• Journal of Intelligence and Information Systems
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• v.17 no.3
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• pp.25-41
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• 2011

Recently, support vector machines (SVMs) are being recognized as competitive tools as compared with other data mining techniques for solving pattern recognition or classification decision problems. Furthermore, many researches, in particular, have proved them more powerful than traditional artificial neural networks (ANNs) (Amendolia et al., 2003; Huang et al., 2004, Huang et al., 2005; Tay and Cao, 2001; Min and Lee, 2005; Shin et al., 2005; Kim, 2003).The classification decision, such as a binary or multi-class decision problem, used by any classifier, i.e. data mining techniques is so cost-sensitive particularly in financial classification problems such as the credit ratings that if the credit ratings are misclassified, a terrible economic loss for investors or financial decision makers may happen. Therefore, it is necessary to convert the outputs of the classifier into wellcalibrated posterior probabilities-based multiclass credit ratings according to the bankruptcy probabilities. However, SVMs basically do not provide such probabilities. So it required to use any method to create the probabilities (Platt, 1999; Drish, 2001). This paper applied AdaBoost algorithm-based support vector machines (SVMs) into a bankruptcy prediction as a binary classification problem for the IT companies in Korea and then performed the multi-class credit ratings of the companies by making a normal distribution shape of posterior bankruptcy probabilities from the loss functions extracted from the SVMs. Our proposed approach also showed that their methods can minimize the misclassification problems by adjusting the credit grade interval ranges on condition that each credit grade for credit loan borrowers has its own credit risk, i.e. bankruptcy probability.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.23-45
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• 2020

Big data is creating in a wide variety of fields such as medical care, manufacturing, logistics, sales site, SNS, and the dataset characteristics are also diverse. In order to secure the competitiveness of companies, it is necessary to improve decision-making capacity using a classification algorithm. However, most of them do not have sufficient knowledge on what kind of classification algorithm is appropriate for a specific problem area. In other words, determining which classification algorithm is appropriate depending on the characteristics of the dataset was has been a task that required expertise and effort. This is because the relationship between the characteristics of datasets (called meta-features) and the performance of classification algorithms has not been fully understood. Moreover, there has been little research on meta-features reflecting the characteristics of multi-class. Therefore, the purpose of this study is to empirically analyze whether meta-features of multi-class datasets have a significant effect on the performance of classification algorithms. In this study, meta-features of multi-class datasets were identified into two factors, (the data structure and the data complexity,) and seven representative meta-features were selected. Among those, we included the Herfindahl-Hirschman Index (HHI), originally a market concentration measurement index, in the meta-features to replace IR(Imbalanced Ratio). Also, we developed a new index called Reverse ReLU Silhouette Score into the meta-feature set. Among the UCI Machine Learning Repository data, six representative datasets (Balance Scale, PageBlocks, Car Evaluation, User Knowledge-Modeling, Wine Quality(red), Contraceptive Method Choice) were selected. The class of each dataset was classified by using the classification algorithms (KNN, Logistic Regression, Nave Bayes, Random Forest, and SVM) selected in the study. For each dataset, we applied 10-fold cross validation method. 10% to 100% oversampling method is applied for each fold and meta-features of the dataset is measured. The meta-features selected are HHI, Number of Classes, Number of Features, Entropy, Reverse ReLU Silhouette Score, Nonlinearity of Linear Classifier, Hub Score. F1-score was selected as the dependent variable. As a result, the results of this study showed that the six meta-features including Reverse ReLU Silhouette Score and HHI proposed in this study have a significant effect on the classification performance. (1) The meta-features HHI proposed in this study was significant in the classification performance. (2) The number of variables has a significant effect on the classification performance, unlike the number of classes, but it has a positive effect. (3) The number of classes has a negative effect on the performance of classification. (4) Entropy has a significant effect on the performance of classification. (5) The Reverse ReLU Silhouette Score also significantly affects the classification performance at a significant level of 0.01. (6) The nonlinearity of linear classifiers has a significant negative effect on classification performance. In addition, the results of the analysis by the classification algorithms were also consistent. In the regression analysis by classification algorithm, Naïve Bayes algorithm does not have a significant effect on the number of variables unlike other classification algorithms. This study has two theoretical contributions: (1) two new meta-features (HHI, Reverse ReLU Silhouette score) was proved to be significant. (2) The effects of data characteristics on the performance of classification were investigated using meta-features. The practical contribution points (1) can be utilized in the development of classification algorithm recommendation system according to the characteristics of datasets. (2) Many data scientists are often testing by adjusting the parameters of the algorithm to find the optimal algorithm for the situation because the characteristics of the data are different. In this process, excessive waste of resources occurs due to hardware, cost, time, and manpower. This study is expected to be useful for machine learning, data mining researchers, practitioners, and machine learning-based system developers. The composition of this study consists of introduction, related research, research model, experiment, conclusion and discussion.

• Management & Information Systems Review
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• v.33 no.5
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• pp.185-212
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• 2014

This study investigated the base of marine leisure facilities and studied the future vision for development of marine industry by conducting a systematic analysis on the category of marine leisure products for development of design and specialization of southeast area of Korea. If the age of $20,000 of per capita national income is called 'the age of my car', $20,000 of per capita national income is called 'the age of my boat'. According to the report of UK-based Marine South East, the scale of world's small boat and personal waterborne equipment reached 277 trillion won in 2010 and domestic market scale is expected to be 11 trillion won. Marine leisure facilities are the new growth engine industry that the government should promote as a nation's strategic and core industry, and the government is pushing ahead with promotion of marine industry actively by announcing Marine Leisure Equipment Industry Activation Plan(June 2009, Ministry of Knowledge Economy), Marine Leisure Activation Plan(July 2010, Ministry of Land, Infrastructure and Transport), The 1st General Plan for Marina Port(January 2010, Ministry of Land, Infrastructure and Transport) etc. The purpose of marine design lies in seeking the status of the country and qualitative value in human life through functional, artistic, industrial and cultural development of design elements for all marine activities made around the sea. Related to all activities made in the ocean and cost, marine design is a sphere of design that includes special conditions centering around water. Considering the condition that 3 sides of land are facing the sea, this study systematically analyzed present condition of equipment possessed by each area, type of facilities, operational status, current status of sectoral use of marine leisure facilities and future prospect of marine leisure products that become the basis of value to raise the statue as an advanced marine power in 2010s through development of the qualitative level of the people, establishment of the direction of national strategy, convergence of industry and culture and specialization of area focusing on the actual condition survey of marine leisure facilities. Especially, this study will be predicting the basis of strategy for strengthening marketability and competitiveness by suggesting role and process of design in developing a promising marine leisure product through an actual condition survey of marine leisure products of southeast area.

• Management & Information Systems Review
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• v.36 no.4
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• pp.1-19
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• 2017

These days, the concept of creating shared value is drawn keen attentions to. This interest comes out of the expectation that Creating Shared Value(CSV) can offer an answer to some social issues by creating societal and economic values on the top of the achievements that existing Corporate Social Responsibility(CSR) has made. However, it is difficult to make a clear distinction between the achievements that the activities of CSR and CSV have made. In this regard, developing a methodology to make an actual proof analysis on the accomplishments of CSV and to verify customer's awareness of and attitude towards the CSV is necessarily required. A company needs to gain a competitive advantage in the marketplace as well as resolve a social issue by innovating value chain. The research has verified the cause and effect relationship between the CSV from the point of view of value chain and the purchase intention aroused by its economic, societal and cultural values through the company image and credibility with actual proof analysis and come up with following results. First, a societal and cultural value resulted in giving positive impact on a company's image, which implies that CSV activities can be the thin end of the wedge through which customers have a good image of the company involved in CSV. Second, a societal value makes a positive influence on the credibility of a company. In this regard, CSV should be recognized not just as a thing that generates a cost, but a way to win-win as well as future development. Third and last, the research results show that both company image and credibility influence on purchase intention. Considering that CSV generates a positive evaluation on a company that will ultimately cause continuous profit-making, the company's ultimate goal of activities, it should be approached from the perspective of making a mid-and-long term strategy.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.243-264
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• 2018

Although the worldwide battery market is recently spurring the development of lithium secondary battery, lead acid batteries (rechargeable batteries) which have good-performance and can be reused are consumed in a wide range of industry fields. However, lead-acid batteries have a serious problem in that deterioration of a battery makes progress quickly in the presence of that degradation of only one cell among several cells which is packed in a battery begins. To overcome this problem, previous researches have attempted to identify the mechanism of deterioration of a battery in many ways. However, most of previous researches have used data obtained in a laboratory to analyze the mechanism of deterioration of a battery but not used data obtained in a real world. The usage of real data can increase the feasibility and the applicability of the findings of a research. Therefore, this study aims to develop a model which predicts the battery deterioration using data obtained in real world. To this end, we collected data which presents change of battery state by attaching sensors enabling to monitor the battery condition in real time to dozens of golf carts operated in the real golf field. As a result, total 16,883 samples were obtained. And then, we developed a model which predicts a precursor phenomenon representing deterioration of a battery by analyzing the data collected from the sensors using machine learning techniques. As initial independent variables, we used 1) inbound time of a cart, 2) outbound time of a cart, 3) duration(from outbound time to charge time), 4) charge amount, 5) used amount, 6) charge efficiency, 7) lowest temperature of battery cell 1 to 6, 8) lowest voltage of battery cell 1 to 6, 9) highest voltage of battery cell 1 to 6, 10) voltage of battery cell 1 to 6 at the beginning of operation, 11) voltage of battery cell 1 to 6 at the end of charge, 12) used amount of battery cell 1 to 6 during operation, 13) used amount of battery during operation(Max-Min), 14) duration of battery use, and 15) highest current during operation. Since the values of the independent variables, lowest temperature of battery cell 1 to 6, lowest voltage of battery cell 1 to 6, highest voltage of battery cell 1 to 6, voltage of battery cell 1 to 6 at the beginning of operation, voltage of battery cell 1 to 6 at the end of charge, and used amount of battery cell 1 to 6 during operation are similar to that of each battery cell, we conducted principal component analysis using verimax orthogonal rotation in order to mitigate the multiple collinearity problem. According to the results, we made new variables by averaging the values of independent variables clustered together, and used them as final independent variables instead of origin variables, thereby reducing the dimension. We used decision tree, logistic regression, Bayesian network as algorithms for building prediction models. And also, we built prediction models using the bagging of each of them, the boosting of each of them, and RandomForest. Experimental results show that the prediction model using the bagging of decision tree yields the best accuracy of 89.3923%. This study has some limitations in that the additional variables which affect the deterioration of battery such as weather (temperature, humidity) and driving habits, did not considered, therefore, we would like to consider the them in the future research. However, the battery deterioration prediction model proposed in the present study is expected to enable effective and efficient management of battery used in the real filed by dramatically and to reduce the cost caused by not detecting battery deterioration accordingly.

• Journal of the Korean Institute of Landscape Architecture
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• v.42 no.3
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• pp.1-12
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• 2014

Urban Green space takes charge of the important role for the physical activity and promotion of health to the residents. Therefore, this study is trying to examine the relationship between the various characteristics of green space and green space usage for physical activity and health promotion. A questionnaire survey was conducted to obtain the information about patterns of green space usage and perceived neighborhood environments for the residents living in Changwon-si, Gyeongsangnam-do(n=541). Geographic Information System(GIS) was used to construct spatial data about green space accessibility and physical neighborhood environments. A Multiple Linear Regression model was used to examine the association between the characteristics of green space and physical activity, perceived health status and BMI(Body Mass Index). The study results revealed that the residents' physical activities are positively and directly influenced by the number of available public parks and green spaces in the vicinity(${\leq}200m$). The frequency at which residents witness others exercising nearby or the perceived abundance of low-cost gym facilities also factor as positive influences. The closer to the park, the higher the number of parks and area of green spaces, the more comfortable the walk thereto and the denser the neighboring residential area distribution, the perceived health level was found to be the more positively influenced. Further, it was verified that BMI is correlated with the number of public parks and green spaces within 400 m of the resident's home as well as the safety of walkways, the density of neighboring residential areas, the ratio of road, and the density of crosswalk. The significant multiple regression models between the characteristics of green spaces and physical activities and perceived health level were extracted within the significance level of 10%. This study will contribute to provide better understanding the ways in which green space and neighborhood characteristics are associated with physical activity and health. The result of this research will be available in the landscape architecture plan aimed at improving the use of green space for physical activity and reducing obesity.

• Journal of the Korean Geographical Society
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• v.42 no.4
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• pp.469-487
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• 2007

Grain-Size Trend Analysis is the methodology to identify net sediment transport pathways, based on the assumption that the movement of sediment from the source to deposit leaves the identifiable spatial pattern of mean, sorting, and skewness of grain size. It can easily be implemented with low cost, so it has great potentials to contribute to geomorphological research, whereas it can also be used inadequately without recognition of its limitations. This research aims to compare three established methods of grain-size trend analysis to search for the adequate way of application, and also suggest the research tasks needed in improving this methodology 1D pathway method can corporate the field experience into analyzing the pathway, provide the useful information of depositional environments through X-distribution, and identify the long-term trend effectively. However, it has disadvantage of the dependence on subjective interpretation, and a relatively coarse temporal scale. Gao-Collins's 2D transport vector method has the objective procedure, has the capability to visualize the transport pattern in 2D format, and to identify the pattern at a finer temporal scale, whereas characteristic distance and semiquantitative filtering are controversial. Le Roux's alternative 2D transport vector method has two improvement of Gao-Collins's in that it expands the empirical rules, considers the gradient of each parameters as well as the order, and has the ability to identify the pattern at a finer temporal scale, while the basic concepts are arbitrary and complicated. The application of grain sire trend analysis requires the selection of adequate method and the design of proper sampling scheme, based on the field knowledge of researcher, the temporal scale of sediment transport pattern targeted, and information needed. Besides, the relationship between the depth of sample and representative temporal scale should be systematically investigated in improving this methodology.

• Asia pacific journal of information systems
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• v.24 no.3
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• pp.325-344
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• 2014

Technical support of Window XP ended in March, 8, 2014, and it makes OS(Operating System) users fall in a state of confusion. Sudden decision making of OS upgrade and replacement is not a simple problem. Firms need to change the long term capacity plan in enterprise IS management, but they are pressed for time and cost to complete it. Individuals can not help selecting the second best plan, because the following OSs of Window XP are below expectations in performances, new PC sales as the opportunities of OS upgrade decrease, and the potential risk of OS technical support ending had not announced to OS users at the point of purchase. Microsoft as the OS vendors had not presented precaution or remedy for this confusion. Rather, Microsoft announced that the technical support of the other following OSs of Wndow XP such as Window 7 would ended in two years. This conflict between OS vendor and OS users could not happen in one time, but could recur in recent future. Although studies on the ways of OS user protection policy would be needed to escape from this conflict, few prior studies had conducted this issue. This study had challenge to cautiously investigate in such OS user's reactions as the confirmation with OS user's expectation in the point of purchase, three types of justice perception on the treatment of OS vendor, psychological contract violation, satisfaction and the other betrayal behavioral intention in the case of Window XP technical support ending. By adopting the justice perception on this research, and by empirically validating the impact on OS user's reactions, I could suggest the direction of establishing OS user protection policy of OS vendor. Based on the expectation-confirmation theory, the theory of justice, literatures about psychological contract violation, and studies about consumer betrayal behaviors in the perspective of Herzberg(1968)'s dual factor theory, I developed the research model and hypothesis. Expectation-confirmation theory explain that consumers had expectation on the performance of product in the point of sale, and they could satisfied with their purchase behaviors, when the expectation could have confirmed in the point of consumption. The theory of justice in social exchange argues that treatee could be willing to accept the treatment by treater when the three types of justice as distributive, procedural, and interactional justice could be established in treatment. Literatures about psychological contract violation in human behaviors explains that contracter in a side could have the implied contract (also called 'psychological contract') which the contracter in the other side would sincerely execute the contract, and that they are willing to do vengeance behaviors when their contract had unfairly been broken. When the psychological contract of consumers had been broken, consumers feel distrust with the vendors and are willing to decrease such beneficial attitude and behavior as satisfaction, loyalty and repurchase intention. At the same time, consumers feel betrayal and are willing to increase such retributive attitude and behavior as negative word-of-mouth, complain to the vendors, complain to the third parties for consumer protection. We conducted a scenario survey in order to validate our research model at March, 2013, when is the point of news released firstly and when is the point of one year before the acture Window XP technical support ending. We collected the valid data from 238 voluntary participants who are the OS users but had not yet exposed the news of Window OSs technical support ending schedule. The subject had been allocated into two groups and one of two groups had been exposed this news. The data had been analyzed by the MANOVA and PLS. MANOVA results indicate that the OSs technical support ending could significantly decrease all three types of justice perception. PLS results indicated that it could significantly increase psychological contract violation and that this increased psychological contract violation could significantly reduce the trust and increase the perceived betrayal. Then, it could significantly reduce satisfaction, loyalty, and repurchase intention, and it also could significantly increase negative word-of-month intention, complain to the vendor intention, and complain to the third party intention. All hypothesis had been significantly approved. Consequently, OS users feel that the OSs technical support ending is not natural value added service ending, but the violation of the core OS purchase contract, that it could be the posteriori prohibition of OS user's OS usage right, and that it could induce the psychological contract violation of OS users. This study would contributions to introduce the psychological contract violation of the OS users from the OSs technical support ending in IS field, to introduce three types of justice as the antecedents of psychological contract violation, and to empirically validate the impact of psychological contract violation both on the beneficial and retributive behavioral intentions of OS users. For practice, the results of this study could contribute to make more comprehensive OS user protection policy and consumer relationship management practices of OS vendor.

• Progress in Medical Physics
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• v.26 no.4
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• pp.258-266
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• 2015

The modern radiotherapy technique which delivers a large amount of dose to patients asks to confirm the positions of patients or tumors more accurately by using X-ray projection images of high-definition. However, a rapid increase in patient's exposure and image information for CT image acquisition may be additional burden on the patient. In this study, by introducing structural similarity (SSIM) index that can effectively extract the structural information of the image, we analyze the differences between daily acquired x-ray images of a patient to verify the accuracy of patient positioning. First, for simulating a moving target, the spherical computational phantoms changing the sizes and positions were created to acquire projected images. Differences between the images were automatically detected and analyzed by extracting their SSIM values. In addition, as a clinical test, differences between daily acquired x-ray images of a patient for 12 days were detected in the same way. As a result, we confirmed that the SSIM index was changed in the range of 0.85~1 (0.006~1 when a region of interest (ROI) was applied) as the sizes or positions of the phantom changed. The SSIM was more sensitive to the change of the phantom when the ROI was limited to the phantom itself. In the clinical test, the daily change of patient positions was 0.799~0.853 in SSIM values, those well described differences among images. Therefore, we expect that SSIM index can provide an objective and quantitative technique to verify the patient position using simple x-ray images, instead of time and cost intensive three-dimensional x-ray images.

• Journal of Hospice and Palliative Care
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• v.5 no.2
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• pp.94-100
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• 2002

Purpose : The system to refer terminally ill patients to palliative or hospice care which ultimately give them emotional, psychological, and social support hasn't been fully developed and organized yet in Korea. The controversies concerning the current referral system are being analyzed to present the improvements. Methods : The questionnaires were asked to be filled out by family members of the 76 patients by phone interview, who were referred from the Seoul National University Hospital between April, 2001 to March, 2002. They were referred to the 35 palliative and hospice care-giving institutes and hospitals which were given questionnaires by mail. Results : Of the 76 patient's family members, 47 family members accepted to answer the questionnaire. The first thing that influence to family to determine the referral of patient was solicitation of doctors or nurses (44%). And they were influenced by allowance for the other things such as convenience of patients (32%), convenience of caring family members (24%). In the course of determining of referred institutes, responders had considered at first their dwelling area, and then fame of institutes, the place which patent had wanted to spend last hours or which is suitable for patient's funeral service, and their financial condition. Thirty-eight the 47 responders answered that they had experienced difficulties in referral procedure. The worst among difficulties was unwanted discharge, and followings were lack of information about the referred institutes, concern about patient's suffering, resistance of patient and opposition of other family members, etc. Although they expressed dissatisfaction in referral procedure, most of them answered they had been satisfied with hospice care at referred institute after referral. Merits of referral which responders counted were patient's peace, caring family's comfort and reduced cost in order. Of the 35 referred institutes, 24 institutes' staffs responded mail questionnaires and sent to us in return. Except one responder, the rest approved the referral system and thought that referred patients had been satisfied with their hospice care. And they claimed that systemic support of the government is definitely necessary. The most difficult thing which responders experienced in care of referred patients was lack of information about patients. Besides, there were patient's financial problems, lack of understanding about their institutes of patients or family, and inconvenience of terminal cancer patient's pain control. Conclusion : The development and support of the organized referral system is needed to alleviate the troubles which patients, family members, and palliative or hospice institutes and hospitals have to face through the procedure of the referral.