• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.3B
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• pp.279-289
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• 2006

The reconstruction of low dimension nonlinear behavior from the hydrologic time series has been an active area of research in the last decade. In this study, we present the applications of a powerful state space reconstruction methodology using the method of Support Vector Machines (SVM) to the Great Salt Lake (GSL) volume. SVMs are machine learning systems that use a hypothesis space of linear functions in a Kernel induced higher dimensional feature space. SVMs are optimized by minimizing a bound on a generalized error (risk) measure, rather than just the mean square error over a training set. The utility of this SVM regression approach is demonstrated through applications to the short term forecasts of the biweekly GSL volume. The SVM based reconstruction is used to develop time series forecasts for multiple lead times ranging from the period of two weeks to several months. The reliability of the algorithm in learning and forecasting the dynamics is tested using split sample sensitivity analyses, with a particular interest in forecasting extreme states. Unlike previously reported methodologies, SVMs are able to extract the dynamics using only a few past observed data points (Support Vectors, SV) out of the training examples. Considering statistical measures, the prediction model based on SVM demonstrated encouraging and promising results in a short-term prediction. Thus, the SVM method presented in this study suggests a competitive methodology for the forecast of hydrologic time series.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.2D
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• pp.233-239
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• 2006

Most research for until at now link travel time were research for mean link travel time calculate or estimate which uses the average of the individual vehicle. however, the link travel time distribution is divided caused by with the impact factor which is various traffic condition, signal operation condition and the road conditional etc. preceding study result for link travel time distribution characteristic showed that the patterns of going through traffic were divided up to 2 in the link travel times. therefore, it will be more accurate to divide up the link travel time into the one involving delay and the other without delay, rather than using the average link travel time in terms of assessing the traffic situation. this study is it analyzed transit hour distribution characteristic and a cause using examine to the variables which give an effect at link travel time distribute using simulation program and determinate link travel time distribute ratio estimation model. to assess the distribution of the link travel times, this research develops the regression model and the fuzzy model. the variables that have high level of correlations in both estimation models are the rest time of green ball and the delay vehicles. these variables were used to construct the methods in the estimation models. The comparison of the two estimation models-fuzzy and regression model- showed that fuzzy model out-competed the regression model in terms of reliability and applicability.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.6A
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• pp.977-988
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• 2006

The goal of this study is to develop a realistic methodology for determination of the Life-Cycle Cost (LCC)-effective optimal seismic retrofit and maintenance strategy of deteriorating bridges. The proposed methodology is based on the concept of minimum LCC which is expressed as the sum of present value of seismic retrofit costs, expected maintenance costs, and expected economic losses with the constraints such as design requirements and acceptable risk of death. The proposed methodology is applied to the LCC-effective optimal seismic retrofit and maintenance strategy of a steel bridge considered as a example bridge in the accompanying study, and various conditions such as corrosion environments and Average Daily Traffic Volumes (ADTVs) are considered to investigate the effects on total expected LCC. In addition, to verify the validity of the developed methodology, the results are compared with the existing methodology. From the numerical investigation, it may be positively expected that the proposed methodology can be effectively utilized as a practical tool for the decision-making of LCC-effective optimal seismic retrofit and maintenance strategy of deteriorating bridges.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.6B
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• pp.579-587
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• 2010

The mid-range streamflow forecast was performed using NWP(Numerical Weather Prediction) provided by KMA. The NWP consists of RDAPS for 48-hour forecast and GDAPS for 240-hour forecast. To enhance the accuracy of the NWP, QPM to downscale the original NWP and Quantile Mapping to adjust the systematic biases were applied to the original NWP output. The applicability of the suggested streamflow prediction system which was verified in Geum River basin. In the system, the streamflow simulation was computed through the long-term continuous SSARR model with the rainfall prediction input transform to the format required by SSARR. The RQPM of the 2-day rainfall prediction results for the period of Jan. 1~Jun. 20, 2006, showed reasonable predictability that the total RQPM precipitation amounts to 89.7% of the observed precipitation. The streamflow forecast associated with 2-day RQPM followed the observed hydrograph pattern with high accuracy even though there occurred missing forecast and false alarm in some rainfall events. However, predictability decrease in downstream station, e.g. Gyuam was found because of the difficulties in parameter calibration of rainfall-runoff model for controlled streamflow and reliability deduction of rating curve at gauge station with large cross section area. The 10-day precipitation prediction using GQPM shows significantly underestimation for the peak and total amounts, which affects streamflow prediction clearly. The improvement of GDAPS forecast using post-processing seems to have limitation and there needs efforts of stabilization or reform for the original NWP.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.4D
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• pp.351-360
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• 2010

In 2010, the number of registered vehicles reached almost at 17.48 millions in Korea. This dramatic increase of vehicles influenced to increase the number of traffic accidents which is one of the serious social problems and also to soar the personal and economic losses in Korea. Through this research, an enhanced intersection hazard prediction model by combining Genetic Algorithm and Artificial Neural Network will be developed in order to obtain the important data for developing the countermeasures of traffic accidents and eventually to reduce the traffic accidents in Korea. Firstly, this research has investigated the influencing factors of road geometric features on the traffic volume of each approaching for the intersections where traffic accidents and congestions frequently take place and, a linear regression model of traffic accidents and traffic conflicts were developed by examining the relationship between traffic accidents and traffic conflicts through the statistical significance tests. Secondly, this research also developed an intersection hazard prediction model by combining Genetic Algorithm and Artificial Neural Network through applying the intersection traffic volume, the road geometric features and the specific variables of traffic conflicts. Lastly, this research found out that the developed model is better than the existed forecasting models in terms of the reliability and accuracy by comparing the actual number of traffic accidents and the predicted number of accidents from the developed model. In conclusion, it is expect that the cost/effectiveness of any traffic safety improvement projects can be maximized if this developed intersection hazard prediction model by combining Genetic Algorithm and Artificial Neural Network use practically at field in the future.

• Journal of Korean Tunnelling and Underground Space Association
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• v.12 no.1
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• pp.1-14
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• 2010

Until now, the evaluation method of spalling depth using Martin et al. (1999)'s linear regression relations has long been known applicable. However, it is not likely that the proposed equation is applicable to the openings other than circular type and mostly overpredict the spalling depth in comparison with actual spalling cases. Moreover, the evaluation method to estimate the spalling width has not been presented yet; it is essential to evaluate the spalling width in addition to the spalling depth, because the shape of the spalled region influences the choice of suitable rock reinforcement. In this study, linear regression equations, in which normalized spalling depth ($d_f/W_D$) and normalized spalling width ($w_f/W_D$) are functions of three spalling evaluation indices, ${\sigma}_1/{\sigma}_c,\;D_{is}(={\sigma}_{max}/{\sigma}_c)$ and ${\sigma}_{dev}/{\sigma}_{cm}$, are established based on in-situ spalling observations and CWFS simulation results. Confidence intervals of 95% using the statistical inference theory are used in verifying the reliability of linear regression equations. Spalling depth ($d_f$) and spalling width ($w_f$) predicted from the proposed linear regression relations, which take three spalling evaluation indices into account, showed reasonable match with in-situ observations by adopting weighting factors considering the degree of variance of linear regression relations.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.6A
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• pp.535-542
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• 2010

Precise estimation of a structure's dynamic characteristics is indispensable for ensuring stable dynamic responses during lifetime especially for the structures which can experience resonance such as railway bridges. In this paper, the results of forced vibration tests of different excitation methods (vibration exciter and impact hammer) are compared to examine the differences and the cause of differences of extracted natural frequencies. Consequently a natural frequency modification method is suggested to eliminate effects of non-structural disturbance factors. Also, sequential forced vibration tests are performed before and after track construction according to the construction stage of a railway bridge, and the variation of natural frequencies are examined. Effect of added mass of vibration exciter and variation of support condition due to the level of excitation force are concluded as the major cause of natural frequency differences. Thus eliminating these effects can enhance the reliability of the extracted natural frequencies. Construction of track affects not only the mass of structure but also the stiffness of the structure. Also, the amount of increase in stiffness varies according to the level of structural deflection. Therefore, reasonable estimation of the level of structural response during operation is important for precise natural frequency calculation at design phase.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.4
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• pp.348-355
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• 2023

Biodiesel is known as an environmentally friendly neutral fuel, and a policy of obligatory mixing of a certain ratio is implemented on land. In this study, to verify the feasibility of using biodiesel as a ship fuel, component analysis, metal corrosion test, and storage stability test were performed on the mixing ratios of 0 %, 5 %, 10 %, and 20 % of marine diesel and biodiesel. Component analysis evaluated a total of eight factors including density, kinematic viscosity and flash point according to ISO 8217:2017 standards and the reliability of biodiesel through metal corrosion tests and storage stability tests under atmosphere temperature and harsh conditions (60 ℃) for 180 days. Results demonstrate that component analysis satisfied the ISO 8217:2017 standard in all biodiesel mixing ratios. Furthermore, as the biodiesel mixing ratio increased, the kinematic viscosity, density, and acid value increased and the sulfur content decreased. Metal corrosion rarely occurred in the case of carbon steel, iron, aluminum, and nickel, whereas in the case of copper, corrosion occurred under the influence of oxygen-rich biodiesel under the harsh conditions (60 ℃) of 20 % biodiesel mixture. As for storage stability, discoloration, sludge formation, and fuel separation were not visually confirmed.

• Journal of Korea Entertainment Industry Association
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• v.13 no.6
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• pp.187-202
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• 2019

The main goal of this study is to investigate influence of trust in physical education (PE) teachers and immersion experience in PE classes on attitude and satisfaction during PE classes. Total 863 middle school students in Gwang-ju metropolitan area were recruited by utilizing a convenience sampling method. All data were analyzed by using SPSS statistic program ver. 25.0 (frequency analysis, exploratory factor analysis, reliability analysis, correlation analysis, multiple regression analysis). Alpha was set at 0.05. The results of this study is summarized as in the following. First, all sub-factors of trust in the PE teachers partially positively or negatively influence sub-factors of attitude during PE classes. Second, sub-factors of satisfaction during PE classes were partially positively affected to trust in the PE teachers. Third, Attitude during PE Classes were found to have partial positive influence on immersion experience in PE classes. Fourth, sub-factors of immersion experience in PE classes have partial positive effect on the sub-factors of satisfaction during PE classes. Thus, in order to the positive attitude and greater satisfaction during PE classes, it is important to establish the trust of PE teachers through maintaining interaction with students, constructing better systemic class, and creating the class conditions based on considering students' ability. In addition, in order to enhance immersion experiences of students during PE classes, it is necessary to set up learning goals and tasks based on ability of students, to study various teaching method, and to make only focusing on the performance based PE classes without grading.

• Journal of Korea Entertainment Industry Association
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• v.13 no.7
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• pp.285-294
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• 2019

The purpose of this study is to assess construct validity and verify the concept of the Happiness-enhancing Activities and Positive Practices Inventory(HAPPI) developed by Henricksen & Stephens(2013), for Korean old adults who participating physical activities with measuring happiness-related propensity. In this study, the research model was confirmed by evidenced based on the content validity, EFA, construct validity of the latent structure analysis with CFA, reliability as internal consistency. Using self-reported questionnaire conducted among 370 participants who physical activities. Total of 344 data were selected. As a result, internal consistency α was acceptable. Evidence-based on convergent and discriminant of the CFA as GFI=.925, CFI .962, TLI .953, and RMSEA .062 appeared significantly. Model goodness-of-fit, C.R. ratio(Critical ratio: estimates/SE) and Squared Multiple Correlations(SMC), and average variance extracted(AVE) was verified with the hypothesis of the model. Therefore, HAPPI validity evidence for the model fit was confirmed. In conclusion, the HAPPI 4 factors and 16 items(Other-focused, Personal recreation and interests, Achievement, Self-Concordant Work, Spiritual and thought-related) has reliable evidence to apply for Korean old adults and applicable assessment of happiness.