}}ng$ Man and $T{\acute{a}}m$ Thực Chi $K{\acute{\hat{e}}}$ were still used by $V{\tilde{o}}^{\prime}s$ descendents. His grandson Gia Long used man such as Thai, Khmer, Lao, Chinese, and European to win another man the '$T{\hat{a}}y$ Sơn bandits' that included many of Chinese pirates, Cham, and other mountain peoples. His great grand son Minh Mạng constructed a splendid empire. At the same time, however, Minh Mạng kept expanding the size of his empire by eating all the part of Cambodia and Cham territories.