• Advances in nano research
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• v.16 no.2
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• pp.127-140
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• 2024

Upon direct/indirect exposure to flame or heat, composite structures may burn or thermally buckle. This issue becomes more important in the natural fiber-based composite structures with higher flammability and lower mechanical properties. The main goal of the present study was to obtain an optimal eco-friendly composite system with low flammability and high thermal buckling resistance. The studied composite consisted of polypropylene (PP) and short abaca fiber (AF) with eggshell powder (ESP) and halloysite clay nanotubes (HNTs) additives. An optimal base composite, consisting of 30 wt.% AF and 70 wt.% PP, abbreviated as OAP, was initially introduced based on burning rate (BR) and the Young's modulus determined by horizontal burning test (HBT) and tensile test, respectively. The effects of adding ESP to the base composite were then investigated with the same experimental tests. The results indicated that though the BR significantly decreased with the increase of ESP content up to 6 wt.%, it had a very destructive influence on the stiffness of the composite. To compensate for the damaging effect of ESP, small amount of HNT was used. The performance of OAP composite with 6 wt.% ESP and 3 wt.% HNT (OAPEH) was explored by conducting HBT, cone calorimeter test (CCT) and tensile test. The experimental results indicated a 9~23 % reduction in almost all flammability parameters such as heat release rate (HRR), total heat released (THR), maximum average rate of heat emission (MARHE), total smoke released (TSR), total smoke production (TSP), and mass loss (ML) during combustion. Furthermore, the combination of 6 wt.% ESP and 3 wt.% HNT reduced the stiffness of OAP to an insignificant amount by maximum 3%. Moreover, the char residue analysis revealed the distinct differences in the formation of char between AF/PP and AF/PP/ESP/HNT composites. Afterward, dilatometry test was carried out to examine the coefficient of thermal expansion (CTE) of OAP and OAPEH samples. The obtained results showed that the CTE of OAPEH composite was about 18% less than that of OAP. Finally, a theoretical model was used based on first-order shear deformation theory (FSDT) to predict the critical bucking temperatures of the OAP and OAPEH composite plates. It was shown that in the absence of mechanical load, the critical buckling temperatures of OAPEH composite plates were higher than those of OAP composites, such that the difference between the buckling temperatures increased with the increase of thickness. On the contrary, the positive effect of CTE reduction on the buckling temperature decreased by raising the axial compressive mechanical load on the composite plates which can be assigned to the reduction of stiffness after the incorporation of ESP. The results of present study generally stated that a suitable combination of AF, PP, ESP, and HNT can result in a relatively optimal and environmentally friendly composite with proper flame and thermal buckling resistance with no significant decline in the stiffness.

• Information Systems Review
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• v.23 no.4
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• pp.1-22
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• 2021

In the newly encountered economy caused by the Corona virus Disease-19, remote transaction becomes a new normal that disrupt traditional economic order. In the middle of the disruption, mobile tech is placed and remote finance on mobile is highly noticed and considered as an infra-tech to support the new ecology, In mobile finance. remote payment is becoming the most common service and personal identification on it is critical to operate the new service. There are various means of remotely identifying a person. Recently the use of biometric information is increasing. In this study, a correlation analysis was conducted on factors that effects to biometrics usage and the intention to use in remote personal identification. Variables for critical factor in the remote identification were classified into 4 groups such as Performance expectancy, Effort expectancy, Social influence, and Security. The empirical analysis based on the Unified Theory of Acceptance and Use of Technology (UTAUT) was conducted. The relationship between variables and the intention to use is also analyzed. In the study, stepwise regression analysis was conducted four times in which variables were adjusted in individual stage. As a result, the analysis suggests that performance expectancy, effort expectancy, social influence, security have positive effects for intention to use. Additionally, effort expectancy and security have moderating effects to intention to use depends on biometric authentication experience. The analysis has shown positive effect of variables grouped on the intention to use them. It also suggests that the intention to use biometric authentication will quickly grow. This study is expected to make a contribution to utilize and improve the use of biometric information in mobile payment.

• Culinary science and hospitality research
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• v.22 no.3
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• pp.183-197
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• 2016

This study was conducted to investigate the relationships among service quality, perceived benefit, perceived value and behavioral intention as perceived by franchise snack bars customers. The service quality of franchise snack bars' was tested in three sub-dimensions: environmental quality interaction quality, and outcome quality, which are based on Brady & Cronin's third-dimensional model. A total of 450 survey questionaires were distributed from March 9th to November 12th in 2015, of whi 411 questionnaires were deemed suitable for statistical analysis. SPSS 20.0 program was employed to conduct frequency analysis and reliability analysis, while AMOS 20.0 program was used to test the hypotheses. The results revealed that all three elements of service quality have a positive impact on perceived benefit. In particular, the outcome quality element had the greatest influence on perceived benefit. In sum, customers of a franchise snack bar considered outcome variables such as food taste, reasonable amount, and general quality of food as the most important factors to fulfill the benefit. This results suggest that Korean snack bar franchise companies need to consider improvements to outcome quality features, such as food quality. In addition, perceived benefit was a critical antecedent of perceived value, which was itself a significant predictor of behavioral intention. In conclusion, this study applied the means-end chain theory on franchise sank bar segmentation, as well as three dimension service quality model as developed by Brady and Cronin, and found results that will enable meaningful strategics for snack bar foodservice segmentation in pursuit of the development of efficient business plans, and that can be utilized as a theoretical data for future studies.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.35 no.1
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• pp.153-164
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• 2015

The methods of design of mat foundation may be classified as the rigid method and the flexible method according to the assumptions used. In the rigid method, the mat is assumed to be infinitely rigid and the contact pressure is assumed planar distribution. However, the contact pressure is not planar but curved surface because the real mat is not rigid. Therefore, it is not precise to analyze the mat foundation using the rigid method, and so there is no choice but to accept an error. On the other hand, in the flexible method, the mat is considered as the plate on the elastic foundation. This elastic plate theory is for the infinite plate acting a concentrated load on the elastic foundation. However, the functions for the moment, shear, and the deflection by the flexible method are very complex, there are many difficulties for the designer to use them. Also, it is impossible to use the design aid figures as a substitute of the complex functions, because they do not cover the values at the critical sections for the moment and shear. Therefore, in this research, the simplified functions for the moment, shear, and the deflection are proposed by regression analysis for an designer to use easily the flexible method. The simplified functions are very accurate and very ease to use.

• Proceedings of the Korea Database Society Conference
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• 1999.06a
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• pp.175-186
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• 1999

Detecting the features of significant patterns from their own historical data is so much crucial to good performance specially in time-series forecasting. Recently, a new data filtering method (or multi-scale decomposition) such as wavelet analysis is considered more useful for handling the time-series that contain strong quasi-cyclical components than other methods. The reason is that wavelet analysis theoretically makes much better local information according to different time intervals from the filtered data. Wavelets can process information effectively at different scales. This implies inherent support fer multiresolution analysis, which correlates with time series that exhibit self-similar behavior across different time scales. The specific local properties of wavelets can for example be particularly useful to describe signals with sharp spiky, discontinuous or fractal structure in financial markets based on chaos theory and also allows the removal of noise-dependent high frequencies, while conserving the signal bearing high frequency terms of the signal. To date, the existing studies related to wavelet analysis are increasingly being applied to many different fields. In this study, we focus on several wavelet thresholding criteria or techniques to support multi-signal decomposition methods for financial time series forecasting and apply to forecast Korean Won / U.S. Dollar currency market as a case study. One of the most important problems that has to be solved with the application of the filtering is the correct choice of the filter types and the filter parameters. If the threshold is too small or too large then the wavelet shrinkage estimator will tend to overfit or underfit the data. It is often selected arbitrarily or by adopting a certain theoretical or statistical criteria. Recently, new and versatile techniques have been introduced related to that problem. Our study is to analyze thresholding or filtering methods based on wavelet analysis that use multi-signal decomposition algorithms within the neural network architectures specially in complex financial markets. Secondly, through the comparison with different filtering techniques' results we introduce the present different filtering criteria of wavelet analysis to support the neural network learning optimization and analyze the critical issues related to the optimal filter design problems in wavelet analysis. That is, those issues include finding the optimal filter parameter to extract significant input features for the forecasting model. Finally, from existing theory or experimental viewpoint concerning the criteria of wavelets thresholding parameters we propose the design of the optimal wavelet for representing a given signal useful in forecasting models, specially a well known neural network models.

• Journal of the Korean Geotechnical Society
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• v.15 no.1
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• pp.151-160
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• 1999

A series of laboratory tests for the marine clay sampled under the sea of Kwangyang bay have been conducted. The main types of tests are the general index property tests, the oedometer tests and the triaxial compression tests in both undrained(CIU) and drained(CID) conditions. The clayey samples, classified as CL, CH with natural water content of 38.3~84.6% and liquidity index of 0.71~0.98, are in the normally consolidated state with O.C.R. of 1.0l~l.60. The undrained stress path from CIU tests can be normalized with isotropic consolidation pressure$(p_0)$ and equal shear strain contour is linear passing through the origin in the (q, p) plot. The undrained shear strain is found to be the only function of the stress ratio($\eta$) and linear with intercept in the ($\varepsilon/\eta,\eta$) plot. The built-up pore pressure normalized with pc is also linear with respect to $\eta$. and its slope is defined by ´C´ as a pore pressure parameter. Equations to predict the undrained stress path and the shear strain are proposed. It is proved that the proposed equations give better agreements to the measured values than the Cam-clay theories. The failure points of the stress path are located on the same C.S.L. in (q, p) plot during both CIU and CID tests, which justifies the concept of critical state theory.

• Korean Journal of Social Welfare
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• v.62 no.2
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• pp.279-306
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• 2010

This study is to compare and analyze the policy decision process between Korea Long-term Care Insurance and Japan's using policy network theory as an analysis tool, and to lead political and theoretical implications. The result of the study is summarized as follows. First, a policy agenda about Long-term Care problem for the Elderly set up by the government-leading both Korea and Japan. and the number of policy participation(actors) increased to characteristics of policy process stage. but there is a difference between Korea and Japan in a background of setting up policy agenda about Long-term Care problem. Second, interaction among policy actors is corporative from early policy agenda establishment stage in Korea and Japan. but it changes to dissenting or critical rapidly as being announced the frame of system to the people. Also, it shows that main policy actors play a role in policy making decision and the connection structures of network is similar to both countries although it has a difference in the interaction frequency. Fourth, although the number of policy actors and the extent of their opinion reflection to the policy effect are different, it shows that policy network pattern is very similar to from policy agenda setting stage to parliament(The National Assemble) policy decision stage as a result of government-leading policy process. The theoretical and political implications of this study are as follows. The number and the variety of policy participation, the importance of establishing opened-interaction system, lots of limitation of policy making-decision process of Japan Long-term Care system, and exclusively the government-leading network has demerits about the reflection of too much government's opinion to the policy outcomes.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 1999.03a
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• pp.175-186
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• 1999

Detecting the features of significant patterns from their own historical data is so much crucial to good performance specially in time-series forecasting. Recently, a new data filtering method (or multi-scale decomposition) such as wavelet analysis is considered more useful for handling the time-series that contain strong quasi-cyclical components than other methods. The reason is that wavelet analysis theoretically makes much better local information according to different time intervals from the filtered data. Wavelets can process information effectively at different scales. This implies inherent support for multiresolution analysis, which correlates with time series that exhibit self-similar behavior across different time scales. The specific local properties of wavelets can for example be particularly useful to describe signals with sharp spiky, discontinuous or fractal structure in financial markets based on chaos theory and also allows the removal of noise-dependent high frequencies, while conserving the signal bearing high frequency terms of the signal. To data, the existing studies related to wavelet analysis are increasingly being applied to many different fields. In this study, we focus on several wavelet thresholding criteria or techniques to support multi-signal decomposition methods for financial time series forecasting and apply to forecast Korean Won / U.S. Dollar currency market as a case study. One of the most important problems that has to be solved with the application of the filtering is the correct choice of the filter types and the filter parameters. If the threshold is too small or too large then the wavelet shrinkage estimator will tend to overfit or underfit the data. It is often selected arbitrarily or by adopting a certain theoretical or statistical criteria. Recently, new and versatile techniques have been introduced related to that problem. Our study is to analyze thresholding or filtering methods based on wavelet analysis that use multi-signal decomposition algorithms within the neural network architectures specially in complex financial markets. Secondly, through the comparison with different filtering techniques results we introduce the present different filtering criteria of wavelet analysis to support the neural network learning optimization and analyze the critical issues related to the optimal filter design problems in wavelet analysis. That is, those issues include finding the optimal filter parameter to extract significant input features for the forecasting model. Finally, from existing theory or experimental viewpoint concerning the criteria of wavelets thresholding parameters we propose the design of the optimal wavelet for representing a given signal useful in forecasting models, specially a well known neural network models.

• Journal of Korean Academy of Nursing
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• v.26 no.1
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• pp.73-93
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• 1996

This study aimed to analyse the test contents of the national examination for the registered nurses (NERN) over 3 years from 1991 to 1993 in Korea. In recent years in Korea, the MCQ(multiple choice question) has been showing to be a highly recognized method for assessing the qualification of registered nurses. Unfortunately, nursing faculties have found NERN had some bad MCQs through having evaluation workshop for Some MCQs often provide so many unwriting clues which become a bias of the results, and some items fell into the category of the lower level of educational taxonomy such as isolated recall a fact or data. Frequently the stems of the questions are ambigous, unclear, disputable, esoterical or trivial. Considering those fallacies of the national examination, it is very critical to review the test items to see whether it is of high quality, is more fair, reliable and objective in depth. Therefore, this study was done to provide data for the improvement of the test contents as well as the teachers's assessment skill. For this study, the ad hoc committee was composed of 16 members, including 5 education board members of Korean Academic Nurses Association and 11 nursing faculty members. This committee had one day panel discussion and filled the checklist for this study. The process of analysing data was held over 10 times during 1992-1994. The analysis focussed on educational taxonomy such as cognitive domain(knowledge), psychmotor domain (skill), affective domain(attitude) and the level of learning such as recall, understanding, problems solving, and learning area of theory and practice, and the learning content categorised by nursing process and disease process. The test analysed using difficulty index and the structure of the test items was analysed. The conclusions and suggestion as follows : 1. In learning area, the average ratio of the theory and practice was 1 : 1.1 which was less than 1 : 2 suggested by Korean National Health Institute, and the ratio was different by the 8 leaning subjects of nursing. 2. In category of the educational taxonomy, the knowledge domain was emphasized mostly（79. 7％）, the skill domain was 14.9％, and the attitude domain was 5.4％ only. 3. In the level of learning, generally, the test items of the level of recall（45.5％） and the understanding（46.3％） were covered almost and the problem solving was 8.1％. 4. In the learning contents, generally, the test items related to nursing process was 67.2％ and that of disease process was 32.8％. However, this proportion was different by the 8 leaning subjects. Even though the nursing diagnosis has been emphasized in nursing curricula recently, the test items of this was identified very few. 5. In the structure of the test item, some were not clear, incorrect grammar, unclear description and some have clues to answer. 6. In the item analysis, the non-acceptable level of the difficulty index (means too easy) was 65.7％, and the acceptable level was 33.9％. Considering the results we would like to suggest the followings, 1. Since the test items of knowledge domain was dominant, the test items of the practice domain and attitude domain should be emphasized more. 2. The regular review and analysis of NERN should be arranged in order to improve the quality of the test items which will give influence to the nursing education positively.

• Asia pacific journal of information systems
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• v.18 no.2
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• pp.15-40
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• 2008

With the explosive growth of the Internet, Internet shopping malls have become recognized as one of the major purchasing channels for consumers, as well as one of the competitive distribution channels for companies that allow them to contact with customers without intermediaries. It has motivated information systems(IS) researchers to examine the factors influencing consumer behavior and the purchase decision process in the context of Internet shopping malls. Despite the extensive research that has been conducted on the purchase decision process of consumers in online shopping malls, the results have demonstrated a need for further understanding of consumer behavior due to the unique features of virtual space and the characteristics of online consumers. Previous studies from marketing and consumer behavior domains have suggested that the concept of involvement plays an important role in explaining consumers' purchase behavior. Despite the critical role of involvement and the explosive growth of e-commerce, little research has examined the role of involvement in the Internet shopping mall context. With this motivation, this study has two research objectives. First, it introduces and tests an theoretical model capable of better explaining consumers' intention to purchase in the Internet shopping mall context. The proposed model extends and integrates existing models on purchase intention by incorporating purchase experience, innovativeness, and perceived self-control as the consumer factors, along with perceived risk, information provision, and perceived price as the Internet shopping mall factors. Second, this study examines how involvement differences may affect consumers' intention to purchase. For this purpose, two factors from involvement theory, involvement type and involvement level, are introduced into the research model as moderating variables. In order to test the proposed model, the overall approach employed was a field study using the structural equation model. We developed our data collection instrument by adopting existing validated questions wherever possible. All question items were measured with a seven-point, Likert-type scale, with anchors ranging from 'strongly disagree' to 'strongly agree.' Two IS researchers reviewed the instrument and checked its face validity. We collected empirical data for this study over a period of two weeks from subjects who had purchase experiences through Internet shopping malls. A total of 473 complete and valid responses were obtained. We carried out data analysis using a two-step methodology with AMOS 4.0. The first step in the data analysis was to establish the convergent and discriminant validity of the constructs. In the second step, we examined the structural model based on the cleansed measurement model. The empirical results partly support the proposed model and identify the moderating effect of involvement differences. Theoretical and practical implications of the study are discussed, along with its limitations.