• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.06a
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• pp.275-276
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• 2022

VTS operators instruct ships to wait for entry and departure to sail in one-way to prevent ship collision accidents in ports with narrow routes. Currently, the instructions are not based on scientific and statistical data. As a result, there is a significant deviation depending on the individual capability of the VTS operators. Accordingly, this study built a 1d-convolutional neural network model by collecting ship and weather data to predict the exact travel time for ship entry/departure waiting for instructions in the port. It was confirmed that the proposed model was improved by more than 4.5% compared to other ensemble machine learning models. Through this study, it is possible to predict the time required to enter and depart a vessel in various situations, so it is expected that the VTS operators will help provide accurate information to the vessel and determine the waiting order.

• The Korean Journal of Applied Statistics
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• v.36 no.6
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• pp.561-571
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• 2023

Volatility of a time series is defined as the conditional variance on the past information. In particular, for financial time series, volatility is regarded as a time-varying measure of risk for the financial series. To capture the intrinsic asymmetry in the risk of financial series, various asymmetric volatility processes including threshold-ARCH (TARCH, for short) have been proposed in the literature (see, for instance, Choi et al., 2012). This paper proposes a volatility function featuring non-zero origin in which the origin of the volatility is shifted from the zero and therefore the resulting volatility function is certainly asymmetric around zero and achieves the minimum at a non-zero (rather than zero) point. To validate the proposed volatility function, we analyze the Korea stock prices index (KOSPI) time series during the Covid-19 pandemic period for which origin shift to the left of the zero in volatility is shown to be apparent using the minimum AIC as well as via parametric bootstrap verification.

• The Korean Journal of Applied Statistics
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• v.36 no.6
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• pp.619-629
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• 2023

Fertilizers are crucial for increasing crop yield, but using too much of them without taking into account the nutrients that the crops need can increase costs for farm management and have a negative impact on the environment. Through smart agriculture, fertilizers can be applied as needed at the right time to reflect the growth characteristics of crops, reducing the burden of fertilizer losses and providing economical nutrient management. In this study, we use the total dry weight of field-cultivated red pepper and green onion grown in various growing environments to fit a nonlinear model-based crop growth model using different growth curves (logistic, Gompertz, Richards, and double logistic curve), and we propose a fertilizer distributed algorithm based on crop growth rate.

• Korea Trade Review
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• v.47 no.4
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• pp.215-231
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• 2022

Analysis and forecasting of the Baltic Capsize Index (BCI) is important for managing an entity's losses and risks from the uncertainty and volatility of the fast-changing maritime transport market in the future. This study conducted volatility transition analysis through the GARCH model, using BCI which is highly related to steel raw materials. As for the data, 2,385 monthly data were used from March 1999 to March 2021. In this study, after basic statistical analysis, unit root and cointegration test, the GARCH, EGARCH, and DCC-GARCH models were used for volatility transition analysis. As the results of GARCH and EGARCH model, we confirmed that all variables had no autocorrelation between the standardized residuals for error terms and the square of residuals, that the variability of all variables at this time was likely to persist in the future, and that the variability of the time-series error term impact according to Iron ore trade (IoT). In addition, through the EGARCH model, the magnitude convenience of all variables except the Iron ore price (IOP) and Capesize bulk fleet (BCF) variables was greater than the positive value (+). As a result of analyzing the DCC-GARCH (1,1) model, partial linear combinations were confirmed over the entire period. Estimating the effect of variability transition on BCF and C5 with statistically significant linear combinations with BCI confirmed that the impact of BCF on BCI was greater than the impact of BCI itself.

• Explosives and Blasting
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• v.41 no.4
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• pp.17-28
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• 2023

Recently, the utilization of underground space for research facilities and resource development has been on the rise, expanding development from shallow to deep underground. The establishment of deep underground spaces necessitates a thorough examination of rock stability under conditions of elevated stress and temperature. In instances of greater depth, the stability is influenced not only by the geological structure and discontinuity of rock but also by the propagation of ground vibrations resulting from earthquakes and rock blasting during excavation, causing stress changes in the underground cavity and impacting rock stability. In terms of blasting engineering, empirical regression models and numerical analysis methods are used to predict ground vibration through statistical regression analysis based on measured data. In this study, single-hole blasting was conducted, and the pressure of the blast hole and observation hole and ground vibration were measured. Based on the experimental results, the blast pressure blasting vibration at a distance, and the response characteristics of the tunnel floor, side walls, and ceiling were analyzed.

• Animal Bioscience
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• v.36 no.12
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• pp.1880-1888
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• 2023

Objective: The present experiment aimed to determine standardized ileal digestible (SID) lysine (Lys) requirements for pregnant sows individually housed under commercial farm conditions. Methods: Two hundred multiparous sows (parity = 5.1±2.0) on day 42 of gestation were randomly allocated to five dietary treatments with a balanced parity. Experimental diets were formulated to contain 0.22%, 0.32%, 0.42%, 0.52%, and 0.62% of SID Lys for the mid-gestation period (days 42 to 76) and 0.36%, 0.46%, 0.56%, 0.66%, and 0.76% of SID Lys for the late gestation period (days 77 to 103). All indispensable amino acids except Lys were provided at 110% of their requirement estimates. Daily feed allowance per sow was determined based on the back-fat thickness and body condition score at the second pregnancy check and on day 90 of gestation. Three different statistical models were used to estimate the SID Lys requirement. Results: Total born piglets alive per litter increased linearly and quadratically (p<0.001) as dietary SID Lys increased. For total born piglets alive per litter, the SID Lys requirement estimates ranged from 9.69 to 12.4 g/d for the mid-gestation period (1.19 to 1.52 g/Mcal metabolizable energy; 0.39% to 0.49%) and 14.6 to 17.4 g/d for the late gestation period (1.62 to 1.93 g/Mcal metabolizable energy; 0.52% to 0.62%). Conclusion: The mean values of the SID Lys requirement for the mid-gestation period and the late gestation period are 11.1 and 16.1 g/d (1.36 and 1.79 g/Mcal metabolizable energy; 0.44% and 0.58%), respectively, for maximal total born piglets alive per litter.

• Imaging Science in Dentistry
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• v.53 no.4
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• pp.303-312
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• 2023

Purpose: This study investigated the prevalence of developmental and acquired pathologic conditions associated with impacted third molars (3Ms) in a Southern Brazilian population and evaluated whether demographic and tooth characteristics were correlated with the presence of bone or tooth lesions. Materials and Methods: Panoramic radiographs were assessed for developmental (bone-related) or acquired (tooth-related) pathoses associated with impacted upper or lower 3Ms. Data on tooth positioning, tooth development, and patient demographics were collected. A trained, calibrated postgraduate student evaluated all images. Binary and multivariate logistic regression models were used to assess associations between outcomes and the demographic and radiographic variables. The threshold for statistical significance was set at 5% (P<0.05). Results: The sample comprised panoramic radiographs from 2054 patients, predominantly female (59.2%), with a mean age of 27.2±11.5 years. Overall, 4066 impacted 3Ms were evaluated, revealing 471 (11.6%) developmental and 710 (17.5%) acquired pathoses. Among the developmental pathoses, 460 (95.2%) were indicative of dentigerous cysts. Male sex, lower 3M location, vertical or distoangular positioning, and incomplete root formation were associated with an elevated likelihood of developmental pathology. Lower tooth position, complete root formation, and partial eruption were linked to an increased probability of an acquired pathology in the third or second molar. Conclusion: The prevalence of pathologic conditions associated with impacted 3Ms was low. Male sex, lower 3M placement, horizontal or distoangular positioning, and incomplete root formation were associated with developmental pathoses, while lower tooth position, complete root formation, and partial eruption were related to acquired pathoses.

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

• Journal of Information Science Theory and Practice
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• v.12 no.1
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• pp.1-20
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• 2024

This research aims to study and confirm enabling factors affecting the knowledge transfer and business process of community enterprise groups in Pattani province, Thailand. Key informants were community enterprise entrepreneurs; 30 people were selected purposively with criteria. This study used a mixed-methods approach and conducted semi-structured interviews to collect data. Qualitative data were analyzed using content analysis and classification, while quantitative data were analyzed using descriptive statistics with frequency, percentage, mean, and standard deviation. Moreover, inferential statistics chi-square value, Phi Cramer's V, and multiple regression analysis with the R program for statistical computing were employed to analyze the relationship between the variables, test the research hypothesis, and create forecasting equations. The research results revealed that the overview of enabling factors had a very high relationship (Cramer's V=0.965). Regarding community enterprise, it was found that enabling factors related to the knowledge transfer and business process consisted of four factors: regulations and administrative guidelines, business plan, reinforcement, and brainstorming. Reinforcement was the factor with the highest degree of correlation (Cramer's V=0.873) and predictor of influence on the knowledge transfer and business process (R₂=0.670, p<0.05). This study's findings can lead to the developing of guidelines for promoting community enterprises properly and timely. These guidelines are expected to be used to develop knowledge about business models for community enterprises, which will help to improve their competency and competitiveness.

• The Korean Journal of Applied Statistics
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• v.37 no.1
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• pp.103-118
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• 2024

The horseshoe prior is notably one of the most popular priors in sparse regression models, where only a small fraction of coefficients are nonzero. The parameter space of the horseshoe prior is much smaller than that of the spike and slab prior, so it enables us to efficiently explore the parameter space even in high-dimensions. However, on the other hand, the horseshoe prior has a high computational cost for each iteration in the Gibbs sampler. To overcome this issue, various MCMC algorithms for the horseshoe prior have been proposed to reduce the computational burden. Especially, Johndrow et al. (2020) recently proposes an approximate algorithm that can significantly improve the mixing and speed of the MCMC algorithm. In this paper, we compare (1) the traditional MCMC algorithm, (2) the approximate MCMC algorithm proposed by Johndrow et al. (2020) and (3) its variant in terms of computing times, estimation and variable selection performance. For the variable selection, we adopt the sequential clustering-based method suggested by Li and Pati (2017). Practical performances of the MCMC methods are demonstrated via numerical studies.