• Smart Structures and Systems
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• v.30 no.3
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• pp.273-286
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• 2022

In recent years, vision-based monitoring has received great attention. However, structural identification using vision-based displacement measurements is far less established. Especially, simultaneous identification of structural systems and unknown excitation using vision-based displacement measurements is still a challenging task since the unknown excitations do not appear directly in the observation equations. Moreover, measurement accuracy deteriorates over a wider field of view by vision-based monitoring, so, only a portion of the structure is measured instead of targeting a whole structure when using monocular vision. In this paper, the identification of structural system and excitations using vision-based displacement measurements is investigated. It is based on substructure identification approach to treat of problem of limited field of view of vision-based monitoring. For the identification of a target substructure, substructure interaction forces are treated as unknown inputs. A smoothing extended Kalman filter with unknown inputs without direct feedthrough is proposed for the simultaneous identification of substructure and unknown inputs using vision-based displacement measurements. The smoothing makes the identification robust to measurement noises. The proposed algorithm is first validated by the identification of a three-span continuous beam bridge under an impact load. Then, it is investigated by the more difficult identification of a frame and unknown wind excitation. Both examples validate the good performances of the proposed method.

• Wind and Structures
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• v.9 no.2
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• pp.159-178
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• 2006

For the slender and flexible cable supported bridges, identification of all the flutter derivatives for the vertical, lateral and torsional motions is essential for its stability investigation. In all, eighteen flutter derivatives may have to be considered, the identification of which using a three degree-of-freedom elastic suspension system has been a challenging task. In this paper, a system identification technique, known as covariance-driven stochastic subspace identification (COV-SSI) technique, has been utilized to extract the flutter derivatives for a typical bridge deck. This method identifies the stochastic state-space model from the covariances of the output-only (stochastic) data. All the eighteen flutter derivatives have been simultaneously extracted from the output response data obtained from wind tunnel test on a 3-DOF elastically suspended bridge deck section-model. Simplicity in model suspension and measurements of only output responses are additional motivating factors for adopting COV-SSI technique. The identified discrete values of flutter derivatives have been approximated by rational functions.

• Journal of Biosystems Engineering
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• v.33 no.3
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• pp.196-203
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• 2008

Hybrid robust image processing algorithm to extract visual features of melon during the cultivation was developed based on a wireless tele-operative interface. Features of a melon such as size and shape including position were crucial to successful task automation and future development of cultivation data base. An algorithm was developed based on the concept of hybrid decision-making which shares a task between the computer and the operator utilizing man-computer interactive interface. A hybrid decision-making system was composed of three modules such as wireless image transmission, task specification and identification, and man-computer interface modules. Computing burden and the instability of the image processing results caused by the variation of illumination and the complexity of the environment caused by the irregular stem and shapes of leaves and shades were overcome using the proposed algorithm. With utilizing operator's teaching via LCD touch screen of the display monitor, the complexity and instability of the melon identification process has been avoided. Hough transform was modified for the image obtained from the locally specified window to extract the geometric shape and position of the melon. It took less than 200 milliseconds processing time.

• Korean Journal of Cognitive Science
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• v.15 no.2
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• pp.17-22
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• 2004

Two experiments were executed to investigate the effect of uniform connectedness systematically using the identification task of briefly exposed forms. Previous study observed negative repetition effected (i.e., NRE) in the identification task of two parentheses either connected or disconnected vertically, which was interpreted as an evidence against the hypothesis of uniform connectedness. Experiment I tested the hypothesis that NRE resulted from the Perceptual set or anticipating disconnected displays. Experiment 2 tested the hypothesis that NRE resulted from relatively shorter exposure time. Using partial report task asking participants to report only the cued target and whole report task asking them to report the whole pattern with only connected displays, experiment 1 observed NRE respectively. Experiment 2, with longer exposure time equivalent to 83% accuracy and response bias controlled by use of catch trials, obtained the same NRE. Those results seems to indicate that uniformly connected forms were processed analytically by perceivers without task demand and futhermore, the hypothesis of uniform connectedness as a principle of perceptual organization is not plausible.

• Journal of Applied Reliability
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• v.7 no.2
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• pp.73-87
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• 2007

In this paper, based on the American weapon acquisition management framework in DoD Instruction 5000.2 "Operation of the Defence Acquisition System" and the contents of "DoD Guide for Achieving Reliability, Availability, and Maintainability" published by Defense Acquisition University, the kinds and roles of technical reviews are introduced and the identification of RAM related tasks which are performed at levels of technical reviews during acquisition process are considered. And the task allocations for developers, development managers, and users are proposed. Finally the relationships of acquisition management framework, technical reviews and RAM tasks are tabulated.

• SUVANNABHUMI
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• v.14 no.1
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• pp.193-228
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• 2022

This study investigates the production and perception of Vietnamese tones by Japanese, Lao, and Taiwanese second language (L2) learners [n=30], comparing their performance in an Imitation task to that of Identification and Read-Aloud tasks. The results show that the Imitation task is generally easier for L2 speakers than the Identification and Read-Aloud tasks, suggesting that imitation is performed without some of the skills required by the other two tasks. It is also found that Lao and Taiwanese speakers outperform Japanese speakers, suggesting that prior experience with one tone language facilitates the acquisition of tone in another language. The result on speakers' tonal range show that L2 leaners have significantly narrower tonal F0 range than control Vietnamese speakers [n=11]. The results of error pattern analysis and tonal transcription also suggest that non-modal voice (glottal stop and creakiness) and contour tones (bidirectional fall-rise) are more difficult for L2 learners than modal voice tones (e.g., unidirectional contours: rising, falling, and level).

• Korean Journal of Cognitive Science
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• v.33 no.1
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• pp.1-22
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• 2022

Lavie's perceptual load theory (Lavie, 1995) proposes that the influence of distractors would be blocked as the load gets higher. Studies of perceptual load have usually adopted the flanker task, developed by Eriksen and Eriksen (1974), which measures reaction time on the target flanked by distractors. In the post-cueing forced task, participants should report the identity of the target cued later, and negative repetition effect (NRE) has often been observed. NRE means the effect that the accuracy of identification is worse when the target is flanked by the same nontargets than when flanked by different nontargets. This study has tried to check whether perceptual load has an effect on identification rate and NRE. Experiment 1 manipulated the similarity between targets and a distractor, and observed a tendency of NRE, but not the effect of perceptual load. Experiment 2 used 4, 2 (in two kinds of diagonal arrangement), or none distractors of the same identity to burden more perceptual load. NRE was significant and perceptual load showed significance but not a linear trend. Experiment 3 checked again whether NRE would be varied according to two levels of perceptual load strengthened by positional variability of load stimuli, but did not find the effect of perceptual load. It is concluded that perceptual load might have a limited effect on the early stage of perceptual processing due to divided attentional processing of the targets briefly exposed. Implications of this study were discussed.

• Proceedings of the Korean Society for Language and Information Conference
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• 2002.02a
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• pp.28-35
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• 2002

Automatic identification of Chinese personal names in unrestricted texts is a key task in Chinese word segmentation, and can affect other NLP tasks such as word segmentation and information retrieval, if it is not properly addressed. This paper (1) demonstrates the problems of Chinese personal name identification in some If applications, (2) analyzes the structure of Chinese personal names, and (3) further presents the relevant processing strategies. The geographical differences of Chinese personal names between Beijing and Hong Kong are highlighted at the end. It shows that variation in names across different Chinese communities constitutes a critical factor in designing Chinese personal name Identification algorithm.

• MALSORI
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• no.57
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• pp.165-174
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• 2006

In this paper we use a training algorithm, MCE (Minimum Classification Error), to improve the performance of a text-independent speaker identification system. The MCE training scheme takes account of possible competing speaker hypotheses and tries to reduce the probability of incorrect hypotheses. Experiments performed on a small set speaker identification task show that the discriminant training method using MCE can reduce identification errors by up to 54% over a baseline system trained using Bayesian adaptation to derive GMM (Gaussian Mixture Models) speaker models from a UBM (Universal Background Model).

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1997.10a
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• pp.115-120
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• 1997

System identification is the task of inferring a mathematical description of a dynamic system from a series of measurements of the system. There are several motives for establishing mathematical descriptions of dynamic systems. Typical applications encompass simulation, prediction, fault diagnostics, and control system design. The paper demonstrates that neural networks can be used effective for the identification of nonlinear dynamical systems. The content of this paper concerns dynamic neural network models, where not all inputs to and outputs from the networks are measurable. Only one model type is treated, the well-known Innovation State Space model(Kalman Predictor). The identification is based only on input/output measurements, so in fact a non-linear Extended Kalman Filter problem is solved. Even for linear models this is a non-linear problem without any assurance of convergence, and in spite of this fact an attempt is made to apply the principles from linear models, an extend them to non-linear models. Computer simulation results reveal that the identification scheme suggested are practically feasible.