• Title/Summary/Keyword: Marine Information

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A channel parameter-based weighting method for performance improvement of underwater acoustic communication system using single vector sensor (단일 벡터센서의 수중음향 통신 시스템 성능 향상을 위한 채널 파라미터 기반 가중 방법)

  • Kang-Hoon, Choi;Jee Woong, Choi
    • The Journal of the Acoustical Society of Korea
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    • v.41 no.6
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    • pp.610-620
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    • 2022
  • An acoustic vector sensor can simultaneously receive vector quantities, such as particle velocity and acceleration, as well as acoustic pressure at one location, and thus it can be used as a single input multiple output receiver in underwater acoustic communication systems. On the other hand, vector signals received by a single vector sensor have different channel characteristics due to the azimuth angle between the source and receiver and the difference in propagation angle of multipath in each component, producing different communication performances. In this paper, we propose a channel parameter-based weighting method to improve the performance of an acoustic communication system using a single vector sensor. To verify the proposed method, we used communication data collected from the experiment conducted during the KOREX-17 (Korea Reverberation Experiment). For communication demodulation, block-based time reversal technique which is robust against time-varying channels were utilized. Finally, the communication results showed that the effectiveness of the channel parameter-based weighting method for the underwater communication system using a single vector sensor was verified.

Factor Analysis of Seaborne Trade Volume Affecting on The World Economy (품목별 해상 물동량이 세계 경제에 미치는 영향 요인분석)

  • Ahn, Young-Gyun;Lee, Min-Kyu;Park, Ju-Dong
    • Korea Trade Review
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    • v.42 no.2
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    • pp.277-296
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    • 2017
  • More than 95% of imports and exports in the World are being transported by vessels. In other words, marine transportation accounts for a large portion of share in the world trade. The purpose of this study is to analyze factors of seaborne trade volume according to items affecting on the world economy. This study conducted a linear regression analysis between seaborne trade volume and the world economy (world GDP) to estimate the correlation between them. Panel data analysis and random effects model analysis have been applied to examine the effect of seaborne trade volume. For this study, the seaborne trade volume is categorized into 10 items, and estimated how much global GDP will be affected when the trade volume changes. In addition, the granger causality test was conducted to verify the relationship between seaborne trade volume and the world GDP. As a result, seaborne trade volume and the world GDP were mutually influenced each other. However, seaborne trade volume affects the world economy more significantly. The items affecting world economic growth include petroleum products, crude oil, chemical products, and so on. The estimated value of the coefficients of petroleum products, crude oil and chemical products were 1.014, 1.013 and 1.010, respectively. The estimated value 1.014 of petroleum products means that the growth rate is 1.014 times higher than the current world GDP growth rate when the seaborne trade volume of petroleum products increased by one unit Lastly, this study examines the seaborne trade volume of 10 categories and then verifies whether the growth rate of world GDP will increase when the volume of seaborne trade increased. This study is expected to provide policy-makers with useful information about formulating policies related to international trade.

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Uncertainty Estimation of Single-Channel Temperature Estimation Algorithm for Atmospheric Conditions in the Seas around the Korean Peninsula (한반도 주변해역 대기환경에 대한 싱글채널 온도추정 알고리즘의 불확도 추정)

  • Jong Hyuk Lee;Kyung Woong Kang;Seungil Baek;Wonkook Kim
    • Korean Journal of Remote Sensing
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    • v.39 no.3
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    • pp.355-361
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    • 2023
  • Temperature of the Earth's surface is a crucial physical variable in understanding weather and atmospheric dynamics and in coping with extreme heat events that have a great impact on living organismsincluding humans. Thermalsensors on satellites have been a useful meansfor acquiring surface temperature information for wide areas on the globe, and thus characterization of its estimation uncertainty is of central importance for the utilization of the data. Among various factors that affect the estimation, the uncertainty caused by the algorithm itself has not been tested for the atmospheric environment of Korean vicinity. Thisstudy derivesthe uncertainty of the single-channel algorithm under the local atmospheric and oceanic conditions by using reanalysis data and buoy temperature data collected around Korea. Atmospheric profiles were retrieved from two types of reanalysis data, the fifth generation of European Centre for Medium-Range Weather Forecasts reanalysis of the global climate and weather (ERA5) and Modern-Era Retrospective analysis for Research and Applications-2 (MERRA-2) to investigate the effect of reanalysis data. MODerate resolution atmospheric TRANsmission (MODTRAN) was used as a radiative transfer code for simulating top of atmosphere radiance and the atmospheric correction for the temperature estimation. Water temperatures used for MODTRAN simulations and uncertainty estimation for the single-channel algorithm were obtained from marine weather buoyslocated in seas around the Korean Peninsula. Experiment results showed that the uncertainty of the algorithm varies by the water vapor contents in the atmosphere and is around 0.35K in the driest atmosphere and 0.46K in overall, regardless of the reanalysis data type. The uncertainty increased roughly in a linear manner as total precipitable water increased.

A Study on the Re-establishment of the Accident Classification for Aids to Navigation (항로표지사고 분류체계의 재정립에 관한 연구)

  • Beom-Sik Moon;Tae-Goun Kim;Chae-uk Song;Young-Jin Kim
    • Journal of Navigation and Port Research
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    • v.47 no.3
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    • pp.128-133
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    • 2023
  • In order for Aids to Navigation to provide sustainable services to users, it is possible when there is no Aids to Navigation accident. If an Aids to Navigation accident occurs, the manager should efficiently manage it to prevent the same accident. However, the current Aids to Navigation accident management only specifies the cause and type of the accident. There are no separate guidelines. Thus, the accident is recorded differently depending on the manager. Therefore, this study attempted to redefine Aids to Navigation accident. To this end, Aids to Navigation accidents that have occurred over the past 23 years (year 2000 to years 2022), IALA's Aids to Navigation information standard, S-201, and categories of accidents (traffic accidents and marine accidents) were analyzed. Causes of Aids to Navigation accidents were divided into internal and external causes. Accidents were divided into three types: Light tower accident, buoy accident, and equipment accident. By further subdividing primary items, the cause of accident was reestablished into 7 items such as mooring and bad weather and 11 items such as Light tower damage, buoy loss, and equipment breakdown. These research results can be used as basic data to provide future Aids to Navigation accident statistics.

A Review of Deep Learning-based Trace Interpolation and Extrapolation Techniques for Reconstructing Missing Near Offset Data (가까운 벌림 빠짐 해결을 위한 딥러닝 기반의 트레이스 내삽 및 외삽 기술에 대한 고찰)

  • Jiho Park;Soon Jee Seol;Joongmoo Byun
    • Geophysics and Geophysical Exploration
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    • v.26 no.4
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    • pp.185-198
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    • 2023
  • In marine seismic surveys, the inevitable occurrence of trace gaps in the near offset resulting from geometrical differences between sources and receivers adversely affects subsequent seismic data processing and imaging. The absence of data in the near-offset region hinders accurate seismic imaging. Therefore, reconstructing the missing near-offset information is crucial for mitigating the influence of seismic multiples, particularly in the case of offshore surveys where the impact of multiple reflections is relatively more pronounced. Conventionally, various interpolation methods based on the Radon transform have been proposed to address the issue of the nearoffset data gap. However, these methods have several limitations, leading to the recent emergence of deep-learning (DL)-based approaches as alternatives. In this study, we conducted an in-depth analysis of two representative DL-based studies to scrutinize the challenges that future studies on near-offset interpolation must address. Furthermore, through field data experiments, we precisely analyze the limitations encountered when applying previous DL-based trace interpolation techniques to near-offset situations. Consequently, we suggest that near-offset data gaps must be approached by extrapolation rather than interpolation.

LAN Based MFD Interface for Integrated Operation of Radio Facilities using Fishery Vessel (어선용 무선설비의 통합운용을 위한 LAN 기반 MFD 인터페이스)

  • In-ung Ju;In-suk Kang;Jeong-yeon Kim;Seong-Real Lee;Jo-cheon Choi
    • Journal of Advanced Navigation Technology
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    • v.26 no.6
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    • pp.496-503
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    • 2022
  • In the reality that the fishing population is decreasing and the single-man fishing vessels is increasing, mandatory equipment for navigation and radio equipments for the safety of fishing boats has continued to be added. Therefore, many equipment such as navigation, communication and fishing are installed in the narrow steering room, so it is very confusing and a number of monitors are placed in the front, which is a factor that degrades the function of maritime observation. To solve this problem, we studied an interface that integrates and operates to major radio facilities such as very high frequency-digital selective calling equipment (VHF-DSC), automatic identification system (AIS) and fishing boat location transmission device (V-pass) into one multi function display (MFD) based on LAN. In addition, IEC61162-450 UDP packets and IEC61162 sentence were applied to exchange data through link between MFD and radio equipments, and additional messages needed for each equipment and function were defined. The integrated MFD monitor is easily operated by the menu method, and the performance of the interface was evaluated by checking the distress and emergency communication functions related to maritime safety and the message transmission status by equipment.

A Study on the User-Based Small Fishing Boat Collision Alarm Classification Model Using Semi-supervised Learning (준지도 학습을 활용한 사용자 기반 소형 어선 충돌 경보 분류모델에대한 연구)

  • Ho-June Seok;Seung Sim;Jeong-Hun Woo;Jun-Rae Cho;Jaeyong Jung;DeukJae Cho;Jong-Hwa Baek
    • Journal of Navigation and Port Research
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    • v.47 no.6
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    • pp.358-366
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    • 2023
  • This study aimed to provide a solution for improving ship collision alert of the 'accident vulnerable ship monitoring service' among the 'intelligent marine traffic information system' services of the Ministry of Oceans and Fisheries. The current ship collision alert uses a supervised learning (SL) model with survey labels based on large ship-oriented data and its operators. Consequently, the small ship data and the operator's opinion are not reflected in the current collision-supervised learning model, and the effect is insufficient because the alarm is provided from a longer distance than the small ship operator feels. In addition, the supervised learning (SL) method requires a large number of labeled data, and the labeling process requires a lot of resources and time. To overcome these limitations, in this paper, the classification model of collision alerts for small ships using unlabeled data with the semi-supervised learning (SSL) algorithms (Label Propagation and TabNet) was studied. Results of real-time experiments on small ship operators using the classification model of collision alerts showed that the satisfaction of operators increased.

A Case Study on Forecasting Inbound Calls of Motor Insurance Company Using Interactive Data Mining Technique (대화식 데이터 마이닝 기법을 활용한 자동차 보험사의 인입 콜량 예측 사례)

  • Baek, Woong;Kim, Nam-Gyu
    • Journal of Intelligence and Information Systems
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    • v.16 no.3
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    • pp.99-120
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    • 2010
  • Due to the wide spread of customers' frequent access of non face-to-face services, there have been many attempts to improve customer satisfaction using huge amounts of data accumulated throughnon face-to-face channels. Usually, a call center is regarded to be one of the most representative non-faced channels. Therefore, it is important that a call center has enough agents to offer high level customer satisfaction. However, managing too many agents would increase the operational costs of a call center by increasing labor costs. Therefore, predicting and calculating the appropriate size of human resources of a call center is one of the most critical success factors of call center management. For this reason, most call centers are currently establishing a department of WFM(Work Force Management) to estimate the appropriate number of agents and to direct much effort to predict the volume of inbound calls. In real world applications, inbound call prediction is usually performed based on the intuition and experience of a domain expert. In other words, a domain expert usually predicts the volume of calls by calculating the average call of some periods and adjusting the average according tohis/her subjective estimation. However, this kind of approach has radical limitations in that the result of prediction might be strongly affected by the expert's personal experience and competence. It is often the case that a domain expert may predict inbound calls quite differently from anotherif the two experts have mutually different opinions on selecting influential variables and priorities among the variables. Moreover, it is almost impossible to logically clarify the process of expert's subjective prediction. Currently, to overcome the limitations of subjective call prediction, most call centers are adopting a WFMS(Workforce Management System) package in which expert's best practices are systemized. With WFMS, a user can predict the volume of calls by calculating the average call of each day of the week, excluding some eventful days. However, WFMS costs too much capital during the early stage of system establishment. Moreover, it is hard to reflect new information ontothe system when some factors affecting the amount of calls have been changed. In this paper, we attempt to devise a new model for predicting inbound calls that is not only based on theoretical background but also easily applicable to real world applications. Our model was mainly developed by the interactive decision tree technique, one of the most popular techniques in data mining. Therefore, we expect that our model can predict inbound calls automatically based on historical data, and it can utilize expert's domain knowledge during the process of tree construction. To analyze the accuracy of our model, we performed intensive experiments on a real case of one of the largest car insurance companies in Korea. In the case study, the prediction accuracy of the devised two models and traditional WFMS are analyzed with respect to the various error rates allowable. The experiments reveal that our data mining-based two models outperform WFMS in terms of predicting the amount of accident calls and fault calls in most experimental situations examined.

The Influences of Coastal Upwelling on Phytoplankton Community in the Southern Part of East Sea, Korea (동해 남부 연안 해역에서 냉수대 발생이 식물플랑크톤 군집에 미치는 영향)

  • Kim, A-Ram;Youn, Seok-Hyun;Chung, Mi-Hee;Yoon, Sang-Chol;Moon, Chang-Ho
    • The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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    • v.19 no.4
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    • pp.287-301
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    • 2014
  • In order to understand environment condition and phytoplankton community before and after coastal upwelling, the influences of upwelling events on phytoplankton community were studied at 18 stations located the Southern part of East Sea, Korea from May to August 2013. The surface water masses showed low temperature and high salinity due to upwelling events at coastal stations (A1, B1, C1). Correlation between temperature and nutrients (DIP, r=-0.218, p<0.01; DIN, r=-0.306, p<0.01; silicate, r=-0.274, p<0.01) was significantly negative. This result could be explained that nutrients were supplied to surface water by the upwelling of bottom water. Phytoplankton communities were composed of 186 species. Phytoplankton abundance were relatively high in May (C1, $726{\times}10^3cells\;L^{-1}$) and July (A1, $539{\times}10^3cells\;L^{-1}$). Total chlorophyll a and micro-size fraction ($&gt;20{\mu}m$) increased at coastal stations in July and August, while phytoplankton abundance and total chl. a was much low in June. Dominant species in June was Pseudo-nitzschia spp. of which the cell size was $309{\mu}m^3$. Cell size of Pseudo-nitzschia spp. was smaller than dominant species in other period. Therefore, the increase in total chloro-phyll a and the size of phytoplankton was resulted in the sufficient supply of nutrients. In contrast, these tendencies were not observed at outside stations. These results suggested that coastal upwelling was an important influencing factor to determine the species composition and standing stock of phytoplankton community in the coastal waters of the Southern part of East Sea, Korea.

Comparison of Landcover Map Accuracy Using High Resolution Satellite Imagery (고해상도 위성영상의 토지피복분류와 정확도 비교 연구)

  • Oh, Che-Young;Park, So-Young;Kim, Hyung-Seok;Lee, Yanng-Won;Choi, Chul-Uong
    • Journal of the Korean Association of Geographic Information Studies
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    • v.13 no.1
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    • pp.89-100
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    • 2010
  • The aim of this study is to produce land cover maps using satellite imagery with various degrees of high resolution and then compare the accuracy of the image types and categories. For the land cover map produced on a small-scale classification the estuary area around the Nakdong river, including an urban area, farming land and waters, was selected. The images were classified by analyzing the aerial photos taken from KOMPSAT2, Quickbird and IKONOS satellites, which all have a resolution of over 1m to the naked eye. Once all of the land cover maps with different images and land cover categories had been produced they were compared to each other. Results show that image accuracy from the aerial photos and Quickbird was relatively higher than with KOMPSAT2 and IKONOS. The agreement ratio for the large-scale classification across the classification methods ranged between 0.934 and 0.956 for most cases. The Kappa value ranged between 0.905 and 0.937; the agreement ratio for the middle-scale classification was 0.888~0.913 and the Kappa value was 0.872~0.901. The agreement ratio for the small-scale classification was 0.833~0.901 and the Kappa value was 0.813~0.888. In addition, in terms of the degree of confusion occurrence across the images, there was confusion on the urbanized arid areas and empty land in the large-scale classification. For the middle-scale classification, the confusion mainly occurred on the rice paddies, fields, house cultivating area and artificial grassland. For the small-scale classification, confusion mainly occurred on natural green fields, cultivating land with facilities, tideland and the surface of the sea. The findings of this study indicate that the classification of the high resolution images with the naked eye showed an agreement ratio of over 80%, which means that it can be used in practice. The findings also suggest that the use of higher resolution images can lead to increased accuracy in classification, indicating that the time when the images are taken is important in producing land cover maps.