• Geophysics and Geophysical Exploration
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• v.25 no.4
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• pp.242-251
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• 2022

Automatic differentiation automatically calculates the derivatives of a function using the chain rule once the forward operation of a function is defined. Given the recent development of computing libraries that support automatic differentiation, many researchers have adopted automatic differentiation techniques to solve geophysical inverse problems. We analyzed the advantages, disadvantages, and performances of automatic differentiation techniques using the gradient calculations of seismic full waveform inversion objective functions. The gradients of objective functions can be expressed as multiplications of the derivatives of the model parameters, wavefields, and objective functions using the chain rule. Using numerical examples, we demonstrated the speed of analytic differentiation and the convenience of complex gradient calculations for automatic differentiation. We calculated derivatives of model parameters and objective functions using automatic differentiation and derivatives of wavefields using analytic differentiation.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.36 no.7
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• pp.634-641
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• 2008

Automatic Differentiation(AD) is a tool for generating sensitivities, such as gradient or Jacobian, automatically. AD tools provide mathematically exact sensitivities for the given source code. In this paper applications of automatic differentiation are studied. Derivative codes are generated with AD tools for structural analysis code and flow analysis code. How to apply AD tools is explained and the accuracy of sensitivities is compared with the finite difference. Sensitivities of generated derivative code accord well with finite difference, but the calculation time of derivative code increases. It was found that the calculation time can be decreased by additional modification of derivative code.

• Journal of the Korean Society for information Management
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• v.24 no.1 s.63
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• pp.251-271
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• 2007

This paper studies the problem of classifying documents with labeled and unlabeled learning data, especially with regards to using document similarity features. The problem of using unlabeled data is practically important because in many information systems obtaining training labels is expensive, while large quantities of unlabeled documents are readily available. There are two steps In general semi-supervised learning algorithm. First, it trains a classifier using the available labeled documents, and classifies the unlabeled documents. Then, it trains a new classifier using all the training documents which were labeled either manually or automatically. We suggested two types of semi-supervised learning algorithm with regards to using document similarity features. The one is one step semi-supervised learning which is using unlabeled documents only to generate document similarity features. And the other is two step semi-supervised learning which is using unlabeled documents as learning examples as well as similarity features. Experimental results, obtained using support vector machines and naive Bayes classifier, show that we can get improved performance with small labeled and large unlabeled documents then the performance of supervised learning which uses labeled-only data. When considering the efficiency of a classifier system, the one step semi-supervised learning algorithm which is suggested in this study could be a good solution for improving classification performance with unlabeled documents.

• Journal of Korean Society of Steel Construction
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• v.12 no.5 s.48
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• pp.569-579
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• 2000

An improved multi-level (IML) optimization algorithm using automatic differentiation (AD) of framed structures is proposed in this paper. For the efficiency of the proposed algorithm, multi-level optimization techniques using a decomposition method that separates both system-level and element-level optimizations, that utilizes and an artificial constraint deletion technique, are incorporated in the algorithm. And also to save the numerical efforts, an efficient reanalysis technique through approximated structural responses such as moments and frequencies with respect to intermediate variables is proposed in the paper. Sensitivity analysis of dynamic structural response is executed by AD that is a powerful technique for computing complex or implicit derivatives accurately and efficiently with minimal human effort. The efficiency and robustness of the IML algorithm, compared with a plain multi-level (PML) algorithm, is successfully demonstrated in the numerical examples.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.7
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• pp.842-848
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• 2020

Music markets have entered the era of streaming. In order to select and propose music that suits the taste of music consumers, there is an active demand and research on an automatic music genre classification system. We propose a method to improve the accuracy of genre unclassified songs, which was a lack of the previous system, by using a generative adversarial network (GAN) to further develop the automatic voting system for deep learning music genre using Softmax proposed in the previous paper. In the previous study, if the spectrogram of the song was ambiguous to grasp the genre of the song, it was forced to leave it as an unclassified song. In this paper, we proposed a system that increases the accuracy of genre classification of unclassified songs by converting the spectrogram of unclassified songs into an easy-to-read spectrogram using GAN. And the result of the experiment was able to derive an excellent result compared to the existing method.

• ICROS
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• v.2 no.1
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• pp.72-84
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• 1996

• Computational Structural Engineering
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• v.35 no.4
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• pp.23-26
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• 2022

• Computational Structural Engineering
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• v.36 no.4
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• pp.14-17
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• 2023

• Journal of the Korea Society for Simulation
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• v.2 no.1
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• pp.78-90
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• 1993

기존의 모의 실험언어를 이용해서 연속 체계를 모의 실험하는 것을 사용자가 언어에서 요구하는 형태로 모델을 형성해야 하는 어려움이 따른다. 따라서 본 연구에서는 사용자에게 최대한 편의성을 제공하는 연속체계 모의 실험언어인 PCSL (Postech Continuous -system Simulation Language)를 개발하였다. PCSL은 주어진 대상을 모델링한 미분방정식과 그것을 푸는데 필요한 여러 가지 제약 사항으로 이루어진 간단한 프로그램을 입력으로 받아 자동으로 모의 실험을 수행함으로서 사용자의 노력이 최소화하게 된다. PCSL 처리 시스템의 구성은 주어진 모델을 C 프로그램으로 변형하는 변환기, 모의 실험 알고리즘을 구현한 C 프로그램을 생성하는 생성기, 모의 실험을 수행하는 실행기, 사용자 인터페이스 등으로 되어있다. 구현 예로는 먼저 선형 상미분방정식의 예로 mass-damper-spring system, 비선형 상미분방정식의 예로 van der Pol 방정식, 연립 상미분방정식의 예로는 mixing tank problem 등을 보였다.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.44 no.1
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• pp.100-107
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• 2007

AABR(automated auditory brainstem response) test is used for the screening purpose of hearing ability of neonates. In this paper, algorithm using Rolle's theorem is suggested for automatic detection of the ensemble averaged ABR waveform. The ABR waveforms were recorded from 55 normal-hearing ears of neonates at screening levels varying from 30 to 60 dBnHL. Recorded signals were analyzed by expert audiologist and by the proposed algorithm. The results showed that the proposed algorithm correctly identified latencies of the major ABR waves (III, V) with latent difference below 0.2 ms. No significant differences were found between the two methods. We also analyzed the ABR signals using derivative algorithm and compared the results with proposed algorithm. The number of detected candidate waves using the proposed algorithm was 47 % less than that of the existing one. The proposed method had lower relative errors (0.01 % error at 60dBnHL) compared to the existing one. By using proposed algorithm, clinicians can detect and label waves III and V more objectively and quantitatively than the manual detection method.