• PNF and Movement
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• v.12 no.2
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• pp.97-106
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• 2014

Purpose: The purpose of this study was to investigate changes in EEG through attention. Concentration training and performing tasks are important factors in the improvement of motor learning ability. Methods: In the experiment, 22 healthy people were divided into two groups: the trail making test (TMT) group and the computerized neurocognitive function test (CNT) group. A one-way Neuro Harmony M test to see whether there was a significant difference among the groups. Results: The TMT group showed a significant increase in ${\alpha}$ wave, ${\alpha}$ wave sequence, and ${\beta}$ wave sequence; however, there were no significant differences in SMR wave, SMR wave sequence, and ${\beta}$ wave. The CNT group showed increases in ${\alpha}$ wave, ${\alpha}$ wave sequence, SMR wave, SMR wave sequence, and ${\beta}$ wave sequence; however, there was no significant difference in ${\beta}$ wave. In EEGs before and after two performance tasks were changed, there were significant differences in ${\beta}$ wave, SMR wave, SMR wave sequence; however, there were no significant differences in ${\alpha}$ wave sequence, ${\beta}$ wave, and ${\beta}$ wave sequence. Conclusion: Attention training and concentration training offer feedback and repetition for constant stimulus and response. Moreover, attention training and concentration training can contribute to new studies and motivation by developing fast sensory and motor skills through acceptable visual and auditory stimulation.

• Journal of Fisheries and Marine Sciences Education
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• v.26 no.5
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• pp.1013-1025
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• 2014

Marine meterological characteristics off the coast in the East Sea between 2006 and 2013 were investigated by comparing the high wind-wave alert and moored-measured significant wave high. Monthly and yearly variations of the high wind-wave alert duration off the coast in the central part of the East Sea are correlated with those of the significant wave height measurement with their minima in June and 2008 and maxima in December and 2012. Both the high wind-wave alert duration and significant wave height increase remarkably during 2010-2013 when compared with during 2006-2009. The remarkable increase, occurring dominantly in December, seems to be related with Arctic oscillation variability. However, the comparisons reveal that only about a half of high wind-wave alerts satisfy the criteria for issuing the high wind-wave alert. To issue the high wind-wave alert, the wind speed at the sea should exceed 14 m/s or the significant wave height should be higher than 3 m. The high wind-wave alerts unsatisfying the significant wave height criteria are issued mainly during spring and summer. These results imply that additional surface buoy moorings in the open basin of the East Sea are necessary for more accurate issue of the high wind-wave alert.

• Journal of Ocean Engineering and Technology
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• v.21 no.1 s.74
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• pp.7-17
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• 2007

Based on the Boussinesq wave model, the wave distribution in the Chagui-Do sea area in Jeju was simulated by applying the directional irregular waves at an incident boundary. The time and spatial variations of monthly mean wave height and period were investigated, which aims to provide basic information on optimal sites for wave power generation. The grid size and time interval of the Boussinesq wave model were validated by examining wave distributions around a surface piercing wall, fixed at sea bottom with a constant slope. Except for the summer season, the significant wave height is dominated by wind waves and appears to be relatively high at the north sea of Chagui-Do, which is open to the ocean, while it is remarkably reduced at the rear sea of Chagui-Do because of its blocking effect on incident waves. In the summer, the significant wave height is higher at the south sea, and it is dominated by the swell waves, which is contributed by the strong south-west wind. The magnitude of significant wave height is the largest in the winter and the lowest in the spring. Annual average of the significant wave height is distinctively high at the west sea close to the Chagui-Do coast, due to a steep variation of water depth and corresponding wave focusing effect. The seasonal and spatial distribution of the wave period around Chagui-Do sea reveals very similar characteristics to the significant wave height. It is suggested that the west sea close to the Chagui-Do coast is the mast promising site for wave power generation.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.16 no.3
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• pp.178-189
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• 2004

For designing a reliable harbor, a methodology for estimating design waves of 97.5% operable harbor condition is suggested using long-term wave data. For a practical application of the methodology, a marine police harbor was selected as a site. Wave data used were collected from February 1993 to December 2003 at Jodo wave gage station in front of Pusan harbor. Joint distributions of significant wave height and significant wave period for specified wave directions were obtained and used to feed as input waves for parabolic mild-slope wave model. Results showed that input waves with significant wave height of 1.75 m, significant wave period off sec and wave direction E yield design waves height of 1.06 m at the site of interests, which is a 97.5% operable harbor condition. Wind waves generated inside harbor showed to be no effect on the design wave condition. Swells propagated from deep water into harbor are shown to be dominant effects on the design waves of operable harbor condition.

• Journal of the Korean Society for Marine Environment & Energy
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• v.15 no.4
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• pp.357-362
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• 2012

Despite the Wave observations data is very important information to human life at sea, the technology development and research for wave equipments are lacking. In this study, the wave observation system using GPS was evaluated the quality of wave observation data by comparing of long-term observations. The result of the comparison of the acceleration sensor (Hippy-40) and GPS sensor (Mose-1000), the correlation coefficient of the significant wave height and significant wave periods is 0.997 and 0.990 respectively. Also in case of BIAS, the significant wave height is 0.014 m, the significant wave period is -0.212 sec. It makes no significant differences whether the acceleration sensor (Hippy-40) and GPS sensor (Mose-1000). These results of the wave observation data using GPS quality will be evaluated as very good.

• Journal of the Korean Society for Marine Environment & Energy
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• v.7 no.3
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• pp.137-145
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• 2004

Long-term wave distribution at Jeju sea is investigated by a numerical simulation based on the thirdgeneration wave model SWAN (Simulating WAves Nearshore). The Jeju sea which retains relatively high wave energy density among Korean coastal regions is considered to be a suitable site for wave power generation and the efficiency of wave power generation is closely related to local wave characteristics. The monthly mean of a large-scale long-term wave data from 1979 to 2002, which is provided by Korea Ocean Research & Development Institute. is used as the boundary condition of SWAN model simulation with 1km grid. An analysis of wave distribution concentrates on the seasonal variation and spatial distribution of significant wave heights, mean wave directions and mean wave periods. Significant wave heights are higher in winter and summer and the west sea of Jeju appears relatively higher than east's. The highest significant wave height occurs at the northeast sea in winter and the second highest significant wave height appears at the southeast sea in summer, while the significant wave heights in spring and autumn are relatively low but homogeneous. The distribution of wave directions reveals that except the rear region influenced by wave refraction, the northwest wave direction is dominant in summer and the southeast in winter. Wave periods are longer in summer and winter and the west sea of Jeju appears relatively longer than east's. The longest wave period occurs at the west sea in winter, and in summer it appears relatively homogeneous with a little longer period at the south sea.

• Journal of Environmental Science International
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• v.32 no.11
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• pp.841-852
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• 2023

In this study, the significant wave height and wave period of a specially designed observation system that connected two drifting buoys to an ocean data buoy was observed for 23 days from February 7 to 29, 2020, and the results were compared and analyzed. The results indicated that, in comparison to the ocean data buoy, the drifting buoy exhibited greater variability in significant wave height over shorter time intervals. The wave period of the ocean data buoy also appeared longer than that of the drifting buoy. The greater the observed significant wave height and wave period from both the ocean data and drifting buoys, the more pronounced the differences between the two observation instruments become. Moreover, the study revealed that the disparity in observation methods between the ocean data and drifting buoys did not significantly affect the significant wave height characteristics, as long as the period remained unchanged for up to half of the observation time.

• Journal of Ocean Engineering and Technology
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• v.35 no.5
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• pp.336-346
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• 2021

The prediction of wave conditions is crucial in the field of marine and ocean engineering. Hence, this study aims to predict the significant wave height through machine learning (ML), a soft computing method. The adopted metocean data, collected from 2012 to 2020, were obtained from the Korea Institute of Ocean Science and Technology. We adopted the feedforward neural network (FNN) and long-short term memory (LSTM) models to predict significant wave height. Input parameters for the input layer were selected by Pearson correlation coefficients. To obtain the optimized hyperparameter, we conducted a sensitivity study on the window size, node, layer, and activation function. Finally, the significant wave height was predicted using the FNN and LSTM models, by varying the three input parameters and three window sizes. Accordingly, FNN (W48) (i.e., FNN with window size 48) and LSTM (W48) (i.e., LSTM with window size 48) were superior outcomes. The most suitable model for predicting the significant wave height was FNN(W48) owing to its accuracy and calculation time. If the metocean data were further accumulated, the accuracy of the ML model would have improved, and it will be beneficial to predict added resistance by waves when conducting a sea trial test.

• Journal of the Korean Society for Marine Environment & Energy
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• v.12 no.2
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• pp.61-67
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• 2009

In this paper time series wave data which contain a freak wave is investigated. Various wave characteristics are compared between wave data with a freak wave and without. Among 24 hour wave data measured in the Yura Sea, two adjacent 30 min wave data with and without a freak wave are examined intensively. It is seen that the highest waves do not have the longest wave period. The wave period of the longest period waves is a little longer than the average wave period and much shorter than the significant wave period. Although the sea state is quite high, the Rayleigh distribution fits well to the probability of wave height. The characteristics of the wave spectra do not change much, but the nonlinearity increases for the wave data with a freak wave. The significant wave height without a freak wave is larger than that with a freak wave. Hence, the higher significant wave height does not always increase the probability of the occurrence of the freak waves.

• 한국신재생에너지학회:학술대회논문집
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• 2011.05a
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• pp.164.1-164.1
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• 2011

Previously, many researchers assessed nearshore wave energy in two ways. The first is a simulation with respect to the offshore wave time series to validate the wave buoy data and the wave model results, and the other is to simulate the representative waves of typical seasonal wave conditions. The former requires enormous computational time and effort. The latter yields inspection on the patterns for the spatial and temporal distribution of nearshore wave energy but tends to underestimates the amount of wave energy in the nearshore region owing to the correlation between the significant wave height and wave period. $\ddot{O}$zger et al. (2004) derived the stochastic wave energy formulation by introducing a correction factor explicitly in terms of the covariance of the wave energy and significant wave height. In this study, a correction factor was applied for the assessment of nearshore wave energy obtained by numerical simulation of wave transformation with respect to representative waves.