• Journal of the Korean Home Economics Association
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• v.40 no.12
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• pp.49-61
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• 2002

The purpose of this study was to investigate the effect of clothing involvement on the perceived risk in internet shopping and store selection criteria. The subjects used for the study were 210 male and 338 female college students. The clothing involvement consisted of pleasure, symbolism, and selection difficulty factors. The perceived risk consisted of size/defect risk, social psychological risk, privacy risk, delivery risk, and price risk. The store selection criteria had security/service, entertainment/variety, price/convenience factors. The results showed that consumers were segmented by four groups based on clothing involvement factors: clothing pleasure group, symbolism group, confidence group, and low clothing involvement group. The four segmented groups differed in regard to the perceived risk, store selection criteria, and demographics. For example, clothing pleasure group perceived the size/defect risk and social psychological risk higher than did the other groups. Also, the clothing pleasure group considered entertainment/variety more important and had younger female consumers.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.23
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• pp.10539-10542
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• 2015

A method to predict the risk of lung cancer is proposed, based on two feature selection algorithms: Fisher and ReliefF, and BP Neural Networks. An appropriate quantity of risk factors was chosen for lung cancer risk prediction. The process featured two steps, firstly choosing the risk factors by combining two feature selection algorithms, then providing the predictive value by neural network. Based on the method framework, an algorithm LCRP (lung cancer risk prediction) is presented, to reduce the amount of risk factors collected in practical applications. The proposed method is suitable for health monitoring and self-testing. Experiments showed it can actually provide satisfactory accuracy under low dimensions of risk factors.

• Journal of Information Technology and Architecture
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• v.9 no.1
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• pp.21-31
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• 2012

We focus on the issues of the non-linear return/risk relationship of IT investment and the balance between return and risk of IT portfolio. We develop an IT project selection model by integrating DEA models with Markowitz portfolio selection theory. The project data collected from a Fortune 100 company are used to illustrate the implementation of the model. In addition, computational experiments are conducted to demonstrate the validity of the proposed model.

• Journal of Distribution Science
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• v.20 no.3
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• pp.1-11
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• 2022

Purpose: This study aims at understanding the impacts of three omnichannel attributes (channel transparency, channel uniformity, channel convenience) and four customer perceptions (perceived innovativeness, perceived personalization, perceived risk, perceived credibility) on customer experience and channel selection decision. Research design and methodology: A quantitative online survey with 356 shoppers was executed. The partial least squares linear structural model (PLS-SEM) and Smart PLS were adopted to analyze the collected data and test the proposed hypotheses. Results: The research findings indicate four dominant results: (i) The customers' channel selection is directly determined by customer experience; perceived innovativeness; perceived personalization; perceived risk; and perceived credibility; and (ii) among these, the perceived risk shows negative impact on the customer's experience and customers' channel selection whereas others reveal the positive status; (iii) The customer experience represents the most decisive impact on the channel selection, then perceived personalization, perceived credibility, perceived innovativeness, and perceived risk. (iv) Three proposed channel attributes (transparency, uniformity, convenience) significantly influence the overall customer experience. Conclusions: This research adds to the body of knowledge in omnichannel retailing, customer experience, and customer channel selection. Furthermore, this research provides omnichannel retailers with practical implications for improving customer channel selection.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.05a
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• pp.323-325
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• 2021

In this article, we have improved the prediction of hypertension detection using the feature selection method for the Korean national health data named by the KNHANES database. The study identified a variety of risk factors associated with chronic hypertension. The paper is divided into two modules. The first of these is a data pre-processing step that uses a factor analysis (FA) based feature selection method from the dataset. The next module applies a predictive analysis step to detect and predict hypertension risk prediction. In this study, we compare the mean standard error (MSE), F1-score, and area under the ROC curve (AUC) for each classification model. The test results show that the proposed FIFA-OE-NB algorithm has an MSE, F1-score, and AUC outcomes 0.259, 0.460, and 64.70%, respectively. These results demonstrate that the proposed FIFA-OE method outperforms other models for hypertension risk predictions.

• Asia pacific journal of information systems
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• v.18 no.4
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• pp.1-26
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• 2008

Rapid progress of information technology and widespread use of the personal computers have brought various conveniences in our life. But this also provoked a series of problems such as hacking, malicious programs, illegal exposure of personal information etc. Information security threats are becoming more and more serious due to enhanced connectivity of information systems. Nevertheless, users are not much aware of the severity of the problems. Using appropriate password is supposed to bring out security effects such as preventing misuses and banning illegal users. The purpose of this research is to empirically analyze a research model which includes a series of factors influencing the effectiveness of passwords. The research model incorporates the concept of risk based on information systems risk analysis framework as the core element affecting the selection of passwords by users. The perceived risk is a main factor that influences user's attitude on password security, security awareness, and intention of security behavior. To validate the research model this study relied on questionnaire survey targeted on evening class MBA students. The data was analyzed by AMOS 7.0 which is one of popular tools based on covariance-based structural equation modeling. According to the results of this study, while threat is not related to the risk, information assets and vulnerability are related to the user's awareness of risk. The relationships between the risk, users security awareness, password selection and security effectiveness are all significant. Password exposure may lead to intrusion by hackers, data exposure and destruction. The insignificant relationship between security threat and perceived risk can be explained by user's indetermination of risk exposed due to weak passwords. In other words, information systems users do not consider password exposure as a severe security threat as well as indirect loss caused by inappropriate password. Another plausible explanation is that severity of threat perceived by users may be influenced by individual difference of risk propensity. This study confirms that security vulnerability is positively related to security risk which in turn increases risk of information loss. As the security risk increases so does user's security awareness. Security policies also have positive impact on security awareness. Higher security awareness leads to selection of safer passwords. If users are aware of responsibility of security problems and how to respond to password exposure and to solve security problems of computers, users choose better passwords. All these antecedents influence the effectiveness of passwords. Several implications can be derived from this study. First, this study empirically investigated the effect of user's security awareness on security effectiveness from a point of view based on good password selection practice. Second, information security risk analysis framework is used as a core element of the research model in this study. Risk analysis framework has been used very widely in practice, but very few studies incorporated the framework in the research model and empirically investigated. Third, the research model proposed in this study also focuses on impact of security awareness of information systems users on effectiveness of password from cognitive aspect of information systems users.

• Genomics & Informatics
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• v.5 no.3
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• pp.95-101
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• 2007

In this paper, we consider the variable selection methods in the Cox model when a large number of gene expression levels are involved with survival time. Deciding which genes are associated with survival time has been a challenging problem because of the large number of genes and relatively small sample size (n<

• Journal of the Chungcheong Mathematical Society
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• v.34 no.2
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• pp.169-180
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• 2021

This paper investigates the time-inconsistent agent's optimal consumption and investment problem under inflation risk. The agents' discount factor is governed by hyperbolic discounting, which has a random time to change. We impose the inflation risk which plays a crucial role in long-term financial planning. We derive the semi-analytic solution to the problem of sophisticated agents when the time horizon is finite.

• The Journal of the Korean life insurance medical association
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• v.27 no.2
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• pp.85-95
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• 2008

When an insurance company receives an application for life or health insurance, the company must evaluate the degree of risk the individual for insurance coverage presents before the company agrees to issue the policy. A medical factor is a physical or psychological characteristic that may increases a hazard. A financial factor is financial information that is taken into account by underwriter to determine if a person is applying for more than he/she reasonably needs or can afford. A personal factor is a lifestyle choice. There are several medical risk selection systems in Korean life insurance market. They are attending physician's statement, direct examination by insurance doctors, and paramedic examination. However there is some dissatisfaction of current system. It is possible that cooperation of part-time insurance doctors system may be one of useful system of medical risk selection. Improvement of medical risk selection system will be an important matter of profitability of insurance company and it will contribute to sound life insurance system.

• The Journal of the Korean life insurance medical association
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• v.26
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• pp.31-39
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• 2007

Background and main issue: In the Korean insurance market, an outstanding issue is the decrease of margin of risk ratio. This affects the solvency and profitability of insurance companies. Insurance medicine, which has been developed in Western countries, is so-called medical risk selection or medical underwriting. Medical risk selection is based on clinical follow-up study and mortality analysis methodology. Unfortunately, there have been few clinical follow-up studies, and no intercompany disease analysis system is available in the Korean insurance market. In practice, we use underwriting guidelines, which were developed by some global reinsurance companies. However, these guidelines were developed under clinical follow-up studies performed abroad. So, we cannot rule out underestimation of excess mortality factors such as mortality ratio, excess death rate, and life expectancy. It is necessary to perform medical assessment in claims administration. Comparing the insured's statement by medical records with products' benefit according to this procedure, we can make sound claim decisions and participate in the role of sound underwriting. We can call this scientific procedure as the verification of medical claims review. Another area of medical claims review is medical counsel for claims staff. Result: There is another insurance medicine in addition to medical risk selection. Independent medical assessment by medical records of insured is medical claims review. Medical claims review is composed of verification and counsel.