• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2003.05a
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• pp.60-65
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• 2003

The paper describes on the implementation of marine casualty prediction model that is one of the main part of Marine Casualty Forecasting System (MCFS). In this work, Cell Distributed Linear-In-the Parameter (CD-LIP) model is developed and compared with Baltic model using regression analysis of variance. As comparing, it is known that the proposed CD-LIP model has less residual than the Baltic model and, it gives best performance to the marine casualty numeric D/B of target area.

• Journal of the Mineralogical Society of Korea
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• v.22 no.4
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• pp.395-405
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• 2009

The maturity of amber matrix and inclusion was studied to explore the effect of heat treatment on the formation of the sun spangle in the transparent Baltic amber from Gdansk, Poland. Optical microscope revealed two types of inclusions in the original amber samples. The inclusions in the amber which had sun spangle were dramatically expanded by the heat treatment, comparing to those without sun spangle which contains fissure and shows different refractive index. The amber sample which didn't show sun spangle after the heat treatment showed a strong carbon related peak in TOF-SIMS spectra and weak oxygen related peak. it means that the maturity of this amber sample is comparatively higher than the one with spangle. The two amber samples show similar IR spectra before the heat treatment. However, the amber which had sun spangle exhibited an additional 1019 $cm^{-1}$ absorption peak and a more intense 887 $cm^{-1}$ peak. The different chemical compositions between the two types of amber is believed to be due to the different absorption spectra between 1000~600 $cm^{-1}$. According to the study of DSC analysis, the two samples show different DSC profiles. Although they have the same geological origin, their geological ages are different and have different chemical compositions. Thus, they exhibited different behavior after the heat treatment. The formation of sun spangle seemed to depend on the difference in the heat expansion rate of amber matrix with different maturity and chemical compositions.

• Journal of fish pathology
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• v.9 no.1
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• pp.11-13
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• 1996

Ergasilus sieboldi, a parasitic Copepoda, was detected from the gill of Silurus asotus fingerling(7~10 cm long) cultured at a fish farm in Chungnam Province (Fig. 1 and 2). The infected fish did not show any particular external symptoms except a feeble swimming around the boarder of the pond. The isolated parasite was of 1.07 mm in body length with two egg sacks of 1.05 mm and one pair of hook-shaped secondary tentacle. Bychowsky(1963) described that this parasite infected the gill of Salmonidae, Serranidae, Cyprinidae and Siluridae and that the fish in the Baltic Sea, Black Sea. Caspian Sea. Japanese sea zones, Siberian rivers and Lake Bikal were infectd. Bychowsky further pointed out that heavily infected fish with this parasite become emaciated and slow in growth. and often die. As this parasite infected on the peri-branchial area. the infected fish showed a severe disturbance of respiration. Urawa et ai.(1980) studied on the development of Neoergasilus japonicus. an Ergasilidae, which infects Japanese freshwater fish. In Korea, Chun(1985) reported the identification of Ergasilus sieboldi from imported carp. and Neoergasilus and Pseudogasilus japonicus from bluegills. respectively. Chun also identified Pseudoergasilus zacconis in cultured ayu(Plecoglossus altivelis). However. this report deals with the detection of Ergasilus sieboldi from cultured catfish(Silurus asotus) for the first time in Korea.

• Korea Trade Review
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• v.44 no.2
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• pp.127-141
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• 2019

In this study, the relationship between Baltic Dry Index(BDI) and maritime trade volume in the dry cargo market was verified using the vector autoregressive (VAR) model. Data was analyzed from 1992 to 2018 for iron ore, steam coal, coking coal, grain, and minor bulks of maritime trade volume and BDI. Granger causality analysis showed that the BDI affects the trade volume of coking coal and minor bulks but the trade volume of iron ore, steam coal and grain do not correlate with the BDI freight index. Impulse response analysis showed that the shock of BDI had the greatest impact on coking coal at the two years lag and the impact was negligible at the ten years lag. In addition, the shock of BDI on minor cargoes was strongest at the three years lag, and were negligible at the ten years lag. This study examined the relationship between maritime trade volume and BDI in the dry bulk shipping market in which uncertainty is high. As a result of this study, there is an economic aspect of sustainability that has helped the risk management of shipping companies. In addition, it is significant from an academic point of view that the long-term relationship between the two time series was analyzed through the causality test between variables. However, it is necessary to develop a forecasting model that will help decision makers in maritime markets using more sophisticated methods such as the Bayesian VAR model.

• Journal of the Korea Society of Computer and Information
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• v.26 no.7
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• pp.127-132
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• 2021

This paper applies a machine learning model to forecasting freight rates in dry bulk and tanker markets with wavelet decomposition and empirical mode decomposition because they can refect both information scattered in the time and frequency domain. The decomposition with wavelet is outperformed for the dry bulk market, and EMD is the more proper model in the tanker market. This result provides market players with a practical short-term forecasting method. This study contributes to expanding a variety of predictive methodologies for one of the highly volatile markets. Furthermore, the proposed model is expected to improve the quality of decision-making in spot freight trading, which is the most frequent transaction in the shipping industry.

• Proceedings of the Korean Society of Computer Information Conference
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• 2021.01a
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• pp.329-330
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• 2021

벌크화물운송은 해상운송시장에서 가장 큰 규모이고 철강 및 에너지 산업을 뒷받침 하는 중요한 시장이다. 또한 운임의 변동성이 가장 큰 시장으로 상당한 수익을 기대할 수 있는 반면에 파산에 이르는 큰 손실이 발생할 수 있기때문에 시장 참여자들은 합리적이고 과학적인 예측을 기반하여 의사결정을 해야 한다. 그러나 해운시장에서는 과학적 의사결정보다는 경험기반의 의사결정에 의존하기 때문에 시황변동성에 취약하다. 본 논문은 벌크운임예측에 신호 분해 방법인 EMD와 인공신경망을 결합한 하이브리드 모델을 적용하여 과학적 예측방법을 제시하고자 한다. 본 논문은 학문적으로 해운시장 운임예측연구에서 거의 시도되지 않았던 시계열분해법과 기계학습기법을 결합한 하이브리드 모델을 제시하였다는데 의미가 있으며 실무적으로는 해운시장에서 빈번이 일어나는 의사결정의 질이 제고되는데 기여할 것으로 기대된다.

• Journal of the Korean association of regional geographers
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• v.15 no.1
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• pp.67-85
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• 2009

The Trans-Central Asian Railway consists of the Trans-Caspian Railroad, the Kazalinsk Route, the Turk-Sib, and the Trans-Kazakhstan Trunk Line. Currently, one-fifth of the residents in Central Asia are living around these railroads on which 70% of the economic activities in the region depends. The construction of the railroads in Central Asia was motivated by the Russian Empire's competition 'with its maritime rival, the United Kingdom, over the Eurasian heartland in a geostrategic sense. Using the railroads, the Russian Empire aspired to connect its central industrial regions in European Russia with the remote frontier areas in the Central Asian republics and to increase economic specialization of the region. After the breakdown of the USSR, however, the rail network, which had well been linked among the regions in the former Soviet nations, has been in a deteriorated linkage with their non-Soviet neighboring nations. Despite a lot of problems to be solved, the Trans-Central Asian rail network is expected to play a crucial role as a land bridge between East Asia and Europe as well as between Russia/the Baltic sea and the Indian Ocean/the Persian Gulf in the long-term.

• Journal of Navigation and Port Research
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• v.42 no.1
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• pp.57-66
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• 2018

Maritime industry is affected by outside factors significantly due to its derivative demand characteristics. However, the supply side can not react to these changes immediately and due to this uniqueness, maritime industry repeats the boom-bust cycle. Therefore the government itself needs to operate early warning system in order to monitor the market and notice the upcoming risks by setting up a system to prepare for the situations. In this research, signal approach is used to establish early warning system. Overall leading index is composed of crisis index that is based on BDI(Baltic Dry Index) and various leading indexes such as finance, economy, shipping and the others. As a result of computing overall leading index which is early warning system in maritime through signal approach, the index showed a high correlation coefficient with actual maritime risk index by difference of 4 months. Also, the result was highly accurate with overall leading index's QPS(Quadratic Probability Score) at 0.37.

• Korea Trade Review
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• v.48 no.2
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• pp.27-43
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• 2023

The maritime industry is playing an increasingly vital part in global economic expansion. Specifically, the Baltic Dry Index is highly correlated with global commodity prices. Hence, the importance of BDI prediction research increases. But, since the global situation has become more volatile, it has become methodologically more difficult to predict the BDI accurately. This paper proposes an integrated machine-learning strategy for accurately forecasting BDI trends. This study combines the benefits of a convolutional neural network (CNN) and long short-term memory neural network (LSTM) for research on prediction. We collected daily BDI data for over 27 years for model fitting. The research findings indicate that CNN successfully extracts BDI data features. On this basis, LSTM predicts BDI accurately. Model R2 attains 94.7 percent. Our research offers a novel, machine-learning-integrated approach to the field of shipping economic indicators research. In addition, this study provides a foundation for risk management decision-making in the fields of shipping institutions and financial investment.

• Proceedings of KOSOMES biannual meeting
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• 2018.06a
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• pp.16-16
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• 2018

2017년 겨울, 기록적인 한파로 인해 바다가 얼면서 인천 앞바다로 유빙이 유입되었다. 2013년 해상에서 유빙이 발견된 이후 약 5년만에 다시 유빙이 등장한 것이다. 중부청 소속 항공단 순찰결과에 따르면, 2018년 1월 12일 인천대교 인근 해상에서 최초로 발견된 이후 강화 연안, 영종도 북단 등 해상에서 광범위하고 불규칙한 형태로 유빙이 분포되어 있는 것으로 나타났다. 유빙의 문제점은 해상에서 선박의 안전운항을 저해하고 경비함정의 안전에 지장을 초래하며 기름 유출 시, 유출유의 거동 특성이 달라져 일반적인 방제방법의 적용이 곤란한 점이다. 이에 따라 해상에서의 해양오염사고 대응방안 마련을 위해 저온 및 유빙 유입 해상에서 유출유의 거동 특성을 알아보았다. 구분인자를 극한의 추위(Extreme Cold), 유빙(Pack Ice), 정착빙(Fast Ice) 3가지로 분류하여 기름의 성상변화 및 시사점을 살펴보고, 유출된 기름의 효율적 방제를 크게 3가지로 분류(기계적 봉쇄 및 회수, 화학적 분산제의 사용, 현장소각)하였다. 일반적인 방제장비를 저온 및 얼음분포 해상에서 사용 시 슬러시화 된 얼음으로 인해 유출유 회수가 어렵고, 동결온도에서 장비가 오작동할 우려가 있다. 이미 북유럽 국가에서는 극한의 추위와 얼음분포 해상에 특화된 방제장비를 도입하여 해양오염대비 대응을 하고 있다. 2003년 3월 발틱해에서 불법적으로 유출한 선저폐수를 특화 장비는 brush bucket 유회수기 이용 방제조치한 사례가 있으며, 2006년 5월 같은 장소에서 선박 침몰로 인한 기름 유출이 발생했을때도 brush bucket 유회수기 이용 방제조치를 하였다. 국내에도 이상 기후로 인해 기록적인 한파가 지속되면서 북극에서나 볼 법한 유빙들이 발견되고, 해양오염사고는 언제 어디서나 발생할 수 있으므로, 해양오염방제의 임무를 맡고 있는 국가기관으로써 특수한 환경까지도 고려하여 대응방안을 마련할 필요가 있다. 해양오염이 재난으로 인식되고 있는 상황에서, 그리고 지구온난화로 인한 이상기후변화가 지속되는 상황에서 겨울철 유빙 유입은 점점 더 많아질 수 있다. 본 연구에서는 자료나 방제경험이 부족하므로 일찌감치 북극항로 개발로 앞선 방제기술과 경험을 가지고 있는 북극이사회를 벤치마킹하여 관할 해역 특성에 맞는 대응방안을 고찰해 본다.