• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.10
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• pp.2292-2298
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• 2010

A mashup is a web page or application that uses and combines information, contents or Open APIs available on the web to create a new service. The mashup developed by the need not combination of simple information can contribute to new added-values with practicality and convenience. Thus, in this paper, we want to develop a RIA-based dynamic mashup service for the users considering weather forecast and marine information importantly. We design and implement the system that it can register a number of information about a domain dynamically through registration process based on the map and present a mark of domain location on the map and the information including internal environment, external environment and weather of related to the domain within a webpage. Implemented service need not require a tedious process visiting other web sites every time to confirm the relevant information because we can see simultaneously related information with a map within a page.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.42 no.2
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• pp.78-85
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• 2006

A survey on the fishing gear for octopus drift-line fishing was done in Gangwon-do, Sacheon, Gyeongnam and Hokkaido, Japan, while a survey on the environments of fishing grounds used data from January to August from the Korea east coast farming forecast system of Donghae Fisheries Research and Development Institute. The present situation of fishing was examined with boats engaging in drift-line fishing from March to August in the coastal waters along Gangneung. The fishing tackle for octopus drift-line fishing was made manually, and the size, shape, and weight of the hook and number of shooting used vary according to the fishing time and region. Lead is used as the material for sinkers. As bait, pork fat with skin is mostly used in Gangwon-do. The temperature of the bottom water layer in the coastal fishing ground of Gangneung from April to June ranges from $3.2-12.4^{\circ}C$, which is the optimal temperature for octopuses. During July and August, the temperature ranges from $5.0-20.6^{\circ}C$. The maximum difference between day and night temperatures reached up to $9.2^{\circ}C$. Salinity is generally stable at $33.2-35.324.6%_{\circ}$, which does not affect the inhabitation of octopuses. The octopus catch reached its peak from May to July, while most octopuses weighed less than 1 kg (76.7%). The results show that it is effective to carry out octopus drift-line fishing up to a depth of 40 meters; and that the maximum number of octopuses per line is obtained with an operation time of six hours.

• Journal of Ocean Engineering and Technology
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• v.22 no.3
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• pp.8-17
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• 2008

Wrenching climatic changes due to ecocide and global wanning are producing a natural disaster. Coastal zones have been damaged by typhoons and accompanying storm surges. Severe waves, and destruction of the environment are adding to the severity of coastal disasters. There has been an increased interest in these coastal zone problems, and associated social confusion, after the loss of life and terrible property damage caused by typhoon Maemi. Especially if storm surges coincide with high ticks, the loss of life and property damage due to high waters are even worse. Therefore, it is desirable to accurately forecast not only the timing of storm surges but also the amount water level increase. Such forecasts are very important from the view point of coastal defense. In this study, using a numerical model, storm surge was simulated to examine its fluctuation characteristics for the coastal area behind Masan Bay, Korea. In the numerical model, a moving boundary condition was incorporated to explain wave run-up. Numerically predicted inundation regimes and depths were compared with measurements from a field survey. Comparisons of the numerical results and measured data show a very good correlation. The numerical model adapted in this study is expected to be a useful tool for analysis of storm surges, and for predicting inundation regimes due to coastal flooding by severe water waves.

• Journal of Ocean Engineering and Technology
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• v.22 no.2
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• pp.28-33
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• 2008

From the 1997 to January, 2004, a groin 156m long was constructed at the mouth of the Heoya river-mouth as a protection and barrier. To understand the changes to Jinha beach from the blockade of the river mouth, several aerial photographs, etc., were compared, which showed that the changes were significant. Comparing these results to the state of the area before construction of the groin, the blockade of the river was relaxed, but the formation of the tombolo, in the middle groin area was accelerated and the total Jinha beach erosion and especially the erosion of the southern part of Jinha beach was developed. But according to statements by residents and some current documents, the blockade of the Heoya-river mouth is still underway at the surrounding areas of the groin and chronic dredged sand has been used for littoral nourishment at the northern part of the middle groin and on Jinha beach. The result of numerical simulation based on the present state shows that if this sort of dredging is stopped, the sand accumulation will progress near the river mouth groin and the existing tombolo at the middle groin will progress to the north and severe erosion will occur at the southern coastline near the middle groin and the farthest southern part of Jinha beach, and Jinha beach itself will experience a gradual erosion. The main reason for these erosions should be the typhoons that are happening during the summer season. To provide protection from these kinds of undesirable erosions, a total of 23 numerical simulations have been done. It has been shown that submerged breakwaters at the front area of the beach will be efficient to protect from main beach erosion, but there should be alternative proposals for the influence of the river mouth blockade.

• Journal of Navigation and Port Research
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• v.44 no.6
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• pp.564-570
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• 2020

In order to propose a realistic demand forecast for harbor pilots, define a direction for securing a supply of pilots for the betterment of national logistic services, and ensure the competitiveness of Korean ports, this study intended first to propose a new forecasting process for harbor pilot requirements through conducting analysis of determining factors affecting harbor pilot demand. Additionally, analyzing relevant previous studies allowed us to estimate the number of pilots required in the past and asses the studies limitations. Our second purpose was to propose a more stable allocation method among different pilot areas after forecasting the demand of harbor pilots until 2027 through application of the new forecasting process. From this application, the total number of pilots required was forecasted at 270, suggesting the total demand for harbor pilots will be increased by 7.57% compared with 251 pilots in 2018.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.32 no.6
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• pp.465-480
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• 2020

Numerical simulations of the storm surge and the wave induced by the Typhoon Sanba incident on the south coast of Korea in 2012 are conducted using the JMA-MSM forecast weather field, NCEP-CFSR reanalysis weather field, ECMWF-ERA5 reanalysis weather field, and the pressure and wind fields obtained using the best track information provided by JTWC. The calculated surge heights are compared with the time history observed at harbors along the coasts of Korea. For the waves the calculated significant wave heights are compared with the data measured using the wave buoys and the underwater pressure type wave gauge. As a result the JMA-MSM and the NCEP-CFSR weather fields give the highest reliability. The ECMWF-ERA5 gives in general surge and wave heights weaker than the measured. The ECMWF-ERA5, however, reproduces the best convergence belt formed in front of the typhoon. The weather field obtained using JTWC best track information gives the worst agreement.

• Journal of Korean Society for Quality Management
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• v.50 no.4
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• pp.701-716
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• 2022

Purpose: This study aims to predict the dry cargo transportation market economy. The subject of this study is the BDI (Baltic Dry Index) time-series, an index representing the dry cargo transport market. Methods: In order to increase the accuracy of the BDI time-series, we have pre-processed the original time-series via time-series decomposition and data augmentation techniques and have used them for ANN learning. The ANN algorithms used are Multi-Layer Perceptron (MLP), Recurrent Neural Network (RNN), and Long Short-Term Memory (LSTM) to compare and analyze the case of learning and predicting by applying time-series decomposition and data augmentation techniques. The forecast period aims to make short-term predictions at the time of t+1. The period to be studied is from '22. 01. 07 to '22. 08. 26. Results: Only for the case of the MAPE (Mean Absolute Percentage Error) indicator, all ANN models used in the research has resulted in higher accuracy (1.422% on average) in multivariate prediction. Although it is not a remarkable improvement in prediction accuracy compared to uni-variate prediction results, it can be said that the improvement in ANN prediction performance has been achieved by utilizing time-series decomposition and data augmentation techniques that were significant and targeted throughout this study. Conclusion: Nevertheless, due to the nature of ANN, additional performance improvements can be expected according to the adjustment of the hyper-parameter. Therefore, it is necessary to try various applications of multiple learning algorithms and ANN optimization techniques. Such an approach would help solve problems with a small number of available data, such as the rapidly changing business environment or the current shipping market.

• Journal of the Korean Society for Marine Environment & Energy
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• v.7 no.4
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• pp.207-215
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• 2004

Recently, securing a vast land in the land region becomes more difficult and efforts to seek its alternation in the sea area have been increased. As a consequence, the coastal region has been faced to extensive beach erosion problems. In planning offshore structures such as artificial islands, it is necessary to forecast the influence of the structure construction exerting on the beach erosion of the adjacent coast. In the present study, the sediment movement pattern behind offshore structure was examined through a series of three dimensional movable bed experiments, so as to develop the numerical model which forecasts morphological change including beach erosions. The experimental results reveal that the sediment movement patterns of the beach line side and the depth region are separated at a certain boundary line. In details, at the beach side including swash zone the sediment movement becomes dominant, which is governed by a relation between depth contours and incident wave directions, while at the depth region the bed load and suspended load due to the orbit motion of waves are carried by nearshore currents, and both movements are clearly separated at a specified boundary that is related to partial standing wave from the beach. It is expected that these results can be effectively used for verification of a numerical model on morphological change of the coast.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.34 no.2
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• pp.117-134
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• 1998

The study on the Assembling Mechanism of the Hairtail, Trichiurus lenpturus, at the Fishing Grounds of the Cheju Strait had been investigated by analyzing the relationship of the oceanographic conditions and the fishing ground of the Hairtail in the Cheju Strait. 1. The fishing grounds of the hairtail at the Cheju Strait are formed at the bottom of a high temperature of the tidal front at the coast. area of northern Cheju Island, the tip of the linguiform is high in salinity at the eastern and western entrances of Cheju Island, low salinity eddy on the surface and its surrounding front, various water masses in the Strait and coastal waters of the South Sea in Korea. 2. The fishing grounds of the Hairtail at the Cheju Strait begins with the sea surface temperature higher than $15^{\circ}C$ and the incoming of low salinity water now from the East China Sea. 3. Estimation of optimum temperature and salinity per season based upon analysis for relationship between temperature of water and salinity of the bottom layer and the catch is : 15.2~$16.4^{\circ}C$, 34.20~34.40${\textperthousand}$ in spring(June); 14.4~ $17.0^{\circ}C$, 33.70~34.30${\textperthousand}$ in summer(July~September); and 15.7~ $18.6^{\circ}C$, 33.70~34.50$\textperthousand$ in autumn(October~December). Hairtail are mostly caught at the Yellow Sea Warm Current and Tsushima Current with temperature over $14.5^{\circ}C$ and salinity over 33.70${\textperthousand}$ at the bottom layers of the Cheju Strait. 4. Considering the relationship between the amount of hairtail catch and the water temperature of bottom layer, when the bottom water being above $14.0^{\circ}C$ flowed into Cheju Strait through the western entrance of the strait in summer, the ca-h appears to have been abundant. In contrast, the catch has been poor when the temperature of such water was recorded to be below $13^{\circ}C$ Therefore, distribution patterns of water at the bottom layer can be used as a forecast index whether the catch of a certain year will be good or poor.

• Journal of Navigation and Port Research
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• v.44 no.3
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• pp.187-194
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• 2020

It is very important to forecast freight volume accurately to establish major port policies and future operation plans. Thus, related studies are being conducted because of this importance. In this paper, stepwise regression analysis and artificial neural network model were analyzed to compare the predictive power of each model on Gwangyang Port, the largest domestic port for coal and iron ore transportation. Data of a total of 121 months J anuary 2009-J anuary 2019 were used. Factors affecting coal and iron ore trade volume were selected and classified into supply-related factors and market/economy-related factors. In the stepwise regression analysis, the tonnage of ships entering the port, coal price, and dollar exchange rate were selected as the final variables in case of the Gwangyang Port coal volume forecasting model. In the iron ore volume forecasting model, the tonnage of ships entering the port and the price of iron ore were selected as the final variables. In the analysis using the artificial neural network model, trial-and-error method that various Hyper-parameters affecting the performance of the model were selected to identify the most optimal model used. The analysis results showed that the artificial neural network model had better predictive performance than the stepwise regression analysis. The model which showed the most excellent performance was the Gwangyang Port Coal Volume Forecasting Artificial Neural Network Model. In comparing forecasted values by various predictive models and actually measured values, the artificial neural network model showed closer values to the actual highest point and the lowest point than the stepwise regression analysis.