• Composites Research
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• v.36 no.4
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• pp.246-252
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• 2023

A secondary barrier made of glass fiber reinforced composites has been installed infinitely using automatic bonding machine(ABM) in membrane type LNG cargo containment system (CCS). At the same time, significant thermal stress due to cryogenic heat shrinkage has occurred in the composite on the non-bonding area between the adhesive fixation at both ends. There have been studies from the perspective of structural safety evaluation taking this into account, but none that have analyzed mechanical property taking an prolonged length into account. In this study, 2-parameter Weibull distribution statistical analysis was used to standardize reliable mechanical property for actual length, taking into account the composite's brittle fracture of ceramic material with wide fracture strength dispersion. Related experimental data were obtained by performing uniaxial tensile tests at specific temperatures below cryogenic condition considering LNG environment. As a result, the mechanical strength increased about 1.5 times compared to -20℃ at -70℃ and initial non-linear behavior of fiber stretched was suppressed. As the temperature decreased until the cryogenic, the mechanical strength continued to increase due to cold brittleness. The suggested mechanical property in this study would be employed to secure reliable analysis support material property when assessing the safety of secondary barrier's structures.

• Journal of Korean Association for Spatial Structures
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• v.4 no.2 s.12
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• pp.89-97
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• 2004

The objective of this study is the development of a scheme and discrete optimum design algorithm, which is based on the genetic algorithm. The algorithm can perform both scheme and size optimum designs of plane trusses. The developed Scheme genetic algorithm was implemented in a computer program. For the optimum design, the objective function is the weight of structures and the constraints are limits on loads and serviceability. The basic search method for the optimum design is the genetic algorithm. The algorithm is known to be very efficient for the discrete optimization. However, its application to the complicated structures has been limited because of the extreme time need for a number of structural analyses. This study solves the problem by introducing the size & scheme genetic algorithm operators into the genetic algorithm. The genetic process virtually takes no time. However, the evolutionary process requires a tremendous amount of time for a number of structural analyses. Therefore, the application of the genetic algorithm to the complicated structures is extremely difficult, if not impossible. The scheme genetic algorithm operators was introduced to overcome the problem and to complement the evolutionary process. It is very efficient in the approximate analyses and scheme and size optimization of plane trusses structures and considerably reduces structural analysis time. Scheme and size discrete optimum combined into the genetic algorithm is what makes the practical discrete optimum design of plane fusses structures possible. The efficiency and validity of the developed discrete optimum design algorithm was verified by applying the algorithm to various optimum design examples: plane pratt, howe and warren truss.

• Journal of Genetic Medicine
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• v.7 no.1
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• pp.59-66
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• 2010

Purpose: Quantitative fluorescent polymerase chain reaction (QF-PCR) allows for the rapid prenatal diagnosis of common aneuploidies. The main advantages of this assay are its low cost, speed, and automation, allowing for large-scale application. However, despite these advantages, it is not a routine method for prenatal aneuploidy screening in Korea. Our objective in the present study was to validate the performance of QF-PCR using short tandem repeat (STR) markers in a Korean population as a means for rapid prenatal diagnosis. Material and Methods: A QF-PCR assay using an Elucigene kit (Gen-Probe, Abingdon, UK), containing 20 STR markers located on chromosomes 13, 18, 21, X and Y, was performed on 847 amniotic fluid (AF) samples for prenatal aneuploidy screening referred for prenatal aneuploidy screening from 2007 to 2009. The results were then compared to those obtained using conventional cytogenetic analysis. To evaluate the informativity of STR markers, the heterozygosity index of each marker was determined in all the samples. Results: Three autosomes (13, 18, and 21) and X and Y chromosome aneuploidies were detected in 19 cases (2.2%, 19/847) after QF-PCR analysis of the 847 AF samples. Their results are identical to those of conventional cytogenetic analysis, with 100% positive predictive value. However, after cytogenetic analysis, 7 cases (0.8%, 7/847) were found to have 5 balanced and 2 unbalanced chromosomal abnormalities that were not detected by QF-PCR. The STR markers had a slightly low heterozygosity index (average: 0.76) compared to those reported in Caucasians (average: 0.80). Submicroscopic duplication of D13S634 marker, which might be a unique finding in Koreans, was detected in 1.4% (12/847) of the samples in the present study. Conclusion: A QF-PCR assay for prenatal aneuploidy screening was validated in our institution and proved to be efficient and reliable. However, we suggest that each laboratory must perform an independent validation test for each STR marker in order to develop interpretation guidelines of the results and must integrate QF-PCR into the routine cytogenetic laboratory workflow.

• Management & Information Systems Review
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• v.38 no.1
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• pp.23-41
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• 2019

Smart Factory is different from existing factory automation in that it aims to produce personalized products with minimum time and cost through ICT. However, previous researches, not from consumers but from product suppliers, have focused on technology trends and technology application methods. In order for Smart Factory to be successful, it must go beyond supplier-focus to meet the needs of consumers. In this study, we surveyed the purchase intention of the personalized product manufactured by smart factory. Influencing factors of purchase intention were drawn as consumers' need for uniqueness, innovativeness, need for touch, and privacy concern, based on previous research. As results of data analysis, it was confirmed that respondents were willing to purchase personalized products, and that consumers' need for uniqueness, innovativeness, and need for touch had a significant impact on purchase intention of personalized products. Our findings can be summarized as follows. First, Consumers' need for uniqueness was found to have positive effects(${\beta}=0.168$) on purchase intention of personalized products. The desire to differentiate themselves from others will be reflected in their personalized products. Therefore, consumers with a higher desire for uniqueness tend to be more willing to purchase personalized products. Second, consumer innovativeness was found to have positive effects(${\beta}=0.233$) on purchase intention of personalized products. Personalized shoes suggested in this study is a new type of personalized product that is manufactured by the latest information and communication technologies such as multi-function robots and 3D printing. Therefore, consumers seeking innovative new experiences are more willing to purchase personalized products. Third, need for touch was found to have positive effects(${\beta}=0.299$) on purchase intention of personalized products. In a smart factory environment, prosuming participation is given to consumers. If consumers participate in the product development process and reflect their requirements on the product, they are expected to increase their purchase intention by virtually satisfying the need for touch. Fourth, privacy concern was found to have no significantly related to purchase intention of personalized products. This is interpreted as a willingness to tolerate the risk of exposing personal information such as home address, telephone number, body size, and preference for consumers who feel highly useful in personalized products.