• Aerospace Engineering and Technology
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• v.7 no.2
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• pp.31-37
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• 2008

Flight-test is necessary at the identification of dynamic model of flight vehicle. A commonly faced problem is that once the flight-test instrumentation system is difficult to reschedule in the vehicle at the end of the test. This paper identified the parameter of dynamic model of vehicle using measurement data of non-flight test. The identification algorithm is based on frequency response identification method (CIFER) dealing with a longitudinal motion of Smart UAV 40% scale.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.12
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• pp.793-798
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• 2004

In this paper, the problem of adaptively identifying time-varying nonlinear systems is considered. For that purpose, the discrete time-varying Volterra series is employed as a system model, and the filtered weighted least squares (FWLS) algorithm, developed for adaptive identification of linear time-varying systems, is utilized for the adaptive identification of time-varying quadratic Volterra systems. To demonstrate the performance of the proposed approach, some simulation results are provided. Note that the FWLS algorithm, decomposing the conventional weighted basis function (WBF) algorithm into a cascade of two (i.e., estimation and filtering) procedures, leads to fast parameter tracking with low computational burden, and the proposed approach can be easily extended to the adaptive identification of time-varying higher-order Volterra systems.

• Journal of applied mathematics & informatics
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• v.26 no.5_6
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• pp.1139-1147
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• 2008

A. Saxena et al. first proposed a two-flow blind identification protocol in 2005. But it has a weakness of the active-intruder attack and uses the pairing operation that causes slow implementation in smart cards. In this paper, we give a method of the active-intruder attack on their identification scheme and propose a new zero- knowledge blind identification protocol for Smart cards. Our protocol consists of only two message flows and does not rely on any underlying signature or encryption scheme. The prover using computationally limited devices such as smart cards has no need of computing the bilinear pairings. It needs only for the verifier. Our protocol is secure assuming the hardness of the Discrete-Logarithm Problem in bilinear groups.

• Journal of Mechanical Science and Technology
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• v.18 no.12
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• pp.2114-2124
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• 2004

In this paper, a structural damage identification method (SDIM) is developed for cylindrical shells and the numerically simulated damage identification tests are conducted to study the feasibility of the proposed SDIM. The SDIM is derived from the frequency response function solved from the structural dynamic equations of damaged cylindrical shells. A damage distribution function is used to represent the distribution and magnitudes of the local damages within a cylindrical shell. In contrast with most existing modal parameters-based SDIMs which require the modal parameters measured in both intact and damaged states, the present SDIM requires only the FRF-data measured in the damaged state. By virtue of utilizing FRF-data, one is able to make the inverse problem of damage identification well-posed by choosing as many sets of excitation frequency and FRF measurement point as needed to obtain a sufficient number of equations.

• Proceedings of the KSME Conference
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• 2000.11a
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• pp.671-675
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• 2000

In this study, an FRF-based structural damage identification method (SDIM) is proposed for plate structures. The present SDIM is derived from the partial differential equation of motion of the damaged plate, in which damage is characterized by damage distribution function. Various factors that might affect the accuracy of the damage identification are investigated. They include the number of modal data used in the analysis and the damage-induced modal coupling. In the present SDIM, an efficient iterative damage self-search method is introduced. The iterative damage search method efficiently reduces the size of problem by searching out and then by removing all damage-free zones at each iteration of damage identification analysis. The feasibility of the present SDIM is studied by some numerically simulated tests.

• Proceedings of the KIEE Conference
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• 1995.07b
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• pp.710-713
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• 1995

Hopfield networks have been applied to the problem of linear system identification. In this paper, Hopfield network based parameter identification scheme of non-linear dynamic systems is proposed. Simulation results demonstrate that Hopfield network can be used effectively for the identification of non-linear systems assuming that the system states and their time derivatives are available. Therefore, the proposed scheme can be applied in fault detection and isolation(FDI) and adaptive control of non-linear systems where the Hopfield networks perform on-line identification of system parameters.

• Journal of Information Processing Systems
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• v.15 no.4
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• pp.785-796
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• 2019

Due to the view point, illumination, personal gait and other background situation, person re-identification across cameras has been a challenging task in video surveillance area. In order to address the problem, a novel method called Joint Bayesian across different cameras for person re-identification (JBR) is proposed. Motivated by the superior measurement ability of Joint Bayesian, a set of Joint Bayesian matrices is obtained by learning with different camera pairs. With the global Joint Bayesian matrix, the proposed method combines the characteristics of multi-camera shooting and person re-identification. Then this method can improve the calculation precision of the similarity between two individuals by learning the transition between two cameras. For investigating the proposed method, it is implemented on two compare large-scale re-ID datasets, the Market-1501 and DukeMTMC-reID. The RANK-1 accuracy significantly increases about 3% and 4%, and the maximum a posterior (MAP) improves about 1% and 4%, respectively.

• ETRI Journal
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• v.46 no.4
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• pp.697-707
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• 2024

Music identification is widely regarded as a solved problem for music searching in quiet environments, but its performance tends to degrade in TV broadcast audio owing to the presence of dialogue or sound effects. In addition, constructing an accurate dataset for measuring the performance of background music monitoring in TV broadcast audio is challenging. We propose a framework for monitoring background music by automatic identification and introduce a background music cue sheet. The framework comprises three main components: music identification, music-speech separation, and music detection. In addition, we introduce the Cue-K-Drama dataset, which includes reference songs, audio tracks from 60 episodes of five Korean TV drama series, and corresponding cue sheets that provide the start and end timestamps of background music. Experimental results on the constructed and existing datasets demonstrate that the proposed framework, which incorporates music identification with music-speech separation and music detection, effectively enhances TV broadcast audio monitoring.

• Structural Engineering and Mechanics
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• v.11 no.3
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• pp.237-258
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• 2001

Structural identification via modal analysis in structural mechanics is gaining popularity in recent years, despite conceptual difficulties connected with its use. This paper is devoted to illustrate both the capabilities and the indeterminacy characterizing structural identification problems even in quite simple instances, as well as the cautions that should be accordingly adopted. In particular, we discuss an application of an identification technique of variational type, based on the measurement of eigenfrequencies and mode shapes, to a steel frame with friction joints under various assembling conditions. Experience has suggested, so as to restrict the indeterminacy frequently affecting identification issues, having resort to all the a priori acknowledged information on the system, to the symmetry and presence of structural elements with equal stiffness, to mention one example, and mindfully selecting the parameters to be identified. In addition, considering that the identification techniques have a local character and correspond to the updating of a preliminary model of the structure, it is important that the analytical model on the first attempt should be adequately accurate. Secondly, it has proved determinant to cross the results of the dynamic identification with tests of other typology, for instance, static tests, so as to fully understand the structural behavior and avoid the indeterminacy due to the nonuniqueness of the inverse problem.

• Journal of KIISE
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• v.42 no.2
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• pp.220-226
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• 2015

Semantic role labeling (SRL) systems determine the semantic role labels of the arguments of predicates in natural language text. An SRL system usually needs to perform four tasks in sequence: Predicate Identification (PI), Predicate Classification (PC), Argument Identification (AI), and Argument Classification (AC). In this paper, we use the Korean Propbank to develop our Korean semantic role labeling system. We describe our Korean semantic role labeling system that uses sequence labeling with structured Support Vector Machine (SVM). The results of our experiments on the Korean Propbank dataset reveal that our method obtains a 97.13% F1 score on Predicate Identification and Classification (PIC), and a 76.96% F1 score on Argument Identification and Classification (AIC).