• Korean Journal of Adult Nursing
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• v.20 no.2
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• pp.353-363
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• 2008

Purpose: This study was conducted to develop a timeout protocol as the process of patients verification in the operating room, and to evaluate its effects. Methods: The timeout protocol was developed based on the experience of practices and the universal protocol of JCAHO 2004. The subjects of this study were 192 surgical members working in the operating room at an university hospital in Daegu, Korea. Results: The timeout protocol was developed in six steps; participants verification, encouragement of compliance, verification of right 3 PSP, agreement of surgical team members, verification of the parties to a patient, patient agreement. The data which have been resulted from the experimental group show significantly higher than those of control group as follows; cognition(t = -6.580, p = .000), contents of performance; progress of anesthesiologist as leader(${\chi}^2$ = 29.029, p = .000), verification of right patient, right site and right procedure(${\chi}^2$ = 40.663, p = .000), participation of surgical team(${\chi}^2$ = 68.412, p = .000), and the number of cases of performance(${\chi}^2$ = 242.900, p = .000). Conclusion: It suggests that medical accidents caused by failures in a preoperative verification process can be prevented if a timeout is conducted active involvement and effective communication among surgical team members for a final verification of the correct patient, procedure, and site.

• ETRI Journal
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• v.33 no.3
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• pp.423-433
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• 2011

This paper introduces an adaptive and integrated utterance verification (UV) framework using minimum verification error (MVE) training as a new set of solutions suitable for real applications. UV is traditionally considered an add-on procedure to automatic speech recognition (ASR) and thus treated separately from the ASR system model design. This traditional two-stage approach often fails to cope with a wide range of variations, such as a new speaker or a new environment which is not matched with the original speaker population or the original acoustic environment that the ASR system is trained on. In this paper, we propose an integrated solution to enhance the overall UV system performance in such real applications. The integration is accomplished by adapting and merging the target model for UV with the acoustic model for ASR based on the common MVE principle at each iteration in the recognition stage. The proposed iterative procedure for UV model adaptation also involves revision of the data segmentation and the decoded hypotheses. Under this new framework, remarkable enhancement in not only recognition performance, but also verification performance has been obtained.

• The Journal of Korea Robotics Society
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• v.18 no.4
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• pp.472-480
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• 2023

This paper describes the development of a test-equipment for the pre-verification of navigation performance in cluster-based AUVs (Autonomous Underwater Vehicle). In the development of an AUV, conducting hardware and software development sequentially is not efficient due to the limited research and development period. Therefore, in order to reduce the overall development time and achieve successful development results, it is essential to pre-validate the navigation system and navigation algorithms. Accordingly, this paper explains the test-equipment for pre-verification of navigation performance, and ultimately confirms the stability of the navigation system and the performance of the navigation algorithms through the analysis of five types of navigation sensor data stored during real-sea experiments. The results demonstrate that through the development and verification of the test-equipment, it is possible to shorten the overall development period and improvement of product quality in the process of developing multiple AUVs.

• Phonetics and Speech Sciences
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• v.7 no.4
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• pp.9-16
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• 2015

In this paper, several experiments are performed according to deep neural network (DNN) based features for the performance comparison of speaker verification (SV) systems. To this end, input features for a DNN, such as mel-frequency cepstral coefficient (MFCC), linear-frequency cepstral coefficient (LFCC), and perceptual linear prediction (PLP), are first compared in a view of the SV performance. After that, the effect of a DNN training method and a structure of hidden layers of DNNs on the SV performance is investigated depending on the type of features. The performance of an SV system is then evaluated on the basis of I-vector or probabilistic linear discriminant analysis (PLDA) scoring method. It is shown from SV experiments that a tandem feature of DNN bottleneck feature and MFCC feature gives the best performance when DNNs are configured using a rectangular type of hidden layers and trained with a supervised training method.

• Phonetics and Speech Sciences
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• v.2 no.3
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• pp.127-134
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• 2010

Additive noise and channel mismatch strongly degrade the performance of speaker verification systems, as they distort the features of speech. In this paper a histogram transformation technique is presented to improve the robustness of text-independent speaker verification systems. The technique transforms the features extracted from speech such that their histogram is conformed to a reference distribution. The effect of different standard deviations for the reference distribution is investigated. Experimental results indicate that, in channel mismatched environments, the proposed technique offers significant improvements over existing techniques. We also verify performance improvement of the proposed method using statistics.

• Proceedings of the Korea Contents Association Conference
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• 2003.05a
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• pp.430-434
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• 2003

This article describes the survey of biometrics verification system and the analysis of evaluating performance methodology. For this, firstly, survey is performed biometrics verification methods and systems using bio-based features and behaviour-based features. Also, I want to analyze the trend and utilities of biometrics verification system by evaluating performance methodology.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.33A no.5
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• pp.24-30
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• 1996

In this paper, we propose a fast code acquisition method that can reduce drastically the mean acquisition time of the direct sequence spread spectrum (DS-SS) system by using and integrated search and verification (ISV) scheme. The proposed method performs simultaneously the search and verification processes at every search cell, through storing sufficiently long signal samples enough to perform the verification process form the previously received samples. We analyze and acquisition performance in the case of Gaussian channel to evaluate theacquisition perfomrance of the proposed method. From the simple numericl analysis result, we have shown that the acquisition performance of the proposed method is better than that of the conventional serial search method, and the performance improvement becomes more prominent as the channel environment becomes degraded.

• Proceedings of the IEEK Conference
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• 2003.07d
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• pp.1537-1540
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• 2003

Dynamic signature verification technology is to verify the signer by calculating his writing manner, speed, angle, and the number of strokes, order, down/up/movement of pen when the signer input his signature with an electronic pen for his authentication In this paper, we will study an abjective basis for performance and analysis of the dynamic signature verification system.

• The Journal of the Acoustical Society of Korea
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• v.19 no.6
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• pp.34-40
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• 2000

In text-dependent speaker verification system, which text choice for speaker to utter is very important factor for performance improvement. In this paper, building a consonant mixture system using classification method of korean phonetic value is proposed. When it is applied to the web-based speaker verification system, it can cope with abrupt change of speaker's voice information and have the optimal performance in speaker verification system.

• Speech Sciences
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• v.14 no.2
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• pp.127-135
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• 2007

Feature vectors of speech are generally extracted from whole frequency domain. The inherent character of a speaker is located in the low band or high band frequency. However, if the speech is corrupted by narrowband noise with concentrated energy, speaker verification performance is reduced as the individual characteristic is removed. In this paper, we propose a PCA Covariance Model based on the multiband to extract the robust feature vectors against the narrowband noise. First, we divide the overall frequency band into several subbands. Second, the correlation of feature vectors extracted independently from each subband is removed by PCA. The distance obtained from each subband has different distribution. To normalize against the different distribution, we moved the value into the normalized distribution through the mapping function. Finally, the represented value applying the weighting function is used for speaker verification. In the experiments, the proposed method shows better performance of the speaker verification and reduces the computation.