• Journal of Navigation and Port Research
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• v.31 no.1 s.117
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• pp.43-48
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• 2007

Maritime traffic engineering is a technical field that observes the flow of vessels' traffic in accurate and describes the feature of ship's movement statistically, then contributes for the improvement of traffic flow and the safety of traffic. The flow of marine traffic can be controlled by carrying out assessment and analysis of vessel's traffic. It can realize the safety of marine traffic by accurate research and analysis of vessel's traffic, understanding its flow and analysis data of vessel traffic. This study shows the analysis system of marine traffic connected with Radar, AIS based on ENC(Electronic Navigational Chart). The marine traffic analysis system contributes to the safety of marine traffic through the design of marine traffic route, harbour facilities and improvement of vessels' traffic flow.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.2
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• pp.177-180
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• 2005

AIS needs high efficiency and safety in terms of operational management and, in the aspect of service range, it is time to minimize shadow regions through propagation evaluation of AIS transmitter. Thus this study analyzes shadow regions and the scope of propagation of waves from stations through the electric wave environment of AIS. First, this study examines the characteristics of AIS wave and draws up methods to analyze the scope of propagation of waves according to the characteristics. Second, this study finds out service regions and shadow regions of the 22 stations across the nation by analyzing the actual data based on climate and topography, Lastly, this study summarizes the results of wave conductivity evaluation and conductivity problems and proposes improvement measures.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.06a
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• pp.277-279
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• 2022

Rapid Development and adoption of AIS as a survailance tool has resulted in widespread application of data analysis technology, in addition to AIS ship trajectory clustering. AIS data-based clustering has become an increasingly popular method for marine traffic pattern recognition, ship route prediction and anomaly detection in recent year. In this paper we propose a route waypoint extraction by clustering ships CoG variance trajectory using Density-Based Spatial Clustering of Application with Noise (DBSCAN) algorithm in both port approach channel and coastal waters. The algorithm discovers route waypoint effectively. The result of the study could be used in traffic route extraction, and more-so develop a maritime anomaly detection tool.

• Korean Journal of Remote Sensing
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• v.36 no.2_2
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• pp.379-399
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• 2020

The detection of illegal ship is one of the key factors in building a marine surveillance system. Effective marine surveillance requires the means for continuous monitoring over a wide area. In this study, the possibility of ship detection monitoring based on satellite SAR, HF radar, UAV and AIS integration was investigated. Considering the characteristics of time and spatial resolution for each platform, the ship monitoring scenario consisted of a regular surveillance system using HFR data and AIS data, and an event monitoring system using satellites and UAVs. The regular surveillance system still has limitations in detecting a small ship and accuracy due to the low spatial resolution of HF radar data. However, the event monitoring system using satellite SAR data effectively detects illegal ships using AIS data, and the ship speed and heading direction estimated from SAR images or ship tracking information using HF radar data can be used as the main information for the transition to UAV monitoring. For the validation of monitoring scenario, a comprehensive field experiment was conducted from June 25 to June 26, 2019, at the west side of Hongwon Port in Seocheon. KOMPSAT-5 SAR images, UAV data, HF radar data and AIS data were successfully collected and analyzed by applying each developed algorithm. The developed system will be the basis for the regular and event ship monitoring scenarios as well as the visualization of data and analysis results collected from multiple platforms.

• Korean Journal of Organic Agriculture
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• v.31 no.4
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• pp.259-289
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• 2023

This study analyzed farmers' and experts' perceptions of the Agricultural Income Survey (AIS) conducted by the Rural Development Administration and estimated its socioeconomic value. The research surveyed 104 farmers in Gyeongsangbuk-do and Jeollanam-do. To estimate the AIS's socioeconomic value, this study examined public information projects in the field of agriculture and public information, proposing an estimation methodology based on prior research. The socioeconomic value of the AIS was calculated in three stages (information generation, collection and analysis, and utilization) using the replacement cost and contingent valuation methods. In 2020, the estimated socioeconomic value of the AIS ranged from a minimum of KRW 631.2 billion to a maximum of KRW 799.1 billion per year. To improve the socioeconomic value of the AIS, it is important to booster awareness, expand sample sizes for more reliable data, increase manpower and budget, refine survey questions, and enhance analyzing capabilities. And it's crucial to foster cooperation with surveyed farms, promote collaboration among investigative agencies, improve investigator skills, and strengthen management capabilities to facilitate information dissemination.

• Journal of Navigation and Port Research
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• v.42 no.4
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• pp.277-282
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• 2018

Recently, the Vessel Traffic Service (VTS) coverage has expanded to include coastal areas following the increased attention on vessel traffic safety. However, it has increased the workload on the VTS operators. In some cases, when the traffic volume increases sharply during the rush hour, the VTS operator may not be aware of the risks. Therefore, in this paper, we proposed a new method to recognize ship movement anomalies automatically to support the VTS operator's decision-making. The proposed method generated traffic pattern model without any category information using the unsupervised learning algorithm.. The anomaly score can be calculated by classification and comparison of the trained model. Finally, we reviewed the experimental results using a ship-handling simulator and the actual trajectory data to verify the feasibility of the proposed method.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.12
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• pp.2839-2846
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• 2014

New VHF band for use in VDE is determined by WRC-12 due to the overload of AIS VDL, and the system characteristics of the VDE is recommended as ITU-R M. 1842-1. CS-TDMA, a multiple access method of AIS class B, is recommended as that of the VDE. It is inefficient for CS-TDMA just applying the report interval used in AIS class B to transmit high speed data with higher payload in the aspect of efficiency. In this paper, a simulation is executed in order to determine adequate report interval according to the number of active ships that affects directly network traffic. To this end, the performance of CS-TDMA, which includes the number of received packets, reception success rate, channel utilization, and collision rate, is investigated via a simulation.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.6
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• pp.1195-1202
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• 2016

Recently, a lot of studies that applying the big data technology to various fields, are progressing actively. In the maritime domain, the big data is the meaningful information which makes and gathers by the navigation and communication equipment from the many ships on the ocean. Also, importance of the maritime safety is emphasized, because maritime accidents are rising with increasing of maritime traffic. To support prevention of maritime accidents, in this paper, we developed a vessel traffic display and statistic system based on AIS messages from the many vessels of maritime. Also, to verify the developed system, we conducted tests for vessel track display function and vessel traffic statistic function based on two test scenarios. Therefore, we verified the effectiveness of the developed system for vessel tracks display, abnormal navigation patterns, checking failure of AIS equipments and maritime traffic statistic analyses.

• Journal of Korea Port Economic Association
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• v.39 no.3
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• pp.47-60
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• 2023

A thorough inventory of ship emissions, particularly ship's emission of in-port area is necessary to identify significant sources of exhaust gases such as NOx, SOx, PM, and CO₂ and trends in emission levels over time, and reduce their serious effects on the environment and human health. Therefore, the goal of this study is to assess the volume of emissions from ships in Mokpo port, which serves as a gateway to the southwest coast of Korea, using a bottom-up methodology and data from the automatic identification system (AIS) and the Korean Port Management Information System (Port-MIS). In this work, an analysis of ship movement utilizing AIS data and an actual set of data on ship specification were gathered. By examining ship movement using AIS data, We also proposed a new approach for identifying cruising/maneuvering mode. Finally, the results were classified by ship operating mode, by exhaust gas, by ship type, and by berth, which provides a thorough and in-depth analysis of the air pollution caused by ships in Mokpo port.

• Genomics & Informatics
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• v.21 no.2
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• pp.20.1-20.10
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• 2023

Aromatase inhibitors (AI) are drugs that are widely used in treating estrogen receptor (ER)-positive breast cancer patients. Drug resistance is a major obstacle to aromatase inhibition therapy. There are diverse reasons behind acquired AI resistance. This study aims at identifying the plausible cause of acquired AI resistance in patients administered with non-steroidal AIs (anastrozole and letrozole). We used genomic, transcriptomic, epigenetic, and mutation data of breast invasive carcinoma from The Cancer Genomic Atlas database. The data was then separated into sensitive and resistant sets based on patients' responsiveness to the non-steroidal AIs. A sensitive set of 150 patients and a resistant set of 172 patients were included for the study. These data were collectively analyzed to probe into the factors that might be responsible for AI resistance. We identified 17 differentially regulated genes (DEGs) among the two groups. Then, methylation, mutation, miRNA, copy number variation, and pathway analyses were performed for these DEGs. The top mutated genes (FGFR3, CDKN2A, RNF208, MAPK4, MAPK15, HSD3B1, CRYBB2, CDC20B, TP53TG5, and MAPK8IP3) were predicted. We also identified a key miRNA - hsa-mir-1264 regulating the expression of CDC20B. Pathway analysis revealed HSD3B1 to be involved in estrogen biosynthesis. This study reveals the involvement of key genes that might be associated with the development of AI resistance in ER-positive breast cancers and hence may act as a potential prognostic and diagnostic biomarker for these patients.