• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.1
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• pp.35-44
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• 2022

The V_S30 map is used as a key variable for site amplification in the ShakeMap, which predicts ground motion at any site. However, no V_S30 map considering Korean geology and geomorphology has been developed yet. To develop a proxy-based V_S30 map, we used 1,101 V_S profiles obtained from a geophysical survey and collected proxy layers of geological and topographical information for the Korean Peninsula. Then, V_S30 prediction models were developed using linear regression analysis for each geological age considering the distribution of V_S30. As a result, models depending on geomorphology were suggested per each geologic group, including Quaternary, Fill, Ocean, Mesozoic group and Precambrian. Resolution of map is doubled from that of V_S30 map by U.S. Geological Survey (USGS). Standard deviation of residual in natural log of proxy-based V_S30 map is 0.233, whereas standard deviation of slope-based USGS V_S30 map is 0.387. Therefore, the proxy-based V_S30 map developed in this study is expected to have less uncertainty and to contribute to predicting more accurately the ground motion amplitude.

• Korean Journal of Remote Sensing
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• v.38 no.5_3
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• pp.913-924
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• 2022

In this paper, we presented a database construction of undersea images for the Habitats of Ecklonia cava and Sargassum and conducted an experiment for semantic segmentation using state-of-the-art (SOTA) models such as High Resolution Network-Object Contextual Representation (HRNet-OCR) and Shifted Windows-L (Swin-L). The result showed that our segmentation models were superior to the existing experiments in terms of the 29% increased mean intersection over union (mIOU). Swin-L model produced better performance for every class. In particular, the information of the Ecklonia cava class that had small data were also appropriately extracted by Swin-L model. Target objects and the backgrounds were well distinguished owing to the Transformer backbone better than the legacy models. A bigger database under construction will ensure more accuracy improvement and can be utilized as deep learning database for undersea images.

• Journal of Korea Entertainment Industry Association
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• v.15 no.8
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• pp.107-116
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• 2021

In recent years, the research on audience satisfaction after watching programs has been carried out in various fields. However, there is no precedent for the study of simply analyzing the influencing factors of audience satisfaction with the newly established CCTV-9 channel. For CCTV-9, how to explore the strategy of industrial development based on the needs of the audience in the era of big data is a very important part. This article exploratively focuses on the influencing factors related to CCTV-9 audience satisfaction. Using questionnaires, 101 samples of the satisfaction with the channel of men and women of different ages, education backgrounds, majors, and incomes were collected to test, and 9 hypotheses were tentatively proposed as relevant influencing factors of channel satisfaction. Through empirical analysis, this research searches for the determinants. The reliability and validity of the measurement were properly analyzed, and all hypotheses were statistically tested. The empirical results show that: subject matter, program format, program scheduling, program broadcast time, channel advertising, simulcast series of documentaries, diversified communication platforms, brand image packaging and audience satisfaction are significantly positively correlated.

• Journal of Navigation and Port Research
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• v.46 no.4
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• pp.303-312
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• 2022

Bridges across waterways act as interference factors, that reduce the navigable water area from the perspective of navigation safety. To analyze the safety navigational width of ships navigating bridges across waterways, the optimal traffic distribution based on AIS data was investigated, and ships were classified according to size through k-means clustering. As a result of the goodness-of-fit analysis of the clustered data, the lognormal distribution was found to be close to the optimal distribution for Incheon Bridge and Busan Harbor Bridge. Also, the normal distributions for Mokpo Bridge and Machang Bridge were analyzed. Based on the lognormal and normal distribution, the analysis results assumed that the safe passage range of the vessel was 95% of the confidence interval, As a result, regarding the Incheon Bridge, the difference between the normal distribution and the lognormal distribution was the largest, at 64m to 98m. The minimum difference was 10m, which was revealed for Machang Bridge. Accordingly, regarding Incheon Bridge, it was analyzed that it is more appropriate to present a safety width of traffic by assuming a lognormal distribution, rather than suggesting a safety navigation width by assuming a normal distribution. Regarding other bridges, it was analyzed that similar results could be obtained using any of the two distributions, because of the similarity in width between the normal and lognormal distributions. Based on the above results, it is judged that if a safe navigational range is presented, it will contribute to the safe operation of ships as well as the prevention of accidents.

• Journal of Korean Society of Disaster and Security
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• v.16 no.1
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• pp.105-113
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• 2023

Jeollanam-do has 25 land-to-island and island-to-island bridges, the largest number in Korea. It is a local government rich in specialized marine and tourism resources centered on the archipelago and the sea bridges connecting them. However, in the case of sea-crossing bridges, when strong winds or typhoons occur, there is an issue that increases anxiety among users and local residents due to excessive vibration of the bridge, apart from structural safety of the bridge. In fact, in the case of Cheonsa Bridge in Shinan-gun, which was recently opened in 2019, vehicle traffic restrictions due to strong winds and excessive vibrations frequently occurred, resulting in complaints from local residents and drivers due to increased anxiety. Therefore, based on the data measured using IoT measurement technology, it is possible to relieve local residents' anxiety about the safety management of marine bridges by providing quantitative and accurate bridge vibration levels related to traffic and wind conditions of bridges in real time to local residents. This study uses the existing measurement system and IoT sensor to constantly observe the wind speed and vibration of the marine bridge, and transmits it to local residents and managers to relieve anxiety about the safety and traffic of the sea-crossing bridge, and strong winds and to develop technologies capable of preemptively responding to large-scale disasters.

• Geophysics and Geophysical Exploration
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• v.26 no.2
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• pp.84-93
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• 2023

The supervised learning-based deep-learning seismic inversion techniques have demonstrated successful performance in synthetic data examples targeting small-scale areas. The supervised learning-based deep-learning seismic inversion uses time-domain wavefields as input and subsurface velocity models as output. Because the time-domain wavefields contain various types of wave information, the data size is considerably large. Therefore, research applying supervised learning-based deep-learning seismic inversion trained with a significant amount of field-scale data has not yet been conducted. In this study, we predict subsurface velocity models using Laplace-domain wavefields as input instead of time-domain wavefields to apply a supervised learning-based deep-learning seismic inversion technique to field-scale data. Using Laplace-domain wavefields instead of time-domain wavefields significantly reduces the size of the input data, thereby accelerating the neural network training, although the resolution of the results is reduced. Additionally, a large grid interval can be used to efficiently predict the velocity model of the field data size, and the results obtained can be used as the initial model for subsequent inversions. The neural network is trained using only synthetic data by generating a massive synthetic velocity model and Laplace-domain wavefields of the same size as the field-scale data. In addition, we adopt a towed-streamer acquisition geometry to simulate a marine seismic survey. Testing the trained network on numerical examples using the test data and a benchmark model yielded appropriate background velocity models.

• Korea Trade Review
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• v.43 no.3
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• pp.125-145
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• 2018

The Baltic Shipping Exchange is reporting the Baltic Dry Index (BDI) which represents the average charter rate for bulk carriers transporting major cargoes such as iron ore, coal, grain, and so on. And the current BDI index is reflected in the proportion of capesize 40%, panamax 30% and spramax 30%. Like mentioned above, the capesize plays a major role among the various sizes of bulk carriers and this study is to analyze the influence of the factors influencing on charter rate of capesize carriers which transport iron ore and coal as the major cargoes. For this purpose, this study verified causality between variables using Vector Error Correction Model (VECM) and tried to derive a long-run equilibrium model between the dependent variable and independent variables. Regression analysis showed that every six independent variable has a significant effect on the capesize charter rate, even at the 1% level of significance. Charter rate decreases by 0.08% when capesize total fleet increases by 1%, charter rate increases by 0.04% when bunker oil price increases by 1%, and charter rate decreases by 0.01% when Yen/Dollar rate increases by 1%. And charter rate increases by 0.02% when global GDP increases by one unit (1%). In addition, the increase in cargo volume of iron ore and coal which are major transportation items of capesize carriers has also been shown to increase charter rates. Charter rate increases by 0.11% in case of 1% increase in iron ore cargo volume, and 0.09% in case of 1% increase in coal cargo volume. Although there have been some studies to analyze the influence of factors affecting the charterage of bulk carriers in the past, there have been few studies on the analysis of specific size vessels. At present moment when ship size is getting bigger, this study carried out research on capesize vessels, which are biggest among bulk carriers, and whose utilization is continuously increasing. This study is also expected to contribute to the establishment of trade policies for specific cargoes such as iron ore and coal.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.6D
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• pp.759-766
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• 2008

Road classification system is the first step for determining the road function and design standards. Currently, roads are classified by various indices such as road location and function. In this study, we classify road using various traffic indices as well as to identify traffic characteristics for each type of road. To accomplish the objectives, mixture model was applied for classifying road and analyzing traffic characteristics using traffic data that observed at permanent traffic count stations. A total of 8 variables were applied: annual average daily traffic(AADT), $K_{30}$ coefficient, heavy vehicle proportion, day volume proportion, peak hour volume proportion, sunday coefficient, vacation coefficient, and coefficient of variation(COV). A total of 350 permanent traffic count points were categorized into three groups : Group I (Urban road), Group II (Rural road), and Group III (Recreational road). AADT were 30,000 for urban, 16,000 for rural, and 5,000 for recreational road. Group III was typical recreational road showing higher average daily traffic volume during Sunday and vacational periods. Group I showed AM peak and PM peak, while group II and group III did not show AM peak and PM peak.

• Journal of the Korean earth science society
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• v.44 no.1
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• pp.79-89
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• 2023

The purpose of this study was to investigate the effects of engineering design-based ocean cleanup classes on STEAM attitudes and creative engineering problem-solving dispositions. Furthermore, during this process, we tried to determine interesting points that students encountered in engineering design-based classes. For this study, a science class with six lessons based on engineering design was developed and reviewed by a professor who majored in engineering design, along with five engineering design experts with a master's degree or higher. The subject of the class was selected as the design and implementation of scientific and engineering measures to reduce marine pollution based on the method implemented in an actual Ocean Clean-up Project. The engineering design process utilized the engineering design model presented by NGSS (2013), and was configured to experience redesign through the optimization process. To verify effectiveness, the STEAM attitude questionnaire developed by Park et al. (2019) and the creative engineering problemsolving propensity test tool developed by Kang and Nam (2016) were used. A pre and post t-test was used for statistical analysis for the effectiveness test. In addition, the contents of interesting points experienced by the learners were transcribed after receiving descriptive responses, and were analyzed and visualized through degree centrality analysis. Results confirmed that engineering design in science classes had a positive effect on both STEAM attitude and creative engineering problem-solving disposition (p< .05). In addition, as a result of unstructured data analysis, science and engineering knowledge, engineering experience, and cooperation and collaboration appeared as factors in which learners were interested in learning, confirming that engineering experience was the main factor.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2021.11a
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• pp.78-80
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• 2021

This study is based on Degree of Recognition and AHP surveys for experts, this study investigates changes in the demand of seafarers in response to changes in the shipping industry environment in which Maritime Autonomous Surface Ships(MASS) emerge according to the application of the fourth industrial revolution technology to ships, and it looks into changes in seafarers' skills. It also analyzes and proposes a plan for cultivating seafarers accordingly. As a result of Degree of Recognition and AHP analysis, it is analyzed that a new training system is required because the current training and education system may cover the job competencies of emergency response, caution and danger navigation, general sailing, cargo handling, seaworthiness maintenance, emergency response, and ship maintenance and management, but jobs such as remote control, monitoring diagnosis, device management capability, and big data analysis require competency for unmanned and shore based control.By evaluating the importance of change factors in the duties of seafarers in Maritime Autonomous Surface Ships, this study provides information on seafarers educational institutions response strategies for nurturing seafarers and prioritization of resource allocation, etc. The importance of factors was compared and evaluated to suggest changes in the duties of seafarers and methods of nurturing seafarers according to the introduction of Maritime Autonomous Surface Ships.It is expected that this study is meaningful as it systematically derived the duties and competency factors of seafarers of Maritime Autonomous Surface Ships from a practical point of view and analyzed the perception level of each relevant expert to diagnose expert-level responses to the introduction of Maritime Autonomous Surface Ships.