• 구강회복응용과학지
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• 제22권4호
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• pp.341-348
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• 2006

Accurate fit of the implant prosthesis is important in ensuring long term success of osseointegrated implant. Inaccurate fit of the implant prosthesis may give rise to complications and mechanical failure. To evaluate fite of the implant prosthesis, the development of the methods of analyzing the degree of misfit is important in clinical practice. To analyze the degree of the misfit of implant prosthesis, modal testing was used. A 2-dimensional finite element modal testing was accomplished. Four 2-dimensional finite element models with various levels of misfit of implant prostheses were constructed. Thickness gauges were simulated to make misfit in the implant prostheses. With eigenvalue analysis, the natural frequencies of the models were found in the frequency domain representation of vibration. According to the difference of degree of misfit, natural frequencies of the models were changed.

• 구강회복응용과학지
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• 제22권3호
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• pp.251-260
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• 2006

Accurate fit of the implant prosthesis is important in ensuring long term success of osseointegrated implant. Inaccurate fit of the implant prosthesis may give rise to complications and mechanical failure. To evaluate fite of the implant prosthesis, the development of the methods of analyzing the degree of misfit is important in clinical practice. To analyze the degree of the misfit of implant prosthesis, modal testing was used. A 2-dimensional finite element modal testing was accomplished. Four 2-dimensional finite element models with various levels of misfit of implant prostheses were constructed. Thickness gauges were simulated to make misfit in the implant prostheses. With eigenvalue analysis, the natural frequencies of the models were found in the frequency domain representation of vibration. According to the difference of degree of misfit, natural frequencies of the models were changed.

• Journal of Information Processing Systems
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• 제17권4호
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• pp.818-833
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• 2021

To address the problems of low precision rate, insufficient feature extraction, and poor contextual ability in existing text sentiment analysis methods, a mixed model account of a CNN-BiLSTM-TE (convolutional neural network, bidirectional long short-term memory, and topic extraction) model was proposed. First, Chinese text data was converted into vectors through the method of transfer learning by Word2Vec. Second, local features were extracted by the CNN model. Then, contextual information was extracted by the BiLSTM neural network and the emotional tendency was obtained using softmax. Finally, topics were extracted by the term frequency-inverse document frequency and K-means. Compared with the CNN, BiLSTM, and gate recurrent unit (GRU) models, the CNN-BiLSTM-TE model's F1-score was higher than other models by 0.0147, 0.006, and 0.0052, respectively. Then compared with CNN-LSTM, LSTM-CNN, and BiLSTM-CNN models, the F1-score was higher by 0.0071, 0.0038, and 0.0049, respectively. Experimental results showed that the CNN-BiLSTM-TE model can effectively improve various indicators in application. Lastly, performed scalability verification through a takeaway dataset, which has great value in practical applications.

• ETRI Journal
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• 제35권1호
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• pp.100-108
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• 2013

In this paper, a feature extraction (FE) method is proposed that is comparable to the traditional FE methods used in automatic speech recognition systems. Unlike the conventional spectral-based FE methods, the proposed method evaluates the similarities between an embedded speech signal and a set of predefined speech attractor models in the reconstructed phase space (RPS) domain. In the first step, a set of Gaussian mixture models is trained to represent the speech attractors in the RPS. Next, for a new input speech frame, a posterior-probability-based feature vector is evaluated, which represents the similarity between the embedded frame and the learned speech attractors. We conduct experiments for a speech recognition task utilizing a toolkit based on hidden Markov models, over FARSDAT, a well-known Persian speech corpus. Through the proposed FE method, we gain 3.11% absolute phoneme error rate improvement in comparison to the baseline system, which exploits the mel-frequency cepstral coefficient FE method.

• 대한의용생체공학회:의공학회지
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• 제27권5호
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• pp.237-244
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• 2006

This study proposes an approach to the performance improvement of EMG(Electromyogram) pattern recognition. MFCC(Mel-Frequency Cepstral Coefficients)'s approach is molded after the characteristics of the human hearing organ. While it supplies the most typical feature in frequency domain, it should be reorganized to detect the features in EMG signal. And the dynamic aspects of EMG are important for a task, such as a continuous prosthetic control or various time length EMG signal recognition, which have not been successfully mastered by the most approaches. Thus, this paper proposes reorganized MFCC and HMM-GMM, which is adaptable for the dynamic features of the signal. Moreover, it requires an analysis on the most suitable system setting fur EMG pattern recognition. To meet the requirement, this study balanced the recognition-rate against the error-rates produced by the various settings when loaming based on the EMG data for each motion.

• 대한전자공학회논문지SD
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• 제43권5호
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• pp.34-47
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• 2006

본 논문에서는 무선 트랜시버 구성소자들의 완제품 테스팅을 용이하게 할 수 있는 새로운 테스팅 기법을 제안하였다. 즉 RF 집적회로에 존재하는 고장들에 대하여 설계사양의 정보를 포함하는 구간고장모델(band fault model)을 제안하고 이 구간고장모델들의 변화를 회로의 출력에서 그대로 관찰할 수 있도록 함으로써 시간영역에서 설계사양에 대한 테스트를 용이하게 할 수 있는 방식을 제시하였다. 이 방식은 주파수 영역에서 테스트를 행하는 기존의 설계사양 테스트를 시간영역에서 용이하게 테스트할 수 있도록 함으로써 고가의 테스트 장비가 필요 없으며 테스트 시간이 단축되는 장점이 있다. 본 논문에서 제시된 테스팅 기법을 5.25 GHz 저잡음증폭기의 테스트에 적용하여 설계사양을 고려한 시간영역 테스팅 기법이 저잡음증폭기를 비롯한 RF 집적회로의 테스트에 매우 효과적임을 입증하였다.

• International Journal of Naval Architecture and Ocean Engineering
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• 제12권1호
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• pp.491-500
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• 2020

The present study proposes a time domain model for the Vortex-induced Vibration (VIV) simulation of a catenary riser under the combination of the current and oscillatory flow induced by vessel motion. In this model, the hydrodynamic force of VIV comprises excitation force, hydrodynamic damping and added mass, which are taken as functions of the non-dimensional frequency and amplitude ratio. The non-dimensional frequency is related with the response frequency, natural frequency, lock-in range and the fluid velocity. The relatively oscillatory flow induced by vessel motion is taken into account in the fluid velocity. Considering that the added mass coefficient and the non-dimensional frequency can affect each other, an iterative analysis is conducted at each time step to update the added mass coefficient and the natural frequency. This model is in detail validated against the published test models. The results show that the model can reasonably reflect the effect of the added mass coefficient on the VIV, and can well predict the riser's VIV under stationary and oscillatory flow induced by vessel motion. Based on the model, this study carries out the VIV simulation of a catenary riser with harmonic vessel motion. By analyzing the bending moment near the touchdown point, it is found that under the combination of the ocean current and oscillatory flow the vessel motion may decrease the VIV response, while increase the excited frequencies. In addition, the decreasing rate of the VIV under vessel surge is larger than that under vessel heave at small vessel motion velocity, while the situation becomes opposite at large vessel motion velocity.

• Nuclear Engineering and Technology
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• 제56권2호
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• pp.688-706
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• 2024

Austenitic stainless steels (ASS) are extensively employed in various sectors such as nuclear, power, petrochemical, oil and gas because of their excellent structural strength and resistance to corrosion. SS304 and SS316 are the predominant choices for piping, pressure vessels, heat exchangers, nuclear reactor core components and support structures, but they are susceptible to stress corrosion cracking (SCC) in chloride-rich environments. Over the course of several decades, extensive research efforts have been directed towards evaluating SCC using diverse methodologies and models, albeit some uncertainties persist regarding the precise progression of cracks. This review paper focuses on the application of Acoustic Emission Technique (AET) for assessing SCC damage mechanism by monitoring the dynamic acoustic emissions or inelastic stress waves generated during the initiation and propagation of cracks. AET serves as a valuable non-destructive technique (NDT) for in-service evaluation of the structural integrity within operational conditions and early detection of critical flaws. By leveraging the time domain and time-frequency domain techniques, various Acoustic Emission (AE) parameters can be characterized and correlated with the multi-stage crack damage phenomena. Further theories of the SCC mechanisms are elucidated, with a focus on both the dissolution-based and cleavage-based damage models. Through the comprehensive insights provided here, this review stands to contribute to an enhanced understanding of SCC damage in stainless steels and the potential AET application in nuclear industry.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2004년도 춘계학술대회 논문요약집
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• pp.188-188
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• 2004

Modal testing and analysis is a primary tool for obtaining reliable models to represent the dynamics of structures. When a structure is tested in order to collect measured data in modal testing, we usually use attached accelerometers to pick up the response data. Change in modal parameters due to the mass of transducers in modal testing is a well-known problem. The disadvantages are the shift of measured modal frequencies and the change of modal shapes, which can cause inaccurate results in further analysis. Modal analysis methods in frequency domain are based on a set of measured frequency response functions(FRF).(omitted)

• 한국소음진동공학회논문집
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• 제18권6호
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• pp.642-653
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• 2008

이 연구는 중앙면 상에서 주성분 분석법을 이용하여 시간 및 주파수 영역에서 머리전달함수의 모형화 기법들을 다룬다. 시간영역의 머리전달함수, 복소수 값의 머리전달함수, 확장된 머리전달함수, 로그 크기의 머리전달함수에 기반하여 각각 주성분 분석법을 수행하여 얻은 네 가지 머리전달함수 모형들에 대해서 최소자승오차 관점에서 모형화 성능을 비교하고, 모형들간의 이론적인 관계를 살펴보는 것이 이 연구의 목적이다. 모형화에 사용되는 기저함수의 수가 동일하다면, 시간영역에서의 머리전달함수 혹은 확장된 머리전달함수에 기반한 모형이 복소수 값의 머리전달함수에 기반한 모형보다 최소자승오차 관점에서 더 효율적인 모형화 성능을 지닌다. 시간영역에서의 머리전달함수에 기반한 모형과 확장된 머리전달함수에 기반한 모형은 이론적으로 동일한 모형이며 서로 푸리에 변환 관계가 있다. 로그 크기의 머리전달함수에 기반한 모형은 다른 모형들과 모형화 성능 및 이론적인 관계를 비교할 수가 없는데, 이는 로그 크기의 머리전달함수에 기반한 모형은 머리전달함수의 크기 정보만을 로그 크기로 다루는 반면에 다른 모형들은 선형 크기로 머리전달함수의 크기와 위상정보를 모두 다루기 때문이다.