• Korean Journal of Soil Science and Fertilizer
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• v.12 no.1
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• pp.15-23
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• 1979

In the first paper of the series the five soil fertility factors were evaluated by means of principal component analysis and varimax method. They are interpreted as representing, 1) skeletal available phosporus status, 2) organnic matter status, 3) salt status 4) base status, and 5) free oxide status. In order to resynthesize such fragmented information for the overall soil fertility evaluation, the method of multiple regression analysis was adopted, using the five factor scores and yield data for Korean paddy soils as independent and dependent variables respectively. As test of linear models with different combinations of independent variables the results of t-test of regression coefficient were revealed that the organic matter status (FII) has no relevance to the yield of paddy and that the free oxides and salt supply has by it self only an insignificant contribution to the yield. The multiple correlation coefficient (R) revealed its multiple regression analysis was as low as 0.43. Introduction of quadratic terms to the linear model bettered the result. Thus multiple correlation coefficient (R) was increased as 0.59. Therefore, a coefficient of determination 0.35 was obtained by a quadratic model with interaction terms among the five fertility constituents. Generally we think that the fertility factor has more contribution to raise the rice yield in paddy and that the failure of yield prediction by fertility factor scores was caused by one of follows; 1) the roughness of the yield inspection, and 2) missextraction of fertility constituents. The second step in this study, assuming that the residuals by multiple regression analysis were due to factors other than soil fertility, we can now proceed to predicting the yield from the field characters with the classified fertility groups by means of Hayashi's theory of quantification No. 1. Such variables as fertility groups (FTYG), water availability (WATER), soil drainage (DRNG), climatic zone (CLIZ), surface soil's stickiness (STCKT), surface soil's dry consistence (DCNST), and surface soil's texture (FTEXT) are taken up as the explanatory variables. The quantification appears reasonable; the well to extremely well in soil drainage, very sticky of surface soil, inefficiency in water availability, coarse texture, and very hard to extremely hard dry consistence in soil are detrimental to the rice yield. The R was as high as 0.90 for the set of variables. But the given explanatory variables in this study were not quite effective in explaining rice yield. The method developed seems to be promising only if properly collected data are available. Conditions that should be satisfied in the yield inspection obtained from common cultivator for the purpose of deriving a prediction equation were put forward.

• Membrane Journal
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• v.9 no.4
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• pp.230-239
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• 1999

Perchlorate ion-selective electrodes in PVC membranes that respond linearly to concentration 106 M were developed by incorporating the quaternary phosphonium salts as a canier. The effects of the chemical structure, the contents of canier, the kind of plasticizer and the membrane thickness on electrode characteristics such as the electrode slope, the linear respone range and the detection limit were studied. With this results, the detectable pH range, selectivity coefficients and AC impedance characteristics were compared and investigated. The perchlorate ion substituents of the quaternary phosphonium salts like tetraoctylphosphonium perchlorate (TOPP) , tetraphenylphosphonium perchlorate(TPPP), and tetrabutylphosphonium perchlorate(TBPP) as a canier were used. The electrode characteristics were better in the ascending order of TBPP < TPPP < TOPP, with the increase of carbon chain length of the alkyl group. Dioctylsebacate(OOS) was best as a plasticizer, the canier contents were better with 11.76 wt% and the optimum membrane thickness was 0.19 mm. Under the above condition, the electrode slope was 56.58 mV/$^P{ClO}_4$,the linear response range was $10^{-1}$\times$10^{-6}$ M, the detection limit was 9.66 x $10^{-7}$ M. The performance of electrode was better than Orion electrode. The electrode potential was stable within the pH range from 3 to 11. The order of the selectivity coefficients for the perchlorate ion was sol < F < Br < 1. With the result of impedance spectrum, it was found that the equivalent circuit for the electrode could be expressed by a series combination of solution resistance, parallel circuit consisting of the double layer capacitance and bulk resistance and Warburg impedance. And solution resistance was almost not appeared and Warburg impedance was highly appeared by diffusion. Then Warburg coefficient was 1.32$\times$$10^74 $\Omega$ $\cdot$ ${cm}^2/s^{1/2}$.

• Knowledge Management Research
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• v.22 no.4
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• pp.71-85
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• 2021

The purpose of this study is to find out which artificial intelligence methodology is most suitable for creating a foreign exchange rate prediction model using the indicators of bond market and interest rate market. KTBs and MSBs, which are representative products of the Korea bond market, are sold on a large scale when a risk aversion occurs, and in such cases, the USD/KRW exchange rate often rises. When USD liquidity problems occur in the onshore Korean market, the KRW Cross-Currency Swap price in the interest rate market falls, then it plays as a signal to buy USD/KRW in the foreign exchange market. Considering that the price and movement of products traded in the bond market and interest rate market directly or indirectly affect the foreign exchange market, it may be regarded that there is a close and complementary relationship among the three markets. There have been studies that reveal the relationship and correlation between the bond market, interest rate market, and foreign exchange market, but many exchange rate prediction studies in the past have mainly focused on studies based on macroeconomic indicators such as GDP, current account surplus/deficit, and inflation while active research to predict the exchange rate of the foreign exchange market using artificial intelligence based on the bond market and interest rate market indicators has not been conducted yet. This study uses the bond market and interest rate market indicator, runs artificial neural network suitable for nonlinear data analysis, logistic regression suitable for linear data analysis, and decision tree suitable for nonlinear & linear data analysis, and proves that the artificial neural network is the most suitable methodology for predicting the foreign exchange rates which are nonlinear and times series data. Beyond revealing the simple correlation between the bond market, interest rate market, and foreign exchange market, capturing the trading signals between the three markets to reveal the active correlation and prove the mutual organic movement is not only to provide foreign exchange market traders with a new trading model but also to be expected to contribute to increasing the efficiency and the knowledge management of the entire financial market.

• Journal of Korean Society of Forest Science
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• v.66 no.1
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• pp.16-36
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• 1984

It is very important in forestry to study the shear strength of weathered granitic soil, because the soil covers 66% of our country, and because the majority of land slides have been occured in the soil. In general, the causes of land slide can be classified both the external and internal factors. The external factors are known as vegetations, geography and climate, but internal factors are known as engineering properties originated from parent rocks and weathering. Soil engineering properties are controlled by the skeleton structure, texture, consistency, cohesion, permeability, water content, mineral components, porosity and density etc. of soils. And the effects of these internal factors on sliding down summarize as resistance, shear strength, against silding of soil mass. Shear strength basically depends upon effective stress, kinds of soils, density (void ratio), water content, the structure and arrangement of soil particles, among the properties. But these elements of shear strength work not all alone, but together. The purpose of this thesis is to clarify the characteristics of shear strength and the related elements, such as water content ($w_o$), void ratio($e_o$), dry density (${\gamma}_d$) and specific gravity ($G_s$), and the interrelationship among related elements in order to decide the dominant element chiefly influencing on shear strength in natural/undisturbed state of weathered granitic soil, in addition to the characteristics of soil hardness of weathered granitic soil and root distribution of Pinus rigida Mill and Pinus rigida ${\times}$ taeda planted in erosion-controlled lands. For the characteristics of shear strength of weathered granitic soil and the related elements of shear strength, three sites were selected from Kwangju district. The outlines of sampling sites in the district were: average specific gravity, 2.63 ~ 2.79; average natural water content, 24.3 ~ 28.3%; average dry density, $1.31{\sim}1.43g/cm^3$, average void ratio, 0.93 ~ 1.001 ; cohesion, $ 0.2{\sim}0.75kg/cm^2$ ; angle of internal friction, $29^{\circ}{\sim}45^{\circ}$ ; soil texture, SL. The shear strength of the soil in different sites was measured by a direct shear apparatus (type B; shear box size, $62.5{\times}20mm$; ${\sigma}$, $1.434kg/cm^2$; speed, 1/100mm/min.). For the related element analyses, water content was moderated through a series of drainage experiments with 4 levels of drainage period, specific gravity was measured by KS F 308, analysis of particle size distribution, by KS F 2302 and soil samples were dried at $110{\pm}5^{\circ}C$ for more than 12 hours in dry oven. Soil hardness represents physical properties, such as particle size distribution, porosity, bulk density and water content of soil, and test of the hardness by soil hardness tester is the simplest approach and totally indicative method to grasp the mechanical properties of soil. It is important to understand the mechanical properties of soil as well as the chemical in order to realize the fundamental phenomena in the growth and the distribution of tree roots. The writer intended to study the correlation between the soil hardness and the distribution of tree roots of Pinus rigida Mill. planted in 1966 and Pinus rigida ${\times}$ taeda in 199 to 1960 in the denuded forest lands with and after several erosion control works. The soil texture of the sites investigated was SL originated from weathered granitic soil. The former is situated at Py$\ddot{o}$ngchangri, Ky$\ddot{o}$m-my$\ddot{o}$n, Kogs$\ddot{o}$ng-gun, Ch$\ddot{o}$llanam-do (3.63 ha; slope, $17^{\circ}{\sim}41^{\circ}$ soil depth, thin or medium; humidity, dry or optimum; height, 5.66/3.73 ~ 7.63 m; D.B.H., 9.7/8.00 ~ 12.00 cm) and the Latter at changun-long Kwangju-shi (3.50 ha; slope, $12^{\circ}{\sim}23^{\circ}$; soil depth, thin; humidity, dry; height, 10.47/7.3 ~ 12.79 m; D.B.H., 16.94/14.3 ~ 19.4 cm).The sampling areas were 24quadrats ($10m{\times}10m$) in the former area and 12 in the latter expanding from summit to foot. Each sampling trees for hardness test and investigation of root distribution were selected by purposive selection and soil profiles of these trees were made at the downward distance of 50 cm from the trees, at each quadrat. Soil layers of the profile were separated by the distance of 10 cm from the surface (layer I, II, ... ...). Soil hardness was measured with Yamanaka soil hardness tester and indicated as indicated soil hardness at the different soil layers. The distribution of tree root number per unit area in different soil depth was investigated, and the relationship between the soil hardness and the number of tree roots was discussed. The results obtained from the experiments are summarized as follows. 1. Analyses of simple relationship between shear strength and elements of shear strength, water content ($w_o$), void ratio ($e_o$), dry density (${\gamma}_d$) and specific gravity ($G_s$). 1) Negative correlation coefficients were recognized between shear strength and water content. and shear strength and void ratio. 2) Positive correlation coefficients were recognized between shear strength and dry density. 3) The correlation coefficients between shear strength and specific gravity were not significant. 2. Analyses of partial and multiple correlation coefficients between shear strength and the related elements: 1) From the analyses of the partial correlation coefficients among water content ($x_1$), void ratio ($x_2$), and dry density ($x_3$), the direct effect of the water content on shear strength was the highest, and effect on shear strength was in order of void ratio and dry density. Similar trend was recognized from the results of multiple correlation coefficient analyses. 2) Multiple linear regression equations derived from two independent variables, water content ($x_1$ and dry density ($x_2$) were found to be ineffective in estimating shear strength ($\hat{Y}$). However, the simple linear regression equations with an independent variable, water content (x) were highly efficient to estimate shear strength ($\hat{Y}$) with relatively high fitness. 3. A relationship between soil hardness and the distribution of root number: 1) The soil hardness increased proportionally to the soil depth. Negative correlation coefficients were recognized between indicated soil hardness and the number of tree roots in both plantations. 2) The majority of tree roots of Pinus rigida Mill and Pinus rigida ${\times}$ taeda planted in erosion-controlled lands distributed at 20 cm deep from the surface. 3) Simple linear regression equations were derived from indicated hardness (x) and the number of tree roots (Y) to estimate root numbers in both plantations.

• Korean Journal of Remote Sensing
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• v.28 no.4
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• pp.409-420
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• 2012

Since the Industrial Revolution, CO2 levels have been increasing with climate change. In this study, Analyze time-series changes in snow cover quantitatively and predict the vanishing point of snow cover statistically using remote sensing. The study area is Mt. Kilimanjaro, Tanzania. 23 image data of Landsat-5 TM and Landsat-7 ETM+, spanning the 27 years from June 1984 to July 2011, were acquired. For this study, first, atmospheric correction was performed on each image using the COST atmospheric correction model. Second, the snow cover area was extracted using the NDSI (Normalized Difference Snow Index) algorithm. Third, the minimum height of snow cover was determined using SRTM DEM. Finally, the vanishing point of snow cover was predicted using the trend line of a linear function. Analysis was divided using a total of 23 images and 17 images during the dry season. Results show that snow cover area decreased by approximately $6.47km^2$ from $9.01km^2$ to $2.54km^2$, equivalent to a 73% reduction. The minimum height of snow cover increased by approximately 290 m, from 4,603 m to 4,893 m. Using the trend line result shows that the snow cover area decreased by approximately $0.342km^2$ in the dry season and $0.421km^2$ overall each year. In contrast, the annual increase in the minimum height of snow cover was approximately 9.848 m in the dry season and 11.251 m overall. Based on this analysis of vanishing point, there will be no snow cover 2020 at 95% confidence interval. This study can be used to monitor global climate change by providing the change in snow cover area and reference data when studying this area or similar areas in future research.

• Korean Journal of Soil Science and Fertilizer
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• v.20 no.1
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• pp.55-61
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• 1987

A series of laboratory experiments were carried out to find the effects of soil organic matter contents, soil temperature, pH values, kinds and amount of nitrogen fertilizers on the denitrification-$N_2O$ gas evolution-. The results obtained were summarized as follows: 1. Denitrification rate, amount of $N_2O$ gas evolution, was influenced the order of organic matter contents>soil temperature>pH values>kinds of N-fertilizer>levels of N-fertilizer. 2. The highest dentrification rate was observed in organic matter content of 3.0%, pH values at 6.0 with application of $KNO_3$ at levels of 20 mgN/100g soil. 3. For the evolution of I mole $N_2O$ gas, averaged carbon consumption was obtained as 0.5 mole in all these experiment condition. However, the highest carbon consumption rate was obtained in organic matter contents for 1.0% with application of $(NH_4)_2SO_4$ at levels of 10 mgN/100g soil (1.06 mole) while lowest carbon consumption rate was obtained in organic matter contents for 3.0% with application of $KNO_3$ at levels of 20 mgN/100g soil (0.13 mole). 4. According to Michaelis-Menten's equation, the V/2 values for evolution of $N_2O$ gas was estimated by progress curve. The results obtained was as 550 ug for $(NH_2)_2CO$ and 1100 ug $N_2O/100g$ soil by application of $KNO_3$ in organic matter contents of 1.0% soil. On the other hand, when the application $(NH_4)_2SO_4$ the V/2 values of $N_2O$ gas was obtained as the amount of 490 ug/100g soil while V/2 values of $N_2O$ gas by application of $KNO_3$ was on the linear line in soil organic matter contents of 3.0%.

• Journal of the Mineralogical Society of Korea
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• v.15 no.4
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• pp.329-344
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• 2002

Mineralogical and chemical characterization of some domestic bentonites, such as quantitative XRD analysis, chemical leaching experiments, pH and CEC determinations, were done without any separation procedures to understand their relationships among mineral composition, characteristics, and cation exchange properties. XRD quantification results based on Rietveld method reveal that the bentonites contain totally more than 25 wt% of impurities, such as zeolites, opal-CT, and feldspars, in addition to montmorillonite ranging 30～75 wt%. Cation exchange properties of the zeolitic bentonites are deeply affected by the content of zeolites identified as clinoptilolite-heulandite series. Clinoptilolite is common in the silicic bentonites with lighter color. and occurs closely in association with opal-CT. Ca is mostly the dominant exchangeable cation, but some zeolitic bentonites have K as a major exchangeable cation, The values of cation exchange capacity (CEC) determined by Methylene Blue method are comparatively low and have roughly a linear relationship with the montmorillonite content of the bentonite, though the correlated data tend to be rather dispersed. Compared to this, the CEC determined by Ammonium Acetate method, i.e.‘Total CEC’, has much higher values (50～115 meq/100 g). The differences between those CEC values are much greater in zeolitic bentonites, which obviously indicates the CEC increase affected by zeolite. Other impurities such as opal-CT and feldspars seem to affect insignificantly on the CEC of bentonites. When dispersed in distilled water, the pH of bentonites roughly tends to increase up to 9.3 with increasing the alkali abundance, especially Na, in exchangeable cation composition. However, some bentonites exhibit lower pH (5～6) so as to regard as ‘acid clay’. This may be due to the presence of $H^{＋}$ in part as an exchangeable cation in the layer site of montmorillonite. All the works of this study ultimately suggest that an assesment of domestic bentonites in grade and quality should be accomplished through the quantitative XRD analysis and the ‘Total CEC’measurement.

• Proceedings of the KOR-BRONCHOESO Conference
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• 1982.05a
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• pp.11.2-12
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• 1982

The major advancement in phonosurgery due to recent development of laryngomicrosurgery enabled more accurate diagnosis and treatment of patient with voice disorders. Among large proportion of voice disordered patients, prominent linear furrow running parallel along the free edge of vocal cord extending from the vocal process to anterior commissure can be seen as well as incomplete closure during phonation. These cases were illustrated and coined as sulcus vocalis by Salvi in 1901, since then other similar paper was reported in Europe and Japan, but has not been reported in Korea. The exact etiology and therapeutic methods of sulcus vocalis has not been elaborated. At Department of Otolaryngology of Yonsei University College of Medicine a series of voice analysis were performed among those 35 patients with sulcus vocalis visited to Vocal Dynamics Laboratory from May, 1981 to March, 1982. Following is the result of clinical statistical investgation and therapeutic modality. 1) The incidance of sulcus vocalis among 290 patients with voice disorder visited to Vocal Dynamics Laboratory was approximately 12%(35 cases). 2) Onset of this voice disorder was most frequent among patient under 10 year-old groups; 19 cases (54%) followed by second decade, third decade groups in decreasing frequency respectably. 3) The etiology of sulcus vocalis was mostly unknown. The sequelae after measle (4 cases) and severe upper respiratory infection (3 cases) and congenital deformity (2 cases) were the possible causes of sulcus vocalis. 4) These patients were involved bilaterally in 25 cases (71%), left side only in 8 cases (23%) and right side only in 2 cases (6%). 5) Almost all patients complained hoarseness and 7 patients were suffering from chronic laryngitis. 6) In aerodynamic analysis, Maximal Phonation Time was decreased in 20 cases (57%), Phonation Quotient was increased in 22 cases (63%) and Mean Air Flow Rate was increased in 23 cases (66%). 7) Among them, 33 cases were analyzed with stroboscopy. The findings were as follows; incomplete glottic closure during phonation in 31 cases (93%), regular vocal cord movement in whole cases, asymmetric cord movement in 4 cases (12%), decreased amplitude in 5 cases (21%) and small mucosal wave in 24 cases (73%). 8) Intracordal Teflon injection in 5 cases and Sulcusectomy in 1 cases were performed as therapeutic management, however, the therapeutic results were not effective except one case with Teflon injection.

• Journal of Soil and Groundwater Environment
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• v.12 no.5
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• pp.19-32
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• 2007

In Korea, there have been various methods of estimating groundwater recharge which generally can be subdivided into three types: baseflow separation method by means of groundwater recession curve, water budget analysis based on lumped conceptual model in watershed, and water table fluctuation method (WTF) by using the data from groundwater monitoring wells. However, groundwater recharge rate shows the spatial-temporal variability due to climatic condition, land use and hydrogeological heterogeneity, so these methods have various limits to deal with these characteristics. To overcome these limitations, we present a new method of estimating recharge based on water balance components from the SWAT-MODFLOW which is an integrated surface-ground water model. Groundwater levels in the interest area close to the stream have dynamics similar to stream flow, whereas levels further upslope respond to precipitation with a delay. As these behaviours are related to the physical process of recharge, it is needed to account for the time delay in aquifer recharge once the water exits the soil profile to represent these features. In SWAT, a single linear reservoir storage module with an exponential decay weighting function is used to compute the recharge from soil to aquifer on a given day. However, this module has some limitations expressing recharge variation when the delay time is too long and transient recharge trend does not match to the groundwater table time series, the multi-reservoir storage routing module which represents more realistic time delay through vadose zone is newly suggested in this study. In this module, the parameter related to the delay time should be optimized by checking the correlation between simulated recharge and observed groundwater levels. The final step of this procedure is to compare simulated groundwater table with observed one as well as to compare simulated watershed runoff with observed one. This method is applied to Mihocheon watershed in Korea for the purpose of testing the procedure of proper estimation of spatio-temporal groundwater recharge distribution. As the newly suggested method of estimating recharge has the advantages of effectiveness of watershed model as well as the accuracy of WTF method, the estimated daily recharge rate would be an advanced quantity reflecting the heterogeneity of hydrogeology, climatic condition, land use as well as physical behaviour of water in soil layers and aquifers.

• Asia pacific journal of information systems
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• v.19 no.2
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• pp.139-155
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• 2009

For the last few decades, many studies have tried to explore and unveil venture companies' success factors and unique features in order to identify the sources of such companies' competitive advantages over their rivals. Such venture companies have shown tendency to give high returns for investors generally making the best use of information technology. For this reason, many venture companies are keen on attracting avid investors' attention. Investors generally make their investment decisions by carefully examining the evaluation criteria of the alternatives. To them, credit rating information provided by international rating agencies, such as Standard and Poor's, Moody's and Fitch is crucial source as to such pivotal concerns as companies stability, growth, and risk status. But these types of information are generated only for the companies issuing corporate bonds, not venture companies. Therefore, this study proposes a method for evaluating venture businesses by presenting our recent empirical results using financial data of Korean venture companies listed on KOSDAQ in Korea exchange. In addition, this paper used multi-class SVM for the prediction of DEA-based efficiency rating for venture businesses, which was derived from our proposed method. Our approach sheds light on ways to locate efficient companies generating high level of profits. Above all, in determining effective ways to evaluate a venture firm's efficiency, it is important to understand the major contributing factors of such efficiency. Therefore, this paper is constructed on the basis of following two ideas to classify which companies are more efficient venture companies: i) making DEA based multi-class rating for sample companies and ii) developing multi-class SVM-based efficiency prediction model for classifying all companies. First, the Data Envelopment Analysis(DEA) is a non-parametric multiple input-output efficiency technique that measures the relative efficiency of decision making units(DMUs) using a linear programming based model. It is non-parametric because it requires no assumption on the shape or parameters of the underlying production function. DEA has been already widely applied for evaluating the relative efficiency of DMUs. Recently, a number of DEA based studies have evaluated the efficiency of various types of companies, such as internet companies and venture companies. It has been also applied to corporate credit ratings. In this study we utilized DEA for sorting venture companies by efficiency based ratings. The Support Vector Machine(SVM), on the other hand, is a popular technique for solving data classification problems. In this paper, we employed SVM to classify the efficiency ratings in IT venture companies according to the results of DEA. The SVM method was first developed by Vapnik (1995). As one of many machine learning techniques, SVM is based on a statistical theory. Thus far, the method has shown good performances especially in generalizing capacity in classification tasks, resulting in numerous applications in many areas of business, SVM is basically the algorithm that finds the maximum margin hyperplane, which is the maximum separation between classes. According to this method, support vectors are the closest to the maximum margin hyperplane. If it is impossible to classify, we can use the kernel function. In the case of nonlinear class boundaries, we can transform the inputs into a high-dimensional feature space, This is the original input space and is mapped into a high-dimensional dot-product space. Many studies applied SVM to the prediction of bankruptcy, the forecast a financial time series, and the problem of estimating credit rating, In this study we employed SVM for developing data mining-based efficiency prediction model. We used the Gaussian radial function as a kernel function of SVM. In multi-class SVM, we adopted one-against-one approach between binary classification method and two all-together methods, proposed by Weston and Watkins(1999) and Crammer and Singer(2000), respectively. In this research, we used corporate information of 154 companies listed on KOSDAQ market in Korea exchange. We obtained companies' financial information of 2005 from the KIS(Korea Information Service, Inc.). Using this data, we made multi-class rating with DEA efficiency and built multi-class prediction model based data mining. Among three manners of multi-classification, the hit ratio of the Weston and Watkins method is the best in the test data set. In multi classification problems as efficiency ratings of venture business, it is very useful for investors to know the class with errors, one class difference, when it is difficult to find out the accurate class in the actual market. So we presented accuracy results within 1-class errors, and the Weston and Watkins method showed 85.7% accuracy in our test samples. We conclude that the DEA based multi-class approach in venture business generates more information than the binary classification problem, notwithstanding its efficiency level. We believe this model can help investors in decision making as it provides a reliably tool to evaluate venture companies in the financial domain. For the future research, we perceive the need to enhance such areas as the variable selection process, the parameter selection of kernel function, the generalization, and the sample size of multi-class.