• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2016.05a
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• pp.285-286
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• 2016

We aim to propose the prediction modeling method of ship's position with extracting ship's trajectory model through pattern recognition based on the data that are being collected in VTS centers at real time. Support Vector Machine algorithm was used for data modeling. The optimal parameters are calculated with k-fold cross validation and grid search. We expect that the proposed modeling method could support VTS operators' decision making in case of complex encountering traffic situations.

• Phonetics and Speech Sciences
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• v.6 no.2
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• pp.29-34
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• 2014

In the Vector Taylor Series (VTS)-based noisy speech recognition methods, Hidden Markov Models (HMM) are usually trained with clean speech. However, better performance is expected by training the HMM with noisy speech. In a previous study, we could find that Minimum Mean Square Error (MMSE) estimation of the training noisy speech in the log-spectrum domain produce improved recognition results, but since the proposed algorithm was done in the log-spectrum domain, it could not be used for the HMM adaptation. In this paper, we modify the previous algorithm to derive a novel mathematical relation between test and training noisy speech in the cepstrum domain and the mean and covariance of the Multi-condition TRaining (MTR) trained noisy speech HMM are adapted. In the noisy speech recognition experiments on the Aurora 2 database, the proposed method produced 10.6% of relative improvement in Word Error Rates (WERs) over the MTR method while the previous MMSE estimation of the training noisy speech produced 4.3% of relative improvement, which shows the superiority of the proposed method.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.3
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• pp.519-526
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• 2016

As marine accidents happen frequently, it is required to establish a marine traffic monitoring system, which is designed to improve the safety and efficiency of navigation in VTS (Vessel Traffic Service). For this aim, recently, X-band marine radar is used for extracting the sea surface information and, it is necessary to retrieve wave information correctly and provide for the safe and efficient movement of vessel traffic within the VTS area. In this paper, three different current estimation algorithms including the classical least-squares (LS) fitting, a modified iterative least-square fitting routine and a normalized scalar product of variable current velocities are compared with buoy data and then, the iterative least-square method is modified to estimate wave information by improving the initial current velocity. Through several simulations with radar signals, it is shown that the proposed method is effective in retrieving the wave information compared to the conventional methods.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.3
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• pp.47-53
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• 2017

There is a difficulty in preventing drunken driving by enforcing alcohol control on the sea due to the environment of Marine transportation rather than roads. In the previous study, we proposed the algorithm, that was developed to identify the voices changed according to be drunk. Using the developed algorithm, it became possible to know the possibility of drinking by long distance ship operators and crew members. In that method drinking can be measured in real time, no matter how far the distance is, if the interception is through a voice that can be transmitted over a distance, rather than a short distance. When communicating voice using the VTS wireless devices, clipping occurs when that environment is uneven, and the rate of judgment of the possibility of drinking may be lowered. Therefore, in this paper, we proposed an enhanced method to compensate the signal in order to reduce the error rate of the possibility of drinking due to distortion of the speech signal.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2009.10a
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• pp.62-63
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• 2009

A monitoring system of collision risk among multiple ships is newly-designed in order to reduce human error and make vessel traffic control more effective. By using AIS data as ships' navigational information, an estimation algorithm of collision risk among multiple ships is newly-designed. To consider ships' course of now and future, collision risks of multiple ships can be calculated by using fuzzy algorithm. To test the performance of new algorithm, replay simulations are carried out on actual AIS data collected from VTS center of Ulsan harbor in Korea. The AIS data include 25 ships' information for two hours. In this paper, the features of newly-designed estimation algorithm of collision risk and the results of replay simulation are discussed.

• 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.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2018.05a
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• pp.160-161
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• 2018

ITU-R Study Group Working Party 5B에서는 해상에서 자율운항선을 안전하게 운항하기 위해 자율운항선을 통한 제어센터-VTS, 제어센터-유인선 간의 정보교환이 이루어 질 수 있도록 Vessel traffic control voice relay의 기능을 제시하였다. 이에 자율운항선을 통해 제어센터-VTS, 제어센터-유인선 간의 원활한 정보교환이 가능하도록 사용자 기능 요구사항, 사용자 비기능 요구사항, 인터페이스 요구사항으로 분석함으로써 통신중계시스템 설계 및 각 운용 기기별 정보교환 체계를 구축하였다. 하지만 자율운항선-타 선박간의 충돌 위험성을 감지할 경우 충돌회피를 위한 흐름 및 통신중계시템을 활용한 메시지 처리과정은 설계되지 아니한 실정이다. 이에 본 연구에서는 액티비티, 제어흐름, 작업 흐름 등의 표현이 가능한 UML(unified modeling language)을 활용함으로써 항해단계 중 발생할 수 있는 상황별 시나리오를 제어 흐름 형태로 표현한 정보교환 메시지 처리 알고리즘을 제안하고자 한다.

• The Journal of the Acoustical Society of Korea
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• v.16 no.5
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• pp.112-121
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• 1997

In this paper, we study a model parameter compensation method for noise-robust speech recognition. We study model parameter compensation on a sentence by sentence and no other informations are used. Parallel model combination(PMC), well known as a model parameter compensation algorithm, is implemented and used for a reference of performance comparision. We also propose a modified PMC method which tunes model parameter with an association factor that controls average variability of gaussian mixtures and variability of single gaussian mixture per state for more robust modeling. We obtain a re-estimation solution of environmental variables based on the expectation-maximization(EM) algorithm in the cepstral domain. To evaluate the performance of the model compensation methods, we perform experiments on speaker-independent isolated word recognition. Noise sources used are white gaussian and driving car noise. To get corrupted speech we added noise to clean speech at various signal-to-noise ratio(SNR). We use noise mean and variance modeled by 3 frame noise data. Experimental result of the VTS approach is superior to other methods. The scheme of the zero order VTS approach is similar to the modified PMC method in adapting mean vector only. But, the recognition rate of the Zero order VTS approach is higher than PMC and modified PMC method based on log-normal approximation.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2015.07a
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• pp.310-311
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• 2015

Ships' tracking data are being monitored and collected by vessel traffic service center in real time. In this paper, we intend to contribute to vessel traffic service operators' decision making through extracting ships' tracking patterns and models based on these data. Support Vector Machine algorithm was used for vessel track modeling to handle and process the data sets and k-fold cross validation was used to select the proper parameters. Proposed data processing methods could support vessel traffic service operators' decision making on case of anomaly detection, calculation ships' dead reckoning positions and etc.

• Journal of the Korean Institute of Navigation
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• v.15 no.2
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• pp.39-47
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• 1991

As per the rapid development of world economics the marine traffic volume was increased accordingly and caused frequent disasters in human lives and natural environment in the consequence of accidents. As the result of the above they started to establish Vessel Traffic System(VTS) and separation scheme in waterway from 1960' to prevent the marin traffic accident but the problem of safety at sea appears now as neither fully defined nor sufficiently analysed. At the present, the dominant factor in establishing the strategy of marine traffic has been safety of navigation concerning only with the ship, but the risk of society derives almost wholly from the nature of cargo. To measure the degree of danger for each ship there is suggested concept of safety factor numbers denoting the level of latent danger in connection with ship and her cargo. In this paper, where the strategy of VTS is put on controlling density of safety factor for control area. it suggested algorithms how to assign the vessels and also to get optimal sequence of vessels located to a sector in the sense of minimizing the passage delay. For the formulation of problem, min max and 0-1 programming methods are applied and developed heuristic algorithm is presented with numerical example to improve the efficiency of calculation.