• International Journal of Advanced Culture Technology
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• 제7권1호
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• pp.28-34
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• 2019

The purpose of this study is to analyze the meaning and structure of the experiences of 20 years old women who participated in the pregnancy recognition improvement program developed by JA Kim et al. The participants of the study were interviewed three times in total for 20 years old of 6 women. The interview period was from December 1 to December 30, 2018. The interview data were processed through the analysis and interpretation process using the phenomenological research of Giorgi method. As a result, 33 semantic units were derived, and then divided into 4 subcomponents and divided into 2 categories. After participating in the program, they tried to maintain their health, use appropriate welfare policies, and deeply consider their lives as mysterious mothers. In conclusion, this study suggests that the implementation of the pregnancy awareness improvement program for young women in a small group, more systematically and continuously, effectively implements low fertility measures in Korea.

• International journal of advanced smart convergence
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• 제9권4호
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• pp.192-197
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• 2020

In this study, we try to find ways to recognize face recognition more stably and to improve the effectiveness and reliability of face recognition. In order to improve the face recognition rate, a lot of data must be used, but that does not necessarily mean that the recognition rate is improved. Another criterion for improving the recognition rate can be seen that the top/bottom of the recognition rate is determined depending on how accurately or precisely the degree of classification of the data to be used is made. There are various methods for classification analysis, but in this study, classification analysis is performed using a support vector machine (SVM). In this study, feature information is extracted using a normalized image with rotation information, and then projected onto the eigenspace to investigate the relationship between the feature values through the classification analysis of SVM. Verification through classification analysis can improve the effectiveness and reliability of various recognition fields such as object recognition as well as face recognition, and will be of great help in improving recognition rates.

• 한국주거학회논문집
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• 제13권3호
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• pp.93-101
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• 2002

The goal of this survey is to propose planning and design informations for the public open spaces in apartment housing, through the observation and analysis of the current situations. For this, the planning information of housing suppliers about public open spaces and the spatial utilization of users were compared and by analyzing facility utilization and resident\`s recognition. This study is also intended to guide the future directions of the research for the improvement of public open spaces. The research follows three phases; \circled1 To understand the conditions of public open spaces in apartment housing sites through survey and analysis of catalogues and references. \circled2 To study on facility utilization and resident's recognition by observation and analysis. \circled3 To propose planning guidelines for the improvement of public open space by recognition differences of facilities.

• 융합신호처리학회논문지
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• 제12권4호
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• pp.228-236
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• 2011

Emotion recognition plays an important role in the research area of human-computer interaction, and it allows a more natural and more human-like communication between humans and computer. Most of previous work on emotion recognition focused on extracting emotions from face, speech or EEG information separately. Therefore, a novel approach is presented in this paper, including face, speech and EEG, to recognize the human emotion. The individual matching scores obtained from face, speech, and EEG are combined using a weighted-summation operation, and the fused-score is utilized to classify the human emotion. In the experiment results, the proposed approach gives an improvement of more than 18.64% when compared to the most successful unimodal approach, and also provides better performance compared to approaches integrating two modalities each other. From these results, we confirmed that the proposed approach achieved a significant performance improvement and the proposed method was very effective.

• 전기학회논문지
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• 제61권1호
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• pp.143-147
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• 2012

The rapid growth of camera technology can provide various types of information which was not previously provided. Furthermore, IP camera which has rapid data transfer rate and high resolution particularly provide a lot of useful functions beyond the existing simple surveillance capabilities. We are developing Real-Time Face Recognition Access Control System based on the camera technology, and improvement of face detection and recognition algorithms are vitally needed to realize that system. In this paper, we proposes a method to improve the computing speed and detection rate by adding new features to the existing Viola-Jones detection algorithm.

• 한국멀티미디어학회논문지
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• 제14권1호
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• pp.85-93
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• 2011

기존의 어휘 인식에서는 일반적인 벡터 값을 데이터베이스를 이용하여 구하므로 탐색 중에 형성되는 음소를 처리하지 못하는 문제점을 제공하며, 음소 데이터에 대한 모델을 구성할 수 없는 단점으로 인하여 가우시안 모텔의 정확성을 확보하지 못하게 된다. 따라서 본 논문에서는 음소가 갖는 특징을 기반으로 바타챠랴 거리 측정법을 이용하여 정확한 음소로 인식할 수 있도록 유도하였으며 유사 음소 인식과 오인식 오류를 최소화하여 인식률을 향상시켰다. 연속 확률 분포의 공유로부터 가우시안 모델 최적화를 실험한 결과 향상된 신뢰도로 인해 높은 인식 성능을 확인하였으며, 본 논문에서 제안한 바타챠랴 거리 측정법을 이용하여 실험한 결과 기존의 방법들에 비하여 평균 1.9%의 성능 향상을 나타내었으며 신뢰성을 바탕으로 인식율에서 평균 2.9%의 성능 향상을 나타내었다.

• 대한의용생체공학회:의공학회지
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• 제27권5호
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• pp.237-244
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• 2006

This study proposes an approach to the performance improvement of EMG(Electromyogram) pattern recognition. MFCC(Mel-Frequency Cepstral Coefficients)'s approach is molded after the characteristics of the human hearing organ. While it supplies the most typical feature in frequency domain, it should be reorganized to detect the features in EMG signal. And the dynamic aspects of EMG are important for a task, such as a continuous prosthetic control or various time length EMG signal recognition, which have not been successfully mastered by the most approaches. Thus, this paper proposes reorganized MFCC and HMM-GMM, which is adaptable for the dynamic features of the signal. Moreover, it requires an analysis on the most suitable system setting fur EMG pattern recognition. To meet the requirement, this study balanced the recognition-rate against the error-rates produced by the various settings when loaming based on the EMG data for each motion.

• 디지털융복합연구
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• 제16권11호
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• pp.335-340
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• 2018

정확한 인식률을 보이고 있는 상업적인 음성인식 시스템은 화자종속 고립데이터로부터 학습 모델을 사용한다. 그러나 잡음 환경에서 데이터양에 따라 음성인식의 성능이 저하되는 문제점이 있다. 본 논문에서는 가우시안 분포에서 Maximum Log Likelihood를 이용한 벡터 양자화 기반 음성 인식 성능 향상을 제안한다. 제안하는 방법은 음성에 대한 특징을 가지고 벡터 양자화와 Maximum Log Likelihood 음성 특징 추출 방법을 이용하여 유사 음성에 대한 음성 인식의 정확성을 높이는 최적 학습 모델 구성 방법이다. 이를 위해 HMM을 기반으로 음성 특징을 추출하는 방법을 사용한다. 제안하는 방법을 사용하여 기존 시스템에서 생성되어 사용되는 음성 모델에 대한 부정확한 음성 모델에 대한 정확성을 향상시킬 수 있으므로 음성 인식에 강인한 모델을 구성할 수 있다. 제안하는 방법은 음성 인식 시스템에서 향상된 인식의 정확도를 보인다.

• 한국조경학회지
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• 제43권1호
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• pp.54-68
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• 2015

본 연구는 근린공원에 대한 이용자의 공원지각환경이 건강증진인식에 미치는 영향을 분석하기 위해 경상남도 창원시의 8개 근린공원을 대상으로 공원별 현장조사 및 설문조사를 실시하였다. 연구결과에 따르면, 먼저 공원별 공원지각환경에서는 대부분의 공원이 집에서 공원까지의 거리와 집에서 공원까지의 길 환경이 높게 평가된 반면, 수공간과 공원 내 다양한 볼거리는 충분하지 못한 것으로 분석되었다. 다음으로 23개의 지각환경 변수들을 요인분석한 결과, 경관성, 안락성, 접근성, 활동성, 편의성, 쾌적성의 6개 요인으로 분류되었다. 이를 토대로 건강증진인식과 지각환경요인과의 관련성을 분석한 결과, 8개 공원 중 4개 공원에서 지각환경요인이 신체적 건강증진인식에 유의한 영향을 주는 것으로 나타났다. 특히, 접근성과 활동성이 3개의 공원에서 영향력이 있는 변수로 분석되었다. 또한, 심리적 건강증진인식의 경우, 8개 공원 중 5개 공원에서 유의한 영향을 주는 것으로 나타났으며, 접근성이 4개의 공원에서 영향력이 있는 변수로 평가되었다. 이상과 같은 결과들은 기존의 공원 환경을 개선하고, 새로운 공원을 조성하고자 할 때 효율적인 기초자료로 활용될 수 있을 것으로 판단된다.

• 대한전기학회논문지
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• 제40권4호
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• pp.351-359
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• 1991

This paper describes performances of speaker adaptation using a probabilistic spectral mapping matrix in hidden-Markov model(HMM) -based Korean isolated word recognition. Speaker adaptation based on probabilistic spectral mapping uses a well-trained prototype HMM's and is carried out by Viterbi, dynamic time warping, and forward-backward algorithms. Among these algorithms, the best performance is obtained by using the Viterbi approach together with codebook adaptation whose improvement for isolated word recognition accuracy is 42.6-68.8 %. Also, the selection of the initial values of the matrix and the normalization in computing the matrix affects the recognition accuracy.