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

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

• Journal of Korean Society of Forest Science
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• v.77 no.4
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• pp.429-444
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• 1988

Considering the recent trent toward the development of multiple-use of forest trees, investigations for comprehensive information on these young stands of Hinoki cypress are necessary for rational forest management. From this point of view, 83 sample trees were selected and cut down from 23-ear old stands of Hinoki cypress at Changsung-gun, Chonnam-do. Various stem growth factors of felled trees were measured and canonical correlaton analysis, principal component analysis and factor analysis were applied to investigate the stem growth characteristics, relationships among stem growth factors, and to get potential information and comprehensive information. The results are as follows ; Canonical correlation coefficient between stem volume and quality growth factor was 0.9877. Coefficient of canonical variates showed that DBH among diameter growth factors and height among height growth factors had important effects on stem volume. From the analysis of relationship between stem-volume and canonical variates, which were linearly combined DBH with height as one set, DBH had greater influence on volume growth than height. The 1st-2nd principal components here adopted to fit the effective value of 85% from the pincipal component analysis for 12 stem growth factors. The result showed that the 1st-2nd principal component had cumulative contribution rate of 88.10%. The 1st and the 2nd principal components were interpreted as "size factor" and "shape factor", respectively. From summed proportion of the efficient principal component fur each variate, information of variates except crown diameter, clear length and form height explained more than 87%. Two common factors were set by the eigen value obtained from SMC (squared multiple correlation) of diagonal elements of canonical matrix. There were 2 latent factors, $f_1$ and $f_2$. The former way interpreted as nature of diameter growth system. In inherent phenomenon of 12 growth factor, communalities except clear length and crown diameter had great explanatory poorer of 78.62-98.30%. Eighty three sample trees could he classified into 5 stem types as follows ; medium type within a radius of ${\pm}1$ standard deviation of factor scores, uniformity type in diameter and height growth in the 1st quadrant, slim type in the 2nd quadrant, dwarfish type in the 3rd quadrant, and fall-holed type in the 4 th quadrant.

• Tuberculosis and Respiratory Diseases
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• v.43 no.3
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• pp.367-376
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• 1996

Background : The diagnosis of emphysema during life is based on a combination of clinical, functional, and radiographic findings, but this combination is relatively insensitive and nonspecific. The development of rapid, high-resolution third and fourth generation CT scanners has enabled us to resolve pulmonary parenchymal abnormalities with great precision. We compared the chest HRCT findings to the pulmonary function test and arterial blood gas analysis in pulmonary emphysema patients to test the ability of HRCT to quantify the degree of pulmonary emphysema. Methods : From october 1994 to october 1995, the study group consisted of 20 subjects in whom HRCT of the thorax and pulmonary function studies had been obtained at St. Mary's hospital. The analysis was from scans at preselected anatomic levels and incorporated both lungs. On each HRCT slice the lung parenchyma was assessed for two aspects of emphysema: severity and extent. The five levels were graded and scored separately for the left and right lung giving a total of 10 lung fields. A combination of severity and extent gave the degree of emphysema. We compared the HRCT quantitation of emphysema, pulmonary function tests, ABGA, CBC, and patients characteristics(age, sex, height, weight, smoking amounts etc.) in 20 patients. Results : 1) There was a significant inverse correlation between HRCT scores for emphysema and percentage predicted values of DLco(r = -0.68, p < 0.05), DLco/VA(r = -0.49, p < 0.05), FEV1(r = -0.53, p < 0.05), and FVC(r = -0.47, p < 0.05). 2) There was a significant correlation between the HRCT scores and percentage predicted values of TLC(r = 0.50, p < 0.05), RV(r = 0.64, p < 0.05). 3) There was a significant inverse correlation between the HRCT scores and PaO2(r = -0.48, p < 0.05) and significant correlation with D(A-a)O2(r = -0.48, p < 0.05) but no significant correlation between the HRCT scores and PaCO2. 4) There was no significant correlation between the HRCT scores and age, sex, height, weight, smoking amounts in patients, hemoglobin, hematocrit, and wbc counts. Conclusion : High-Resolution CT provides a useful method for early detection and quantitating emphysema in life and correlates significantly with pulmonary function tests and arterial blood gas analysis.

• The Korean Journal of Nuclear Medicine Technology
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• v.23 no.1
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• pp.35-39
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• 2019

Purpose Hepatitis B virus (hepatitis B virus, HBV) infection is a worldwide major public health problem and it is known as a major cause of chronic hepatitis, liver cirrhosis and liver cancer. And serologic tests of hepatitis B virus is essential for diagnosing and treating these diseases. In addition, with the development of molecular diagnostics, the detection of HBV DNA in serum diagnoses HBV infection and is recognized as an important indicator for the antiviral agent treatment response assessment. We performed HBeAg assay using Immunoradiometric assay (IRMA) and Chemiluminescent Microparticle Immunoassay (CMIA) in hepatitis B patients treated with antiviral agents. The detection rate of HBV DNA in serum was measured and compared by RT-PCR (Real Time - Polymerase Chain Reaction) method Materials and Methods HBeAg serum examination and HBV DNA quantification test were conducted on 270 hepatitis B patients undergoing anti-virus treatment after diagnosis of hepatitis B virus infection. Two serologic tests (IRMA, CMIA) with different detection principles were applied for the HBeAg serum test. Serum HBV DNA was quantitatively measured by real-time polymerase chain reaction (RT-PCR) using the Abbott m2000 System. Results The detection rate of HBeAg was 24.1% (65/270) for IRMA and 82.2% (222/270) for CMIA. Detection rate of serum HBV DNA by real-time RT-PCR is 29.3% (79/270). The measured amount of serum HBV DNA concentration is $4.8{\times}10^7{\pm}1.9{\times}10^8IU/mL$($mean{\pm}SD$). The minimum value is 16IU/mL, the maximum value is $1.0{\times}10^9IU/mL$, and the reference value for quantitative detection limit is 15IU/mL. The detection rates and concentrations of HBV DNA by group according to the results of HBeAg serological (IRMA, CMIA)tests were as follows. 1) Group I (IRMA negative, CMIA positive, N = 169), HBV DNA detection rate of 17.7% (30/169), $6.8{\times}10^5{\pm}1.9{\times}10^6IU/mL$ 2) Group II (IRMA positive, CMIA positive, N = 53), HBV DNA detection rate 62.3% (33/53), $1.1{\times}10^8{\pm}2.8{\times}10^8IU/mL$ 3) Group III (IRMA negative, CMIA negative, N = 36), HBV DNA detection rate 36.1% (13/36), $3.0{\times}10^5{\pm}1.1{\times}10^6IU/mL$ 4) Group IV(IRMA positive, CMIA negative, N = 12), HBV DNA detection rate 25% (3/12), $1.3{\times}10^3{\pm}1.1{\times}10^3IU/mL$ Conclusion HBeAg detection rate according to the serological test showed a large difference. This difference is considered for a number of reasons such as characteristics of the Ab used for assay kit and epitope, HBV of genotype. Detection rate and the concentration of the group-specific HBV DNA classified serologic results confirmed the high detection rate and the concentration in Group II (IRMA-positive, CMIA positive, N = 53).

• Communications of Mathematical Education
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• v.24 no.1
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• pp.235-257
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• 2010

Contemporary belief is that the creative talented can create new knowledge and lead national development, so lots of countries in the world have interest in Gifted Education. As we well know, U.S.A., England, Russia, Germany, Australia, Israel, and Singapore enforce related laws in Gifted Education to offer Gifted Classes, and our government has also created an Improvement Act in January, 2000 and Enforcement Ordinance for Gifted Improvement Act was also announced in April, 2002. Through this initiation Gifted Education can be possible. Enforcement Ordinance was revised in October, 2008. The main purpose of this revision was to expand the opportunity of Gifted Education to students with special education needs. One of these programs is, the opportunity of Gifted Education to be offered to lots of the Gifted by establishing Special Classes at each school. Also, it is important that the quality of Gifted Education should be combined with the expansion of opportunity for the Gifted. Social opinion is that it will be reckless only to expand the opportunity for the Gifted Education, therefore, assessment on the Teaching and Learning Program for the Gifted is indispensible. In this study, 3 middle schools were selected for the Teaching and Learning Programs in mathematics. Each 1st Grade was reviewed and analyzed through comparative tables between Regular and Gifted Education Programs. Also reviewed was the content of what should be taught, and programs were evaluated on assessment standards which were revised and modified from the present teaching and learning programs in mathematics. Below, research issues were set up to assess the formation of content areas and appropriateness for Teaching and Learning Programs for the Gifted in mathematics. A. Is the formation of special class content areas complying with the 7th national curriculum? 1. Which content areas of regular curriculum is applied in this program? 2. Among Enrichment and Selection in Curriculum for the Gifted, which one is applied in this programs? 3. Are the content areas organized and performed properly? B. Are the Programs for the Gifted appropriate? 1. Are the Educational goals of the Programs aligned with that of Gifted Education in mathematics? 2. Does the content of each program reflect characteristics of mathematical Gifted students and express their mathematical talents? 3. Are Teaching and Learning models and methods diverse enough to express their talents? 4. Can the assessment on each program reflect the Learning goals and content, and enhance Gifted students' thinking ability? The conclusions are as follows: First, the best contents to be taught to the mathematical Gifted were found to be the Numeration, Arithmetic, Geometry, Measurement, Probability, Statistics, Letter and Expression. Also, Enrichment area and Selection area within the curriculum for the Gifted were offered in many ways so that their Giftedness could be fully enhanced. Second, the educational goals of Teaching and Learning Programs for the mathematical Gifted students were in accordance with the directions of mathematical education and philosophy. Also, it reflected that their research ability was successful in reaching the educational goals of improving creativity, thinking ability, problem-solving ability, all of which are required in the set curriculum. In order to accomplish the goals, visualization, symbolization, phasing and exploring strategies were used effectively. Many different of lecturing types, cooperative learning, discovery learning were applied to accomplish the Teaching and Learning model goals. For Teaching and Learning activities, various strategies and models were used to express the students' talents. These activities included experiments, exploration, application, estimation, guess, discussion (conjecture and refutation) reconsideration and so on. There were no mention to the students about evaluation and paper exams. While the program activities were being performed, educational goals and assessment methods were reflected, that is, products, performance assessment, and portfolio were mainly used rather than just paper assessment.

• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.35-48
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• 2014

According to the 2013 construction market outlook report, the liquidation of construction companies is expected to continue due to the ongoing residential construction recession. Bankruptcies of construction companies have a greater social impact compared to other industries. However, due to the different nature of the capital structure and debt-to-equity ratio, it is more difficult to forecast construction companies' bankruptcies than that of companies in other industries. The construction industry operates on greater leverage, with high debt-to-equity ratios, and project cash flow focused on the second half. The economic cycle greatly influences construction companies. Therefore, downturns tend to rapidly increase the bankruptcy rates of construction companies. High leverage, coupled with increased bankruptcy rates, could lead to greater burdens on banks providing loans to construction companies. Nevertheless, the bankruptcy prediction model concentrated mainly on financial institutions, with rare construction-specific studies. The bankruptcy prediction model based on corporate finance data has been studied for some time in various ways. However, the model is intended for all companies in general, and it may not be appropriate for forecasting bankruptcies of construction companies, who typically have high liquidity risks. The construction industry is capital-intensive, operates on long timelines with large-scale investment projects, and has comparatively longer payback periods than in other industries. With its unique capital structure, it can be difficult to apply a model used to judge the financial risk of companies in general to those in the construction industry. Diverse studies of bankruptcy forecasting models based on a company's financial statements have been conducted for many years. The subjects of the model, however, were general firms, and the models may not be proper for accurately forecasting companies with disproportionately large liquidity risks, such as construction companies. The construction industry is capital-intensive, requiring significant investments in long-term projects, therefore to realize returns from the investment. The unique capital structure means that the same criteria used for other industries cannot be applied to effectively evaluate financial risk for construction firms. Altman Z-score was first published in 1968, and is commonly used as a bankruptcy forecasting model. It forecasts the likelihood of a company going bankrupt by using a simple formula, classifying the results into three categories, and evaluating the corporate status as dangerous, moderate, or safe. When a company falls into the "dangerous" category, it has a high likelihood of bankruptcy within two years, while those in the "safe" category have a low likelihood of bankruptcy. For companies in the "moderate" category, it is difficult to forecast the risk. Many of the construction firm cases in this study fell in the "moderate" category, which made it difficult to forecast their risk. Along with the development of machine learning using computers, recent studies of corporate bankruptcy forecasting have used this technology. Pattern recognition, a representative application area in machine learning, is applied to forecasting corporate bankruptcy, with patterns analyzed based on a company's financial information, and then judged as to whether the pattern belongs to the bankruptcy risk group or the safe group. The representative machine learning models previously used in bankruptcy forecasting are Artificial Neural Networks, Adaptive Boosting (AdaBoost) and, the Support Vector Machine (SVM). There are also many hybrid studies combining these models. Existing studies using the traditional Z-Score technique or bankruptcy prediction using machine learning focus on companies in non-specific industries. Therefore, the industry-specific characteristics of companies are not considered. In this paper, we confirm that adaptive boosting (AdaBoost) is the most appropriate forecasting model for construction companies by based on company size. We classified construction companies into three groups - large, medium, and small based on the company's capital. We analyzed the predictive ability of AdaBoost for each group of companies. The experimental results showed that AdaBoost has more predictive ability than the other models, especially for the group of large companies with capital of more than 50 billion won.

• Korean Journal of Weed Science
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• v.15 no.4
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• pp.254-261
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• 1995

The nationwide weed survey was conducted in lowland rice fields over whole country of Korea in 1992 in order to determine a change of weed community and to identify a major dominant weed species and/or problem weed. Based on morphological characteristics of weeds, population ratio of broad leaf weed was 42.6%, grasses weed-9.0%, sedges-33.4% and others were 15.0%. Annual weed was 33.4% while perennial weed was 66.6% in terms of life cycle of weeds. Meanwhile, there was different weed occurrence as affected by planting method of the rice plant. In hand transplanted paddy fields predominant weed species was Sagittaria trifolia L., Monochoria vaginalis Presl., and Aneilema japonica Kunth. In machine transplanted rice fields of infant and young rice seedling Eleocharis kuroguwai Ohwi. and S. trifolia L. were more predominant. There was high occurrence of M. vaginalis, Echinochloa crus-galli L., and Leesia japonica Makino in water seeding while E. crus-galli and Cyperus serotinus Rottb. were predominant weed species in dry seeded rice. Monoculture of the rice plant would cause to high occurrence of E. kuroguwai, S. trifolia, M. vaginalis, E. crus-galli, and Sagittaria pygmaea Miq and there was higher population of S. trifolia, S. pygmaea, M. vaginalis, E crus-galli, and E. kuroguwai in double cropping system based on rice culture. In particular, there was high different weed occurrence under different transplanting times. E. kuroguwai, S. trifolia, S. pygmaea, M. vaginalis, and C. serotinus were higher population at the transplanting of 25 May and S. trifolia, E crus-galli, C. serotinus, and M. vaginalis at 10 June and S. pygmaea, E. kuroguwai, M. vaginalis, S. trifolia, and E. crusgalli at 25 June in Korea, respectively. Autumn tillage in terms of tillage time would cause more predominant weed species such as S. trifolia, E. kuroguwai, M. vaginalis, and S. pygmaea while spring tillage was higher population of E. kuroguwai, S. trifolia, E. crusgalli, M. vaginalis, and S. pygmaea. In plain area of paddy field there was higher occurrence of E. kuroguwai, S. trifolia, M. vaginalis, E. crus-galli, and S. pygmaea and in mid-mountainous area S. trifolia, E. kuroguwai, M. vaginalis, E. crus-galli, and Ludwigia prostrate Roxb. while in mountainous area S. trifolia, M. vaginalis, Potamogeton distinctus Ben., E. kuroguwai, and E. crus-galli were. In 1992 the most ten predominant weed species at the rice field of Korea based on summed dominant ratio(SDR) were E. kuroguwai > S. trifolia > E. crus-galli > M. vaginalis > S. pygmaea > C. serotinus > L. prostrate > P. distinctus > A. japonica > Scirpus juncoides Roxb.

• The Korean Journal of Nuclear Medicine
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• v.38 no.4
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• pp.294-299
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• 2004

Purpose: Both human NIS and mutant $D_2R$ transgenes are proposed as reporting system in transplanted cell tracking. Using hepatoma cell lines, we constructed a dual reporter system containing human sodium-iodide symporter (hNIS) and dopamine 2 receptor ($D_2R$) and compared its characteristics. Materials and Methods: The recombinant plasmid ($pIRES-hNIS/D_2R$) was constructed with IRES (internal ribosome entry site) under control of the CMV promoter $pIRES-hNIS/D_2R$ was transfected to human hepatoma SK-Hep1 cell line with lipofectamine. HEP-ND ($SK-Hep1-hNIS/D_2R$) cells stably expressing hNIS and $D_2R$ was established by selection with G418 for two weeks. RT-PCR was performed to investigate the expression of both hNIS and $D_2R$ genes. The expressions of hNIS and $D_2R$ were measured by $^{125}I$ uptake assays and receptor binding assays. Specific binding of $D_2R$ to $[^3H]spiperone$ was verified by Scatchard plot with (+) butaclamol as a specific inhibitor. $K_d\;and\;B_{max}$ values were estimated. The correlation between hNIS and $D_2R$ expression was compared by using each clone. Results: Similar quantities of hNIS and $D_2R$ genes were expressed on HEP-ND as RT-PCR assays. HEP-ND cells showed 30 to 40 fold higher radioiodine uptakes than those of parental SK-Hep1 cells. $^{125}I$ uptake in HEP-ND cells was completely inhibited by $KClO_4$, a NIS inhibitor Specific binding to HEP-ND cells was saturable and the $K_d\;and\;B_{max}$ values for HEP-ND cells were 2.92 nM, 745.25 fmol/mg protein and 2.91nM, 1323 fmole/mg protein in two clones, respectively. The radioiodine uptake by hNIS activity and $D_2R$ binding was highly correlated. Conclusion: We developed a dual positron and gamma imaging reporter system of hNIS and $D_2R$ in a stably transfected cell line. We expect that $D_2R$ and hNIS genes can complement mutually as a nuclear reporting system or that $D_2R$ can be used as reporter gene when hNIS gene were used as a treatment gene.

• Journal of The Korean Society of Grassland and Forage Science
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• v.37 no.4
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• pp.290-300
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• 2017

In vitro fermentation was conducted to figure out alternative fiber sources for horse feed. For the development of value-added products as a horse feed resource, the pomaces from apple, carrot, grape, and citrus were fermented under solid-state conditions in the presence of 60% soybean meal with 40% of each fruit pomace at 60% of moisture content. Lactobacillus plantarum SK3873, Lactobacillus plantarum SK3893, Weissella cibaria SK3880, and Bacillus subtilis SK3889 were isolated from the fermented fruit pomace by inoculation of horse feces. For the growth of Bacillus subtilis, Saccharomyces cerevisiae, and Lactobacillus plantarum, they were inoculated in 3-step order at 0, 12, and 24 h, respectively. The fruit pomace was fermented for 48 h at $35^{\circ}C$. The pH of the apple, carrot, grape, citrus and all mixed pomaces decreased from 5.45~6.25 to 4.40~4.77. Microbial growth was maintained at $10^8{\sim}10^9cfu/g$. After 12 and 24 h incubation, dry matter of carrot pomace were highest at 54.84 and 56.66%, respectively (P<0.05) and that of grape pomace was lower than others during fermentation (P<0.05). Dry matter was generally reduced by about 20%. NDF decreased gradually or maintained after 24 h, indicating the fiber degradation. Ash content tended to decrease during fermentation. After 48 hours fermentation, Bacillus, yeast and Lactobacillus showed an excellent growth by using juice by-products. These results suggest that fermented juice pomace has a potential as horse feedstuff with probiotics to maintain beneficial microflora in horse gut.

• Journal of the Korean Society of Food Science and Nutrition
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• v.41 no.10
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• pp.1346-1355
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• 2012

This study was carried out to investigate the characteristics of black jujube and Zizyphus jujube extracts during lactic acid fermentation. Both extracts were fermented using Lactobacillus fermentum YL-3. As a result, viable cell number rapidly increased until 24 hours, after which it gradually decreased. Before lactic acid fermentation, the $IC_{50}$ of black jujube, which was 0.014 mg/mL, was lower than that of Zizyphus jujube. Further, black jujube showed stronger antioxidant activity (374.21 mg AA eq/g) than Zizyphus jujube. Contents of total polyphenolics in both extracts were 15.46 mg/g and 13.61 mg/g, respectively, whereas contents of total flavonoids were 374.21 ${\mu}g/g$ and 64.25 ${\mu}g/g$. After lactic acid fermentation, there was no significant increase in DPPH or ABTS free radical scavenging activity. Total polyphenolic content of Zizyphus jujube decreased to 12.39 mg/g upon fermentation, whereas flavonoid content significantly increased to 291.58 ${\mu}g/g$. Further, polyphenolic and flavonoid contents of black jujube increased from 15.46 mg/g to 17.46 mg/g and from 374.21 ${\mu}g/g$ to 1,135.29 ${\mu}g/g$, respectively. These results demonstrate that 9-Times Steamed and Dried increased functional components. Especially, lactic acid fermented black jujube showed remarkably high antioxidant activity. These results confirm the potential use of lactic acid fermented black jujube as a valuable resource for the development of functional foods.