• Structural Engineering and Mechanics
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• v.83 no.4
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• pp.415-433
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• 2022

Eighteen (18) (120×300×2200 mm) beams were prepared and tested to evaluate the shear strength of Glass Fiber Reinforced Concrete (GFRC) beams with no shear reinforcement, and evaluate the effectiveness of various innovative strengthening systems to increase the shear capacity of the GFRC beams. The test variables are the amount of discrete glass fiber (0.0, 0.6, and 1.2% by volume of concrete) and the type of longitudinal reinforcement bars (steel or GFRP), the strengthening systems (externally bonded (EB) sheet, side near-surface mounted (SNSM) bars, or the two together), strengthening material (GFRP or steel) links, different configurations of NSM GFRP bars (side bonded links, full wrapped stirrups, side C-shaped stirrups, and side bent bars), link spacing, link inclination angle, and the number of bent bars. The experimental results showed that adding the discrete glass fiber to the concrete by 0.6%, and 1.2% enhanced the shear strength by 18.5% and 28%, respectively in addition to enhancing the ductility. The results testified the efficiency of different strengthening systems, where it is enhanced the shear capacity by a ratio of 28.4% to 120%, and that is a significant improvement. Providing SNSM bent bars with strips as a new strengthening technique exhibited better shear performance in terms of crack propagation, and improved shear capacity and ductility compared to other strengthening techniques. Based on the experimental shear behavior, an analytical study, which allows the estimation of the shear capacity of the strengthened beams, was proposed, the results of the experimental and analytical study were comparable by a ratio of 0.91 to 1.15.

• Journal of Korea Port Economic Association
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• v.39 no.1
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• pp.35-46
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• 2023

This study was conducted to evaluating the willingness to pay for marine leisure ships through a contingent valuation method that can estimate the value of non-market economy. The questionnaire adopted a double-bound dichotomous choice Model and the variables for evaluating the amount of willingness to pay consisted of demographic variables and respondent behavior variables, and related information verified through previous studies. As a result of collecting and analyzing a total of 309 questionnaires, the amount of willingness to pay for marine leisure ships was estimated to be 25,510 won. In addition, significant variables affecting the amount of willingness to pay were the experience of visiting the island, satisfaction with the introduction of new maritime transportation, and intention to revisit the island. Through this study, it can be used as a basis for evaluating the economic value of new maritime transportation by estimating the willingness to pay for marine leisure ships using the contingent valuation method.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.413-415
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• 2022

Since human joints can be used as useful information for analyzing human behavior as a component of the human body, many studies have been conducted on human action recognition using joint information. However, it is a very complex problem to recognize human action that changes every moment using only each independent joint information. Therefore, an additional information extraction method to be used for learning and an algorithm that considers the current state based on the past state are needed. In this paper, we propose a human action recognition technique considering the positional relationship of connected joints and the change of the position of each joint over time. Using the pre-trained joint extraction model, position information of each joint is obtained, and bone information is extracted using the difference vector between the connected joints. In addition, a simplified neural network is constructed according to the two types of inputs, and spatio-temporal features are extracted by adding LSTM. As a result of the experiment using a dataset consisting of 9 behaviors, it was confirmed that when the action recognition accuracy was measured considering the temporal and spatial relationship features of each joint, it showed superior performance compared to the result using only single joint information.

• Computers and Concrete
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• v.31 no.5
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• pp.405-417
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• 2023

The submerged floating tunnel (SFT) is tethered by mooring lines anchored to the seabed, therefore, the structural integrity of the anchor should be sensitively managed. Despite their importance, reaction forces cannot be simply measured by attaching sensors or load cells because of the structural and environmental characteristics of the submerged structure. Therefore, we propose an effective method for estimating the reaction forces at the seabed anchor of a submerged floating tunnel using a structural pattern model. First, a structural pattern model is established to use the correlation between tunnel motion and anchor reactions via a deep learning algorithm. Once the pattern model is established, it is directly used to estimate the reaction forces by inputting the tunnel motion data, which can be directly measured inside the tunnel. Because the sequential characteristics of responses in the time domain should be considered, the long short-term memory (LSTM) algorithm is mainly used to recognize structural behavioral patterns. Using hydrodynamics-based simulations, big data on the structural behavior of the SFT under various waves were generated, and the prepared datasets were used to validate the proposed method. The simulation-based validation results clearly show that the proposed method can precisely estimate time-series reactions using only acceleration data. In addition to real-time structural health monitoring, the proposed method can be useful for forensics when an unexpected accident or failure is related to the seabed anchors of the SFT.

• Journal of the Korea institute for structural maintenance and inspection
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• v.27 no.2
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• pp.50-57
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• 2023

Autonomous driving technologies have been gradually improved for road traffic owing to the development of artificial intelligence. Since the truck platooning is beneficial in terms of the associated transporting expenses, the Connected-Automated Vehicle technology is rapidly evolving. The structural performance is, however, rarely investigated to capture the effect of truck platooning on civil infrastructures.In this study, the dynamic behavior of bridges under truck platooning was investigated, and the amplification factor of responses was estimated considering several parameters associated with the driving conditions. Artificial intelligence techniques were used to estimate the maximum response of the mid span of a bridge as the platooning vehicles passing, and the importance of the parameters was evaluated. The most suitable algorithm was selected by evaluating the consistency of the estimated displacement.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.6D
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• pp.767-774
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• 2008

This study has been developed the way that evaluates the road safety using the speed of individual vehicles at curve sections in 2-lane rural highways. For this study, we developed variation of operational speed for the individual vehicle using the speed of vehicles in 96points of selected roads. Drawing out of variation of operational speed for the individual vehicle, estimation models for speed variation of individual vehicles considering horizontal alignments and vertical alignments of the roads have been developed. These models presents the way to evaluate road safety out of the operational speed and acceleration of individual vehicles. Considering safety and based on the results of these study above, some regular spots are ranked by "good", "fair", "bad". The results that this study showed in this paper could be useful to derive some particular spots that needs to be improve in terms of safety.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.6C
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• pp.241-253
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• 2010

For seismic design of a vertical shaft, three-dimensional Finite Element (FE) analyses were performed to evaluate the accurate response of a vertical shaft and to apply a Response Displacement Method (RDM). Special attention is given to the evaluation of seismic base and response displacement of surrounding soil, estimation of load and loading method. Based on the result, it was found that shear wave velocity of seismic base greater than 1500m/s was appropriate for the seismic design. It was also found that double cosine method which evaluates a response displacement of surrounding soil was most appropriate to consider the characteristic of multi-layered soil. Finally, shape effect of the structure was considered to clarify the dynamic behavior of vertical shaft and it would be more economical vertical shaft design when a vertical shaft was analyzed by using RDM.

• Journal of the Korean Society of Food Culture
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• v.21 no.1
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• pp.57-64
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• 2006

The purpose of this study was to measure the pizza purchasing behavioral characteristics of respondents and importances of factors affecting pizza purchase, to estimate the effects of attributes on pizza restaurant choice, and to predict probability of selecting a particular pizza restaurant. The questionnaire consisted of two parts: The paired experimental profiles, purchasing behavior and importances of factors affecting pizza purchase. This study generated profiles of 16 hypothetical pizza restaurant based on the seven attributes. The profiles comprised 16 discrete sets of variables, each of which had two levels. For this study, researcher randomly selected 150 students of university as respondents. Twenty students did not complete the survey instrument, resulting in a final sample size of 129. All estimations were carried out using frequencies, $X^2$, independent samples t-test, phreg procedure of SAS package. The results are as follows. Some purchasing behavioral characteristics and importances of factors affecting pizza purchase were significantly different by gender. Based on the estimated models developed for male student group and female student group, the Chi-square statistics were significant at p<0.001. The parameter estimate for late delivery time with male student group was highest, and the parameter estimate for price with female student group was highest. The pizza restaurant that charged \20,000, offered 100% discount on eleventh pizza, promised to deliver pizza in 40 mins, usually delivered the pizza as promised time, offered only 1 type of pizza crust, delivered warm pizza, offered the money-back guarantee was favored by each of male student group and female student group. The results from this study suggested that there was an opportunity to increase market share and profit by improving operations so that customers receive discount and money-back guarantee simultaneously, and by reducing price, delivery time.

• Analytical Science and Technology
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• v.37 no.3
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• pp.189-199
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• 2024

In forensic genetics, when it is not possible to confirm an individual's identity through STR profile analysis, additional information about the individual can be obtained using DNA-based phenotypic traits estimation. Recently, various researches have been conducted on methods to determine externally visible characteristics (EVC) such as eyes, hair, and skin color. However, relying solely on such phenotypic traits information has limitations for application in East Asian regions, including Korea. In this study, in order to utilize EVC related to an individual's appearance as investigative information, SNPs related to eye shape, hair thickness, skin color, as well as baldness, body type, high myopia, facial shape, acne, and behavioral habits were explored. A total of 50 SNPs were selected, and a targeted amplicon NGS panel capable of amplifying them all at once was developed. Experimental results confirmed the allelic types and frequencies of the 50 SNPs in 14 samples. We plan to use this panel to investigate the correlation between genotype and phenotype using various samples, and to develop methods for interpreting the results.

• Steel and Composite Structures
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• v.51 no.5
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• pp.509-527
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• 2024

Bonding carbon fiber-reinforced polymer (CFRP) laminates have been extensively employed in the restoration of steel constructions. In addition to the mechanical properties of the CFRP, the bond strength (P_U) between the CFRP and steel is often important in the eventual strengthened performance. Nonetheless, the bond behavior of the CFRP-steel (CS) interface is exceedingly complicated, with multiple failure causes, giving the P_U challenging to forecast, and the CFRP-enhanced steel structure is unsteady. In just this case, appropriate methods were established by hybridized Random Forests (RF) and support vector regression (SVR) approaches on assembled CS single-shear experiment data to foresee the P_U of CS, in which a recently established optimization algorithm named Aquila optimizer (AO) was used to tune the RF and SVR hyperparameters. In summary, the practical novelty of the article lies in its development of a reliable and efficient method for predicting bond strength at the CS interface, which has significant implications for structural rehabilitation, design optimization, risk mitigation, cost savings, and decision support in engineering practice. Moreover, the Fourier Amplitude Sensitivity Test was performed to depict each parameter's impact on the target. The order of parameter importance was t_c> L_c > E_A > t_A > E_c > b_c > f_c > f_A from largest to smallest by 0.9345 > 0.8562 > 0.79354 > 0.7289 > 0.6531 > 0.5718 > 0.4307 > 0.3657. In three training, testing, and all data phases, the superiority of AO - RF with respect to AO - SVR and MARS was obvious. In the training stage, the values of R² and VAF were slightly similar with a tiny superiority of AO - RF compared to AO - SVR with R² equal to 0.9977 and VAF equal to 99.772, but large differences with results of MARS.