• Smart Structures and Systems
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• v.16 no.1
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• pp.163-181
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• 2015

This research investigates the structural health monitoring of nonlinear structures after a major seismic event. It considers the identification of flag-shaped or pinched hysteresis behavior in response to structures as a more general case of a normal hysteresis curve without pinching. The method is based on the overall least squares methods and the log likelihood ratio test. In particular, the structural response is divided into different loading and unloading sub-half cycles. The overall least squares analysis is first implemented to obtain the minimum residual mean square estimates of structural parameters for each sub-half cycle with the number of segments assumed. The log likelihood ratio test is used to assess the likelihood of these nonlinear segments being true representations in the presence of noise and model error. The resulting regression coefficients for identified segmented regression models are finally used to obtain stiffness, yielding deformation and energy dissipation parameters. The performance of the method is illustrated using a single degree of freedom system and a suite of 20 earthquake records. RMS noise of 5%, 10%, 15% and 20% is added to the response data to assess the robustness of the identification routine. The proposed method is computationally efficient and accurate in identifying the damage parameters within 10% average of the known values even with 20% added noise. The method requires no user input and could thus be automated and performed in real-time for each sub-half cycle, with results available effectively immediately after an event as well as during an event, if required.

• Earthquakes and Structures
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• v.2 no.4
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• pp.357-376
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• 2011

Ground motion models predict the mean and standard deviation of the logarithm of spectral acceleration, as a function of predictor variables such as earthquake magnitude, distance and site condition. Such models have been developed for a variety of seismic environments throughout the world. Some calculations, such as the Conditional Mean Spectrum calculation, use this information but additionally require knowledge of correlation coefficients between logarithmic spectral acceleration values at multiple periods. Such correlation predictions have, to date, been developed primarily from data recorded in the Western United States from active shallow crustal earthquakes. This paper describes results from a study of spectral acceleration correlations from Japanese earthquake ground motion data that includes both crustal and subduction zone earthquakes. Comparisons are made between estimated correlations for Japanese response spectral ordinates and correlation estimates developed from Western United States ground motion data. The effect of ground motion model, earthquake source mechanism, seismic zone, site conditions, and source to site distance on estimated correlations is evaluated and discussed. Confidence intervals on these correlation estimates are introduced, to aid in identifying statistically significant differences in correlations among the factors considered. Observed general trends in correlation are similar to previous studies, with the exception of correlation of spectral accelerations between orthogonal components, which is seen to be higher here than previously observed. Some differences in correlations between earthquake source zones and earthquake mechanisms are observed, and so tables of correlations coefficients for each specific case are provided.

• Korea journal of population studies
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• v.8 no.2
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• pp.93-99
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• 1985

There have been numerous studies in Korea and other countries of which the major hypotheses are identifying and dearibing the conditions under which the value of children has been formed. The present study proposes to view the formation of the value of children as a correlate of family's consumption-saving and work4eisure behavior pattern. The objectives of the proposed study are to identify the socio-economic and demographic factors determining the family's consumption-saving and work-leisure behavior pattern and to analyse the relationship between the value of children and this behavior pattern. The conceptual framwork of the analysis is that an individual family's socio-economic and demographic factors influence and shape the consumption-saving and work-leisure behaviors and these behaviors in turn influence and reflect the correlates and proximate determinants of the family'sfertility. In this paper, regression model is used to analyse the hypothesized relationship among the various variables. The regression methods used are first and second stage multiple regressions. In addition, MONOVA has been used to show the interactions. Data used are collected from the government publicactions. The major findings from this study are as follows: As the living Standard improves, n individual family's consumption of necessities and its working hours decline, while savings and leisure activities increase. The phenomena result in the fertility reduction as can be seen in the more developed conntries. Child-bearing and rearing activities are found to be the important component to determine the condumption-saving and work-leisure activies. The married women's labor participation, and the investment in education and health are also found to be the factors reducing fertility rate.

• Journal of Korean Society for Quality Management
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• v.49 no.4
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• pp.505-525
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• 2021

Purpose: The purpose of this study was to investigate factors influencing the intention to use Fintech Digital Sand(D-Testbed), which facilitate digital innovation in the financial sectors and allow fintech startups to simulate the PoC their innovative ideas before starting a business. Methods: This study used the Extended Technology Acceptance Model (TAM2), with independent variables such as social influence, personal innovativeness, service quality, relative advantage, and security concerns used in previous studies, for analysis. For mediator variables, the perceived usefulness and perceived ease of use were used in this study. Results: The results indicated that social influence and perceived usefulness have a positive effect on the intention to use. It was also analyzed that relative advantage has a mediating effect on perceived usefulness whereas service quality nor personal innovativeness are not statistically significant mediation. On the other hand, perceived ease of use on the intention is not statistically significant. By this, it was confirmed that the intention to use Fintech Digital Sand(D-Testbed) was to improve the business performance of fintech companies, but not because it was easy to learn and take less effort. Conclusion: The finding of the study provides valuable implications for invigorating the use of fintech digital sandbox(D-testbed) and identifying the factors that affect the perception and intention to use among employees in fintech companies in advance.

• Journal of Korean Society for Quality Management
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• v.49 no.3
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• pp.327-340
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• 2021

Purpose: The purpose of this study is to propose a system predicting whether an electricity distribution system is abnormal by analyzing the temperature of the deteriorated system. Traditional electricity distribution system abnormality diagnosis was mainly limited to post-inspection. This research presents a remote monitoring system for detecting thermal images of the deteriorated electricity distribution system efficiently hereby providing safe and efficient abnormal diagnosis to electricians. Methods: In this study, an object detection algorithm (YOLOv5) is performed using 16,866 thermal images of electricity distribution systems provided by KEPCO(Korea Electric Power Corporation). Abnormality/Normality of the extracted system images from the algorithm are classified via the limit temperature. Each classification model, Random Forest, Support Vector Machine, XGBOOST is performed to explore 463,053 temperature datasets. The process capability index is employed to indicate the quality of the electricity distribution system. Results: This research performs case study with transformers representing the electricity distribution systems. The case study shows the following states: accuracy 100%, precision 100%, recall 100%, F1-score 100%. Also the case study shows the process capability index of the transformers with the following states: steady state 99.47%, caution state 0.16%, and risk state 0.37%. Conclusion: The sum of caution and risk state is 0.53%, which is higher than the actual failure rate. Also most transformer abnormalities can be detected through this monitoring system.

• Journal of Information Technology Services
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• v.20 no.4
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• pp.95-111
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• 2021

Recently, many organizations are actively adopting VDI (Virtual Desktop Infrastructure), an IT-based business system, to build a non-face-to-face business environment for smart-work. However, most of the existing research on VDI has focused on the satisfaction of system service quality or the use of IT resources and investment for VDI introduction. However, research on effective management and utilization of factors according to the characteristics of VDI technology is urgently required. This study is an empirical research study on how VDI technology characteristics affect interactions and work performance by identifying differences in utilization factors between general organization members and IT managers, presenting standards for business utilization and management. This study proposed a model and hypothesis that the system technology characteristics for VDI use are mediated by interactions in which users respond to functions appropriate to their work. In order to verify the hypothesis, a questionnaire survey was conducted on 188 people of companies and institutions that have adopted and used VDI through a questionnaire survey. Data analysis was performed with partial least squares (PLS), a structural equation modeling (SEM) technique that uses a component-based approach to estimation. As a result of the empirical analysis, the same environmental function for performing work, N-th security, and remote access function factors for non-face-to-face work have a significant effect on interactivity, and IT managers have an additional significant effect on the management technology characteristics of resource reallocation. Has been shown to affect. The results of this study aim to minimize trial and error due to new introduction by presenting considerations for future VDI introduction through case analysis.

• The Journal of the Acoustical Society of Korea
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• v.40 no.5
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• pp.466-472
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• 2021

Speaker Change Detection (SCD) refers to finding the moment when the main speaker changes from one person to the next in a speech conversation. In speaker change detection, difficulties arise due to overlapping speakers, inaccuracy in the information labeling, and data imbalance. To solve these problems, TIMIT corpus widely used in speech recognition have been concatenated artificially to obtain a sufficient amount of training data, and the detection of changing speaker has performed after identifying overlapping speakers. In this paper, we propose an speaker change detection system that considers the speaker overlapping. We evaluated and verified the performance using various approaches. As a result, a detection system similar to the X-Vector structure was proposed to remove the speaker overlapping region, while the Bi-LSTM method was selected to model the speaker change system. The experimental results show a relative performance improvement of 4.6 % and 13.8 % respectively, compared to the baseline system. Additionally, we determined that a robust speaker change detection system can be built by conducting related studies based on the experimental results, taking into consideration text and speaker information.

• The Journal of Industrial Distribution & Business
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• v.12 no.5
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• pp.47-58
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• 2021

Purpose - Current research aimed at exploring the effect differences between the two types of processing product information such as the imagining and the considering on psychological product ownership which could influence the intent to purchase or use the product, and focused on identifying the interaction effects of activated memory information type and advertising information type on each of the information processing types. Research design, data, and methodology - This study divided the information processing types into imagining and considering, and the consumer's memories were divided into autobiographical or episodic and semantic memory. The advertising information was approached in each of event information being together with the product and product feature information. At empirical study, 2(two types of memory activation: episodic and semantic memory activation) ∗ 2(two types of advertising information: event-focused and product feature-focused advertising information) between-subjects design was used to make four types of questionnaire according to the type of experimental groups. Through the survey platform, 'questionnaire stars' of 'WeChat' in China, 219 questionnaire data were collected for empirical study. The structural equation model in AMOS 26 and Anova were used to verify hypotheses. Results - First, the ownership affected the usage intent positively. Second, the imagining did not affect the psychological ownership but did directly affect the usage intention, and the considering affected the ownership positively. Third, the episodic memory activation positively influenced the imagining and negatively affected the considering, whereas the semantic memory activation positively influenced the considering and negatively affected the imagining. Fourth, event-advertising information increased the effects of the activated episodic memory on the imagining, and feature-advertising information increased the effects of the activated semantic memory on the considering. Conclusions - marketers should develop and advertise their product-related event message to trigger the imaging that directly increase the intent to purchase or use their product, when consumers are under the activation of their episodic memory. And marketers should advertise their product feature-related message to trigger the considering that could induce consumers' ownership for their product to increase the intent to purchase or use their product, when they are under the activation of their semantic memory.

• Journal of Microbiology and Biotechnology
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• v.29 no.7
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• pp.1061-1070
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• 2019

In the present study, the optimization of poly(${\gamma}$-glutamic acid) (${\gamma}$-PGA) production by Bacillus sp. FBL-2 was studied using a statistical approach. One-factor-at-a-time method was used to investigate the effect of carbon sources and nitrogen sources on ${\gamma}$-PGA production and was utilized to select the most significant nutrients affecting the yield of ${\gamma}$-PGA. After identifying effective nutrients, response surface methodology with central composite design (CCD) was used to obtain a mathematical model to identify the optimum concentrations of the key nutrients (sucrose, $\text\tiny{L}$-glutamic acid, yeast extract, and citric acid) for improvement of ${\gamma}$-PGA production. The optimum amount of significant medium components appeared to be sucrose 51.73 g/l, $\text\tiny{L}$-glutamic acid 105.30 g/l, yeast extract 13.25 g/l, and citric acid 10.04 g/l. The optimized medium was validated experimentally, and ${\gamma}$-PGA production increased significantly from 3.59 g/l (0.33 g/l/h) to 44.04 g/l (3.67 g/l/h) when strain FBL-2 was cultivated under the optimal medium developed by the statistical approach, as compared to non-optimized medium.

• The Journal of Information Systems
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• v.28 no.2
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• pp.53-72
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• 2019

Purpose The purpose of this study is to examine the impact of tie strength in the network of industrial clustering on the knowledge acquisition, integration and innovation performance of small and medium sized enterprises. We test the positive relationship of weak tie and knowledge acquisition, strong tie and knowledge integration, and the interaction effect of two tie strengths on both processes of knowledge acquisition and integration. By identifying these relationships, we can better understand how to manage the attributes of social networks in terms of tie strength in order to improve the performance of innovation for the small and medium sized enterprises. Design/methodology/approach We collect 200 survey data from 2 industrial cluster respectively: Pankyo and Guroo. In Pankyo, the proportion of IT industry is the highest (35%) while the proportion of manufacturing is highest (35%) in Guroo. Pooling the data from two industrial cluster, we check the reliability and validity of our research model and test the hypotheses. Findings First, we find the positive relationship of weak tie and knowledge acquisition from both industrial clustering. Weak tie is composed of heterogeneous organizations with various background and expertise. The communication and information sharing of organizations in the weak tie network helps the idea generation for organization's innovation, which is the knowledge acquisition process. Second, the relationship of strong tie and knowledge integration is insignificant. Typically the strong tie from long-lasting partnership is expected to be beneficial in the action stage of innovation, which is the knowledge integration process. However it is not identified in our industry cluster. Finally, the interaction effect of weak and strong tie is identified to be effective on both knowledge acquisition and integration processes.