• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.189-192
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• 2014

Recently, U.S. and Europe, which are advanced to Air Traffic Control Management, are interest in replacing Radar System with Communications, Navigation and Surveillance(CNS) and Air Traffic Management(ATM). They pursue to research the efficient Air Traffic Control Management. This paper covers ADS-B 1090ES system which is one of CNS/ATM surveillance systems. This research satisfied all performance required by RTCA DO-268B and EUROCAE ED-129. It optimized algorism to mainly enhance performance such as quality of receiver signal, dynamic range, and so on. The optimized mechanism provided stable performance of demodulation, tuned the level of signal, and had reduced the false reception ratio by the signal level difference. The analyzed algorism helped great performance and will be considered to apply broad system applications.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.4
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• pp.190-197
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• 2020

Recently there was an incident that military radars, coastal CCTVs and other surveillance equipment captured a small rubber boat smuggling a group of illegal immigrants into South Korea, but guards on duty failed to notice it until after they reached the shore and fled. After that, the detection of such vessels before it reach to the Korean shore has emerged as an important issue to be solved. In the fields of marine navigation, Automatic Identification System (AIS) is widely equipped in vessels, and the vessels incessantly transmits its position information. In this paper, we propose a method of automatically identifying abnormally behaving vessels with AIS using convolutional autoencoder (CAE). Vessel anomaly detection can be referred to as the process of detecting its trajectory that significantly deviated from the majority of the trajectories. In this method, the normal vessel trajectory is gridded as an image, and CAE are trained with images from historical normal vessel trajectories to reconstruct the input image. Features of normal trajectories are captured into weights in CAE. As a result, images of the trajectories of abnormal behaving vessels are poorly reconstructed and end up with large reconstruction errors. We show how correctly the model detects simulated abnormal trajectories shifted a few pixel from normal trajectories. Since the proposed model identifies abnormally behaving ships using actual AIS data, it is expected to contribute to the strengthening of security level when it is applied to various maritime surveillance systems.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.6
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• pp.992-1001
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• 2022

The maritime traffic analysis has been conducted in various ways to solve problems arising from the complex marine environment. However, recent trends in the maritime industry, such as the development of the maritime autonomous surface ships (MASS), suggest that maritime traf ic analysis needs change. Accordingly, based on the studies conducted over the past decade for improvements, automatic identification system (AIS) data is mainly used for maritime traffic analysis. Moreover, the use of geographic information that directly af ects ship operation is relatively insufficient. Therefore, this study presented a method of using a combination of shape format data and AIS data to enhance maritime traffic analysis in preparation for the commercialization of autonomous ships. Consequently, extractable marine traffic characteristics were presented when shape format data were used for marine traffic analysis. This is expected to be used for marine traffic analysis for the introduction of autonomous ships in the future.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.4
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• pp.617-624
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• 2022

The small electric vehicles equipped with V2X(vehicle to everything) systems may provide more information and function to the existing navigation system of the vehicle. The key components of V2X technology include V2V (vehicle to vehicle), V2N(vehicle to network) and V2I (vehicle to infrastructure). This study is to design and implementation of VI type E-PTO which is interfaced with external equipments, the work designs the components of E-PTO such as DC/DC converter, DC/AC converter, battery bidirectional charging system etc. Also, it implements the devices and control systems for driving. The test results of VI type E-PTO components showed allowable 10% requirements of transient voltage variation rate and recovery time within 100ms for start/stop and normal operation.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.90-90
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• 2022

전자파표면유속계를 이용한 유량측정은 전자파를 발사한 후 수표면에 반사되는 전자파의 도플러효과를 이용하여 표면유속을 측정하는 방법이다. 국제적으로 1980년대부터 홍수유량측정의 어려움을 극복하고자 전자파표면유속계를 개발하여 하천 유량측정 업무에 활용하였다. 미국의 경우U.S. Geological Survey (USGS)에서 교량, 케이블웨이, 제방, 헬리콥터, 비행기 등 전자파표면유속계의 측정 위치에 따라 주파수 범위를 달리하며 유속을 측정하는 연구가 진행되었다. 국내의 경우 Lee et al.(2021)은 드론을 이용한 전자파표면유속계 측정을 위해 드론으로부터 전자파표면유속계로 전달되는 진동을 제거하고 전자파표면유속계의 흔들림 방지를 위한 댐퍼플레이트를 개발하여 드론과 전자파표면유속계를 결합한 DSVM(Dron and Surface Veloctity Meter using doppler radar) 측정방법에 대한 실용성을 확인하였다. 기존 연구에서 DSVM 방법은 드론의 각 측선 이동을 위한 조종 및 전자파표면유속계 측정의제어를 측정자가 수행하였는데 본 연구에서는 자동 측정 시스템 개발을 통해 측정자의 조종 의존도를 줄임과 동시에 안전하고 정확한 유량측정을 위해 노력하였다. 측정지점의 위치정보를 DB화하여 각 측선별 이동하는 자율운항 기능과 전자파표면유속계를 자동으로 제어하여 측정을 실시하는 기능을 개발하였다. 또한 전자파표면유속계 컨트롤 시스템과 GCS(Ground Control System)를 통합하여 한 시스템에서 측정의 모든 상황을 컨트롤 할 수 있게 하였다. 현재까지는 DSVM 방법의 자율운항 기능과 자동 측정 시스템의 테스트를 완료하였고 2022년 홍수기 유량측정에 도입하여 홍수기 유량측정의 실용성을 판단할 계획이다.

• Journal of the Ergonomics Society of Korea
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• v.36 no.5
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• pp.525-533
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• 2017

Objective: The aim of this study is to investigate maritime officers' strategies to avoid the ship collision in crossing situations. Background: In a situation where there is a risk of collision between two ships, maritime officers can change the direction and speed of the own-ship to avoid the collision. They have four options to select; adjusting the speed only, the direction only, both the speed and direction at the same time and no action. Research questions were whether the strategy they are using differs according to the shipboard experience of maritime officers and the representation method of ARPA (automatic radar plotting aid) - radar graphic information. Method: Participants were 12. Six of them had more than 3 years of onboard experience, while the others were 4th grade students at Korea Maritime and Ocean University. For each participant, 32 ship encounter situations were provided with ARPA-radar information. 16 situations were presented by the north-up display and 16 situations were presented by the track-up display. Participants were asked to decide how to move the own-ship to avoid the ship collision for each case. Results: Most participants attempted to avoid the collision by adjusting the direction of the ship, representing an average of 22.4 times in 32 judgment trials (about 70%). Participants who did not have experience on board were more likely to control speed and direction at the same time than participants with onboard experience. Participants with onboard experience were more likely to control the direction of the ship only. On the other hand, although the same ARPA Information was provided to the participants, the participants in many cases made different judgments depending on the method of information representation; track-up display and north-up display. It was only 25% that the participants made the same judgment under the same collision situations. Participants with onboard experience did make the same judgment more than participants with no onboard experience. Conclusion: In marine collision situations, maritime officers tend to avoid collisions by adjusting only the direction of their ships, and this tendency is more pronounced among maritime officers with onboard experience. The effect of the method of information representation on their judgment was not significant. Application: The results of this research might help to train maritime officers for safe navigation and to design a collision avoidance support system.

• Journal of Korea Society of Industrial Information Systems
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• v.23 no.1
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• pp.13-21
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• 2018

AGVS (Automated Guided Vehicle System) is a core technology of logistics automation which automatically moves specific objects or goods within a certain work space. Conventional AGVS generally requires the in-door localization system and each AGV equips expensive sensors such as laser, magnetic, inertial sensors for the route recognition and automatic navigation. thus the high installation cost is inevitable and there are many restrictions on route(path) modification or expansion. To address this issue, in this paper, we propose a cost-effective and scalable AGV based on a light-weight pattern recognition technique. The proposed pattern recognition technology not only enables autonomous driving by recognizing the route(path), but also provides a technique for figuring out the loc ation of AGV itself by recognizing the simple patterns(bar-code like) installed on the route. This significantly reduces the cost of implementing AGVS as well as benefiting from route modification and expansion. In order to verify the effectiveness of the proposed technique, we first implement a pattern recognition algorithm on a light-weight MCU(Micro Control Unit), and then verify the results by implementing an MCU_controlled AGV prototype.

• Journal of Satellite, Information and Communications
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• v.7 no.3
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• pp.30-34
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• 2012

National Meteorological Satellite Center(NMSC) of Korea Meteorological Administration(KMA) has launched to implement the application development to get prepared for the space weather operation since 2010. As a action of KMA's space weather work, NMSC constructed Global Navigation Satellite System(GNSS) application system for meteorology and space weather. We will introduce NMSC's space weather application system which derives regional TEC(Total Electron Content) in near real time using nation-wide GNSS network data. First, We constructed system for collecting GNSS data, which is currently collecting about 80 stations operated by agencies like NGII(National Geographic Information Institute), Central Office of DGPS(Differential GPS), and KASI(Korea Astronomy and Space Science) including KMA's own data of 2 stations. In order to retreive regional TEC over Korean peninsular, we build up the automatic processes running every 1-hour. In these processes, firstly, GNSS data of every stations with 24 hours time window are processed to derive DCBs(Differential Code Biases) of each GNSS station and TEC values on every ionosphere piercing point(IPP). Then we made gridded regional TEC map with resolution of 0.25 degree from 31N, 121E to 41N, 135E by combination of all station results within 30 minutes window with assumption that TEC of a given point during a given 30 minutes window would have a constant value. The grid points without TEC value are interpolated using Barnes objective analysis. We presentour regional TEC maps, which can describe better on the status of ionosphere over Korean peninsular compared to IGS TEC maps.

• The KIPS Transactions:PartB
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• v.8B no.5
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• pp.455-462
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• 2001

The World Wide Web has become one of the major services provided through Internet. When searching the vast web space, users use bookmarking facilities to record the sites of interests encountered during the course of navigation. One of the typical problems arising from bookmarking is that the list of bookmarks lose coherent organization when the the becomes too lengthy, thus ceasing to function as a practical finding aid. In order to maintain the bookmark file in an efficient, organized manner, the user has to classify all the bookmarks newly added to the file, and update the folders. This paper introduces our learning agent called BClassifier that automatically classifies bookmarks by analyzing the contents of the corresponding web documents. The chief source for the training examples are the bookmarks already classified into several bookmark folders according to their subject by the user. Additionally, the web pages found under top categories of Yahoo site are collected and included in the training examples for diversifying the subject categories to be represented, and the training examples for these categories as well. Our agent employs naive Bayesian learning method that is a well-tested, probability-based categorizing technique. In this paper, the outcome of some experimentation is also outlined and evaluated. A comparison of naive Bayesian learning method alongside other learning methods such as k-Nearest Neighbor and TFIDF is also presented.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.10a
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• pp.331-339
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• 2008

Nowadays with advancement in technology and aging society, the number of disabled citizens is increasing. The disabled citizens always need a caretaker for daily life routines especially for mobility. In future, the need is considered to increase more. To reduce the burden from the disabled, various devices for healthcare are introduced using computer technology. The power wheelchair is an important and convenient mobility device. The demand of power wheelchair is increasing for assistance in mobility. In this paper we proposed a robotic wheelchair for mobility aid to reduce the burden from the disabled. The main issue in an autonomous wheelchair is the automatic detection and avoidance of obstacles and going to the pre-designated place. The proposed algorithm detects the obstacles and avoids them to drive the wheelchair to the desired place safely. By this way, the disabled will not always have to worry about paying deep attention to the surroundings and his path. User has a handheld bio-sensor monitoring system for get user's bio-signal. If user detects unusual signal, alarm send to protector.