• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.4 no.3
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• pp.255-263
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• 2006

Vol-oxidizer is a device to convert $UO_2$ pellets into $U_3O_8$ powder and to feed a homogeneous powder into a Metal Conversion Reactor in the ACP(Advanced Spent Fuel Conditioning Process). In this paper, we propose a design model of the vol-oxidizer, develop the new vol-oxidizer with a capacity of 20 kg HM/batch in $UO_2$ pellets, and conduct a verification for the device. Design considerations include the internal structure, the capacity, the heating position of the device, and the size. The dimensions of the new vol-oxidizer are decided by the design model. We determine a permeability test of the $U_3O_8$ measuring the temperature distribution, and the volume of $UO_2$ and $U_3O_8$. We manufactured the new vol-oxidizer for a 20 kg HM/batch in $UO_2$ pellets, and then analyzed the characteristics of the $U_3O_8$ powder for the verification. The experimental results show that the permeability of the $U_3O_8$ throughout mesh enhance more than old vol-oxidizer, the oxidation time takes only 8 hours when compared with the 13 hours of the old device, and the average distribution of particle size is $40{\mu}m$. The capacities of new vol-oxidizer for a 20 kg HM/batch in $UO_2$ pellets were agree well with the predictions of design model.

• Journal of Intelligence and Information Systems
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• v.18 no.4
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• pp.59-77
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• 2012

This study focuses on predicting which firms will increase capital by issuing new stocks in the near future. Many stakeholders, including banks, credit rating agencies and investors, performs a variety of analyses for firms' growth, profitability, stability, activity, productivity, etc., and regularly report the firms' financial analysis indices. In the paper, we develop predictive models for rights issues using these financial analysis indices and data mining techniques. This study approaches to building the predictive models from the perspective of two different analyses. The first is the analysis period. We divide the analysis period into before and after the IMF financial crisis, and examine whether there is the difference between the two periods. The second is the prediction time. In order to predict when firms increase capital by issuing new stocks, the prediction time is categorized as one year, two years and three years later. Therefore Total six prediction models are developed and analyzed. In this paper, we employ the decision tree technique to build the prediction models for rights issues. The decision tree is the most widely used prediction method which builds decision trees to label or categorize cases into a set of known classes. In contrast to neural networks, logistic regression and SVM, decision tree techniques are well suited for high-dimensional applications and have strong explanation capabilities. There are well-known decision tree induction algorithms such as CHAID, CART, QUEST, C5.0, etc. Among them, we use C5.0 algorithm which is the most recently developed algorithm and yields performance better than other algorithms. We obtained data for the rights issue and financial analysis from TS2000 of Korea Listed Companies Association. A record of financial analysis data is consisted of 89 variables which include 9 growth indices, 30 profitability indices, 23 stability indices, 6 activity indices and 8 productivity indices. For the model building and test, we used 10,925 financial analysis data of total 658 listed firms. PASW Modeler 13 was used to build C5.0 decision trees for the six prediction models. Total 84 variables among financial analysis data are selected as the input variables of each model, and the rights issue status (issued or not issued) is defined as the output variable. To develop prediction models using C5.0 node (Node Options: Output type = Rule set, Use boosting = false, Cross-validate = false, Mode = Simple, Favor = Generality), we used 60% of data for model building and 40% of data for model test. The results of experimental analysis show that the prediction accuracies of data after the IMF financial crisis (59.04% to 60.43%) are about 10 percent higher than ones before IMF financial crisis (68.78% to 71.41%). These results indicate that since the IMF financial crisis, the reliability of financial analysis indices has increased and the firm intention of rights issue has been more obvious. The experiment results also show that the stability-related indices have a major impact on conducting rights issue in the case of short-term prediction. On the other hand, the long-term prediction of conducting rights issue is affected by financial analysis indices on profitability, stability, activity and productivity. All the prediction models include the industry code as one of significant variables. This means that companies in different types of industries show their different types of patterns for rights issue. We conclude that it is desirable for stakeholders to take into account stability-related indices and more various financial analysis indices for short-term prediction and long-term prediction, respectively. The current study has several limitations. First, we need to compare the differences in accuracy by using different data mining techniques such as neural networks, logistic regression and SVM. Second, we are required to develop and to evaluate new prediction models including variables which research in the theory of capital structure has mentioned about the relevance to rights issue.

• Korean Journal of Social Welfare
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• v.57 no.3
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• pp.305-335
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• 2005

This paper is a result from validation study for SPDA(A Screening Scale For Potential Drug-use Adolescents) created in 2003 and newly developed during 2004. SPDA aims to screen adolescents in their early stage of drug-use and to help practitioners make a preventive approach for the adolescents. 4307 junior and senior high school students were selected as primary research subjects by stratified and quota sampling methods. 305 adolescents on probation were also selected as a comparison group and asked to answer the same questionnaire. Reliability for SPDA recorded 0.914, which proved to be better than previous year's (0.898). Exploratory and confirmatory factor analyses to test construct validity proved that SPDA could be divided into 7 factors and that each factor structure of SPDA could be a proper measurement model with high level of fitness and factor loadings. Discriminant analysis to test predictive validity confirmed that SPDA could classify the adolescents excellently by the frequency of drug-use, with hit ratio of 86.6 percent(78.8% and 87.4% for junior and senior high school students respectively). For concurrent validity test, Hare Home Self-Esteem Scale, Hare School Self-Esteem, Zuckerman-Kuhlman Sensation-seeking Scale were employed to find correlation with SPDA and all the three scales had significant Pearson correlation coefficients with SPDA. Known-groups validity test indicated that SPDA had an adequate power to classify out adolescents on probation from those in schooling, with a hit ratio of 71.8 percent. Cut-off point to detect adolescents with high risk of substance use was 77, which indicated approximately T score, 55 (0.5 SD), satisfying sensitivity, specificity, and efficiency criteria.

• Geophysics and Geophysical Exploration
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• v.11 no.3
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• pp.250-262
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• 2008

In order to assess the feasibility of the dipole-dipole electric method to the investigation of metallic ore deposit, both field data simulation and inversion are carried out for several simplified ore deposit models. Our interest is in a vein-type model, because most of the ore deposits (more than 70%) exist in a vein type in Korea. Based on the fact that the width of the vein-type ore deposits ranges from tens of centimeters to 2m, we change the width and the material property of the vein, and we use 40m-electrode spacing for our test. For the vein-type model with too small width, the low resistivity zone is not detected, even though the resistivity of the vein amounts to 1/300 of that of the surrounding rock. Considering a wide electrode interval and cell size used in the inversion, it is natural that the size of the low resistivity zone is overestimated. We also perform field data simulation and inversion for a vein-type model with surrounding hydrothermal alteration zones, which is a typical structure in an epithermal ore deposits. In the model, the material properties are assumed on the basis of resistivity values directly observed in a mine originated from an epithermal ore deposits. From this simulation, we can also note that the high resistivity value of the vein does not affect the results when the width of the vein is narrow. This indicates that our main target should be surrounding hydrothermal alteration zones rather than veins in field survey. From these results, we can summarize that when the vein is placed at the deep part and the difference of resistivity values between the vein and the surrounding rock is not large enough, we cannot detect low resistivity zone and interpret the subsurface structures incorrectly using the electric method performed at the surface. Although this work is a little simple, it can be used as references for field survey design and field data Interpretation. If we perform field data simulation and inversion for a number of models and provide some references, they will be helpful in real field survey and interpretation.

• Journal of the Korean Society of Radiology
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• v.14 no.3
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• pp.279-287
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• 2020

Recently, interest in radiation protection is increasing because of the occurrence of accidents related to exposure dose. So, the nuclear safety act provides to install the shields to avoid exceeding the dose limit. In particular, when the worker conducts the non-destructive testing (NDT) without the fixed shielding structure, we should monitor the access to the workplace based on a constant dose rate. However, when we apply for permits for NDT work in these work environments, the consideration factors to the estimation of the distance and exposure dose are not legally specified. Therefore, we developed the excel model that automatically calculates the distance, exposure dose, and cost if we input the factors. We applied the assumption data to this model. As a result of the application, the distance change rate was low when the thickness of the lead blanket and collimator is above 25 mm, 21.5 mm, respectively. However, we didn't consider the scattering and build-up factor. And, we assumed the shape of the lead blanket and collimator. Therefore, if we make up for these limitations and use the actual data, we expect that we can build a database on the distance and exposure dose.

• Asia pacific journal of information systems
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• v.21 no.4
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• pp.1-25
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• 2011

Internet-based commerce has undergone an explosive growth over the past decade as consumers today find it more economical as well as more convenient to shop online. Nevertheless, the shift in the common mode of shopping from offline to online commerce has caused consumers to have worries over such issues as private information leakage, online fraud, discrepancy in product quality and grade, unsuccessful delivery, and so forth, Numerous studies have been undertaken to examine the role of perceived risk as a chief barrier to online purchases and to understand the theoretical relationships among perceived risk, trust and purchase intentions, However, most studies focus on empirically investigating the effects of trust on perceived risk, with little attention devoted to the effects of perceived risk on trust, While the influence trust has on perceived risk is worth studying, the influence in the opposite direction is equally important, enabling insights into the potential of perceived risk as a prohibitor of trust, According to Pavlou (2003), the primary source of the perceived risk is either the technological uncertainty of the Internet environment or the behavioral uncertainty of the transaction partner. Due to such types of uncertainty, an increase in the worries over the perceived risk may negatively affect trust, For example, if a consumer who sends sensitive transaction data over Internet is concerned that his or her private information may leak out because of the lack of security, trust may decrease (Olivero and Lunt, 2004), By the same token, if the consumer feels that the online merchant has the potential to profit by behaving in an opportunistic manner taking advantage of the remote, impersonal nature of online commerce, then it is unlikely that the merchant will be trusted, That is, the more the probable danger is likely to occur, the less trust and the greater need to control the transaction (Olivero and Lunt, 2004), In summary, a review of the related studies indicates that while some researchers looked at the influence of overall perceived risk on trust level, not much attention has been given to the effects of different types of perceived risk, In this context the present research aims at addressing the need to study how trust is affected by different types of perceived risk, We classified perceived risk into six different types based on the literature, and empirically analyzed the impact of each type of perceived risk upon consumer trust in an online merchant and further its impact upon purchase intentions. To meet our research objectives, we developed a conceptual model depicting the nomological structure of the relationships among our research variables, and also formulated a total of seven hypotheses. The model and hypotheses were tested using an empirical analysis based on a questionnaire survey of 206 college students. The reliability was evaluated via Cronbach's alphas, the minimum of which was found to be 0.73, and therefore the questionnaire items are all deemed reliable. In addition, the results of confirmatory factor analysis (CFA) designed to check the validity of the measurement model indicate that the convergent, discriminate, and nomological validities of the model are all acceptable. The structural equation modeling analysis to test the hypotheses yielded the following results. Of the first six hypotheses (H1-1 through H1-6) designed to examine the relationships between each risk type and trust, three hypotheses including H1-1 (performance risk ${\rightarrow}$ trust), H1-2 (psychological risk ${\rightarrow}$ trust) and H1-5 (online payment risk ${\rightarrow}$ trust) were supported with path coefficients of -0.30, -0.27 and -0.16 respectively. Finally, H2 (trust ${\rightarrow}$ purchase intentions) was supported with relatively high path coefficients of 0.73. Results of the empirical study offer the following findings and implications. First. it was found that it was performance risk, psychological risk and online payment risk that have a statistically significant influence upon consumer trust in an online merchant. It implies that a consumer may find an online merchant untrustworthy if either the product quality or the product grade does not match his or her expectations. For that reason, online merchants including digital storefronts and e-marketplaces are suggested to pursue a strategy focusing on identifying the target customers and offering products that they feel best meet performance and psychological needs of those customers. Thus, they should do their best to make it widely known that their products are of as good quality and grade as those purchased from offline department stores. In addition, it may be inferred that today's online consumers remain concerned about the security of the online commerce environment due to the repeated occurrences of hacking or private information leakage. Online merchants should take steps to remove potential vulnerabilities and provide online notices to emphasize that their website is secure. Second, consumer's overall trust was found to have a statistically significant influence on purchase intentions. This finding, which is consistent with the results of numerous prior studies, suggests that increased sales will become a reality only with enhanced consumer trust.

• Land and Housing Review
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• v.2 no.4
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• pp.453-461
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• 2011

This study is to derive a project model based on potential demand for Korean-style houses, focusing on new town detached housing sites that LH supplies and to test validity of the derived model and to present the direction and supply methods of the projects. The existing high-class new town Korean-style housing developments that have been considered were found to have little business value due to problems in choice of location and discordance of demand, so 6 types of projects were established through the methods of changes in planned scale, combined use, and subdivision of plot of land based on the results of survey. The type that has the highest business value among the project models was block-type multifamily houses, and this can be interpreted as the increase in total construction area leading to increase inrevenues of allotment sales due to economies of scale. The feasibility of mass housing model in which small-scale Korean-style houses are combined with amenities was found to be high, and if the same project conditions as those of the block-type multifamily houses are applied, the business value of the Korean-style tenement houses was found to be high. Besides, the high-class housing models within block-type detached housing areas are typical projects that the private sector generally promotes, and the construction cost was found to be most expensive with 910 million won per house. In order to enhance the business value of the Korean-style housing development, collectivization such as choice of location, diversification of demand classes, optimization of house sizes, and combination of uses is needed. And in order to adopt Korean-style houses in the detached housing sites, the adjustments and division of the existing planned plots are needed, and the strategies to cope with new demand through supplying Korean-style housing types of sites can be suggested. Also breaking away from the existing uniform residential development methods, the development method through supplying original land that is natural land not yet developed besides basic infrastructures (main roads and water and sewage) can be considered, and as the construction of more than 1~2 stories building is impossible due to the structure of Korean-style house roof and furniture. So it can be suggested that original land in the form of hilly land is considered to be most suitable to large-scale development projects.

• Journal of the Society of Disaster Information
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• v.17 no.4
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• pp.864-881
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• 2021

Purpose: This study aims is to provide a total care solution preventing disaster based on Big Data and AI technology and to service safety considered by individual situations and various risk characteristics. The purpose is to suggest a method that customized comprehensive index services to prevent and respond to safety accidents for calculating the living safety index that quantitatively represent individual safety levels in relation to daily life safety. Method: In this study, we use method of mixing AHP(Analysis Hierarchy Process) and Likert Scale that extracted from consensus formation model of the expert group. We organize evaluation items that can evaluate life safety prevention services into risk indicators, vulnerability indicators, and prevention indicators. And We made up AHP hierarchical structure according to the AHP decision methodology and proposed a method to calculate relative weights between evaluation criteria through pairwise comparison of each level item. In addition, in consideration of the expansion of life safety prevention services in the future, the Likert scale is used instead of the AHP pair comparison and the weights between individual services are calculated. Result: We obtain result that is weights for life safety prevention services and reflected them in the individual risk index calculated through the artificial intelligence prediction model of life safety prevention services, so the comprehensive index was calculated. Conclusion: In order to apply the implemented model, a test environment consisting of a life safety prevention service app and platform was built, and the efficacy of the function was evaluated based on the user scenario. Through this, the life safety index presented in this study was confirmed to support the golden time for diagnosis, response and prevention of safety risks by comprehensively indication the user's current safety level.

• Korean Journal of Psychosomatic Medicine
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• v.27 no.2
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• pp.77-84
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• 2019

Objectives : The Illness Intrusiveness Rating Scale (IIRS) is a well-validated self-report instrument for assessing negative impact of chronic illness and/or adverse effects of its treatment on everyday life domains. Although extensive literature probed its psychometric properties in medical illness, little attention was paid for its validity for psychiatric population. This study aimed to test factorial structure of the Korean Version of the IIRS (IIRS-K) in a consecutive sample of psychiatric outpatients. Methods : Data set of 307 first-visit patients of psychiatric clinic at Guri Hanyang univ. Hospital were used. Exploratory and confirmatory factor analysis, internal consistency were tested in IIRS-K. We also checked Spearman's correlation analysis between IIRS-K, Zung's self-report anxiety scale and Zung's self-report depression scale. Results : 76.9% of the patients were with anxiety disorder and depressive disorder. The principal component factor analysis of the IIRS-K extracted three-factor structure accounted for 63.2% of total variance that was contextually similar to the original English version. This three-factor solution showed the best fit when tested confirmatory factor analysis compared to the original IIRS, two-factor model of IIRS-K suggested from medical outpatients, and one-factor solution. The IIRS-K also showed good internal consistency (Cronbach's α=0.90) and good convergent validity with anxiety and depression scales. Conclusions : The IIRS-K showed the three-factor structure that was similar but not identical to original version. Overall, this study proved factorial validity of the IIRS-K and it can be used for Korean clinical population.

• Asia pacific journal of information systems
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• v.17 no.3
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• pp.105-130
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• 2007

Recently, there is a substantial interest in implementing Business Process Management System(BPMS) among enterprises with the purpose of business process innovation. BPMS redesigns and coordinates business processes in terms of both automated steps and human involvement in order to maximize the value of both involved people and systems. The reason why BPMS is getting attention from top managers is that it has the possibility to optimize the business processes by cycling the process of modeling, execution, monitoring, evaluation, and redesigning work processes. Thus, it has created high expectations about not only productivity improvement but also business process innovation. However. having an innovative nature, which is used for process innovation, BPMS implementation has great potential to stir up employee resistance. The analysis and the discussion about the prevention of the resistance against IS(Information Systems) is important because IS change the way people work and also alter the power structure within the organization, in general. The purpose of this study is to investigate factors that have an impact on the effective adoption of BPMS at the enterprise level. To find out these factors, this study considers two characteristics of BPMS: First. BPMS shares some characteristics with other enterprise-wide IS such as ERP. Second, it has special BPMS-specific characteristics. Due to the lack of previous research on BPMS adoption, interviews were carried out with IT-consultants and CIOs who conducted BPMS projects previously to find out BPMS-specific features that would make BPMS unique when compared to other enterprise-wide IS. As a result, the monitoring function was chosen as the main BPMS-specific factor. Thus, this paper reviewed studies both on enterprise-wide IS adoptions, which applied Technology Acceptance Model (TAM) and secondly on computer based monitoring to find out factors that would influence the employees' perception on the monitoring function of BPMS. Based on the literature review, the study suggested three factors that would have an impact on the employee's perception of the monitoring function: fairness of enterprise evaluation system, fairness of the boss, and self-efficacy of their work. Three factors that would impact the enterprise-wide IS adoption were also set: the shared belief in the benefit of BPMS, training, and communication. Then, these factors were integrated with TAM. Structural equation modeling was used to test hypotheses, out factors that would impact the employees' perception on the monitoring function of BPMS. Based on the literature review the study suggested three factors that would have an impact on the employee's perception of the monitoring function: fairness of enterprise evaluation system, fairness of the boss, and self-efficacy of their work. Three factors that would impact the enterprise-wide IS adoption were also set: the shared belief in the benefit of BPMS, training, and communication. Then, these factors were integrated with TAM. Structural equation modeling was used to test hypotheses. The data analysis results showed that two among three monitoring function related factors - enterprise evaluation system and fairness of the boss - were significant. This implies that employees would worry less about the BPMS implementation as long as they perceive the monitoring results will be used fairly for their performance evaluation. However, employees' high self-efficacy on their job was not a significant factor in their perception of the usefulness of BPMS. This is related to cases that showed employees resisted against the information systems because they automated their works (Markus, 1983). One specific case was an electronic company, where the accounting department workers were requested to redefine their job because their working processes were automated due to BPMS implementation.