• Journal of Distribution Science
• /
• v.20 no.8
• /
• pp.93-103
• /
• 2022

Purpose: Online shopping festivals have quickly become the newest trend in online shopping worldwide due to the COVID-19 pandemic. This has led to marketing distribution channels that traditionally emphasized traditional techniques having turned to electronic commerce platforms. Although the pandemic scenario encourages online purchasing, other factors, such as the influence of participation intention to shop during the Online Shopping Festival, must also be considered. Research design, data and methodology: Multiple linear regression analysis was used to test the hypothesis based on data from 121 respondents who are actively involved with online shopping activities in Klang Valley, Selangor. Results: The results of this study show that promotion categories and the perceived influence of mass participation have a significant influence on participation intention. Meanwhile, the perceived temptation of price promotion and perceived fun promotional activities did not significantly influence participation intention. Conclusions: Theoretically, this study contributes to the literature by using the Theory of Planned Behavior and Stimulus-Response models to explain the factors that drive participation intention for online shopping. In practice, this study attracts and encourages customers to shop during the festival day because various attractive promotions are offered by sellers in Malaysia.

• Animal Bioscience
• /
• v.34 no.9
• /
• pp.1451-1459
• /
• 2021

Objective: The objectives of the study were to evaluate reproductive performance and selection response through genetic trend of community-based breeding programs (CBBPs) of Bonga sheep. Methods: Reproduction traits data were collected between 2012 and 2018 from Bonga sheep CBBPs. Phenotypic performance was analyzed using the general linear model procedures of Statistical Analysis System. Genetic parameters were estimated by univariate animal model for age at first lambing (AFL) and repeatability models for lambing interval (LI), litter size (LS), and annual reproductive rate (ARR) traits using restricted maximum likelihood method of WOMBAT. For correlations bivariate animal model was used. Best model was chosen based on likelihood ratio test. The genetic trends were estimated by the weighted regression of the average breeding value of the animals on the year of birth/lambing. Results: The overall least squares mean±standard error of AFL, LI, LS, and ARR were 375±12.5, 284±9.9, 1.45±0.010, and 2.31±0.050, respectively. Direct heritability estimates for AFL, LI, LS, and ARR were 0.07±0.190, 0.06±0.120, 0.18±0.070, and 0.25±0.203, respectively. The low heritability for both AFL and LI showed that these traits respond little to selection programs but rather highly depend on animal management options. The annual genetic gains were -0.0281 days, -0.016 days, -0.0002 lambs and 0.0003 lambs for AFL, LI, LS, and ARR, respectively. Conclusion: Implications of the result to future improvement programs were improving management of animals, conservation of prolific flocks and out scaling the CBBP to get better results.

• Korean Journal of Schizophrenia Research
• /
• v.24 no.2
• /
• pp.60-67
• /
• 2021

Objectives: The optimal duration of maintenance treatment for patients with first-episode schizophrenia (FES) remains unclear. We examined the first antipsychotic treatment duration and its association with re-initiation of treatment using a nationwide claim database. Methods: Data from the Health Insurance Review and Assessment Service database in South Korea for 2007-2016 were used. Linear regression analysis and Cox proportional hazard models were used to evaluate the associations between the duration of the first antipsychotic treatment, time to re-initiation of treatment, and occurrence of treatment re-initiation. Results: Of 30,143 patients with FES, 80.4% (n=24,231) received <2 years of the first antipsychotic treatment. In patients who discontinued treatment (n=23,030), the rate of treatment re-initiation was 74.2% (n=17,086). As the duration of the first antipsychotic treatment increased, the time to re-initiation of treatment decreased (β=-0.146, p<0.001); however, the rate of treatment reinitiation was relatively constant (hazard ratio=1.001, p<0.001). Conclusion: Long-term antipsychotic treatment was not significantly associated with the rate of treatment re-initiation but showed a negative association with the time to re-initiation of treatment. Further research is needed to better understand the optimal treatment duration for FES.

• Journal of Korean Society of Coastal and Ocean Engineers
• /
• v.34 no.1
• /
• pp.11-18
• /
• 2022

In order to improve the accuracy of particle tracking prediction techniques near the Korean Strait, this study compared and analyzed a particle tracking model based on a seawater flow numerical model and a machine learning based on a particle tracking model using field observation data. The data used in the study were the surface drifter buoy movement trajectory data observed in the Korea Strait, prediction data by machine learning (linear regression, decision tree) using the tide and wind data from three observation stations (Gageo Island, Geoje Island, Gyoboncho), and prediciton data by numerical models (ROMS, MOHID). The above three data were compared through three error evaluation methods (Correlation Coefficient (CC), Root Mean Square Errors (RMSE), and Normalized Cumulative Lagrangian Separation (NCLS)). As a final result, the decision tree model had the best prediction accuracy in CC and RMSE, and the MOHID model had the best prediction results in NCLS.

• Journal of the Semiconductor & Display Technology
• /
• v.22 no.1
• /
• pp.124-128
• /
• 2023

Semiconductor engineers have long sought to enhance the energy efficiency of mobile semiconductors by reducing their voltage. During the final stages of the semiconductor manufacturing process, the screening and evaluation of voltage is crucial. However, determining the optimal test start voltage presents a significant challenge as it can increase testing time. In the semiconductor manufacturing process, a wealth of test element group information is collected. If this information can be controlled to predict the test voltage, it could lead to a reduction in testing time and increase the probability of identifying the optimal voltage. To achieve this, this paper is exploring machine learning techniques, such as linear regression and ensemble models, that can leverage large amounts of information for voltage prediction. The outcomes of these machine learning methods not only demonstrate high consistency but can also be used for feature engineering to enhance accuracy in future processes.

• Steel and Composite Structures
• /
• v.45 no.3
• /
• pp.389-408
• /
• 2022

Residual capacity is defined as the load carrying capacity of an RC column after undergoing severe damage. Evaluation of residual capacity of RC columns is necessary to avoid damage initiation in RC structures. The central aspect of the current research is to propose an empirical formula to estimate the residual capacity of RC columns after undergoing severe damage. This formula facilitates decision making of whether a replacement or a repair of the damaged column is adequate for further use. Available literature mainly focused on the simulation of explosion loads by using simplified pressure time histories to develop residual capacity of RC columns and rarely simulated the actual explosive. Therefore, there is a gap in the literature concerning general relation between blast damage of columns with different explosive loading conditions for a reliable and quick evaluation of column behavior subjected to blast loading. In this paper, the Arbitrary Lagrangian Eulerian (ALE) technique is implemented to simulate high fidelity blast pressure propagations. LS-DYNA software is utilized to solve the finite element (FE) model. The FE model is validated against the practical blast tests, and outcomes are in good agreement with test results. Multivariate linear regression (MLR) method is utilized to derive an analytical formula. The analytical formula predicts the residual capacity of RC columns as functions of structural element parameters. Based on intensive numerical simulation data, it is found that column depth, longitudinal reinforcement ratio, concrete strength and column width have significant effects on the residual axial load carrying capacity of reinforced concrete column under blast loads. Increasing column depth and longitudinal reinforcement ratio that provides better confinement to concrete are very effective in the residual capacity of RC column subjected to blast loads. Data obtained with this study can broaden the knowledge of structural response to blast and improve FE models to simulate the blast performance of concrete structures.

• Restorative Dentistry and Endodontics
• /
• v.46 no.2
• /
• pp.23.1-23.11
• /
• 2021

Objectives: This study assessed the reliability of digital color measurements using images of resin composite specimens captured with a cellphone. Materials and Methods: The reference color of cylindrical specimens built-up with the use of resin composite (shades A1, A2, A3, and A4) was measured with a portable spectrophotometer (CIELab). Images of the specimens were obtained individually or pairwise (compared shades in the same photograph) under standardized parameters. The color of the specimens was measured in the images using RGB system and converted to CIELab system using image processing software. Whiteness index (WI_D) and color differences (ΔE₀₀) were calculated for each color measurement method. For the cellphone, the ΔE₀₀ was calculated between the pairs of shades in separate images and in the same image. Data were analyzed using 2-way repeated-measures analysis of variance (α = 0.05). Linear regression models were used to predict the reference ΔE₀₀ values of those calculated using color measured in the images. Results: Images captured with the cellphone resulted in different WI_D values from the spectrophotometer only for shades A3 and A4. No difference to the reference ΔE₀₀ was observed when individual images were used. In general, a similar ranking of ΔE₀₀ among resin composite shades was observed for all methods. Stronger correlation coefficients with the reference ΔE₀₀ were observed using individual than pairwise images. Conclusions: This study showed that the use of cellphone images to measure the color difference seems to be a feasible alternative providing outcomes similar to those obtained with the spectrophotometer.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.29 no.3A
• /
• pp.199-207
• /
• 2009

In this paper, new vehicular load model is developed for reliability-based bridge design code. Rational load model and statistical properties of loads are important for developing reliability-based design code. In the previous paper, truck weight data collected at eight locations using WIM or BWIM system are analyzed to calculate the maximum truck weights for specified bridge lifetime. Probability distributions of upper 20% total truck weight are assumed as Extreme Type I (Gumbel Distribution) and 100 years maximum weights are estimated by linear regression. In this study, effects of multiple presence of trucks are analyzed. Probability of multiple presence of trucks are estimated and corresponding multiple truck weights are calculated using the same probability distribution function as in the previous paper. New vehicular live load model are proposed for span length from 10 m to 200 m. New model is compared with current Korean model and various load models of other countries.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.26 no.5D
• /
• pp.877-884
• /
• 2006

GPS is an essential tool for applications that be required high positioning precision, for the velocity field estimation of tectonic plates. The three years data of eight GPS permanent station were analyzed to estimate crustal deformation velocities using Gipsy-oasis II software. The velocity vectors of GPS stations are estimated by linear regression method in daily solution time series. The velocities have a standard deviation of less than 0.1mm/yr and the magnitude of velocities given by the Korean GPS permanent stations were very small, ranging from 25.1 to 31.1 mm/yr. The comparison between the final solution and other sources, such as IGS velocity result calculated from SOPAC was accomplished and the results generally show good agreement for magnitude and direction in crustal motion. To evaluate the accuracy of our results, the velocities obtained from six plate motion model was compared with the final solution based on GPS observation.

• Journal of Korean society of Dental Hygiene
• /
• v.24 no.1
• /
• pp.9-16
• /
• 2024

Objectives: The demand for dental care is expected to increase as the population ages. This study aimed to predict the utilization of dental implant care following the expansion of national health insurance benefits for dental implants. Methods: Multiple linear regression analysis was performed on HIRA big data open portal data and DNN-based artificial intelligence models to forecast the utilization of dental care in relation to the national health insurance coverage for dental implants. Results: National health insurance coverage of dental implants was found to be associated with the number of patients using dental implant services and demonstrated a statistical significance. The dental implant services utilization increased with the increased dental implant health insurance benefits for the elderly population, increased mean by region, increased number of dental institutions by region, and increased health insurance coverage rate for dental implants. However, the dental implant services utilization decreased with the increased number of older people living alone and increased size of dental institutions. Conclusions: With the expansion of the national health insurance coverage for dental implants, it is predicted that the utilization of dental implant medical services will increase in the future.