• Journal of information and communication convergence engineering
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• v.10 no.3
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• pp.242-247
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• 2012

In the determination of suitable frame sizes associated with dynamic framed slotted Aloha used in radio frequency identification tag identification processes, the widely imposed constraint $L=2^Q$ often yields inappropriate values deviating far from the optimal values, while a straightforward use of the estimated optimal frame sizes causes frequent restarts of read procedures, both resulting in long identification delays. Taking a trade-off, in this paper, we propose a new method for determining effective frame sizes where the effective frame size changes in a multiple of a predetermined step size, namely ${\Delta}$. Through computer simulations, we show that the proposed scheme works fairly well in terms of identification delay.

• Journal of information and communication convergence engineering
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• v.6 no.4
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• pp.364-369
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• 2008

The FSA algorithm for identifying multiple tags in RFID systems is based on the slotted ALOHA scheme with a fixed frame size. The performance of FSA algorithm is dependent on the frame size and the number of tags in the reader's identification range. Therefore, this paper proposes a new ODFSA. The proposed ODFSA algorithm dynamically allocates the optimal frame size at every frame based on the number of tags in the reader's identification range. According to the simulation results, the system efficiency of the proposed algorithm should be maintained optimally. Also, the proposed algorithm always obtained the minimum tag identification delay.

• MALSORI
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• no.61
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• pp.113-123
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• 2007

The environmental differences between training and testing mode are generally considered to be the critical factor for the performance degradation in speaker recognition systems. Especially, general speaker recognition systems try to get as clean speech as possible to train the speaker model, but it's not true in real testing phase due to environmental and channel noise. So in this paper, the new method of weighting the frame-based likelihood according to frame SNR is proposed in order to cope with that problem. That is to make use of the deep correlation between speech SNR and speaker discrimination rate. To verify the usefulness of this proposed method, it is applied to the context dependent speaker identification system. And the experimental results with the cellular phone speech DB which is designed by ETRI for Koran speaker recognition show that the proposed method is effective and increase the identification accuracy by 11% at maximum.

• International journal of advanced smart convergence
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• v.11 no.3
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• pp.64-71
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• 2022

Various types of attendance management systems are being introduced in a remote working environment and research on using face recognition is in progress. To ensure accurate worker's attendance, a face recognition-based attendance management system must analyze every frame of video, but face recognition is a heavy task, the number of the task should be minimized without affecting accuracy. In this paper, we proposed a search model using time interval variation to minimize the number of face recognition task of recorded videos for attendance management system. The proposed model performs face recognition by changing the interval of the frame identification time when there is no change in the attendance status for a certain period. When a change in the face recognition status occurs, it moves in the reverse direction and performs frame checks to more accurate attendance time checking. The implementation of proposed model performed at least 4.5 times faster than all frame identification and showed at least 97% accuracy.

• Journal of information and communication convergence engineering
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• v.10 no.1
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• pp.33-39
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• 2012

In this paper, we compare the accuracy of most representative radio frequency identification (RFID) tag estimation functions in the context of minimizing RFID tag identification delay. Before the comparisons, we first evaluate the accuracy of Schoute's estimation function, which has been widely adopted in many RFID tag identification processes, and show that its accuracy actually depends on the number of tags to be identified and frame size L used for dynamic frame slotted Aloha cycles. Through computer simulations, we show how the accuracy of estimation functions is related to the actual tag read performance in terms of identification delay.

• 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 Advanced Marine Engineering and Technology
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• v.18 no.3
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• pp.34-42
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• 1994

The present study is aimed to improve the PIV performance by suggesting a two-frame particle identification technique and by introducing estimation method of wall pressure distribution from the velocity data. Adopted image processing system consists of one commercial image board slit into a personal computer, 2-D sheet light generator, flow picture recording apparatus and related particle identification software. A revised particle tracking method essential to PIV performance is obtained by particle centroid correlation pairing (CCP) and its effectiveness is ascertained by comparison with multi-frame identification.

• Journal of the Earthquake Engineering Society of Korea
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• v.22 no.3
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• pp.201-210
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• 2018

The improvement in computing systems and sensor technologies devotes to conduct data-driven structural health monitoring algorithms for existing civil infrastructures. Despite of the development of techniques, the uncertainty oriented from the measurement results in the discrepancy to the actual structural parameters and let engineers or decision makers hesitate to adopt such techniques. Many studies have shown that the modal identification results can be affected by the uncertainties due to the applied methods and the types of loading. This paper aims to compare the performance of modal identification methods using Structural Modal Identification Toolsuite (SMIT) which has been developed to facilitate multiple identification methods with a user-friendly designed platform. The data fed into SMIT processes three stages for the comprehensive identification including preprocessing, eigenvalue estimation, and post-processing. The seismic and white noise response for shear frame model was obtained from numerical simulation. The identified modal parameters is compared to the actual modal parameters. In order to improve the quality of coherence in identified modal parameters, several hurdles including modal phase collinearity and extended modal amplitude coherence were introduced. Numerical simulation conducted on the 5 dof shear frame model were used to validate the effectiveness of using these parameters.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.2
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• pp.184-189
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• 2013

In this paper, we propose the injurious moving picture filtering system using certain sounds contained in the injurious moving picture to filter injurious moving picture which is distributed without limitation in internet and internet storage space. For this purpose, the Gaussian Mixture Model which can well represent the characteristics of the sound, is used and frame level likelihood estimation is used to calculate the likelihood between filtering target data and the sound models. Also, the pruning method which can real-time proceed by reducing the comparing number of data, is applied for real-time processing, and MWMR method which showed good performance from existing speaker identification, is applied for the distinguish performance of high precision. In the identification experiment result, in case of the frame rate which is the proportion of total frame to high likelihood frame, is set to 50%, identification error rate is 6.06%, and in case of frame rate is set to 60%, error rate is 3.03%. As the result, the proposed system can distinguish between general and injurious moving picture effectively.

• The Journal of the Acoustical Society of Korea
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• v.21 no.8
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• pp.735-743
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• 2002

In this paper, we propose three new text-independent speaker identification methods. At first, to exclude the frames not having enough features of speaker's vocal from calculation of the maximum likelihood, we propose the FS(Frame Selection) method. This approach selects the important frames by evaluating the difference between the biggest likelihood and the second in each frame, and uses only the frames in calculating the score of likelihood. Our secondly proposed, called the Hybrid, is a combined version of the FS and WMR(Weighting Model Rank). This method determines the claimed speaker using exponential function weights, instead of likelihood itself, only on the selected frames obtained from the FS method. The last proposed, called MWMR (Modified WMR), considers both original likelihood itself and its relative position, when the claimed speaker is determined. It is different from the WMR that take into account only the relative position of likelihood. Through the experiments of the speaker identification, we show that the all the proposed have higher identification rates than the ML. In addition, the Hybrid and MWMR have higher identification rate about 2% and about 3% than WMR, respectively.