• Ocean and Polar Research
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• v.43 no.4
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• pp.321-334
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• 2021

'Marine mammals-based observations' refers to data acquisition activities from marine mammals by instrumenting CTD (Conductivity-Temperature-Depth) sensors on them for recording vertical profiles of ocean variables such as temperature and salinity during animal diving. It is a novel data collecting platform that significantly improves our abilities in observing extreme environments such as the Southern Ocean with low cost compared to the other conventional methods. Furthermore, the system continues to create valuable information until sensors are detached, expanding data coverage in both space and time. Owing to these practical advantages, the marine mammals-based observations become popular to investigate ocean circulation changes in the Southern Ocean. Although these merits may bring us more opportunities to understand ocean changes, the data should be carefully qualified before we interpret it incorporating shipboard/autonomous vehicles/moored CTD data. In particular, we need to pay more attention to salinity correction due to the usage of an unpumped-CTD sensor tagged on marine mammals. In this article, we introduce quality control methods for the marine mammals-based CTD profiles that have been developed in recent studies. In addition, we discuss strategies of quality control specifically for the seal-tagging CTD profiles, successfully having been obtained near Terra Nova Bay, Ross Sea, Antarctica since February 2021. It is the Korea Polar Research Institute's research initiative of animal-borne instruments monitoring in the region. We anticipate that this initiative would facilitate collaborative efforts among Polar physical oceanographers and even marine mammal behavior researchers to understand better rapid changes in marine environments in the warming world.

• 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 information and communication convergence engineering
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• v.8 no.1
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• pp.6-12
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• 2010

In this paper a cross layer protocol, referred to as an underwater ad-hoc communication (UAC) protocol, is proposed for underwater acoustic networks (UANets). An underwater node (UN), which tries to transfer data to another UN or a buoy in ad-hoc manner, can access channel as well as determine routing path by employing the UAC protocol. The channel access, route determination, and reliable data transfer are designed being adaptive to underwater environments. In addition, we propose both UN and packet architectures in order to efficiently implement the UAC protocol for UANets.

• Journal of Ocean Engineering and Technology
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• v.18 no.1
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• pp.10-15
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• 2004

For effective conservation of the oceans and harbors, long-term and systematic development of the ocean and harbor monitoring system is essential. A monitoring system capable of real-time and accurate data acquisition is necessary for dealing with the level of contamination by situations, such as red tide and foods. This paper introduces an effective and economical real-time harbor environmental monitoring system that utilizes PCS wireless data communication technology. The monitoring system has various functions, such as multiple communication, TCP/IP protocol for wireless internet access, system time synchronization, and bi-directional communication between the measuring device and the server. The system has been implemented at Shinseondae harbor pier in Busan to validate the system's stability and effectiveness in data acquisition. The acquired real-time ocean and harbor environmental data is expected to have a large effect, when shared with the public through the Internet.

• Ocean and Polar Research
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• v.44 no.4
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• pp.287-296
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• 2022

High-frequency (HF) radar measures sea surface currents from the radio waves transmitted and received by antenna on land. Since the data quality of HF radar measurements sensitively depend on the radio wave environment around antenna, Antenna Pattern Measurements (APM) plays an important role in evaluating the accuracy of measured surface currents. In this study, APM was performed by selecting the times when the background noise level around antenna was high and low, and radial data were generated by applying the ideal pattern and measured pattern. The measured antenna pattern for each case was verified with the current velocity data collected by drifters. The radial velocity to which the ideal pattern was applied was not affected by the background noise level around antenna. However, the radial velocity obtained with APM in the period of high background noise was significantly lower in quality than the radial velocity in a low noise environment. It is recomended that APM be carried out in consideration of the radio wave environment around antenna, and that the applied result be compared and verified with the current velocity measurements by drifters. If it is difficult to re-measure APM, we suggest using radial velocity in generating total vector with the ideal pattern through comparative verification, rather than poorly measured patterns, for better data quality.

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2006.11a
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• pp.298-302
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• 2006

As the age of information technology is coming, companies stress the need of knowledge management. Companies construct ERP system including knowledge management. But, it is not easy to formalize knowledge in organization. we focused on data mining system by using genetic programming. But, we don't have enough data to perform the learning process of genetic programming. We have to reduce input parameter(s) or increase number of learning or training data. In order to do this, the enhanced data mining system by using GP combined with SOM(Self organizing map) is adopted in this paper. We can reduce the number of learning data by adopting SOM.

• Journal of Ocean Engineering and Technology
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• v.37 no.1
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• pp.38-48
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• 2023

To maintain the existing systems of ships and introduce autonomous operation technology, it is necessary to improve situational awareness through the sensor fusion of the automatic identification system (AIS) and automatic radar plotting aid (ARPA), which are installed sensors. This study proposes an algorithm for determining whether AIS and ARPA signals are sent to the same ship in real time. To minimize the number of errors caused by the time series and abnormal phenomena of heterogeneous signals, a tracking method based on the combination of the unscented Kalman filter and probabilistic data association filter is performed on ARPA radar signals, and a position prediction method is applied to AIS signals. Especially, the proposed algorithm determines whether the signal is for the same vessel by comparing motion-related components among data of heterogeneous signals to which the corresponding method is applied. Finally, a measurement test is conducted on a training ship. In this process, the proposed algorithm is validated using the AIS and ARPA signal data received by the voyage data recorder for the same ship. In addition, the proposed algorithm is verified by comparing the test results with those obtained from raw data. Therefore, it is recommended to use a sensor fusion algorithm that considers the characteristics of sensors to improve the situational awareness accuracy of existing ship systems.

• Journal of Ocean Engineering and Technology
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• v.26 no.1
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• pp.1-8
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• 2012

To correctly estimate ice load and ice resistance for a ship's hull, it is essential to understand the material properties of sea ice during ice field trials and to use the proper experimental procedure for gathering ice strength data. The first Korean-made icebreaking research vessel (IBRV), ARAON, had her second sea ice trial in the Arctic Ocean during July and August of 2010. This paper describes the test procedures used to properly obtain sea ice strength data, which provides the basic information on the ship's performance in an ice-covered sea and can be used to estimate the correct ice load and ice resistance on the IBRV ARAON. The data gathered from three sea ice field trials during the Arctic voyage of the ARAON includes the ice compressive strength, flexural strength, and failure strain of sea ice. This paper analyzes the gathered sea ice data in comparison with data from the first voyage of the ARAON during her Antarctic Sea ice trial in January 2010.

• Journal of Ocean Engineering and Technology
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• v.30 no.6
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• pp.468-473
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• 2016

This paper focuses on the estimation of local ice loads exerted from ship-ice interaction processes. The Korean IBRV ARAON was used to perform field ice trials during her 2015 Arctic voyage. During ARAON's general ice transit, a total of 72 channels of data from both strain gauges on the inner hull plates and those installed on the transverse frames of the ARAON's bow section structures were analyzed to calculate the local ice loads. The local ice loads estimated from the analysis of the shear strain data measured on the side frames were compared to those from the hull plate pressures.

• International Journal of Naval Architecture and Ocean Engineering
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• v.7 no.2
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• pp.301-314
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• 2015

Aiming at accurately distinguishing modeless component and natural vibration mode terms from data series of nonlinear and non-stationary processes, such as Vortex-Induced Vibration (VIV), a new empirical mode decomposition method has been developed in this paper. The key innovation related to this technique concerns the method to decompose modeless component from non-stationary process, characterized by a predetermined 'maximum intrinsic time window' and cubic spline. The introduction of conceptual modeless component eliminates the requirement of using spurious harmonics to represent nonlinear and non-stationary signals and then makes subsequent modal identification more accurate and meaningful. It neither slacks the vibration power of natural modes nor aggrandizes spurious energy of modeless component. The scale of the maximum intrinsic time window has been well designed, avoiding energy aliasing in data processing. Finally, it has been applied to analyze data series of vortex-induced vibration processes. Taking advantage of this newly introduced empirical decomposition method and mode identification technique, the vibration analysis about vortex-induced vibration becomes more meaningful.