• Journal of Intelligence and Information Systems
• /
• v.19 no.2
• /
• pp.39-54
• /
• 2013

Recent explosive increase of electronic commerce provides many advantageous purchase opportunities to customers. In this situation, customers who do not have enough knowledge about their purchases, may accept product recommendations. Product recommender systems automatically reflect user's preference and provide recommendation list to the users. Thus, product recommender system in online shopping store has been known as one of the most popular tools for one-to-one marketing. However, recommender systems which do not properly reflect user's preference cause user's disappointment and waste of time. In this study, we propose a novel recommender system which uses data mining and multi-model ensemble techniques to enhance the recommendation performance through reflecting the precise user's preference. The research data is collected from the real-world online shopping store, which deals products from famous art galleries and museums in Korea. The data initially contain 5759 transaction data, but finally remain 3167 transaction data after deletion of null data. In this study, we transform the categorical variables into dummy variables and exclude outlier data. The proposed model consists of two steps. The first step predicts customers who have high likelihood to purchase products in the online shopping store. In this step, we first use logistic regression, decision trees, and artificial neural networks to predict customers who have high likelihood to purchase products in each product group. We perform above data mining techniques using SAS E-Miner software. In this study, we partition datasets into two sets as modeling and validation sets for the logistic regression and decision trees. We also partition datasets into three sets as training, test, and validation sets for the artificial neural network model. The validation dataset is equal for the all experiments. Then we composite the results of each predictor using the multi-model ensemble techniques such as bagging and bumping. Bagging is the abbreviation of "Bootstrap Aggregation" and it composite outputs from several machine learning techniques for raising the performance and stability of prediction or classification. This technique is special form of the averaging method. Bumping is the abbreviation of "Bootstrap Umbrella of Model Parameter," and it only considers the model which has the lowest error value. The results show that bumping outperforms bagging and the other predictors except for "Poster" product group. For the "Poster" product group, artificial neural network model performs better than the other models. In the second step, we use the market basket analysis to extract association rules for co-purchased products. We can extract thirty one association rules according to values of Lift, Support, and Confidence measure. We set the minimum transaction frequency to support associations as 5%, maximum number of items in an association as 4, and minimum confidence for rule generation as 10%. This study also excludes the extracted association rules below 1 of lift value. We finally get fifteen association rules by excluding duplicate rules. Among the fifteen association rules, eleven rules contain association between products in "Office Supplies" product group, one rules include the association between "Office Supplies" and "Fashion" product groups, and other three rules contain association between "Office Supplies" and "Home Decoration" product groups. Finally, the proposed product recommender systems provides list of recommendations to the proper customers. We test the usability of the proposed system by using prototype and real-world transaction and profile data. For this end, we construct the prototype system by using the ASP, Java Script and Microsoft Access. In addition, we survey about user satisfaction for the recommended product list from the proposed system and the randomly selected product lists. The participants for the survey are 173 persons who use MSN Messenger, Daum Caf$\acute{e}$, and P2P services. We evaluate the user satisfaction using five-scale Likert measure. This study also performs "Paired Sample T-test" for the results of the survey. The results show that the proposed model outperforms the random selection model with 1% statistical significance level. It means that the users satisfied the recommended product list significantly. The results also show that the proposed system may be useful in real-world online shopping store.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.33 no.4
• /
• pp.317-324
• /
• 2015

GNSS was firstly proposed for application in weather forecasting in the mid-1980s. It has continued to demonstrate the practical uses in GNSS meteorology, and other relevant researches are currently being conducted. Precipitable Water Vapor (PWV), calculated based on the GNSS signal delays due to the troposphere of the Earth, represents the amount of the water vapor in the atmosphere, and it is therefore widely used in the analysis of various weather phenomena such as monitoring of weather conditions and climate change detection. In this study we calculated the PWV through the meteorological information from an Automatic Weather Station (AWS) as well as GNSS data processing of a Continuously Operating Reference Station (CORS) in order to analyze the heavy snowfall of the Ulsan area in early 2014. Song’s model was adopted for the weighted mean temperature model (T_m), which is the most important parameter in the calculation of PWV. The study period is a total of 56 days (February 2013 and 2014). The average PWV of February 2014 was determined to be 11.29 mm, which is 11.34% lower than that of the heavy snowfall period. The average PWV of February 2013 was determined to be 10.34 mm, which is 8.41% lower than that of not the heavy snowfall period. In addition, certain meteorological factors obtained from AWS were compared as well, resulting in a very low correlation of 0.29 with the saturated vapor pressure calculated using the empirical formula of Magnus. The behavioral pattern of PWV has a tendency to change depending on the precipitation type, specifically, snow or rain. It was identified that the PWV showed a sudden increase and a subsequent rapid drop about 6.5 hours before precipitation. It can be concluded that the pattern analysis of GNSS PWV is an effective method to analyze the precursor phenomenon of precipitation.

• Journal of Food Hygiene and Safety
• /
• v.29 no.2
• /
• pp.123-130
• /
• 2014

A simultaneous determination was developed for 9 aminoglycoside antibiotics (amikacin, apramycin, dihydrostreptomycin, gentamicin, hygromycin B, kanamycin, neomycin, spectinomycin, and streptomycin) in meat by liquid chromatography tandem mass spectrometry (LC-MS/MS). Each parameter was established by multiple reaction monitoring in positive ion mode. The developed method was validated for specificity, linearity, accuracy, and precision based on CODEX validation guideline. Linearity was over 0.98 with calibration curves of the mixed standards. Recovery of 9 aminoglycosides ranged on 60.5~114% for beef, 60.1~112% for pork and 63.8~131% for chicken. The limit of detection (LOD) and limit of quantification (LOQ) were 0.001~0.009 mg/kg and 0.006~0.03 mg/kg, respectively in livestock products including beef, pork and chicken. This study also performed survey of residual aminoglycoside antibiotics for 193 samples of beef, pork and chicken collected from 9 cities in Korea. Aminoglycosides were not found in any of the samples.

• Korean Journal of Soil Science and Fertilizer
• /
• v.40 no.6
• /
• pp.435-441
• /
• 2007

Ground-based optical sensing over the crop canopy provides information on the mass of plant body which reflects the light, as well as crop nitrogen content which is closely related to the greenness of plant leaves. This method has the merits of being non-destructive real-time based, and thus can be conveniently used for decision making on application of nitrogen fertilizers for crops standing in fields. In the present study relationships among leaf nitrogen content of rice canopy, crop growth status, and Normalized Difference Vegetation Index (NDVI) values were investigated. We measured Green normalized difference vegetation index($gNDVI=({\rho}0.80{\mu}m-{\rho}0.55{\mu}m)/({\rho}0.80{\mu}m+{\rho}0.55{\mu}m)$) and NDVI($({\rho}0.80{\mu}m-{\rho}0.68{\mu}m)/({\rho}0.80{\mu}m+{\rho}0.68{\mu}m)$) were measured by using two different active sensors (Greenseeker, NTech Inc. USA). The study was conducted in the years 2005-06 during the rice growing season at the experimental plots of National Institute of Agricultural Science and Technology located at Suwon, Korea. The experiments carried out with randomized complete block design with the application of four levels of nitrogen fertilizers (0, 70, 100, 130kg N/ha) and same amount of phosphorous and potassium content of the fertilizers. gNDVI and rNDVI increased as growth advanced and reached to maximum values at around early August, G(NDVI) were a decrease in values of observed with the crop maturation. gNDVI values and leaf nitrogen content were highly correlated at early July in 2005 and 2006. On the basis of this finding we attempted to estimate the leaf N contents using gNDVI data obtained in 2005 and 2006. The determination coefficients of the linear model by gNDVI in the years 2005 and 2006 were 0.88 and 0.94, respectively. The measured and estimated leaf N contents using gNDVI values showed good agreement ($R^2=0.86^{***}$). Results from this study show that gNDVI values represent a significant positive correlation with leaf N contents and can be used to estimate leaf N before the panicle formation stage. gNDVI appeared to be a very effective parameter to estimate leaf N content the rice canopy.

• The Korean Journal of Nuclear Medicine
• /
• v.39 no.4
• /
• pp.224-230
• /
• 2005

Purpose: The maximal elastance ($E_{max}$) of myocardium has been established as a reliable load-independent contractility index. Recently, we developed a noninvasive method to measure the regional contractility using gated myocardial SPECT and arterial tonometry data. In this study, we measured regional $E_{max}(rE_{max}$ in the patients who underwent coronary artery bypass graft surgery (CABG), and assessed its relationship with other variables. Materials and Methods: 21 patients (M:F=17:4, $58{\pm}12$ y) who underwent CABG were enrolled. $^{201}TI$ rest/dipyridamole stress $^{99m}Tc$-sestamibi gated SPECT were performed before and 3 months after CABG. For 15 myocardial regions, regional time-elastance curve was obtained using the pressure data of tonometry and the volume data of gated SPECT. To investigate the coupling with myocardial function, preoperative regional $E_{max}$ was compared with regional perfusion and systolic thickening. In addition, the correlation between $E_{max}$ and viability was assessed in dysfunctional segments (thickening <20% before CABG). The viability was defined as improvement of postoperative systolic thickening more than 10%. Results: Regional $E_{max}$ was slightly increased after CABG from $2.41{\pm}1.64 (pre)\;to\;2.78{\pm}1.83 (post)$ mmHg/ml. $E_{max}$ had weak correlation with perfusion and thickening (r=0.35, p<0.001). In the regions of preserved perfusion (${\geq}60%$), $E_{max}$ was $2.65{\pm}1.67$, while it was $1.30{\pm}1.24$ in the segments of decreased perfusion. With regard to thickening, $E_{max}$ was $3.01{\pm}1.92$ mmHg/ml for normal regions (thickening ${geq}40%$), $2.40{\pm}1.19$ mmHg/ml for mildly dysfunctional regions (<40% and ${\geq}20%$), and $1.13{\pm}0.89$ mmHg/ml for severely dysfunctional regions (<20%). $E_{max}$ was improved after CABG in both the viable (from $1.27{\pm}1.07\;to\;1.79{\pm}1.48$ mmHg/ml) and non-viable segments (from $0.97 {\pm}0.59\;to\;1.22{\pm}0.71$ mmHg/ml), but there was no correlation between $E_{max}$ and thickening improvements (r=0.007). Conclusions: Preoperative regional $E_{max}$ was relatively concordant with regional perfusion and systolic thickening on gated myocardial SPECT. In dysfunctional but viable segments, $E_{max}$ was improved after CABG, but showed no correlation with thickening improvement. As a load-independent contractility index of dysfunctional myocardial segments, we suggest that the regional $E_{max}$ could be an independent parameter in the assessment of myocardial function.

• Korean Journal of Soil Science and Fertilizer
• /
• v.8 no.1
• /
• pp.1-17
• /
• 1975

Laboratory experiments on the phosphorus adsorption by soil were conducted to evaluate the parameters for determination of phosphorus adsorption capacity of soil, which serve as a basis for establishing the amount of phosphorus required to improve newly reclaimed soil and volcanic ash soil. The calculated Langmuir adsorption maxima varied from 6.2-32.9, 74.7-90.4 and 720-915mg p/100g soil for cultivated soils, non-cultivated soils, and volcanic ash soils respectively. The phosphorus absorption coefficient ranged from 116-179, 161-259 and 1,098-1,205mg p/100g soil for cultivated soils, non-cultivated soils, and volcanic ash soils respectively. The ratio of the phosphorus absorption coefficient to Langmuir adsorption maximum was low in soils of high phosphorus adsorption capacity (1.3-1.5) and high in soils of low phosphorus adsorption capacity (2.2-18.7). Changes in the amount of phosphurus adsorption induced by liming and preaddition of phosphorus were hadly detected by the phosphorus absorption coefficient, which is measured using a test solution with a relatively high phosphorus concentration. The Langmuir adsorption maximum was a more sensitive index of the phosphorus adsorption capacity. The Langmuir adsorption maxima of the non-cultivated soils, which were treated with an amount of calcium hydroxide equivalent to the exchangeable Al and incubated ($25-30^{\circ}C$) for 40 days at field capacity, were lower than the original soils. The change in the adorption maximum on incubation following the liming of soils was insignificant for other soils. The secondary adsorption maximum of soils, which received phosphorus equivalent to the Langmuir adsorption maximum of the limed soils incubated ($25-30^{\circ}C$) for 50 days at held capacity, was 74.5, 5.6 and 23.8% of the primary adsorption maximum for volcanic ash soils, non-cultivated soils, and cultivated soils respectively. The amount of phosphorus adsorbed by soils increased quadratically with the concentration of phosphorus solution added to the soils. The amount of phosphorus adsorbed by 5-g soil samples from 100ml of 100- and 1,000mg p/l solution for the mineral soils and volcanic ash soils respectively was found to be close to the Langmuir adsorption maximum. The amount of the phosphorus adsorbed at these concentrations is defined as a saturation adsorption maximum and proposed as a new parameter for the phosphorus adsorption capacity of the soil. The evaluation of the phosphorus adsorption capacity by the saturation adsorption maximum is regarded as a more practical method in that it obviates the need for the various concentrations used for the determination of the Langmuir adsorption maximum.

• Journal of Hospice and Palliative Care
• /
• v.5 no.2
• /
• pp.111-124
• /
• 2002

Purpose : Although the average life expectancy has increased due to advances in medicine, mortality due to cancer is on an increasing trend. Consequently, the number of terminally ill cancer patients is also on the rise. Predicting the survival period is an important issue in the treatment of terminally ill cancer patients since the choice of treatment would vary significantly by the patents, their families, and physicians according to the expected survival. Therefore, we investigated the prognostic factors for increased mortality risk in terminally ill cancer patients to help treat these patients by predicting the survival period. Methods : We investigated 31 clinical parameters in 157 terminally ill cancer patients admitted to in the Department of Family Medicine, National Health Insurance Corporation Ilsan Hospital between July 1, 2000 and August 31, 2001. We confirmed the patients' survival as of October 31, 2001 based on medical records and personal data. The survival rates and median survival times were estimated by the Kaplan-Meier method and Log-rank test was used to compare the differences between the survival rates according to each clinical parameter. Cox's proportional hazard model was used to determine the most predictive subset from the prognostic factors among many clinical parameters which affect the risk of death. We predicted the mean, median, the first quartile value and third quartile value of the expected lifetimes by Weibull proportional hazard regression model. Results : Out of 157 patients, 79 were male (50.3%). The mean age was $65.1{\pm}13.0$ years in males and was $64.3{\pm}13.7$ years in females. The most prevalent cancer was gastric cancer (36 patients, 22.9%), followed by lung cancer (27, 17.2%), and cervical cancer (20, 12.7%). The survival time decreased with to the following factors; mental change, anorexia, hypotension, poor performance status, leukocytosis, neutrophilia, elevated serum creatinine level, hypoalbuminemia, hyperbilirubinemia, elevated SGPT, prolonged prothrombin time (PT), prolonged activated partial thromboplastin time (aPTT), hyponatremia, and hyperkalemia. Among these factors, poor performance status, neutrophilia, prolonged PT and aPTT were significant prognostic factors of death risk in these patients according to the results of Cox's proportional hazard model. We predicted that the median life expectancy was 3.0 days when all of the above 4 factors were present, $5.7{\sim}8.2$ days when 3 of these 4 factors were present, $11.4{\sim}20.0$ days when 2 of the 4 were present, and $27.9{\sim}40.0$ when 1 of the 4 was present, and 77 days when none of these 4 factors were present. Conclusions : In terminally ill cancer patients, we found that the prognostic factors related to reduced survival time were poor performance status, neutrophilia, prolonged PT and prolonged am. The four prognostic factors enabled the prediction of life expectancy in terminally ill cancer patients.

• Journal of Chest Surgery
• /
• v.39 no.9 s.266
• /
• pp.692-698
• /
• 2006

Background: Owing to the fact that the average life span has increased and the progress in medical science has been made, the number of patients with chronic renal failure (CRF) who have to take hemodialysis (HD) has been going up gradually. Accordingly, it is considered to be as a significant issue to obtain blood vessels which can be used repetitively and supply enough blood flows. Therefore, there have been various kinds of study on an inosculation rate andfactors influencing it following an arteriovenous fistula (AV fistula) and lots of studies are ongoing for the purpose of escalating the inosculation rate. The authors analyzed the effects of short-term result, age, sex, diabetes and hypertension on arteriovenous inosculations in 134 anatomical snuffbox operated subjects among the patients who have taken an AV fistula at this center. Material and Method: Based on 134 patients who underwent an AV fistula at the department of thoracic surgery of this center from July, 2000 to May, 2004, the difference in arteriovenous inosculation rate was compared and analyzed depending or age (discriminated by 65-year-old), sex and the condition of the presence or absence of diabetes and hypertension. Correlation analyses were conducted for each parameter and statistical tests were performed by using SPSS for windows Release 11.0.1, which were determined to be statistically significant if p value was below 0.05. Result: The total number of operations was 169 including 35 of re-operations. The male/female rate was 70 : 64 (52% : 48%). The average age was $56.3{\pm}12.26$ years and there were 33 (24%) old aged patients above 65-year-old; there were 103 (71%) patients with hypertension and 90 (67%) patients with diabetes. Overall arteriovenous inosculation rate was $93{\pm}2.4%,\;91{\pm}2.7%,\;89{\pm}3.0%$ at 6, 12, 24 months, respectively. The arteriovenous inosculation rate of above 65-year-old patient group was $85{\pm}4.8%,\;80{\pm}5.8%,\;80{\pm}5.8%$ and below 64-year-old patient group's was $85{\pm}4.8%,\;80{\pm}5.8%,\;80{\pm}5.8%$ at given time points, respectively, which showed higher inosculation rate in below 64-year-old patient group with a statistical significance (p=0.0034). However, no statistical significance was found between the patients with hypertension and diabetes and the patients with no complication. In addition, there was no statistical significance in inosculation rate between male and female. Conclusion: The arteriovenous inosculation ratewas higher in the treated patient below 64-year-old than in the treated patient above 65-year-old. Thus it is advantageous for increase in long-term inosculation rate to obtain hemodialysis routes at an early age. The conditions of sex and the presence or absence of diabetes and hyper- tension do not make statistically significant effect on the arteriovenous inosculation rate.

• Information Systems Review
• /
• v.16 no.3
• /
• pp.161-177
• /
• 2014

Corporate credit rating assessment consists of complicated processes in which various factors describing a company are taken into consideration. Such assessment is known to be very expensive since domain experts should be employed to assess the ratings. As a result, the data-driven corporate credit rating prediction using statistical and artificial intelligence (AI) techniques has received considerable attention from researchers and practitioners. In particular, statistical methods such as multiple discriminant analysis (MDA) and multinomial logistic regression analysis (MLOGIT), and AI methods including case-based reasoning (CBR), artificial neural network (ANN), and multiclass support vector machine (MSVM) have been applied to corporate credit rating.2) Among them, MSVM has recently become popular because of its robustness and high prediction accuracy. In this study, we propose a novel optimized MSVM model, and appy it to corporate credit rating prediction in order to enhance the accuracy. Our model, named 'GAMSVM (Genetic Algorithm-optimized Multiclass Support Vector Machine),' is designed to simultaneously optimize the kernel parameters and the feature subset selection. Prior studies like Lorena and de Carvalho (2008), and Chatterjee (2013) show that proper kernel parameters may improve the performance of MSVMs. Also, the results from the studies such as Shieh and Yang (2008) and Chatterjee (2013) imply that appropriate feature selection may lead to higher prediction accuracy. Based on these prior studies, we propose to apply GAMSVM to corporate credit rating prediction. As a tool for optimizing the kernel parameters and the feature subset selection, we suggest genetic algorithm (GA). GA is known as an efficient and effective search method that attempts to simulate the biological evolution phenomenon. By applying genetic operations such as selection, crossover, and mutation, it is designed to gradually improve the search results. Especially, mutation operator prevents GA from falling into the local optima, thus we can find the globally optimal or near-optimal solution using it. GA has popularly been applied to search optimal parameters or feature subset selections of AI techniques including MSVM. With these reasons, we also adopt GA as an optimization tool. To empirically validate the usefulness of GAMSVM, we applied it to a real-world case of credit rating in Korea. Our application is in bond rating, which is the most frequently studied area of credit rating for specific debt issues or other financial obligations. The experimental dataset was collected from a large credit rating company in South Korea. It contained 39 financial ratios of 1,295 companies in the manufacturing industry, and their credit ratings. Using various statistical methods including the one-way ANOVA and the stepwise MDA, we selected 14 financial ratios as the candidate independent variables. The dependent variable, i.e. credit rating, was labeled as four classes: 1(A1); 2(A2); 3(A3); 4(B and C). 80 percent of total data for each class was used for training, and remaining 20 percent was used for validation. And, to overcome small sample size, we applied five-fold cross validation to our dataset. In order to examine the competitiveness of the proposed model, we also experimented several comparative models including MDA, MLOGIT, CBR, ANN and MSVM. In case of MSVM, we adopted One-Against-One (OAO) and DAGSVM (Directed Acyclic Graph SVM) approaches because they are known to be the most accurate approaches among various MSVM approaches. GAMSVM was implemented using LIBSVM-an open-source software, and Evolver 5.5-a commercial software enables GA. Other comparative models were experimented using various statistical and AI packages such as SPSS for Windows, Neuroshell, and Microsoft Excel VBA (Visual Basic for Applications). Experimental results showed that the proposed model-GAMSVM-outperformed all the competitive models. In addition, the model was found to use less independent variables, but to show higher accuracy. In our experiments, five variables such as X7 (total debt), X9 (sales per employee), X13 (years after founded), X15 (accumulated earning to total asset), and X39 (the index related to the cash flows from operating activity) were found to be the most important factors in predicting the corporate credit ratings. However, the values of the finally selected kernel parameters were found to be almost same among the data subsets. To examine whether the predictive performance of GAMSVM was significantly greater than those of other models, we used the McNemar test. As a result, we found that GAMSVM was better than MDA, MLOGIT, CBR, and ANN at the 1% significance level, and better than OAO and DAGSVM at the 5% significance level.

• Korean Journal of Weed Science
• /
• v.9 no.1
• /
• pp.56-68
• /
• 1989

aA series of experiments were conducted to investigate the effect of plant growth regulator treatments on the growth and lateral root formation in soybean sprouts in order to establish the effective method of producing root-less or short-rooted soybean sprouts with larger diameter in the hypocotyl. Major results can be summarized as follows. 1. Soybean sprouts showed fairly uniform elongation rate from 3 to g days after imbibition with daily increase of 3.8cm. The speed of elongation of hypocotyl was reduced whereas that of root accelerated 7 days after imbibition. Lateral roots began to emerge fairly evenly from 5 to 9 days after imbibition with a daily increase of 4.4. 2. Auxins(IAA, IBA, NAA, 2,4-D) inhibited hypocotyl elongation and formation of lateral roots and increased hypocotyl diameter without influencing root length and hook diameter at higher concentrations. The dry weight of cotyledon was increased significantly as compared to that of hypocotyl and root. Among the tested auxins, 2, 4-D was the most effective. 3. BA and 4PU-30 significantly reduced elongation of hypocotyl and root and resulted in the biggest diameter of hypocotyl when treated at higher concentrations. The lowest effective concentration of BA to prevent the formation of larval gal roots was 12.5ppm. The formation of lateral roots could be completely prevented by BA and 4PU-30 treatment but kinetin, zeatin, zeatin riboside resulted in many lateral roots and increased thickness of soybean sprouts with little influence. Cotyledon deformation was found in soybean sprouts treated by 4PU-30. 4. 2, 4-D was the most effective for increasing the hypocotyl diameter while 4PU-30 was the most effective for reducing no. of lateral roots. 5. It can be concluded that among the plant growth regulators tested, BA was effective in reducing root length and increasing hypocotyl diameter. BA 12.5 ppm or 15 ppm may thus be the more practical for production of soybean sprouts. 6. ABA showed no significant effect of growth parameter, however ABA 25 ppm inhibited only no of lateral roots with little influence on the growth of seedling. 7. Ethephon inhibited the elongation of hypocotyl and root and increased hypocotyl diameter at higher concentrations. 8. The combined effect of cytokinins and ethephon was very similar to result of BA treatment alone. As the ethephon concentration increased, hypocotyl diameter and dry weight of cotyledon tended to increase.