• Proceedings of the Acoustical Society of Korea Conference
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• autumn
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• pp.189-192
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• 1999

수중소음체의 음원 특징을 해석하기 위해서는 배경잡음과 해면$\cdot$해저반사파의 영향이 적은 심해에서 측정하여 분석하여야 한다. 그러나 측정의 어려움으로 인공 수조에서 측정하여 수면과 수조벽에 의해 발생되는 반사파들을 제거하여 신호 고유의 특징을 해석한다 이러한 반사파들의 부가효과를 보상하여 수중소음체의 신호특징을 해석하기 위하여 정합필터배열처리(Matched Filter Array Process : MFAP)기법을 적용하고자 할 때 각 센서에 적용되는 정합필터는 처리시간의 문제로 인해 필터길이를 제한하여 구성되게 된다 정합필터는 수조의 임펄스응답함수의 시역전함수로 정의되는데 필터길이에 따라 수신신호 특징 개선 정도가 좌우된다 본 연구에서는 인공수조에서 부가되는 반사파들의 효과를 보상하여 수신신호 특징 개선을 위해 정합필터배열처리기법을 적용할 때 각 센서의 정합필터의 시간길이가 특징 개선에 미치는 영향을 신호대잡음비(SNR)로 정의하여 분석하였고 수조의 특성에 따른 최적의 정합필터 시간길이를 제안하고자 한다.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.13 no.2
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• pp.63-70
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• 1999

This paper is proposed a new method to deal with the optimized auto-tuning for the Pill controller which is used to the process-control in various fields. First of all, in this method, 1st order delay system with dead time which is modelled from the unit step response of the system is Pade-approximated, then initial values are determined by the Ziegler-Nichols method. So we can find the parameters of Pill controller so as to minimize the fuzzy criterion function which includes the maximum overshoot, damping ratio, rising time and settling time. Finally, after studying the parameters of Pill controller by Backpropagation of Neural-Network, when we give new K, L, T values to Neural-Network, the optimized parameter of Pill controller is found by Neural-Network Program.rogram.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.37 no.3
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• pp.248-254
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• 2009

The use of evolutionary algorithm is limited in the field of aerodynamics, mainly because the population-based search algorithm requires excessive CPU time. In this paper a coupling method with adaptive range genetic algorithm for floating point and back-propagation neural network is proposed to efficiently obtain a converged solution. As a result, it is shown that a reduction of 14% and 33% respectively in wave drag and its consumed time can be achieved by the new method.

• Journal of English Language & Literature
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• v.58 no.2
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• pp.347-378
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• 2012

Holocaust fiction has always raised the moral and aesthetic questions about the nature of mimesis and the literary representation of atrocity. The Holocaust, defying any representation of it, has been considered as unspeakable, unknowable, and incomprehensible. This essay aims to explore Martin Amis's narrative strategies in Time's Arrow to conduct the difficult tasks of re-creating the primal scene and of discovering a moral reality behind the Holocaust. One of the major narrative experiments in Time's Arrow is the time reversal: the story moves from the present of phony innocence to the past of unrelieved horror. Reversing the temporal order of events reverses causality and generates the revision of the morality, ultimately creating the epistemological and ontological uncertainties. Amis's novel is also narrated from the perspective of a double persona of the protagonist who, as a Nazi doctor, participated in the massacre in Auschwitz and then fled to the United States following the war. As almost a self-conscious storyteller, the narrator shares a sense of retrospective guilt with the reader who finally realizes that the Holocaust was a world turned upside down morally. Amis's postmodern narrative strategies are unusual enough to warrant a new way of representing the Holocaust.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.44 no.2
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• pp.161-172
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• 2024

A Copula approach has the advantage of providing structural dependencies for representing multivariate distributions for the hydrometeorological variable marginal distribution involved, however, copulas are inflexible for extending in high dimensions, and satisfy certain assumptions to make the dependency. In addition, since the process of estimating design rainfall under the future climate associated with durations given a return period is mainly analyzed by 24-hour annual maximum rainfalls, the dependency structure contains information only on the daily and sub-daily extreme precipitation. Methods based on bivariate copula do not provide information for other duration's dependencies, which causes the intensity to be reversed. The vine copula has been proposed to process the multivariate analysis as vines consisting of trees with nodes and edges connecting pair-copula construction. In this study, we aimed to downscale under climate change to produce sub-daily extreme precipitation data considering different durations based on vine copula.

• The Journal of the Acoustical Society of Korea
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• v.13 no.1
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• pp.5-13
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• 1994

This paper presents a study on Neural Networks for Phoneme Recognition and performs the Phoneme Recognition using TDNN (Time Delay Neural Network). Also, this paper proposes training algorithm for speech recognition using neural nets that is a proper to large scale TDNN. Because Phoneme Recognition is indispensable for continuous speech recognition, this paper uses TDNN to get accurate recognition result of phonemes. And this paper proposes new training algorithm that can converge TDNN to an optimal state regardless of the number of phonemes to be recognized. The recognition experiment was performed with new training algorithm for TDNN that combines backpropagation and Cauchy algorithm using stochastic approach. The results of the recognition experiment for three phoneme classes for two speakers show the recognition rates of $98.1\%$. And this paper yielded that the proposed algorithm is an efficient method for higher performance recognition and more reduced convergence time than TDNN.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.36 no.3
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• pp.157-165
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• 2000

A small hydraulic winch system with an automatic tension control unit was designed to improve the work efficiency of coastal small vessels and the dynamic response characteristics of the winch system operated in the open loop condition was investigated. The inlet and the outlet pressures in hydraulic motor, the torque and the rotating speed of winch drum were measured as a function of time, and the behaviour in autotension mode for stepped load changes was analyzed. The results obtained are summarized as follows : 1. The developed winch system for coastal small vessels will result in better fishing with improved efficiency and lower manpower consumption by remote control of winch system. 2. The rotating delay times of winch drum for on/off operations of solenoid valve were 0.09 see at CW mode and 0.04 sec at CCW mode, respectively. After the solenoid valve was controlled, response characteristics were unstable slightly but showed good tracking behaviour over short time. 3. The driving torque of winch system in autotension mode was kept almost constant of 55.9 kgf·m, and 11.1 then the rotating speed of winch drum was kept almost constant of 5.1 rpm in the larger torque than 55.9 kgf·m and 11.1 rpm in the lower torque than that. 4. The 5% settling times in the transient response characteristics of autotension mode under rapid increasing and decreasing conditions of load were 0.12 sec and 0.2 sec, respectively, and then the rotating speeds were 11 rpm and 5.3 rpm, respectively. 5. The tracking behaviour of torque and rotating speed by remote control operation were stable within 0.23 sec at CW mode and 0.37 sec at CCW mode, respectively.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.5B
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• pp.485-493
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• 2008

The Artificial Neural Network (ANN) model was suggested for predicting probability of precipitation (PoP) using RDAPS NWP model, observation at AWS and upper-air sounding station. The prediction work was implemented for flood season and the data period is the July, August of 2001 and June of 2002. Neural network input variables (predictors) were composed of geopotential height 500/750/1000 hPa, atmospheric thickness 500-1000 hPa, X & Y-component of wind at 500 hPa, X & Y-component of wind at 750 hPa, wind speed at surface, temperature at 500/750 hPa/surface, mean sea level pressure, 3-hr accumulated precipitation, occurrence of observed precipitation, precipitation accumulated in 6 & 12 hrs previous to RDAPS run, precipitation occurrence in 6 & 12 hrs previous to RDAPS run, relative humidity measured 0 & 12 hrs before RDAPS run, precipitable water measured 0 & 12 hrs before RDAPS run, precipitable water difference in 12 hrs previous to RDAPS run. The suggested ANN has a 3-layer perceptron (multi layer perceptron; MLP) and back-propagation learning algorithm. The result shows that there were 6.8% increase in Hit rate (H), especially 99.2% and 148.1% increase in Threat Score (TS) and Probability of Detection (POD). It illustrates that the suggested ANN model can be a useful tool for predicting rainfall event prediction. The Kuipers Skill Score (KSS) was increased 92.8%, which the ANN model improves the rainfall occurrence prediction over RDAPS.

• Journal of KIISE:Computer Systems and Theory
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• v.30 no.2
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• pp.68-77
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• 2003

The Least-Laxity First(or LLF) scheduling algorithm assigns the highest priority to a task with the least laxity, and has been proved to be optimal for a uni-processor and sub-optimal for a multi-processor. However, this algorithm Is Impractical to implement because laxity tie results in the frequent context switches among tasks. In this paper, a Modified Least-Laxity First on Multiprocessor(or MLLF/MP) scheduling algorithm is proposed to solve this problem, i.e., laxity tie results in the excessive scheduling overheads. The MLLF/MP is based on the LLF, but allows the laxity inversion. MLLF/MP continues executing the current running task as far as other tasks do not miss their deadlines. Consequently, it avoids the frequent context switches. We prove that the MLLF/MP is also sub-optimal in multiprocessor systems. By simulation results, we show that the MLLF/MP has less scheduling overheads than LLF.

• The Journal of the Acoustical Society of Korea
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• v.32 no.4
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• pp.308-316
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• 2013

A set of experiments (Shallow Water 2006, SW06) was carried out in shallow water near the New Jersey shelf break in summer 2006. Significant fluctuations in direct and surface reflected arrivals were observed from the chirp data (1100~2900 Hz) measured on a vertical line array. This paper presents a geoacoustic inverssion technique for short-range acoustic data with fluctuating arrivals and inversion results of experimental data. In order to reduce effects of random sea surface on the inversion, the acoustic energy back-propagated from the array to the source through direct and bottom-reflected paths is defined as the objective function. A multi-step inversion scheme is applied to the data using VFSR (Very Fast Simulated Reannealing) optimization technique. The inversion results show a source depth oscillation period equal to the measured ocean surface wave period. The inverted bottom sound speed is 1645 m/s and is similar to that estimated by other work at the same site.