• Journal of Intelligence and Information Systems
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• v.17 no.1
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• pp.153-169
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• 2011

Today using Internet environment is considered absolutely essential for establishing corporate marketing strategy. Companies have promoted their products and services through various ways of on-line marketing activities such as providing gifts and points to customers in exchange for participating in events, which is based on customers' membership data. Since companies can use these membership data to enhance their marketing efforts through various data analysis, appropriate website membership management may play an important role in increasing the effectiveness of on-line marketing campaign. Despite the growing interests in proper membership management, however, there have been difficulties in identifying inappropriate members who can weaken on-line marketing effectiveness. In on-line environment, customers tend to not reveal themselves clearly compared to off-line market. Customers who have malicious intent are able to create duplicate IDs by using others' names illegally or faking login information during joining membership. Since the duplicate members are likely to intercept gifts and points that should be sent to appropriate customers who deserve them, this can result in ineffective marketing efforts. Considering that the number of website members and its related marketing costs are significantly increasing, it is necessary for companies to find efficient ways to screen and exclude unfavorable troublemakers who are duplicate members. With this motivation, this study proposes an approach for managing duplicate membership based on the social network analysis and verifies its effectiveness using membership data gathered from real websites. A social network is a social structure made up of actors called nodes, which are tied by one or more specific types of interdependency. Social networks represent the relationship between the nodes and show the direction and strength of the relationship. Various analytical techniques have been proposed based on the social relationships, such as centrality analysis, structural holes analysis, structural equivalents analysis, and so on. Component analysis, one of the social network analysis techniques, deals with the sub-networks that form meaningful information in the group connection. We propose a method for managing duplicate memberships using component analysis. The procedure is as follows. First step is to identify membership attributes that will be used for analyzing relationship patterns among memberships. Membership attributes include ID, telephone number, address, posting time, IP address, and so on. Second step is to compose social matrices based on the identified membership attributes and aggregate the values of each social matrix into a combined social matrix. The combined social matrix represents how strong pairs of nodes are connected together. When a pair of nodes is strongly connected, we expect that those nodes are likely to be duplicate memberships. The combined social matrix is transformed into a binary matrix with '0' or '1' of cell values using a relationship criterion that determines whether the membership is duplicate or not. Third step is to conduct a component analysis for the combined social matrix in order to identify component nodes and isolated nodes. Fourth, identify the number of real memberships and calculate the reliability of website membership based on the component analysis results. The proposed procedure was applied to three real websites operated by a pharmaceutical company. The empirical results showed that the proposed method was superior to the traditional database approach using simple address comparison. In conclusion, this study is expected to shed some light on how social network analysis can enhance a reliable on-line marketing performance by efficiently and effectively identifying duplicate memberships of websites.

• Journal of Intelligence and Information Systems
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• v.20 no.4
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• pp.121-139
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• 2014

Predicting corporate failure has been an important topic in accounting and finance. The costs associated with bankruptcy are high, so the accuracy of bankruptcy prediction is greatly important for financial institutions. Lots of researchers have dealt with the topic associated with bankruptcy prediction in the past three decades. The current research attempts to use ensemble models for improving the performance of bankruptcy prediction. Ensemble classification is to combine individually trained classifiers in order to gain more accurate prediction than individual models. Ensemble techniques are shown to be very useful for improving the generalization ability of the classifier. Bagging is the most commonly used methods for constructing ensemble classifiers. In bagging, the different training data subsets are randomly drawn with replacement from the original training dataset. Base classifiers are trained on the different bootstrap samples. Instance selection is to select critical instances while deleting and removing irrelevant and harmful instances from the original set. Instance selection and bagging are quite well known in data mining. However, few studies have dealt with the integration of instance selection and bagging. This study proposes an improved bagging ensemble based on instance selection using genetic algorithms (GA) for improving the performance of SVM. GA is an efficient optimization procedure based on the theory of natural selection and evolution. GA uses the idea of survival of the fittest by progressively accepting better solutions to the problems. GA searches by maintaining a population of solutions from which better solutions are created rather than making incremental changes to a single solution to the problem. The initial solution population is generated randomly and evolves into the next generation by genetic operators such as selection, crossover and mutation. The solutions coded by strings are evaluated by the fitness function. The proposed model consists of two phases: GA based Instance Selection and Instance based Bagging. In the first phase, GA is used to select optimal instance subset that is used as input data of bagging model. In this study, the chromosome is encoded as a form of binary string for the instance subset. In this phase, the population size was set to 100 while maximum number of generations was set to 150. We set the crossover rate and mutation rate to 0.7 and 0.1 respectively. We used the prediction accuracy of model as the fitness function of GA. SVM model is trained on training data set using the selected instance subset. The prediction accuracy of SVM model over test data set is used as fitness value in order to avoid overfitting. In the second phase, we used the optimal instance subset selected in the first phase as input data of bagging model. We used SVM model as base classifier for bagging ensemble. The majority voting scheme was used as a combining method in this study. This study applies the proposed model to the bankruptcy prediction problem using a real data set from Korean companies. The research data used in this study contains 1832 externally non-audited firms which filed for bankruptcy (916 cases) and non-bankruptcy (916 cases). Financial ratios categorized as stability, profitability, growth, activity and cash flow were investigated through literature review and basic statistical methods and we selected 8 financial ratios as the final input variables. We separated the whole data into three subsets as training, test and validation data set. In this study, we compared the proposed model with several comparative models including the simple individual SVM model, the simple bagging model and the instance selection based SVM model. The McNemar tests were used to examine whether the proposed model significantly outperforms the other models. The experimental results show that the proposed model outperforms the other models.

• Journal of the Korean Institute of Landscape Architecture
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• v.39 no.4
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• pp.60-73
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• 2011

Since Jeju Ollegil opened in September 2007 and attracted the sensation of popularity throughout the country, the interest in 'Walking Trails' has increased, and the central ministries and the local governments composite and assign various 'Walking Trails'. Walking trails are not tours on which people go to see one spot and move to another spot by vehicle, but a long linear journey that leads people to see, to feel and to experience a region's landscape and culture while walking on the trail. 'Walking Trails' are efficient routes to discover and to use a former way and to link the various ecological regions' histories and cultural resources, so it is most important to select a route. Although the routes were selected by considering the various planning factors and giving each route a specified theme, some problems like the inconvenience of visitors caused by lack of facilities have occurred. After designation and construction of the trails, they were not properly evaluated by visitors. Therefore, it is the purpose of this study to suggest a better way to construct the trails by surveying visitor satisfaction and by analyzing the impact of planning a route on visitor satisfaction at Bukhansan Dulegil which was completed. For this study, with a questionnaire based on the literature review to identify the important planning factors for selecting a route, a survey was conducted on visitor satisfaction for each section and their intention to revisit and to recommend that trail. Based on the characteristics of each section that was identified in the field research, the trails were classified into five types and satisfaction of each type and each type was analyzed. In addition, analyzing the impact of planning factors on satisfaction, the impact of satisfaction on revisiting and recommending and visitors' perception of the theme, further improvement for better construction of the trail was presented. Satisfaction of sectors with strong natural elements was higher; 'walking comfort' was the highest planning factor affecting satisfaction. In addition, satisfaction was surveyed to have high influence on revisiting and recommending.

• Journal of the Korea Organic Resources Recycling Association
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• v.25 no.1
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• pp.103-110
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• 2017

In Concentrated Animal Feeding Operations(CAFOs), emission of ammonia from stored manure contributes negatively on the wellness of livestock. In CAFOs facilities, indoor aerial ammonia concentration oftentime surpasses the critical level potentially harmful to livestock's immune system. Understandably, numerous researches to control aerial ammonia have been conducted in countries where CAFOs were practiced for many decades. Some innovative technologies, such as scrubber, bio-filter, and additives emerged, as a result. Among them, microbial additives became popular in Korea, due to an easiness of use and affordability. However, microbial additives still have some weaknesses. Their price is still high enough to discourage farmers who run a small scale farm and their effectiveness are still questioned by many users and researchers. In the present study, we found soluble carbohydrates, such as sugar, glucose, and molasses, when supplemented to pig slurry manure, can mitigate ammonia emission. To be more specific, pig manure slurry(120kg), stored in container(200L), was supplemented with sugar at 0.1%(w/w) and was, subsequently, monitored for pH and aerial ammonia for next 10 days. From this experiment, it was found that the sugar supplementation was effective in mitigating the aerial ammonia concentration (33% in average) when monitored daily. Also, the pH of manure slurry was maintained at relatively low level(8.2) in sugar-supplemented manure slurry while it was elevated to 8.5 in untreated slurry. Conclusively, the obtained data suggest that soluble carbohydrate can mitigate ammonia emission by acidifying manure slurry. Additionally, it can be suggested that soluble carbohydrates, such as sugar, glucose, and molasses, can be reasonable choices for animal farmers who have been looking for an alternative choice to replace expensive microbial additives.

• Korean Journal of Poultry Science
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• v.39 no.1
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• pp.63-70
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• 2012

This study was conducted to determine the possible use of Red Ginseng marc as stress inhibiter in thermal stress (temperature humidity index 86) and lipopolysaccharide (LPS) - exposed laying hens by investigating their effects on laying performance, blood biochemical parameters, immunoglobulin concentration and serum superoxide dismutase (SOD) like ability. A total of forty-five 52-wk-old laying hens (ISA Brown) were divided into 3 treatment groups with 5 replicates of 3 birds in each group. NC (negative control, no immune substances), PC (positive control, ${\beta}$-glucan 25 ppm) and RGM (Red Ginseng Marc 3%) were added in feed with respective substance. Egg production in RGM was significantly increased in comparison with NC groups for 8 weeks (P<0.05). On blood biochemical parameters, effects of ambient temperature is definite by showing significant difference in aspartate aminotransferase and others (P<0.05), but RGM both before and after thermal stimulation have no significant difference in comparison with other groups. And for 3 weeks after thermal stimulation, laying performance was also not significantly different among treatments. Immunoglobulin M content and SOD like activities after challenge with LPS were higher in the RGM and PC than NC (P<0.05). In conclusion, although ineffective as inhibiter in thermal stress, dietary supplementation of Red Ginseng marc improved SOD like activity and immune system by regulating immunoglobulin content in laying hens. These findings have laid the foundation for future studies of immunomodulation in laying hens fed Red Ginseng Marc and of evaluation of heat stress inhibitor.

• Progress in Medical Physics
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• v.21 no.1
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• pp.113-119
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• 2010

Software for GafChromic EBT2 film dosimetry was developed in this study. The software provides film calibration functions based on color channels, which are categorized depending on the colors red, green, blue, and gray. Evaluations of the correction effects for light scattering of a flat-bed scanner and thickness differences of the active layer are available. Dosimetric results from EBT2 films can be compared with those from the treatment planning system ECLIPSE or the two-dimensional ionization chamber array MatriXX. Dose verification using EBT2 films is implemented by carrying out the following procedures: file import, noise filtering, background correction and active layer correction, dose calculation, and evaluation. The relative and absolute background corrections are selectively applied. The calibration results and fitting equation for the sensitometric curve are exported to files. After two different types of dose matrixes are aligned through the interpolation of spatial pixel spacing, interactive translation, and rotation, profiles and isodose curves are compared. In addition, the gamma index and gamma histogram are analyzed according to the determined criteria of distance-to-agreement and dose difference. The performance evaluations were achieved by dose verification in the $60^{\circ}$-enhanced dynamic wedged field and intensity-modulated (IM) beams for prostate cancer. All pass ratios for the two types of tests showed more than 99% in the evaluation, and a gamma histogram with 3 mm and 3% criteria was used. The software was developed for use in routine periodic quality assurance and complex IM beam verification. It can also be used as a dedicated radiochromic film software tool for analyzing dose distribution.

• Progress in Medical Physics
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• v.19 no.4
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• pp.231-240
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• 2008

We developed a user-friendly program to independently verify monitor units (MUs) calculated by radiation treatment planning systems (RTPS), as well as to manage beam database in clinic. The off-axis factor, beam hardening effect, inhomogeneity correction, and the different depth correction were incorporated into the program algorithm to improve the accuracy in calculated MUs. A beam database in the program was supposed to use measured data from routine quality assurance (QA) processes for timely update. To enhance user's convenience, a graphic user interface (GUI) was developed by using Visual Basic for Application. In order to evaluate the accuracy of the program for various treatment conditions, the MU comparisons were made for 213 cases of phantom and for 108 cases of 17 patients treated by 3D conformal radiation therapy. The MUs calculated by the program and calculated by the RTPS showed a fair agreement within ${\pm}3%$ for the phantom and ${\pm}5%$ for the patient, except for the cases of extreme inhomogeneity. By using Visual Basic for Application and Microsoft Excel worksheet interface, the program can automatically generate beam data book for clinical reference and the comparison template for the beam data management. The program developed in this study can be used to verify the accuracy of RTPS for various treatment conditions and thus can be used as a tool of routine RTPS QA, as well as independent MU checks. In addition, its beam database management interface can update beam data periodically and thus can be used to monitor multiple beam databases efficiently.

• Research in Plant Disease
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• v.20 no.4
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• pp.235-244
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• 2014

Clubroot and Fusarium wilt of cole crops (Brassica oleracea L.) are destructive diseases which for many years has brought a decline in quality and large losses in yields all over the world. The breeding of resistant cultivars is an effective approach to reduce the use of chemical fungicides and minimize crop losses. This study was conducted to evaluate the resistance of 60 cabbage (B. oleracea var. capitata) and 6 broccoli (B. oleracea var. italica) lines provided by The RDA-Genebank Information Center to clubroot and Fusarium wilt. To investigate resistance to clubroot, seedlings of the genetic resources were inoculated with Plasmodiophora brassicae by drenching the roots with a mixed spore suspension (1 : 1) of two isolates. Of the tested genetic resources, four cabbage lines were moderately resistant and 'K166220' represented the highest resistance to P. brassicae. The others were susceptible to clubroot. On the other hand, to select resistant plants to Fusarium wilt, the genetic resources were inoculated with Fusarium oxysporum f. sp. conglutinans by dipping the roots in spore suspension of the fungus. Among them, 17 cabbage and 5 broccoli lines were resistant, 16 cabbage lines were moderately resistant, and the others were susceptible to Fusarium wilt. Especially, three cabbage ('IT227115', 'K161791', 'K173350') and two broccoli ('IT227100', 'IT227099') lines were highly resistant to the fungus. We suggest that the resistant genetic resources can be used as a basic material for resistant B. oleracea breeding system against clubroot and Fusarium wilt.

• Journal of the Korean Society of Clothing and Textiles
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• v.30 no.12 s.159
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• pp.1697-1707
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• 2006

Relentless advances in information technology are constantly transforming market dynamics of the retail industry. RFID is an emerging innovative technology that can reduce labor costs, improve inventory control and increase sales by effective business processes. Apparel retailers need to recognize the benefits of RFID and identify critical success factors. By focusing on apparel retailers, this study attempts (1) to identify the reality of RFID associated with benefits; and (2) to prospect the implementation of RFID in apparel retailing. We conducted a focus group interview with selected six panels who were experts of retail industry in the United States to obtain data regarding RFID attributes. Content analysis was used to generate related excerpts and classify 31 attributes of RFID benefits from the meaningful 173 responses. For experience of RFID, retailers were familiar with RFID technology and expressed the belief that RFID basically would support an existing retail system for speed to markets. However, retailers addressed the level of experience with RFID technology that they were still in the early adoption stage among few innovative companies. The content analysis identified five dimensions of RFID benefits for apparel retailing: Visibility and Velocity, Revenue Enhancement, Customer Service, Security, and Employee Productivity. This result lends support to the belief that RFID has a significant potential to streamline supply chain management, store operation and customer service for apparel retailing. This study provides intellectual and managerial implications far practitioners and researchers by postulating the effective use of RFID in the apparel retail industry.

• Journal of the Korean Society of Clothing and Textiles
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• v.33 no.12
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• pp.1897-1909
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• 2009

This large-scale research project contributes to the theory development in the importance of clothing to the self and in the way that older persons might age successfully by fulfilling the need for self-actualization by incorporating a primary resource environment, such as clothing into their self-system. This paper presents one research objective from a lager project that explores the correlations among the Proximity of Clothing to Self (PCS), age identity (subjective or perceived age), and self-actualization (the highest level of human needs). A mail survey design was applied to this study. In November 2004, two questionnaires, Clothing: A Resource for Successful Aging? (to measure PCS, age identity, and demographic variables) and Personal Orientation Inventory (to measure self-actualization), were sent to 1,700 older persons in the U.S. and 195 completed usable questionnaires were returned (12% response rate). This research discovered that the age identity of older persons did not relate with PCS except for those 85 years and over. There were negative correlations among subscales of PCS and self-actualization. This result can be interpreted as that an older person who has not met the highest level of needs yet, can use clothing as a facilitator or need satisfier to meet a higher level of Self-Actualization (SA). Correlation analyses also revealed that older persons in the age category of 75 to 84 years were different from those in the category of 65 to 74 years and 85 years and over. This result implies that older persons in this age category are undergoing more psychological transitions than those in other categories. Further research is necessary to explore the relationship of several SA subscales with various clothing variables such as clothing interest, clothing involvement, or clothing satisfaction.