• Journal of Navigation and Port Research
• /
• v.45 no.3
• /
• pp.165-172
• /
• 2021

Breaking wave is one of the important design factors in the design of coastal and port structures as they are directly related to various physical phenomena occurring on the coast, such as onshore currents, sediment transport, shock wave pressure, and energy dissipation. Due to the inherent complexity of the breaking wave, many empirical formulas have been proposed to predict breaker indices such as wave breaking height and breaking depth using hydraulic models. However, the existing empirical equations for breaker indices mainly were proposed via statistical analysis of experimental data under the assumption of a specific equation. In this study, a new Munk-type empirical equation was proposed to predict the height of breaking waves based on a representative linear supervised machine learning technique with high predictive performance in various research fields related to regression or classification challenges. Although the newly proposed breaker height formula was a simple polynomial equation, its predictive performance was comparable to that of the currently available empirical formula.

• The Korean journal of internal medicine
• /
• v.39 no.4
• /
• pp.612-624
• /
• 2024

Background/Aims: The predictive value of the estimated pulse wave velocity (ePWV) for the development of metabolic syndrome has not yet been extensively explored. This study aimed to fill this gap by evaluating ePWV as a potential predictor of metabolic syndrome development in middle-aged Korean adults. Methods: Using prospective data obtained from the Ansan-Ansung cohort database, participants without metabolic syndrome at baseline were studied. ePWV was calculated using specific equations based on age and blood pressure. The primary outcome was the incidence of metabolic syndrome during a median follow-up period of 187 months. Results: Among the 6,186 participants, 2,726 (44.1%) developed metabolic syndrome during the follow-up period. ePWV values were categorized into tertiles to assess their predictive value for the development of metabolic syndrome. An ePWV cut-off of 7.407 m/s was identified as a predictor of metabolic syndrome development, with a sensitivity of 0.743 and a specificity of 0.464. Participants exceeding this cut-off, especially those in the third tertile (8.77-14.63 m/s), had a notably higher risk of developing metabolic syndrome. Specifically, the third tertile exhibited a 52.8% cumulative incidence compared with 30.8% in the first tertile. After adjustments, those in the third tertile faced a 1.530-fold increased risk of metabolic syndrome (95% confidence interval, 1.330-1.761). Conclusions: ePWV is a significant predictor of the development of metabolic syndrome. This finding underscores the potential of ePWV as a cardiometabolic risk assessment tool and can thus provide useful information for primary prevention strategies.

• The Journal of Engineering Geology
• /
• v.4 no.3
• /
• pp.297-309
• /
• 1994

For a total of 210 city and Kun areas in Korea, a model was developed to predict the amount of groundwater use at each area. At first, the total areas were classified into 3 groups by the characteristics of groundwater use: residential(87), industrial(27) and agricultural (96) areas. Among them, type areas, represented by the dominant groundwater usage for typical purposes, were selected: residential(22), industrial(8) and agricultural(32) areas. Data for the various factors possibly related to the groundwater use were statistically analyzed. The factors include, 1) agricultural area, 2) industrial area, 3) adininistrative unit area(city or Kun), 4) population, 5) groundwater capadty for community water supply, 6) average water supply for a person per day, 7) agricultural water-use, 8) industrial water-use, 9) residential wateruse, 10) rates of community water supply. The data were correlated to the total amount of groundwater use, and the correlations tested at the 95% and 99% significance levels. Influential, significantly related, factors were identified from the tests. Using the multiple regression method with the influential factors, predictive equations were drawn to calculate the amount of groundwater use for residential-industrial and agricultural areas, respectively. The equations were calibrated to minimize the RMS(root mean square) of the differences between predicted and observed groundwater use. After the validation with future data, the model can be utilized in the regional development plans to predict the maximum groundwater demand at each area.

• Radiation Oncology Journal
• /
• v.32 no.1
• /
• pp.23-30
• /
• 2014

Purpose: The goal of this study is to determine whether the magnitude of overlap between planning target volume (PTV) and rectum ($Rectum_{overlap}$) or PTV and bladder ($Bladder_{overlap}$) in prostate cancer volumetric-modulated arc therapy (VMAT) is predictive of the dose-volume relationships achieved after optimization, and to identify predictive equations and cutoff values using these overlap volumes beyond which the Quantitative Analyses of Normal Tissue Effects in the Clinic (QUANTEC) dose-volume constraints are unlikely to be met. Materials and Methods: Fifty-seven patients with prostate cancer underwent VMAT planning using identical optimization conditions and normalization. The PTV (for the 50.4 Gy primary plan and 30.6 Gy boost plan) included 5 to 10 mm margins around the prostate and seminal vesicles. Pearson correlations, linear regression analyses, and receiver operating characteristic (ROC) curves were used to correlate the percentage overlap with dose-volume parameters. Results: The percentage $Rectum_{overlap}$ and $Bladder_{overlap}$ correlated with sparing of that organ but minimally impacted other dose-volume parameters, predicted the primary plan rectum $V_{45}$ and bladder $V_{50}$ with $R^2$ = 0.78 and $R^2$ = 0.83, respectively, and predicted the boost plan rectum $V_{30}$ and bladder $V_{30}$ with $R^2$ = 0.53 and $R^2$ = 0.81, respectively. The optimal cutoff value of boost $Rectum_{overlap}$ to predict rectum $V_{75}$ >15% was 3.5% (sensitivity 100%, specificity 94%, p < 0.01), and the optimal cutoff value of boost $Bladder_{overlap}$ to predict bladder $V_{80}$ >10% was 5.0% (sensitivity 83%, specificity 100%, p < 0.01). Conclusion: The degree of overlap between PTV and bladder or rectum can be used to accurately guide physicians on the use of interventions to limit the extent of the overlap region prior to optimization.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.32 no.1A
• /
• pp.55-64
• /
• 2012

Experimental investigation on the structural behavior of steel fiber-reinforced ultra high performance concrete (UHPC) beams subjected to shear are presented. Six tests carried out on simply supported I-beams under concentrated loads are presented. The parameters varied were the volume fraction of the fibers (1.0, 1.5 and 2.0%) and shear span-effective depth ratio (2.5, 3.4). The test results indicated that ultimate shear strength increased with increasing fiber volume, and that ultimate shear strength decreased with increasing shear span-effective depth ratio. In addition, applicability of predictive equations for evaluating the ultimate shear strength of steel fiber-reinforced UHPC beams are estimated based on the test results. The comparison between computed values and the experimentally observed values are shown to validate the proposed theoretical equations. It is found that predictions by using AFGC and JSCE recommendations provide the most accurate estimates of shear strength of steel fiber-reinforced UHPC beams.

• Earthquakes and Structures
• /
• v.7 no.4
• /
• pp.485-510
• /
• 2014

In performance-based seismic design procedures Peak Ground Acceleration (PGA) and pseudo-Spectral acceleration ($S_a$) are commonly used to predict the response of structures to earthquake. Recently, research has been carried out to evaluate the predictive capability of these standard Intensity Measures (IMs) with respect to different types of structures and Engineering Demand Parameter (EDP) commonly used to measure damage. Efforts have been also spent to propose alternative IMs that are able to improve the results of the response predictions. However, most of these IMs are not usually employed in probabilistic seismic demand analyses because of the lack of reliable Ground Motion Prediction Equations (GMPEs). In order to define seismic hazard and thus to calculate demand hazard curves it is essential, in fact, to establish a GMPE for the earthquake intensity. In the light of this need, new GMPEs are proposed here for the elastic input energy spectra, energy-based intensity measures that have been shown to be good predictors of both structural and non-structural damage for many types of structures. The proposed GMPEs are developed using mixed-effects models by empirical regressions on a large number of strong-motions selected from the NGA database. Parametric analyses are carried out to show the effect of some properties variation, such as fault mechanism, type of soil, earthquake magnitude and distance, on the considered IMs. Results of comparisons between the proposed GMPEs and other from the literature are finally shown.

• Fire Science and Engineering
• /
• v.21 no.2 s.66
• /
• pp.48-53
• /
• 2007

The knowledge of the flash point of the mixtures is very important for prevention and protection of fire in the industrial field. The flash points for the water+2-propanol system were measured by using Tag open-cup apparatus(ASTM D1310-86). The experimental data were compared with the values calculated by the Raoult's law, the Van Laar equation and the NRTL(Non Random Two Liquids) equation. The calculated values based on the Van Laar and NRTL equations were found to be better than those based on the Raoult's law. It was concluded that Van Laar and NRTL equations were more effective than the Raoult' law at describing the activity coefficients for non-ideal solution such as the water+2-propanol system. And the predictive curve of the flash point prediction model based on the Van Law equation described the experimentally-derived data more effectively than was the case when the prediction model was based upon the NRTL equation.

• Journal of Biosystems Engineering
• /
• v.42 no.3
• /
• pp.190-198
• /
• 2017

Purpose: A thin-layer drying equation was developed to analyze the drying processes of soybeans (white and black beans) and investigate drying conditions by verifying the suitability of existing grain drying equations. Methods: The drying rates of domestic soybeans were measured in a drying experiment using air at a constant temperature and humidity. The drying rate of soybeans was measured at two temperatures, 50 and $60^{\circ}C$, and three relative humidities, 30, 40 and 50%. Experimental constants were determined for the selected thin layer drying models (Lewis, Page, Thompson, and moisture diffusion models), which are widely used for predicting the moisture contents of grains, and the suitability of these models was compared. The suitability of each of the four drying equations was verified using their predicted values for white beans as well as the determination coefficient ($R^2$) and the root mean square error (RMSE) of the experiment results. Results: It was found that the Thompson model was the most suitable for white beans with a $R^2$ of 0.97 or greater and RMSE of 0.0508 or less. The Thompson model was also found to be the most suitable for black beans, with a $R^2$ of 0.97 or greater and an RMSE of 0.0308 or less. Conclusions: The Thompson model was the most appropriate prediction drying model for white and black beans. Empirical constants for the Thompson model were developed in accordance with the conditions of drying temperature and relative humidity.

• Fire Science and Engineering
• /
• v.23 no.5
• /
• pp.161-166
• /
• 2009

The lower flash points for the tert-pentanol + propionic acid and p-xylene + propionic acid systems were measured by Tag open-cup apparatus. The experimental data were compared with the values calculated by the Raoult's law, the van Laar equation and the NRTL equation. The calculated values based on the van Laar and NRTL equations were found to be better than those based on the Raoult's law. It was concluded that the van Laar and NRTL equations were more effective than the Raoult' law at describing the activity coefficients for non-ideal solution such as the tert-pentanol + propionic acid and p-xylene + propionic acid systems. The predictive curve of the flash point prediction model based on the NRTL equation described the experimentally-derived data more effectively than was the case when the prediction model was based upon the van Laar equation.

• Journal of the Korean Society of Marine Environment & Safety
• /
• v.25 no.7
• /
• pp.851-857
• /
• 2019

This study is about ship horsepower prediction of machine learning method using the big data of ship. Currently, new ships use the ISO15016 method to predict external environmental resistance through mathematical equations but due to complicated equations and requires many input variables so it is less applicable to be used in ship. In this recent research, we propose a model capable of predicting ship performance with high performance using SVM (Support Vector Machine) algorithm which shows excellent performance in recent prediction and recognition. The proposed predictive model has the advantage of being able to predict better performance than ISO15016 only if secured big data is used. In this study, we compared the ISO15016 technique and the SVM algorithm-based horsepower analysis method using the 178K bulk carrier's voyage data to reduce ship model data preparation, which is a disadvantage of ISO15016, and improve inaccurate horsepower prediction performance.