• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.4
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• pp.457-464
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• 2021

Cargo securing safety, which is one factor for the safe operation of car ferry ships, has been applied since 2015 and evaluated by comparing the hull motion and securing load capacity generated by waves. To ensure the safe operation of the 3700 ton class car ferry, it is important to analyze the hull acceleration motion based on the sea wave information of the navigation area to determine the cargo securing load that can prevent the movement of cargo. In this study, the meteorological information of three wave buoys installed in Busan and Jeju area was analyzed for the past 5 years. In addition, the hull acceleration was measured in actual sea conditions and compared to that of numerical simulations. Under the condition of a significant wave height of 2.5 m from Feb to Mar, except typhoon seasons, the lateral acceleration was observed to be 1.5 m/s² in real ship measuring and 1.8 m/s² in numerical calculation. It was analyzed to be less than 40% under general weather conditions compared to the high wave warning using an approximate formula for estimating the hull motion by wave height. The cargo securing safety proposed in this study will be widely used based on the actual measuring acceleration with the sea wave height.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.10
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• pp.1331-1340
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• 2020

Object detection in maritime means that the captain detects floating objects that has a risk of colliding with the ship using the computer automatically and as accurately as human eyes. In conventional ships, the presence and distance of objects are determined through radar waves. However, it cannot identify the shape and type. In contrast, with the development of AI, cameras help accurately identify obstacles on the sea route with excellent performance in detecting or recognizing objects. The computer must calculate high-volume pixels to analyze digital images. However, the CPU is specialized for sequential processing; the processing speed is very slow, and smooth service support or security is not guaranteed. Accordingly, this study developed maritime object detection software and implemented it with FPGA to accelerate the processing of large-scale computations. Additionally, the system implementation was improved through embedded boards and FPGA interface, achieving 30 times faster performance than the existing algorithm and a three-times faster entire system.

• 한국노년학
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• v.40 no.1
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• pp.147-161
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• 2020

The purpose of this research is to investigates 10-year trajectories of cognitive functions among older adults in their 70s to understand changes in cognitive functions as a continuum until very late life. This study also examines differences in trajectories of cognitive functions by gender and by changes in marital status, especially widowhood. Among participants of the Korean Longitudinal Study of Ageing(KLoSA), the sample of this study includes 800 older adults in their 70s during the first study wave (2006) and those who reported their cognitive functions for six consecutive study waves (2006, 2008, 2010, 2012, 2014, and 2016). The analyses were conducted in two steps. First, we conducted Latent Class Growth Analyses(LCGA) to investigated heterogeneous trajectories of cognitive functions in 10 years. Then, we performed multinomial logistic regression. Three heterogeneous trajectories of cognitive functions were identified. One group of 48.7% of older adults showed high cognitive function at baseline and maintained it over 10 years. Second group of 14.7% of older adults reported low cognitive function scores at baseline and showed continuous decline over time. Third group of 36.6% were showed mid-level cognitive functions and maintained their functions over time. We also found significant gender differences but not significant differences in marital status when we consider both in our model; however, the we found significant differences in changes in marital status when we did not consider gender in the model. The results suggest that the importance of considering dynamics of gender and changes in marital status to understand changes in cognitive functions in later life.

• The Journal of Engineering Geology
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• v.31 no.4
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• pp.507-522
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• 2021

Specific survey objectives often cannot be met using only one geophysical method, as each method's results are influenced by the specific physical properties of subsurface materials. In particular, areas susceptible to geological hazards require investigation using more than one method in order to reduce risks to life and property. Instead of analyzing the results from each method separately, this work develops a four-quadrant criterion for classifying areas of levees as safe or weak. The assessment is based on statistically determined thresholds of seismic velocity (P-wave velocity from seismic refraction and S-wave velocity from multichannel analysis of surface waves) and electrical resistivity. Thresholds are determined by subtracting the standard deviation from the mean during performance testing of this correlation technique applied to model data of four horizontal and inclined fracture zones. Compared with results from the crossplot of resistivity and P-wave velocity, crossplot analysis using resistivity and S-wave velocity data provides more reliable information on the soil type, ground stiffness, and lithological characteristics of the levee system. A loose and sandy zone (represented by low S-wave velocity and high resistivity) falling within the second quadrant is interpreted to be a weak zone. This interpretation is well supported by the N values from standard penetrating test for the central core.

• Korean Journal of Remote Sensing
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• v.39 no.1
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• pp.77-86
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• 2023

Ship detection is widely used in areas such as maritime security, maritime traffic, fisheries management, illegal fishing, and border control, and ship detection is important for rapid response and damage minimization as ship accident rates increase due to recent increases in international maritime traffic. Currently, according to a number of global and national regulations, ships must be equipped with automatic identification system (AIS), which provide information such as the location and speed of the ship periodically at regular intervals. However, most small vessels (less than 300 tons) are not obligated to install the transponder and may not be transmitted intentionally or accidentally. There is even a case of misuse of the ship'slocation information. Therefore, in this study, ship detection was performed using high-resolution optical satellite images that can periodically remotely detect a wide range and detectsmallships. However, optical images can cause false-alarm due to noise on the surface of the sea, such as waves, or factors indicating ship-like brightness, such as clouds and wakes. So, it is important to remove these factors to improve the accuracy of ship detection. In this study, false alarm wasreduced, and the accuracy ofship detection wasimproved by removing wake.As a ship detection method, ship detection was performed using machine learning-based random forest (RF), and convolutional neural network (CNN) techniquesthat have been widely used in object detection fieldsrecently, and ship detection results by the model were compared and analyzed. In addition, in this study, the results of RF and CNN were combined to improve the phenomenon of ship disconnection and the phenomenon of small detection. The ship detection results of thisstudy are significant in that they improved the limitations of each model while maintaining accuracy. In addition, if satellite images with improved spatial resolution are utilized in the future, it is expected that ship and wake simultaneous detection with higher accuracy will be performed.

• Journal of the Korean Geotechnical Society
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• v.38 no.11
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• pp.149-161
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• 2022

This study selected the indexes for evaluating the damage of the railway embankments due to liquefaction from the earthquake damage cases of railway embankments. The study correlated the selected indexes and the settlement of the embankment crest from the dynamic numerical analysis. Further, the correlation was used to develop a method for evaluating the liquefaction damage to the railway embankment. The damage cases and damage types were analyzed, and referring to the liquefaction damage assessment method for other structures, the embankment height (H), the non-liquefiable layer thickness (H₁), and the liquefaction potential index were selected as indexes for evaluating the damage. The study performed dynamic effective stress analyses on the railway embankment, and the PM4-Sand model was applied as the constitutive liquefaction model for the embankment foundation ground. The model's validity was first verified by comparing it with the existing dynamic centrifugal model test results performed on the railway embankment. Nine sites where the foundation ground can be liquefied were selected from the data of 549 embankments of the Honam High-speed Railway in Korea. Further, dynamic numerical analyses using four seismic waves as input earthquake load were performed for the selected site sections. The numerical analysis results confirmed the correlation between the evaluation indexes and the embankment crest settlement. A method for efficiently evaluating the damage to the embankment due to liquefaction was proposed using the chart obtained from this correlation.

• Journal of Korea Water Resources Association
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• v.55 no.8
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• pp.565-575
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• 2022

Recently, in the field of water resource engineering, interest in predicting time series water levels and flow rates using deep learning technology that has rapidly developed along with the Fourth Industrial Revolution is increasing. In addition, although water-level and flow-rate prediction have been performed using the Long Short-Term Memory (LSTM) model and Gated Recurrent Unit (GRU) model that can predict time-series data, the accuracy of flow-rate prediction in rivers with rapid temporal fluctuations was predicted to be very low compared to that of water-level prediction. In this study, the Paldang Bridge Station of the Han River, which has a large flow-rate fluctuation and little influence from tidal waves in the estuary, was selected. In addition, time-series data with large flow fluctuations were selected to collect water-level and flow-rate data for 2 years and 7 months, which are relatively short in data length, to be used as training and prediction data for the LSTM and GRU models. When learning time-series water levels with very high time fluctuation in two models, the predicted water-level results in both models secured appropriate accuracy compared to observation water levels, but when training rapidly temporal fluctuation flow rates directly in two models, the predicted flow rates deteriorated significantly. Therefore, in this study, in order to accurately predict the rapidly changing flow rate, the water-level data predicted by the two models could be used as input data for the rating curve to significantly improve the prediction accuracy of the flow rates. Finally, the results of this study are expected to be sufficiently used as the data of flood warning system in urban rivers where the observation length of hydrological data is not relatively long and the flow-rate changes rapidly.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.32-32
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• 2023

Incidences of urban flood and extreme heat waves (due to the urban heat island effect) are expected to increase in New Zealand under future climate change (IPCC 2022; MfE 2020). Increasingly, the mitigation of such events will depend on the resilience of a range Nature-Based Solutions (NBS) used in Sustainable Urban Drainage Schemes (SUDS), or Water Sensitive Urban Design (WSUD) (Jamei and Tapper 2019; Johnson et al 2021). Understanding the impact of changing precipitation and temperature regimes due climate change is therefore critical to the long-term resilience of such urban infrastructure and design. Cuthbert et al (2022) have assessed the trade-offs between the water retention and cooling benefits of different urban greening methods (such as WSUD) relative to global location and climate. Using the Budyko water-energy balance framework (Budyko 1974), they demonstrated that the potential for water infiltration and storage (thus flood mitigation) was greater where potential evaporation is high relative to precipitation. Similarly, they found that the potential for mitigation of drought conditions was greater in cooler environments. Subsequently, Jaramillo et al. (2022) have illustrated the locations worldwide that will deviate from their current Budyko curve characteristic under climate change scenarios, as the relationship between actual evapotranspiration (AET) and potential evapotranspiration (PET) changes relative to precipitation. Using the above approach we assess the impact of future climate change on the urban water-energy balance in three contrasting New Zealand cities (Auckland, Wellington, Christchurch and Invercargill). The variation in Budyko curve characteristics is then used to describe expected changes in water storage and cooling potential in each urban area as a result of climate change. The implications of the results are then considered with respect to existing WSUD guidelines according to both the current and future climate in each location. It was concluded that calculation of Budyko curve deviation due to climate change could be calculated for any location and land-use type combination in New Zealand and could therefore be used to advance the general understanding of climate change impacts. Moreover, the approach could be used to better define the concept of urban infrastructure resilience and contribute to a better understanding of Budyko curve dynamics under climate change (questions raised by Berghuijs et al 2020)). Whilst this knowledge will assist in implementation of national climate change adaptation (MfE, 2022; UNEP, 2022) and improve climate resilience in urban areas in New Zealand, the approach could be repeated for any global location for which present and future mean precipitation and temperature conditions are known.

• Journal of International Area Studies (JIAS)
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• v.13 no.1
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• pp.135-156
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• 2009

The two waves of EU enlargement in 2004 and 2007, have been milestones of European integration. While research has been conducted into the impact of these events on both the European and the global economies,1 there have been few attempts to assess the effects of EU enlargement and the introduction of the euro on countries such as Russia, which neighbour the EU but currently have no perspective of accession. This paper aims to provide an assessment of the effects that EU enlargement and the introduction of the euro have had on Russia, the largest country neighbouring the EU. In particular, it focuses on trade and investment links between the EU and Russia, as well as the use of the energy by Russian residents and authorities. Economic links between Russia and the EU are found to have strengthened considerably in the areas of trade, investment and other financial flows in recent years. Strong growth, particularly in Russia, as well as the high price of oil and gas, Russia's major export items, has facilitated this expansion of trade and finance. Moreover, available data do not suggest that EU enlargement has had a negative impact on Russia in terms of trade or investment diversion. Thus, the strategic partnership between Russia and the EU has been increasingly underpinned by an expansion of cross-border economic activities. Thus, the paper contributes to two broad strands of literature on this subject, namely the impact of regional trade and economic arrangements on non-member countries and the international role of currencies.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.288-290
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• 2022

As part of the SOC digitization for smart water management and flood prevention, the government reported that automatic and remote control system for drainage facilities (180 billion won) to 57% of national rivers and established a real-time monitoring system (30 billion won). In addition, they were also planning to establish a smart dam safety management system (15 billion won) based on big data at 11 regions. Therefore, research is needed for smart water management and flood prevention system that can accurately calculate the flow rate through real-time flow rate measurement of rivers. In particular, the most important thing to improve the system implementation and accuracy is to ensure the accuracy of real-time flow rate measurements. To this end, radar sensors for measuring the flow rate of electromagnetic waves in the United States and Europe have been introduced and applied to the system in Korea, but demand for improvement of the system continues due to high price range and performance. Consequently, we would like to propose an improved flow rate measurement and flood forecast system by developing a radar sensor for measuring the electromagnetic surface current meter for real-time flow rate measurement.