• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권8호
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• pp.3966-3991
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• 2018

Due to the lack of visualization services and organic combinations between public and private buildings data, the usability of the basic map has remained low. To address this issue, this paper reports on a solution that organically combines public and private data while providing visualization services to general users. For this purpose, factors that can affect building prices first were examined in order to define the related data attributes. To extract the relevant data attributes, this paper presents a method of acquiring public information data and real estate-related information, as provided by private real estate portal sites. The paper also proposes a pretreatment process required for intelligent machine learning. This report goes on to suggest an intelligent machine learning algorithm that predicts buildings' value pricing and future value by using big data regarding buildings' spatial information, as acquired from a database containing building value attributes. The algorithm's availability was tested by establishing a prototype targeting pilot areas, including Suwon, Anyang, and Gunpo in South Korea. Finally, a prototype visualization solution was developed in order to allow general users to effectively use buildings' value ranking and value pricing, as predicted by intelligent machine learning.

• 통합자연과학논문집
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• 제7권1호
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• pp.67-73
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• 2014

We consider the mean value function for NHPP software reliability model and time series regression model in software failure data. We estimate parameters for the proposed models from two data sets. The values of SSE and MSE is presented from two data sets. We compare the predicted number of faults with the actual two data sets using the mean value function and regression curve.

• Communications for Statistical Applications and Methods
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• 제23권6호
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• pp.555-562
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• 2016

Interval censored data often occur in an observational study where the subject is followed periodically. Instead of observing an exact failure time, two inspection times that include it are available. There are several methods to analyze interval censored failure time data (Sun, 2006). However, in the presence of competing risks, few methods have been suggested to estimate covariate effect on interval censored competing risk data. A sub-distribution hazard model is a commonly used regression model because it has one-to-one correspondence with a cumulative incidence function. Alternatively, Klein and Andersen (2005) proposed a pseudo-value approach that directly uses the cumulative incidence function. In this paper, we consider an extension of the pseudo-value approach into the interval censored data to estimate regression coefficients. The pseudo-values generated from the estimated cumulative incidence function then become response variables in a generalized estimating equation. Simulation studies show that the suggested method performs well in several situations and an HIV-AIDS cohort study is analyzed as a real data example.

• 사상체질의학회지
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• 제34권2호
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• pp.1-14
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• 2022

Objectives The aim of this study was to investigate the change in Sasang constitution prediction value in 2 years and find the factors associated with it. Methods Cohort data from Korean medicine data center was used. Using Korean Sasang Constitutional Diagnostic Questionnaire (KS-15) which consist of questions related to body shape, temperament, and symptoms, participants were categorized into Tae-Yang (TY), Tae-Eum (TE), So-Yang (SY), and So-Eum (SE). Sasang constitution was assessed on the baseline and after two years. Result Total 5,784 participants were analyzed. (TE 3, 341; SE 911; SY 1,532). Among them, 1,402 participants (24.2%) showed different prediction value in KS-15 after two years. The proportion of participants showing different prediction value in two years was the highest in SY, and the lowest in TE group. The factors associated with the change in Sasang constitution prediction value were different by constitution type. The change in feeling after sweating was significantly associated with the change in prediction value in TE and SY groups, not in SE group. Although temperament was not significantly associated with the change in prediction value from TE to SE, it was significantly associated with that in the change from TE to SY. The change in BMI and appetite were associated with the change in constitution prediction value in all three constitution types. Conclusion Although the factors associated with the change in prediction value of Sasang constitution were different by each constitution type, BMI and appetite were significant in all three types. These factors could be useful for developing Sasang constitution questionnaire and deciding re-prediction needs of Sasang constitution. Further research about the factors related to Sasang constitution diagnosis need to be conducted.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2000년도 하계종합학술대회 논문집(3)
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• pp.55-58
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• 2000

To achieve high performance by exploiting instruction level parallelism(ILP) aggressively in superscalar processors, value prediction is used. Value prediction is a technique that breaks data dependences by predicting the outcome of an instruction and executes speculatively it's data dependent instruction based on the predicted outcome. In this paper, the performance of a hybrid value prediction scheme with dynamic classification mechanism is measured and analyzed by using execution-driven simulator for SPECint95 benchmark set.

• 통합자연과학논문집
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• 제5권3호
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• pp.157-162
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• 2012

Measurement error is one of main source of error in survey. It is generally defined as the difference between an observed value and an underlying true value. An observed value with error may be expressed as a function of the true value plus error term. In some cases, the measurement error variance may be also a function of the unknown true value. The error variance function can be rewritten as a function of true value multiplied by a scale factor. This research explore methods for estimation of the measurement error variance based on the data from complex sampling design. We consider the case in which the variance of mesurement error is a linear function of unknown true value, and the error variance scale factor is small. We applied our results to the U.S. Third National Health and Nutrition Examination Survey (the U.S. NHANES III) data for empirical analyses, which has replicate measurements for relatively small subset of initial respondents's group.

• 수산경영론집
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• 제38권2호
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• pp.79-101
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• 2007

The purpose of this study is to estimate the economic value of the Songieong Beach in Off-season, using a Individual Travel Cost Model(ITCM). Songieong Beach is located in Busan but far away from city. These days, however, the increased rate of traffic inflow to the Songieong beach and the five-day working week are reflected in the trend analysis. Moreover, people have changed psychological value. For that reason, visitors are on the increase on the beach in off-season. The ITCM is applied to estimate non-market value or environmental Good like a Contingent Valuation Method and Hedonic Price Model etc. The ITCM was derived from the Count Data Model(i.e. Poisson and Negative Binomial model). So this paper compares Poisson and negative binomial count data models to measure the tourism demands. The data for the study were collected from the Songjeong Beach on visitors over the a week from November 1 through November 23, 2006. Interviewers were instructed to interview only individuals. So the sample was taken in 113. A dependent variable that is defined on the non-negative integers and subject to sampling truncation is the result of a truncated count data process. This paper analyzes the effects of determinants on visitors' demand for exhibition using a class of maximum-likelihood regression estimators for count data from truncated samples, The count data and truncated models are used primarily to explain non-negative integer and truncation properties of tourist trips as suggested by the economic valuation literature. The results suggest that the truncated negative binomial model is improved overdispersion problem and more preferred than the other models in the study. This paper is not the same as the others. One thing is that Estimating Value of the Beach in off-season. The other thing is this study emphasizes in particular 'travel cost' that is not only monetary cost but also including opportunity cost of 'travel time'. According to the truncated negative binomial model, estimates the Consumer Surplus(CS) values per trip of about 199,754 Korean won and the total economic value was estimated to be 1,288,680 Korean won.

• 산경연구논집
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• 제11권10호
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• pp.59-73
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• 2020

Purpose: The ultimate purpose of this work is to investigate gender differences in the relationships between product quality cues and perceived values at a food select shop. Specifically, this study examines the effects of internal and external cues, which are indicators of product quality, on emotional and social values based on gender differences. Research design, data and methodology: In this study, a questionnaire technique was used to collect the data necessary to test the proposed model. 183 data were collected through this technique. PLS SEM (Partial Least Squares Structured Equation Model) was used to test the research model. Results: First, there is no gender difference between intrinsic cue and emotional value. When using male and female data, there was no significant causal relationship between intrinsic cues and emotional values. Second, we found no gender difference between intrinsic cue and social value. When analyzed with female data, there was no significant causal relationship between intrinsic cue and social value. On the other hand, in the case of men, it was found that a weak causal relationship exists. Third, this study found gender difference between extrinsic cue and emotional value. In the case of men, it was found that a weak causal relationship exists, whereas in the case of women, a strong causal relationship exists between extrinsic cue and emotional value. Fourth, we found gender difference between extrinsic cue and social value. In the case of men, there was no causal relationship, whereas in the case of women, there was a strong causal relationship between extrinsic cue and social value. Finally, we found that there are moderating roles of gender in the relationship between external cues and perceived quality. Conclusions: As a result of analysis, it is necessary to focus on extrinsic clues of product in order to increase the perceived emotional and social values of women. On the other hand, in order to improve the perceived emotional and social values of men, it is necessary to pay attention to both intrinsic and extrinsic cues of product. Therefore, it is necessary to consider what clues and values are important to core customers.

• 유통과학연구
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• 제19권9호
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• pp.101-111
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• 2021

Purpose: This study discusses and discovers the important role of fashion product coolness in affecting consumers' perceived value and consumers' value creation behavior. Accordingly, fashion product coolness exerts a direct effect on perceived value while perceived value has a direct impact on value creation. Besides, fashion product coolness has an indirect effect on value creation through perceived value. Research design, data, and methodology: This study adopts the quantitative research approach by cross-sectional technical on a sample of 319 respondents in Vietnam. PLS-SEM has been used to analyze the survey data. Results: The result indicates that the proposed direct and indirect effects are significant. Specifically, utilitarian "coolness" and hedonic "coolness" have positive impacts on perceived value. The perceived value poses an impact on consumers' value creation behavior, including customer lifetime value and influencer value. Finally, the perceived value links utilitarian "coolness", hedonic "coolness" with customer lifetime value and influencer value. Conclusions: Fashion distribution is playing an increasingly important role in the retail sector of the economy. Fashion distribution activities are greatly influenced by the perceived value of consumers. The findings are supposed to strengthen the beliefs of fashion brands and retailers in the promotion of value creation and consumers' perceived value in the field of fashion distribution.

• Asia pacific journal of information systems
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• 제30권1호
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• pp.214-228
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• 2020

Shared value enhances the competitiveness of a company while simultaneously reducing societal burdens. By allowing companies to share their resources, collaborative logistics systems provide companies with an opportunity to create shared value, namely, not only economic value by enhancing the utilization of resources, but also social value by reducing energy consumptions and greenhouse gas emissions associated with logistics and transportation. Emerging businesses, such as ES3 and Flexe, have recently demonstrated how they created shared value through collaborative logistics services, for example, ES3's collaborative warehousing and direct-to-store (D2S) program, and Flexe's on-demand warehousing platform. However, the development of collaborative logistics systems is currently at a nascent stage. There are quite a few socio-technical barriers to overcome for sharing resources (data as well as infrastructure). Drawing on the socio-technical approach, this research examines how companies create both economic and social value from collaborative logistics systems. We highlight socio-technical barriers, particularly one set of social barriers, that is, competition-oriented conservatism prevalent among companies. Using the case study methodology and interview data, we closely investigate ES3 and Flexe, which provide collaborative logistics services, and demonstrate how technical and social barriers are addressed to create shared value from collaborative logistics systems.