• 한국IT서비스학회지
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• 제6권2호
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• pp.161-175
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• 2007

Face recognition technology has lately attracted considerable attention because of its non-intrusiveness, usability and applicability. Related companies insist that their commercial products show the recognition rates more than 95% according to their self-testing. But, the rates cannot be admitted as official recognition rates. So, performance evaluation methods and tools are necessary to objectively measure the accuracy and performance of face recognition systems. In this paper, I propose a reference model for biometrics recognition evaluation tools, and implement an evaluation tool for the face recognition system based on the proposed reference model.

• 가정과삶의질연구
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• 제17권4호
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• pp.1-14
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• 1999

The purpose of this study was to probe the role recognition and role performance of husbands if family and to find out the variables which influence role recognition and role performance. the sample were selected from 503 husbands with children more than one living in Seoul The major findings were : 1) husbands` role recognition was relatively higher than role performance 2) Influential variables on the husbands` role recognition were the degree of home-orientedness communication-satisfaction and stage of life cycle. 3) Husbands` role performance was affected by communication-satisfaction degree of social support job satisfactions sex-role attitudes flexibility of job and jusbands` role recognition.

• 말소리와 음성과학
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• 제10권1호
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• pp.33-38
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• 2018

Although deep neural network-based acoustic models have greatly improved the performance of automatic speech recognition (ASR), reverberation still degrades the performance of distant speech recognition in indoor environments. In this paper, we adopt the DenseNet, which has shown great performance results in image classification tasks, to improve the performance of reverberant speech recognition. The DenseNet enables the deep convolutional neural network (CNN) to be effectively trained by concatenating feature maps in each convolutional layer. In addition, we extend the concept of multi-resolution CNN to multi-resolution DenseNet for robust speech recognition in reverberant environments. We evaluate the performance of reverberant speech recognition on the single-channel ASR task in reverberant voice enhancement and recognition benchmark (REVERB) challenge 2014. According to the experimental results, the DenseNet-based acoustic models show better performance than do the conventional CNN-based ones, and the multi-resolution DenseNet provides additional performance improvement.

• 여성건강간호학회지
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• 제11권3호
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• pp.232-240
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• 2005

Purpose: This study was designed to identify recognition and the performance level for nosocomial infections amongst student nurses and to provide data for preparing on efficient policy and control program for nosocomial infections. Method: 191 senior nursing student participated in this research from 5 nursing college which allowed data collection, in the city of Seoul. The questionnaire was composed of 73 items(likert scale) about eight areas; aseptic technique, disinfection, precaution, hand washing, urinary tract infection, respiratory infection, catheter related infection, and self care about nosocomial infections. Results: The mean score of recognition and performance level for management of nosocomial infection were 4.29 and 3.41 respectively. The mean score of the recognition level was significantly lower than the performance level in the eight areas. The mean score of both recognition and performance were highest in the area of disinfection. However, the mean score of recognition was lowest in the area of aseptic technique and the mean score of performance was lowest in the area of catheter related infections. The correlation of recognition and performance level was statistically significant. Conclusions: These research findings should be useful in promoting an intensive and continuous educational program on nosocomial infection for nursing students and to establish an efficient policy for preventing nosocomial infections.

• 한국생활과학회지
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• 제17권2호
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• pp.223-233
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• 2008

The purpose of this study was to find out conflict of preservice teachers affected by the role recognition and performance of cooperating teachers in the early childhood education practicum. The following research questions were established in order to achieve this purpose. First, Is there any differences in conflict of preservice teachers according to their personal variables? Second, Is there any differences in the role recognition and performance of cooperating teachers according to their personal variables? Third, Is there any differences in conflict of preservice teachers according to the role recognition and performance of cooperating teachers? The subjects of this study were 214 pairs of cooperating teachers who taught preservice teachers. The data were collected with the role recognition and performance of cooperating teachers and conflict of preservice teacher instrument and analyzed by t-test and ANOVA using SPSS 14.0 software. The results show that there was significantly difference conflict of preservice teachers according to their personal variables. Second, there was significantly differences the role recognition and performance of cooperating teachers according to their personal variables. Third, there was significantly differences conflict of preservice teachers affected by the role recognition and performance of cooperating teachers in the early childhood education practicum.

• 융합정보논문지
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• 제9권12호
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• pp.104-114
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• 2019

본 연구는 아동간호사의 말초정맥주입관리에 대한 인지 및 수행 관련 영향요인 규명을 위해 시행되었다. 수집된 자료를 SPSS/WIN 24.0으로 분석한 결과. 인지와 수행은 4점 만점에 각각 3.34±0.39, 3.42±0.37점이었고, 인지 및 수행 각각의 하위영역 중 '유지와 교환' 및 '교육'이 가장 낮았다. 말초정맥주입관리에 따른 인지와 수행은 근무부서에 따라 유의한 차이를 보였고(p=.039, p<.001), 인지와 수행 간 정적 상관관계(r=.591, p<.001)가 있었다. 위계적 다중회귀분석 결과, 인지에는 수행(β=.57)과 근무부서(β=.22)가, 수행에는 인지(β=.57)와 피교육경험(β=.19)이 영향요인이었고, 인지 및 수행에 대한 각 변수들의 설명력은 각각 41.2%와 41.4%이었다. 결론적으로 말초정맥주입관리의 인지와 수행은 상호 간 영향을 미치는 요인이므로, 말초정맥주입관리의 인지를 향상시킬 방안을 마련함으로써 수행의 증가를 도모할 필요가 있다.

• 동아시아식생활학회지
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• 제21권5호
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• pp.746-755
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• 2011

A survey on the status of sanitary education and recognition and perceived performance of cooking operations related to sanitation for cooks at nine deluxe hotels in the Seoul area was conducted. The frequency of a food sanitary training program inside the hotel was 94.0%, and the frequency of training was 'once a month' at 68.5%. The program was taught by a hygienist in the hotel (62.7%), and 64.2% of cooks always attended. Cooks' recognition of HACCP was 3.52, and the importance of education on HACCP was higher at 3.77. Cook's' level of sanitary management was satisfactory with an average of 3.83 out of 5 in a Likert scale. The results showed a high average (4.08) for importance of personal hygiene during cooking, but satisfaction of personal hygiene was rather low at 3.92. Cooks' recognition of food sanitation in work field was very high at 4.15. The average scale of recognition on personal hygiene was 4.36, and out of 10 items related to personal hygiene, 'maintaining hand hygiene' showed the highest recognition (4.43). In a performance scale, the average was 4.24, and 'performing annual health examination' was the highest at 4.38. Perceived recognition of 18 items related to food sanitation had an average of 4.41, whereas the average for performance was lower at 4.31. Perceived recognition of 12 items related to cooking equipments had an average of 4.39, and average scale of performance was 4.28. Therefore, cooks' high recognition of food sanitation but rather low recognition of satisfaction of personal hygiene and perceived performance indicated that systematic sanitation management monitoring tools are necessary for higher performance.

• 전기학회논문지
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• 제66권8호
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• pp.1265-1271
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• 2017

In this paper, the speech parameter fusion method is studied to improve the performance of the conventional emotion recognition system. For this purpose, the combination of the parameters that show the best performance by combining the cepstrum parameters and the various pitch parameters used in the conventional emotion recognition system are selected. Various pitch parameters were generated using numerical and statistical methods using pitch of speech. Performance evaluation was performed on the emotion recognition system using Gaussian mixture model(GMM) to select the pitch parameters that showed the best performance in combination with cepstrum parameters. As a parameter selection method, sequential feature selection method was used. In the experiment to distinguish the four emotions of normal, joy, sadness and angry, fifteen of the total 56 pitch parameters were selected and showed the best recognition performance when fused with cepstrum and delta cepstrum coefficients. This is a 48.9% reduction in the error of emotion recognition system using only pitch parameters.

• 대한임베디드공학회논문지
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• 제8권4호
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• pp.185-194
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• 2013

Abstract- In distant-talking environments, speech recognition performance degrades significantly due to noise and reverberation. Recent work of Michael L. Selzer shows that in microphone array speech recognition, the word error rate can be significantly reduced by adapting the beamformer weights to generate a sequence of features which maximizes the likelihood of the correct hypothesis. In this approach, called Likelihood Maximizing Beamforming algorithm (Limabeam), one of the method to implement this Limabeam is an UnSupervised Limabeam(USL) that can improve recognition performance in any situation of environment. From our investigation for this USL, we could see that because the performance of optimization depends strongly on the transcription output of the first recognition step, the output become unstable and this may lead lower performance. In order to improve recognition performance of USL, some post-filter techniques can be employed to obtain more correct transcription output of the first step. In this work, as a post-filtering technique for first recognition step of USL, we propose to add a Wiener-Filter combined with Feature Weighted Malahanobis Distance to improve recognition performance. We also suggest an alternative way to implement Limabeam algorithm for Hidden Markov Network (HM-Net) speech recognizer for efficient implementation. Speech recognition experiments performed in real distant-talking environment confirm the efficacy of Limabeam algorithm in HM-Net speech recognition system and also confirm the improved performance by the proposed method.

• 말소리와 음성과학
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• 제1권2호
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• pp.9-14
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• 2009

Speech enhancement methods can be generally classified into a few categories and they have been usually compared with each other in terms of speech quality. For the successful use of speech enhancement methods in speech recognition systems, performance comparisons in terms of speech recognition accuracy are necessary. In this paper, we compared the speech recognition performance of some of the representative speech enhancement algorithms which are popularly cited in the literature and used widely. We also compared the performance of speech enhancement methods with other noise robust speech recognition methods like PMC to verify the usefulness of speech enhancement approaches in noise robust speech recognition systems.