• Journal of Fisheries and Marine Sciences Education
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• v.24 no.5
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• pp.712-720
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• 2012

Recently, many problems related on shoreline response to spill oil were exposed again on a occasion of M/T Hebei spirit accident even though the weakness on the shoreline response system has been brought up since M/T Sea Prince oil spill accident. Therefore the establishment of shoreline response system that best suits our country is needed through considering the response system of well-developed country. The socioeconomic conflict between the persons concerned on the clean-up endpoints can be sharpened in Korea because the frequency of coastal use of our country is too high compared to other countries. Thus procedural justification, that is, how the clean-up endpoints be established is more important than what type of clean-up endpoints be used. In the present paper, we attempted to suggest a new manner on the decision making system for clean-up endpoints that best suits our country. The decision making system for clean-up endpoints need to be divided into two steps, that is, set-up step of clean-up endpoints criteria and decision step of clean-up endpoints. The decision making organization of local governments play a key role in case of set-up step of clean-up endpoints criteria, while the response command headquarters under Korean coast guard and decision making organization of local governments codecide whether the clean-up endpoints criteria is fits or not.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.46 no.5
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• pp.8-14
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• 2009

In the research field of speech recognition, pinpointing the endpoints of speech utterance even with the presence of background noise is of great importance. These noise present during recording introduce disturbances which complicates matters since what we just want is to get the stationary parameters corresponding to each speech section. One major cause of error in automatic recognition of isolated words is the inaccurate detection of the beginning and end boundaries of the test and reference templates, thus the necessity to find an effective method in removing the unnecessary regions of a speech signal. The conventional methods for speech endpoint detection are based on two linear time-domain measurements: the short-time energy, and short-time zero-crossing rate. They perform well for clean speech but their precision is not guaranteed if there is noise present, since the high energy and zero-crossing rate of the noise is mistaken as a part of the speech uttered. This paper proposes a novel approach in finding an apparent threshold between noise and speech based on Lyapunov Exponents (LEs). This proposed method adopts the nonlinear features to analyze the chaos characteristics of the speech signal instead of depending on the unreliable factor-energy. The excellent performance of this approach compared with the conventional methods lies in the fact that it detects the endpoints as a nonlinearity of speech signal, which we believe is an important characteristic and has been neglected by the conventional methods. The proposed method extracts the features based only on the time-domain waveform of the speech signal illustrating its low complexity. Simulations done showed the effective performance of the Proposed method in a noisy environment with an average recognition rate of up 92.85% for unspecified person.