• Title/Summary/Keyword: Domain-independent

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Dynamic analysis of structures in frequency domain by a new set of Ritz vectors

  • Aliasghar Arjmandi, S.;Lotfi, Vahid
    • Structural Engineering and Mechanics
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    • v.39 no.5
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    • pp.703-716
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    • 2011
  • The accurate dynamic analysis of structures is usually performed by a fine finite element discretization with very large number of degrees of freedom. Apart from modal analysis, one can reduce the number of final equations by assuming the deformed shape of the structure as a linear combination of independent Ritz vectors. The efficiency of this method relies heavily on the vectors selected. In this paper, a new set of Ritz vectors is proposed. It is primarily proved that these vectors are linearly independent. Subsequently, various two and three-dimensional examples are analyzed based on the proposed method. In each case, the results are compared with the ones obtained based on usual Ritz and modal analysis methods. It is finally concluded that the proposed method is very effective and efficient method for dynamic analysis of structures in frequency domain.

Mixed Noise Cancellation by Independent Vector Analysis and Frequency Band Beamforming Algorithm in 4-channel Environments (4채널 환경에서 독립벡터분석 및 주파수대역 빔형성 알고리즘에 의한 혼합잡음제거)

  • Choi, Jae-Seung
    • The Journal of the Korea institute of electronic communication sciences
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    • v.14 no.5
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    • pp.811-816
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    • 2019
  • This paper first proposes a technique to separate clean speech signals and mixed noise signals by using an independent vector analysis algorithm of frequency band for 4 channel speech source signals with a noise. An improved output speech signal from the proposed independent vector analysis algorithm is obtained by using the cross-correlation between the signal outputs from the frequency domain delay-sum beamforming and the output signals separated from the proposed independent vector analysis algorithm. In the experiments, the proposed algorithm improves the maximum SNRs of 10.90dB and the segmental SNRs of 10.02dB compared with the frequency domain delay-sum beamforming algorithm for the input mixed noise speeches with 0dB and -5dB SNRs including white noise, respectively. Therefore, it can be seen from this experiment and consideration that the speech quality of this proposed algorithm is improved compared to the frequency domain delay-sum beamforming algorithm.

A Domain-independent Dual-image based Robust Reversible Watermarking

  • Guo, Xuejing;Fang, Yixiang;Wang, Junxiang;Zeng, Wenchao;Zhao, Yi;Zhang, Tianzhu;Shi, Yun-Qing
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.16 no.12
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    • pp.4024-4041
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    • 2022
  • Robust reversible watermarking has attracted widespread attention in the field of information hiding in recent years. It should not only have robustness against attacks in transmission but also meet the reversibility of distortion-free transmission. According to our best knowledge, the most recent robust reversible watermarking methods adopt a single image as the carrier, which might lead to low efficiency in terms of carrier utilization. To address the issue, a novel dual-image robust reversible watermarking framework is proposed in this paper to effectively utilize the correlation between both carriers (namely dual images) and thus improve the efficiency of carrier utilization. In the dual-image robust reversible watermarking framework, a two-layer robust watermarking mechanism is designed to further improve the algorithm performances, i.e., embedding capacity and robustness. In addition, an optimization model is built to determine the parameters. Finally, the proposed framework is applied in different domains (namely domain-independent), i.e., Slantlet Transform and Singular Value Decomposition domain, and Zernike moments, respectively to demonstrate its effectiveness and generality. Experimental results demonstrate the superiority of the proposed dual-image robust reversible watermarking framework.

Optimization of Domain-Independent Classification Framework for Mood Classification

  • Choi, Sung-Pil;Jung, Yu-Chul;Myaeng, Sung-Hyon
    • Journal of Information Processing Systems
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    • v.3 no.2
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    • pp.73-81
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    • 2007
  • In this paper, we introduce a domain-independent classification framework based on both k-nearest neighbor and Naive Bayesian classification algorithms. The architecture of our system is simple and modularized in that each sub-module of the system could be changed or improved efficiently. Moreover, it provides various feature selection mechanisms to be applied to optimize the general-purpose classifiers for a specific domain. As for the enhanced classification performance, our system provides conditional probability boosting (CPB) mechanism which could be used in various domains. In the mood classification domain, our optimized framework using the CPB algorithm showed 1% of improvement in precision and 2% in recall compared with the baseline.

Independent Component Analysis Based on Frequency Domain Approach Model for Speech Source Signal Extraction (음원신호 추출을 위한 주파수영역 응용모델에 기초한 독립성분분석)

  • Choi, Jae-Seung
    • The Journal of the Korea institute of electronic communication sciences
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    • v.15 no.5
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    • pp.807-812
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    • 2020
  • This paper proposes a blind speech source separation algorithm using a microphone to separate only the target speech source signal in an environment in which various speech source signals are mixed. The proposed algorithm is a model of frequency domain representation based on independent component analysis method. Accordingly, for the purpose of verifying the validity of independent component analysis in the frequency domain for two speech sources, the proposed algorithm is executed by changing the type of speech sources to perform speech sources separation to verify the improvement effect. It was clarified from the experimental results by the waveform of this experiment that the two-channel speech source signals can be clearly separated compared to the original waveform. In addition, in this experiments, the proposed algorithm improves the speech source separation performance compared to the existing algorithms, from the experimental results using the target signal to interference energy ratio.

ON THE PRINCIPAL IDEAL THEOREM

  • Chang, Gyu-Whan
    • Bulletin of the Korean Mathematical Society
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    • v.36 no.4
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    • pp.655-660
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    • 1999
  • Let R be an integral domain with identity. In this paper we will show that if R is integrally closed or if t-dim $R{\leq}1$, then R[{$X_{\alpha}$}] satisfies the principal ideal theorem for each family {$X_{\alpha}$} of algebraically independent indeterminates if and only if R is an S-domain and it satisfies the principal ideal theorem.

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An Integrated Neural Network Model for Domain Action Determination in Goal-Oriented Dialogues

  • Lee, Hyunjung;Kim, Harksoo;Seo, Jungyun
    • Journal of Information Processing Systems
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    • v.9 no.2
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    • pp.259-270
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    • 2013
  • A speaker's intentions can be represented by domain actions (domain-independent speech act and domain-dependent concept sequence pairs). Therefore, it is essential that domain actions be determined when implementing dialogue systems because a dialogue system should determine users' intentions from their utterances and should create counterpart intentions to the users' intentions. In this paper, a neural network model is proposed for classifying a user's domain actions and planning a system's domain actions. An integrated neural network model is proposed for simultaneously determining user and system domain actions using the same framework. The proposed model performed better than previous non-integrated models in an experiment using a goal-oriented dialogue corpus. This result shows that the proposed integration method contributes to improving domain action determination performance.

Power line interference noise elimination method based on independent component analysis in wavelet domain for magnetotelluric signal

  • Cao, Xiaoling;Yan, Liangjun
    • Geosystem Engineering
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    • v.21 no.5
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    • pp.251-261
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    • 2018
  • With the urbanization in recent years, the power line interference noise in electromagnetic signal is increasing day by day, and has gradually become an unavoidable component of noises in magnetotelluric signal detection. Therefore, a kind of power line interference noise elimination method based on independent component analysis in wavelet domain for magnetotelluric signal is put forward in this paper. The method first uses wavelet decomposition to change single-channel signal into multi-channel signal, and then takes advantage of blind source separation principle of independent component analysis to eliminate power line interference noise. There is no need to choose the layer number of wavelet decomposition and the wavelet base of wavelet decomposition according to the observed signal. On the treatment effect, it is better than the previous power line interference removal method based on independent component analysis. Through the de-noising processing to actual magnetotelluric measuring data, it is shown that this method makes both the apparent resistivity curve near 50 Hz and the phase curve near 50 Hz become smoother and steadier than before processing, i.e., it effectively eliminates the power line interference noise.

Implementation of temporal reasoning services using a domain-independent AI planner (영역-독립적인 인공지능 계획기를 이용한 시간 추론 서비스의 구현)

  • Kim, Hyun-Sik;Park, Chan-Young;Kim, In-Cheol
    • Journal of Korea Society of Industrial Information Systems
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    • v.14 no.4
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    • pp.37-48
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    • 2009
  • Household service robots should be able to provide their users with a variety of temporal reasoning services. In this paper, we propose an effective way of developing such temporal reasoning services using a domain-independent AI planner. Developing temporal reasoning services with a domain-independent AI planner, we have to address both the knowledge engineering problem of how to represent various real-world temporal constraints in a planning domain definition language, and the system design problem of how to realize the interface between the AI planner and the service consumer. In this paper, we introduce an example scenario and a set of typical temporal constraints for a household service robot, and then present how to represent them in the standard planning domain definition language. We also explain how to implement a service agent based on an AI planner in order to develop and provide new services efficiently.

A New Fast Algorithm for Short Range Force Calculation (근거리 힘 계산의 새로운 고속화 방법)

  • Lee, Sang-Hwan;Ahn, Cheol-O
    • 유체기계공업학회:학술대회논문집
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    • 2006.08a
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    • pp.383-386
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    • 2006
  • In this study, we propose a new fast algorithm for calculating short range forces in molecular dynamics, This algorithm uses a new hierarchical tree data structure which has a high adaptiveness to the particle distribution. It can divide a parent cell into k daughter cells and the tree structure is independent of the coordinate system and particle distribution. We investigated the characteristics and the performance of the tree structure according to k. For parallel computation, we used orthogonal recursive bisection method for domain decomposition to distribute particles to each processor, and the numerical experiments were performed on a 32-node Linux cluster. We compared the performance of the oct-tree and developed new algorithm according to the particle distributions, problem sizes and the number of processors. The comparison was performed sing tree-independent method and the results are independent of computing platform, parallelization, or programming language. It was found that the new algorithm can reduce computing cost for a large problem which has a short search range compared to the computational domain. But there are only small differences in wall-clock time because the proposed algorithm requires much time to construct tree structure than the oct-tree and he performance gain is small compared to the time for single time step calculation.

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