• Journal of the Korean Geotechnical Society
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• v.25 no.10
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• pp.87-97
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• 2009

The seismic site coefficients are often used with the seismic hazard maps to develop the design response spectrum at the surface. The site coefficients are most commonly developed deterministically, while the seismic hazarde maps are derived probabilistically. There is, hence, an inherent incompatibility between the two approaches. However, they are used together in the seismic design codes without a clear rational basis. To resolve the fundamental imcompatibility between the site coefficients and hazard maps, this study uses a novel probabilistic seismic hazard analysis (PSHA) technique that simulates the results of a standard PSHA at a rock outcrop, but integrates the site response analysis function to capture the site amplification effects within the PSHA platform. Another important advantage of the method is its ability to model the uncertainty, variability, and randomness of the soil properties. The new PSHA was used to develop fully probabilistic site coefficients for site classes of the seismic design code and another sets of site classes proposed in Korea. Comparisons highlight the pronounced discrepancy between the site coefficients of the seismic design code and the proposed coefficients, while another set of site coefficients show differences only at selected site classes.

• Journal of the Korean Geotechnical Society
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• v.26 no.7
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• pp.161-170
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• 2010

For the development of load and resistance factor design, reliability analysis is required to calibrate resistance factors in the framework of reliability theory. The distribution of measured-to-predicted pile resistance ratio was obrained based on only the results of load tests conducted to failure for the assessment of uncertainty regarding pile resistance and used in the conventional reliability analysis. In other words, successful pile load test (piles resisted twice their design loads without failure) results were discarded, and therefore, were not reflected in the reliability analysis. In this paper, a new systematic method based on Bayesian theory is used to update reliability indices of driven steel pipe piles by adding more proof pile load test results, even not conducted to failure, to the prior distribution of pile resistance ratio. Fifty seven static pile load tests performed to failure in Korea were compiled for the construction of prior distribution of pile resistance ratio. The empirical method proposed by Meyerhof is used to calculate the predicted pile resistance. Reliability analyses were performed using the updated distribution of pile resistance ratio. The challenge of this study is that the distribution updates of pile resistance ratio are possible using the load test results even not conducted to failure, and that Bayesian updates are most effective when limited data are available for reliability analysis.

• Journal of the Korean Society of Safety
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• v.38 no.2
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• pp.96-103
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• 2023

Generally, human stampedes and crowd collapses occur when people press against each other, causing falls that may result in death or injury. Particularly, crowd accidents have become increasingly common since the 1990s, with an average of 380 deaths annually. For instance, in Korea, a stampede occurred during the Itaewon Halloween festival on October 29, 2022, when several people crowded onto a narrow, downhill road, which was 45 meters long and between 3.2 and 4 meters wide. Precisely, this stampede was primarily due to the excessive number of people relative to the road size. Essentially, stampedes can occur anywhere and at any time, not just at events, but also in other places where large crowds gather. More specifically, the likelihood of accidents increases when the crowd density exceeds a turbulence threshold of 5-6 /m². Meanwhile, festivals and events, which have become more frequent and are promoted through social media, garner people from near and far to a specific location. Besides, as cities grow, the number of people gathering in one place increases. While stampedes are rare, their impact is significant, and the uncertainty associated with them is high. Currently, there is no scientific system to analyze the risk of stampedes due to crowd concentration. Consequently, to prevent such accidents, it is essential to prepare for crowd disasters that reflect social changes and regional characteristics. Hence, this study proposes using digital topographic maps and crowd-density risk simulations to develop a 3D model of the region. Specifically, the crowd density simulation allows for an analysis of the density of people walking along specific paths, which enables the prediction of danger areas and the risk of crowding. By using the simulation method in this study, it is anticipated that safety measures can be rationally established for specific situations, such as local festivals, and preparations may be made for crowd accidents in downtown areas.

• Journal of the Korean Geotechnical Society
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• v.38 no.3
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• pp.35-42
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• 2022

The N-value from the Standard Penetration Test (SPT), which is one of the representative in-situ test, is an important index that provides basic geological information and the depth of the bearing layer for the design of geotechnical structures. In the aspect of time and cost-effectiveness, there is a need to carry out a representative sampling test. However, the various variability and uncertainty are existing in the soil layer, so it is difficult to grasp the characteristics of the entire field from the limited test results. Thus the spatial interpolation techniques such as Kriging and IDW (inverse distance weighted) have been used for predicting unknown point from existing data. Recently, in order to increase the accuracy of interpolation results, studies that combine the geotechnics and deep learning method have been conducted. In this study, based on the SPT results of about 22,000 holes of ground survey, a comparative study was conducted to predict the depth of the bearing layer using deep learning methods and IDW. The average error among the prediction results of the bearing layer of each analysis model was 3.01 m for IDW, 3.22 m and 2.46 m for fully connected network and PointNet, respectively. The standard deviation was 3.99 for IDW, 3.95 and 3.54 for fully connected network and PointNet. As a result, the point net deep learing algorithm showed improved results compared to IDW and other deep learning method.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.1
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• pp.24-35
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• 2023

Rapid industrialization and urbanization have led to severe marine pollution. A Water Quality Index (WQI) has been developed to allow the effective management of marine pollution. However, the WQI suffers from problems with loss of information due to the complex calculations involved, changes in standards, calculation errors by practitioners, and statistical errors. Consequently, research on the use of artificial intelligence techniques to predict the marine and coastal WQI is being conducted both locally and internationally. In this study, six techniques (RF, XGBoost, KNN, Ext, SVM, and LR) were studied using marine environmental measurement data (2000-2020) to determine the most appropriate artificial intelligence technique to estimate the WOI of five ecoregions in the Korean seas. Our results show that the random forest method offers the best performance as compared to the other methods studied. The residual analysis of the WQI predicted score and actual score using the random forest method shows that the temporal and spatial prediction performance was exceptional for all ecoregions. In conclusion, the RF model of WQI prediction developed in this study is considered to be applicable to Korean seas with high accuracy.

• Analyses & Alternatives
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• v.2 no.1
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• pp.31-69
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• 2018

This study examines the role of science in resolving trade disputes. After the Great East Japan Earthquake of 11 March 2011 that not only jeopardized the people of Japan, but also put the safety of an entire region at risk, the Republic of Korea (Korea) has imposed import bans as well as increased testing and certification requirements for radioactive material on Japanese food products. Japan has challenged these restrictions at the World Trade Organizations Dispute Settlement Body (DSB). This study aims to explain how international trade agreements and previous DSB rulings have dealt with different scientific viewpoints provided by confronting parties. In doing so, it will contrast the viewpoints espoused by Korean and Japanese representatives, and then analyzes the most similar case studies previously ruled on by the DSB, including the case of beef hormones and the case of genetically modified crops including biotech corn, both between the United States and the European Communities (EC). This study finds that science is largely subordinate to national interests in the case of state decision-making within the dispute settlement processes, and science has largely been relegated to a supportive role. Due to the ambiguity and lack of truly decisive decisions in the Appellate Body in science-based trade disputes, this study concludes that the Appellate Body avoids taking a firm scientific position in cases where science is still inconclusive in any capacity. Due to the panel's unwillingness to establish expert review boards as it has the power to do, instead favoring an individual-based system so that all viewpoints can be heard, it has also developed a system with its own unique weaknesses. Similar to any court of law in which each opposing party defends its own interests, each side brings whatever scientific evidence it can to defend its position, incentivizing them to disregard scientific conclusions unfavorable to their position. With so many questions that can arise, combined with the problems of evolving science, questions of risk, and social concerns in democratic society, it is no wonder that the panel views scientific information provided by the experts as secondary to the legal and procedural issues. Despite being ruled against the EC on legal issues in two previous cases, the EC essentially won both times because the panel did not address whether its science was correct or not. This failure to conclusively resolve a debate over whose science is more scientific enabled the EC to simply fix the procedural issues, while continuing to enforce trade restrictions based on their scientific evidence. Based on the analysis of the two cases of disputes, Korea may also find itself guilty of imposing an unwarranted moratorium on Japan's fish exports, only to subsequently pass new restrictions on labelling and certification requirements because Japan may have much scientific evidence at its disposal. However, Korea might be able to create enough uncertainty in the panel to force them to rule exclusively on the legal issues of the case. This will then equip Korea, like the EC in the past, with a way of working around the ruling, by changing whatever legal procedure they need to while maintaining some, if not most, of its restrictions when the panel fails to address its case on scientific grounds.

• Korea Trade Review
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• v.42 no.4
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• pp.21-47
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• 2017

This study examines the effects of technological capability and domestic marketing capability of SMEs on the export market orientation, focusing on the moderating effect of market turbulence. This empirical analysis, based on surveys collected from 206 small and medium-sized firms located in Gwangju and Jeonnam provinces, yielded the following conclusions. First, technological capability of SMEs has a positive impact on export market orientation. This result not only is consistent with preceding studies but also suggests that when technological capability of SMEs is utilized as their own unique asset to reduce liability of smallness or liability of foreignness, the tendency to export might be increased. Second, domestic marketing capability of SMEs has a positive impact on export market orientation. This result suggests that as the domestic marketing capability of SMEs is used as prior knowledge reducing uncertainty to enter the overseas markets, the tendency to export might be increased. Third, as a result of examining moderating effect of market turbulence, it shows that market turbulence moderates the relationship between domestic marketing capability and export market orientation toward a negative(-) direction. That is, since market turbulence might weaken the relationship between domestic marketing capability and export market orientation, SMEs which belong to the industry considering marketing capability important need to develop strategy with consideration for market turbulence. This study provides theoretical and practical implications in that it reveals factors positively affecting export market orientation and market turbulence can be utilized as a moderator.

• Korean Journal of Remote Sensing
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• v.39 no.3
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• pp.257-268
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• 2023

Sea ice plays an important role in Earth's climate by regulating the amount of solar energy absorbed and controlling the exchange of heat and material across the air-sea interface. Its growth, drift, and melting are monitored on a regular basis by satellite observations. However, low-resolution products with passive microwave radiometer have reduced accuracy during summer to autumn when the ice surface changes rapidly. Synthetic aperture radar (SAR) observations are emerging as a powerful complementary, but previous researches have mainly focused on winter ice. In this study, sea ice drift tracking was evaluated and analyzed using SAR images and tracker with global positioning system (GPS) during late summer-early autumn period when ice surface condition changes a lot. The results showed that observational uncertainty increases compared to winter period, however, the correlation coefficient with GPS measurements was excellent at 0.98, and the performance of the ice tracking algorithm was proportional to the sea ice concentration with a correlation coefficient of 0.59 for ice concentrations above 50%.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.5D
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• pp.453-459
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• 2010

In the study of traffic safety, it is utmost important to obtain more reliable estimates of the expected crashes for a site (or a segment). The observed crashes have been mainly used as the estimate of the expected crashes in Korea, while the empirical Bayes (EB) estimates based on the Poisson-gamma mixture model have been used in the USA and several European countries. Although numerous studies have used the EB method for estimating the expected crashes and/or the effectiveness of the safety countermeasures, no past studies examine the difference in the estimation errors between the two estimates. Thus, this study compares the estimation errors of the two estimates using a Monte Carlo simulation study. By analyzing the crash dataset at 3,000,000 simulated sites, this study reveals that the estimation errors of the EB estimates are always less than those of the observed crashes. Hence, it is imperative to incorporate the EB method into the traffic safety research guideline in Korea. However, the results show that the differences in the estimation errors between the two estimates decrease as the uncertainty of the prior distribution increases. Consequently, it is recommended that the EB method be used with reliable hyper-parameter estimates after conducting a comprehensive examination on the estimated negative binomial model.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.6D
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• pp.859-869
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• 2008

These days, almost every industry's production line has become automatic and this phenomenon brought a lot of benefits such as increase in productivity and economical effect, assurance in industrial safety, better quality and compatibility. However, unlike industrial production line, in construction industry, automation has number of barriers like uncertainty incidents and intellectual judgment to make ability to make solution out of it. Therefore construction industry is still demanding use of construction machine through labor. Due to this matter operational labor in construction industry is aging and fading. To solve these problem, in developed nations like Europe, US or Japan are keep researching for the automation in construction and road pavement, strengthening and some other simple operations have been worked through automation but in civil engineering site, automation research is still low despite of its importance in constructional site. For automating civil engineering operation, effective operational plan have to be set by analyzing ground information acquainted. If skillful worker apply heuristics, trial & error can be reduced with increased safety and the effective work plan can be established. Hence, this research will introduce Intellectual Task Planning System for Intelligent Excavating System's effective work plan and heuristics applied in each steps.