• Korean Journal of Logic
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• v.8 no.2
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• pp.3-32
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• 2005

Hilbert's rational ambition to establish consistency in Number theory and mathematics in general was frustrated by the fact that the statement itself claiming consistency is undecidable within its formal system by $G\ddot{o}del's$ second theorem. Hilbert's optimism that a mathematician should not say "Ignorabimus" ("We don't know") in any mathematical problem also collapses, due to the presence of a undecidable statement that is neither provable nor refutable. The failure of his program receives more shock, because his system excludes any ambiguity and is based on only mechanical operations concerning signs and strings of signs. Above all, $G\ddot{o}del's$ theorem demonstrates the limits of formalization. Now, the notion of provability in the dimension of syntax comes to have priority over that of semantic truth in mathematics. In spite of his failure, the notion of algorithm(mechanical processe) made a direct contribution to the emergence of programming languages. Consequently, we believe that his program is failure, but a great one.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2012.05a
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• pp.555-561
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• 2012

The Hilbert Huang Transform (HHT) technigue with Empirical Mode Decomposition (EMD) is one of the time-frequency domain analysis methods and it has several advantages such that analyzing non-stationary and nonlinear signal is possible. However, there are shortcomings in detecting near-range of frequencies and added noise signals. In this paper, to analyze characteristics of each method, HHT and Short-Time Fourier Transform (STFT) effective in dealing with stationary signals are compared. And with thermoacoustic instabilities signals from a Rijke tube test, HHT and the improved HHT with Ensemble Empirical Mode Decomposition (EEMD) are compared. The results show that the improved HHT is more appropriate than the original HHT due to the relative insensitivity to noise. Therefore it will result in more accurate analysis.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2005.05a
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• pp.982-982
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• 2005

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2014.04a
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• pp.225-226
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• 2014

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2012.04a
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• pp.546-547
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• 2012

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.06a
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• pp.739-742
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• 2007

In the step processing multimedia information signals transmitted by a variety of mediums, noises are generated by the internal or exterior causes of systems and these noises degrade the perception about information signals. Therefore, in order to remove noises and restore signals a great number of researches have been progressed and recently, many noise removal methods using time-frequency localization of wavelet have been applied in wide applications. Moreover, when two wavelet bases are designed to accomplish the Hilbert transform pair, wavelet can be efficiently applied to detect characteristics of signals. Therefore, in this paper, in order to restore the corrupted signal by noises, a noise removal algorithm using the Hilbert transform pair of wavelet was proposed.

• Journal of the Korean Society of Propulsion Engineers
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• v.11 no.2
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• pp.62-70
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• 2007

The aiming ability is a to improve accuracy performance of the firing vehicle. This paper describes the detection method of chatter vibration using disturbance acceleration in the pointing structure. In order to analysis vibration trends of the pointing system occurred during vehicle drive, acceleration data was processed by using data processing algorithm with moving average and Hilbert transform. Specific mode constants of acceleration were obtained under various disturbances. Vehicle velocity, road condition, property of pointing structure were considered as factors which make change of vibration trend in vehicle dynamics. Finally, back propagation neural networks have been applied to the pattern recognition for the classification of vibration signal in various driving conditions. Results of signal processing were compared and analysed.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.2
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• pp.179-190
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• 2017

Hand Accelerometers are widely used to detect human motion patterns in real-time. It is essential to reliably identify which type of activity is performed by human subjects. This rests on having accurate template of each activity. Many human activities are represented as a set of multiple time-series data from such sensors, which are mostly non-stationary and non-linear in nature. This requires a method which can effectively extract patterns from non-stationary and non-linear data. To achieve such a goal, we propose the method to apply Hilbert-Huang Transform which is known to be an effective way of extracting non-stationary and non-linear components from time-series data. It is applied on samples of accelerometer data to determine its effectiveness.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.5
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• pp.631-637
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• 2010

In this paper, We propose a method of motion interpretation of pedestrian for active traffic signal control. We detect pedestrian object in a movie of crosswalk area by using the code book method and acquire contour information. To do this stage fast, we use parallel processing based on CUDA (Compute Unified Device Architecture). And we remove shadow which causes shape distortion of objects. Shadow removed object is judged by using the hilbert scan distance whether to human or noise. If the objects are judged as a human, we analyze pedestrian objects' motion, face area feature, waiting time to decide that they have intetion to across a crosswalk for pdestrians. Traffic signal can be controlled after judgement.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.11a
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• pp.804-807
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• 2013

최근 클라우드 컴퓨팅에 대한 관심이 고조됨에 따라, 이를 활용한 데이터베이스 아웃소싱(Outsourcing)에 대한 연구가 활발히 진행되고 있다. 그러나 아웃소싱 된 데이터베이스는 사용자 개인 정보, 증권, 또는 의료 정보 등 민감한 정보를 포함하기 때문에 서비스 제공자로부터 수행한 질의 결과 데이터가 데이터 소유자로부터 생성된 데이터이며, 정확한 질의 결과를 포함하는지 확인하기 위한 질의 결과 무결성 검증 기법의 필요성이 대두되었다. 기존 질의 결과 무결성 검증 기법은 질의 결과에 포함되는 무결성 검증 데이터의 크기가 증가하여 검증 데이터 전송 오버헤드 증가 및 데이터 노출 위험 증가 문제를 지닌다. 따라서, 본 논문에서는 데이터 보호를 지원하는 암호화 데이터 기반 질의 결과 무결성 검증 기법을 제안한다. 제안하는 질의 결과 무결성 검증 기법은 암호화된 데이터 그룹을 주기 함수를 이용하여 재분할하고, 최종 데이터 그룹 id를 힐버트 커브를 통해 변환한다. 따라서, 검증 데이터 오버헤드를 감소시켜 효율적인 질의 처리를 지원하며, 그룹 id 변경을 통해 검증 데이터 유출 위험을 방지한다. 성능평가를 통해, 제안하는 기법이 기존 기법에 비해 질의 처리 시간 측면에서 평균 2배, 검증 데이터 오버헤드 측면에서 최대 20배의 성능을 개선함을 보인다.