• Structural Engineering and Mechanics
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• v.19 no.3
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• pp.347-359
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• 2005

This paper attempts to develop the analytical model of estimating the fatigue damage using a linear elastic fracture mechanics method. The stress history on a welding member, when a truck passed over a bridge, was defined as a block loading and the crack closure theory was used. These theories explain the influence of a load on a structure. This study undertook an analysis of the stress range frequency considering both dead load stress and crack opening stress. A probability method applied to stress range frequency distribution and the probability distribution parameters of it was obtained by Maximum likelihood Method and Determinant. Monte Carlo Simulation which generates a probability variants (stress range) output failure block loadings. The probability distribution of failure block loadings was acquired by Maximum likelihood Method and Determinant. This can calculate the fatigue reliability preventing the fatigue failure of a welding member. The failure block loading divided by the average daily truck traffic is a predictive remaining life by a day. Fatigue reliability analysis was carried out for the welding member of the bottom flange of a cross beam and the vertical stiffener of a steel box bridge by the proposed model. Results showed that the primary factor effecting failure time was crack opening stress. It was important to decide the crack opening stress for using the proposed model. Also according to the 50% reliability and 90%, 99.9% failure times were indicated.

• The Journal of Society for e-Business Studies
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• v.16 no.3
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• pp.93-112
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• 2011

For the success of an online retail market, it is important to allow consumers to get more helpful reviews by figuring out the factors determining the helpfulness of online reviews. On the basis of elaboration likelihood model, this study analyzes which factors determine the helpfulness of reviews and how the factors affecting the helpfulness of an online consumer review differ for product price. For this study, 75,226 online consumer reviews were collected from Amazon.com. Furthermore, additional information on review messages was also gathered by carrying out a content analysis on the review messages. This study shows that both of peripheral cues such as review rating and reviewer's credibility and central cues such as word count of review message and the proportion of negative words influence the helpfulness of review. In addition, the result of this study reveals that each consumer focuses on different information sources of reviews depending on the product price.

• Journal of The Korean Astronomical Society
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• v.48 no.1
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• pp.83-92
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• 2015

Recent large scale surveys such as Sloan Digital Sky Survey have produced homogeneous samples of multiple-image gravitationally lensed quasars with well-defined selection effects. Statistical analysis on these can yield independent constraints on cosmological parameters. Here we use the image separation statistics of lensed quasars from Sloan Digital Sky Survey Quasar Lens Search (SQLS) to derive constraints on cosmological parameters. Our analysis does not require knowledge of the magnification bias, which can only be estimated from the detailed knowledge on the quasar luminosity function at all redshifts, and includes the consideration for the bias against small image separation quasars due to selection against faint lens galaxy in the follow-up observations for confirmation. We first use the mean image separation of the lensed quasars as a function of redshift to find that cosmological models with extreme curvature are inconsistent with observed lensed quasars. We then apply the maximum likelihood test to the statistical sample of 16 lensed quasars that have both measured redshift and magnitude of lens galaxy. The likelihood incorporates the probability that the observed image separation is realized given the luminosity of the lens galaxy in the same manner as Im et al. (1997). We find that the 95% confidence range for the cosmological constant (i.e., the vacuum energy density) is $0.72{\leq}{\Omega}_{\Lambda}{\leq}1.0$ for a flat universe. We also find that the equation of state parameter can be consistent with -1 as long as the matter density ${\Omega}_m{\leq}0.4$ (95% confidence range). We conclude that the image separation statistics incorporating the brightness of lens galaxies can provide robust constraints on the cosmological parameters.

• Land and Housing Review
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• v.7 no.4
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• pp.315-322
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• 2016

Recently, Ministry of Land, Infrastructure and Transport has amended the law to Design for Safety in working design stage of construction work. There should be informed the disaster likelihood and severity of unit-works to decide risk of unit-works in Design for Safety. Therefore, the construction disaster data of ${\bigcirc}{\bigcirc}$ corporation were classified as 24 unit-works and the disaster likelihood and severity of unit works were analyzed in this study. The safety management level of unit-works which based on analysis data was suggested 3 groups; special management and emphasis management, regular management. The results of this study can be used as basic information to perform Design for Safety in construction. And this information will be able to reduce the disaster.

• Journal of the Earthquake Engineering Society of Korea
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• v.12 no.3
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• pp.37-44
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• 2008

This study investigates the influence of various soil properties on the seismic performance of a three-span FCM bridge. Piers that are vulnerable to seismic vibration are identified through numerical study of plastic hinges possibly occurring at the top and bottom of the piers. The fragility curve is obtained as a lognormal distribution function with respect to peak ground acceleration(PGA). The median and logarithmic standard deviation, which are two parameters of a lognormal distribution function, are estimated using the maximum likelihood method. In order to consider the different soil properties of each support, an equivalent spring based on the Korean Standard Specifications for Highway Bridges(KSSHB) is adopted in this study. For seismic fragility analysis, the rotational ductility demands of bridge piers are used as a damage index of the structure.

• Journal of the Korean Institute of Gas
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• v.14 no.4
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• pp.37-44
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• 2010

To propose a cause analysis method of pressurized facilities, a likelihood of failure (LOF) for the thinning module by hydrochloric acid corrosion was analyzed through the risk-based inspection (RBI) using API-581 BRD. For this investigation, the technical module subfactor (TMSF), as a main factor of the LOF, was estimated, and the effects of parameters on the TMSF were analyzed quantitatively. As a result, we found that the TMSF increased with increasing chloride ion concentration and temperature, but it decreased with increasing thickness of the facilities, inspection number and inspection effectiveness. Also, the TMSF showed a relatively low value for the monitoring system implemented and the overdesign factor>1.5. In this condition, the TMSF changed sensitively with the inspection number, the inspection effectiveness and the overdesign factor, and its magnitude varied with the monitoring system.

• Fashion & Textile Research Journal
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• v.21 no.5
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• pp.574-585
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• 2019

The acceleration of digital transformation (DX) has resulted in SNS influencer marketing trends becoming the mainstream of the new market. SNS influencers act as early adopters in the process of new products being accepted. Chinese consumers are most affected by Hallyu, which increases interest in K-beauty products. This study analyzes how K-beauty SNS influencers are related to Chinese consumers. A survey was conducted among Chinese millennial consumers after watching videos provided by K-beauty SNS influencer; subsequently, 456 responses were used for data analysis. As a result, the analysis based on the Elaboration Likelihood Model (ELM) distinguishes the central route and the peripheral route in the process of Chinese consumers accepting new SNS products. The study findings suggested that information quality, credibility, accuracy, and usefulness had significant effects on acceptance intention for new products among central route factors, and similarity, trustworthiness, pleasure, expertise, and attractiveness also had significant effects on the acceptance intention of new product among peripheral route factors. It was found that variables of the central route, rather than those of peripheral route, had stronger effects on the acceptance intention for new products. Consequently, the central route of K-beauty SNS influencer is more important to Chinese consumers' acceptance of new products. It is expected that this study will offer beauty influencer marketing-based cosmetics brands efficient consumer management suggestions.

• The Journal of Information Systems
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• v.30 no.2
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• pp.29-56
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• 2021

Purpose Cyber deviance of adolescents has become a serious social problem. With a widespread use of smartphones, incidents of cyber deviance have increased in Korea and both quantitative and qualitative damages such as suicide and depression are increasing. Research has been conducted to understand diverse factors that explain adolescents' delinquency in cyber space. However, most previous studies have focused on a single theory or perspective. Therefore, this study aims to comprehensively analyze motivations of juvenile cyber deviance and to develop a predictive model for delinquent adolescents by integrating four different theories on cyber deviance. Design/methodology/approach By using data from Korean Children & Youth Panel Survey 2010, this study extracts 27 potential factors for cyber deivance based on four background theories including general strain, social learning, social bonding, and routine activity theories. Then this study employs econometric analysis to empirically assess the impact of potential factors and utilizes a machine learning approach to predict the likelihood of cyber deviance by adolescents. Findings This study found that general strain factors as well as social learning factors have positive effects on cyber deviance. Routine activity-related factors such as real-life delinquent behaviors and online activities also positively influence the likelihood of cyber diviance. On the other hand, social bonding factors such as community commitment and attachment to community lessen the likelihood of cyber deviance while social factors related to school activities are found to have positive impacts on cyber deviance. This study also found a predictive model using a deep learning algorithm indicates the highest prediction performance. This study contributes to the prevention of cyber deviance of teenagers in practice by understanding motivations for adolescents' delinquency and predicting potential cyber deviants.

• Asia-Pacific Journal of Business
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• v.12 no.1
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• pp.151-163
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• 2021

Purpose - The break-even point refers to the point where total profit and total cost coincide, and from this point on, the entrepreneur's decision-making takes a different route. Strategic decisions can be made for more efficient operation and eventually for more likelihood for growth and sustainability if a startup figures out when it recoups the investment and switches to a net profit. Design/methodology/approach - 748 creativity and skill-based sole proprietors in manufacturing industry were examined to demonstrate the effect of the entrepreneur's entrepreneurial experience and education level, the business launch preparation time, or the self-financing on the achievement of break-even point. Findings - While the business launch preparation time lowered the likelihood of reaching a break-even point, self-financing increased the likelihood. As a result of further analysis by subdividing into subgroups according to skill level, only the business launch preparation time was statistically significant in the highly skilled industries. In the low skilled industries, in addition to the business launch preparation time, the CEO's education level and the self-financing were statistically significant. Research implications or Originality - The longer the business launch preparation time, the higher the start-up cost, which increases the burden of initial cost recovery, and the agile response to market changes is thereby delayed, resulting in the business idea losing its appeal. Self-financing not only provides stability and strong motivation for the business operation but also promotes careful spending which contributes to the achievement of break-even point. In particular, it is found that practical experience is more useful than theoretical knowledge in low skilled industries. Due to the limitation of secondary data based on the recollection, the time required to reach a break-even point, percentage of financing sources, etc. may include cognitive errors. In addition, variables are not included that explain the characteristics of creativity and skill-based sole proprietorship, so it is necessary to exercise caution with the actual application.

• The Journal of the Acoustical Society of Korea
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• v.27 no.7
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• pp.372-378
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• 2008

Voice activity detectors (VAD) are important in wireless communication and speech signal processing, In the conventional VAD methods, an expression for the likelihood ratio test (LRT) based on statistical models is derived in discrete Fourier transform (DFT) domain, Then, speech or noise is decided by comparing the value of the expression with a threshold, This paper presents a new statistical VAD method based on a signal subspace approach, The probabilistic principal component analysis (PPCA) is employed to obtain a signal subspace model that incorporates probabilistic model of noisy signal to the signal subspace method, The proposed approach provides a novel decision rule based on LRT in the signal subspace domain, Experimental results show that the proposed signal subspace model based VAD method outperforms those based on the widely used Gaussian distribution in DFT domain.