• Women's Health Nursing
• /
• v.8 no.4
• /
• pp.506-520
• /
• 2002

The purpose of this study is to research the degree of recognition & performance of traditional postpartal care for postpartal women and to provide the basic data for improvement of service in a postpartum care center. The respondents of this study were 100 women of 6 postpartum care centers within a C province from Oct. 20 to Dec. 10, 2000. The instruments of measure were used for collecting data on the degree of recognition & performance of traditional postpartal care developed by the researcher. Data analysis consisted of frequency, percentage, mean, standard deviation, paired t-test, t-test, ANOVA which are calculated by Scheffe test and Cronbach's alpha which is used as a reliance level by using a SPSS-PC+. The results of the study were as follows:1. The average score for the degree of recognition of traditional postpartal care(Sanhujori) for postpartal women was $3.09{\pm}.31$, and they recognized that it was important. The methods which were ranked were as follows; Protecting the body from a harmful state, invigorating the body by the argumentation of heat and avoidance of cold, handling with whole heart, and keeping clean, resting without working, eating well. 2. The average score for the degree of performance of traditional postpartal care (Sanhujori) for postpartal women was $2.81{\pm}.31$, and they performed that it was important, too. The methods which were ranked were as follows; Protecting the body from a harmful state, invigorating the body by the augumentation of heat and avoidance of cold, eating well, handling with whole heart, and keeping clean, resting without working. 3. There were significant differences statistically (paired-t=-8.39, p=.000) of the degree of recognition & performance of traditional postpartal care(Sanhujori) for the postpartal women. The degree of recognition was higher than the degree of performance. So, the recognition of traditional postpartal care (Sanhujori) was higher than the performance of it. 4. There were no statistical differences of the degree of recognition & performance of traditional postpartal care(Sanhujori) among the postpartal women's age, religion, job, educational background, delivery frequency, delivery method or the sex of baby. So, the Characteristics of the respondents were not influenced as far as the degree of recognition & performance of traditional postpartal care(Sanhujori). 5. There were significant differences statistically of the degree of performance of traditional postpartal care(Sanhujori) among the 5 postpartum care centers except 1 postpartum care center(p<.01). So, the recognition of traditional postpartal care(Sanhujori) was higher than the performance of traditional postpartal care(Sanhujori) in the 5 postpartum care centers. But there was performed as good as recognition in only 1 postpartum care center.

• The Journal of the Korea Contents Association
• /
• v.21 no.8
• /
• pp.315-328
• /
• 2021

The study identified 1,500 adult consumers aged 25-54 years with life insurance within the last year as three groups, top, middle and bottom of need recognition, and demonstrated differences in insurance and finance perception and socioeconomic value perception. In particular, the study sought to identify the influence of socioeconomic value recognition factors in addition to overall recognition factors related to insurance and finance, the number of insurance held and insurance satisfaction. Overall recognition factors related to insurance and finance were classified as 'recognition of insurance as a means of professional management and finance', 'self-directed insurance design and contract' and 'recognition of economic burden on insurance'. Socioeconomic value recognition factors were divided into 'socioeconomic self-sufficiency', 'work-life value pursuit' and 'economic value pursuit'. We identified factors that affect the recognition of a higher need for insurance needs as a higher recognition of need for insurance needs. In particular, the most influential factor for the median group was the recognition of insurance as a professional management asset-tech product, and the upper group was found to be a work-life balance factor. The second influential factor was self-directed insurance design and contract factors for both groups. In order to increase the rate of insurance subscription in the future, insurance should be recognized as an essential product to pursue work-life value, and continuous improvement in information exploration conditions for consumers to explore information and compare products will be important to revitalize the insurance market.

• Journal of Digital Convergence
• /
• v.13 no.2
• /
• pp.393-399
• /
• 2015

Nowaday, beyond the time of wellbeing and LOHAS, many people have great interest in self therapy, so it is called healing era. As the folk medicine fields are actively industrialized and the interest in health improvement, not disease cure, is increased, many researches about the alternative medicine and therapy in various fields are being performed. In the times of the interest in health improvement and spontaneous, natural healing ability of human body is getting increase, it is very meaningful to search the factors which consist of recognition to folk medicine. So in this study, we developed the questionaries on the basis of previous studies, researched the factors affecting the recognition to folk medicine using factor analysis, and tested statistically the difference of recognition character according to demo-statistical traits. As the result, the twenty-four measurable variables related to folk medicine are sorted to four factors, ie, health improvement factor, safety factor, psycholocial factor, and substitutional factor. And overall, the middle and senior ages, the forties to sixties, and higher-educated peoples have more experiences in folk medicine than the younger ages, below thirties and lower-educated peoples. The distiction of sex makes little differences.

• Journal of Digital Convergence
• /
• v.14 no.5
• /
• pp.433-443
• /
• 2016

This study is to research the comprehensive recognition of male elderly about the sex life in old age. We collected data through face to face interview after obtaining the consents of 13 male elderly over 65 years old who reside in Kimhae Gyeongnam and Busan. The result of study showed that the sexual recognition of male elderly participants include the core concept of , , < the sex with restriction> and . In other words, the male elderly recognized the sexual life of old age as a natural and instinctive thing, the restrictions still exist including the negative recognition of family and surrounding people and diseases but it is found that the improvement of social recognition about sexual desire, the sex education and aggressive support for the various solutions are required. As the sexual awareness of the elderly is the comprehensive and broad study, the amalgamative and integrated study should be continued in the various fields. Through this, we tried to suggest the basic documents to the effective and differentiated individual sex consultation based on the empirical characteristics and desire of male elderly, and customized sex education and the development of local society program.

• Journal of the Institute of Electronics Engineers of Korea CI
• /
• v.43 no.3 s.309
• /
• pp.39-49
• /
• 2006

This paper proposes a hand-posture recognition method using reinforcement learning for the performance improvement of vision-based hand-posture recognition. The difficulties in vision-based hand-posture recognition lie in viewing direction dependency and self-occlusion problem due to the high degree-of-freedom of human hand. General approaches to deal with these problems include multiple camera approach and methods of limiting the relative angle between cameras and the user's hand. In the case of using multiple cameras, however, fusion techniques to induce the final decision should be considered. Limiting the angle of user's hand restricts the user's freedom. The proposed method combines angular features and appearance features to describe hand-postures by a two-layered data structure and reinforcement learning. The validity of the proposed method is evaluated by appling it to the hand-posture recognition system using three cameras.

• Journal of Digital Convergence
• /
• v.13 no.10
• /
• pp.313-318
• /
• 2015

A traditional speech enhancement methods distort the sound spectrum generated according to estimation of the remaining noise, or invalid noise is a problem of lowering the speech recognition performance. In this paper, we propose a speech detection method that convergence the sound energy distribution process and sound energy parameters. The proposed method was used to receive properties reduce the influence of noise to maximize voice energy. In addition, the smaller value from the feature parameters of the speech signal The log energy features of the interval having a more of the log energy value relative to the region having a large energy similar to the log energy feature of the size of the voice signal containing the noise which reducing the mismatch of the training and the recognition environment recognition experiments Results confirmed that the improved recognition performance are checked compared to the conventional method. Car noise environment of Pause Hit Rate is in the 0dB and 5dB lower SNR region showed an accuracy of 97.1% and 97.3% in the high SNR region 10dB and 15dB 98.3%, showed an accuracy of 98.6%.

• Journal of the HCI Society of Korea
• /
• v.9 no.1
• /
• pp.23-28
• /
• 2014

In this study we focus on the effect of the interaction between humans and reactive television when emotion recognition through facial expression mechanism is used. Most of today's user interfaces in electronic products are passive and are not properly fitted into users' needs. In terms of the user centered device, we propose that the emotion based reactive television is the most effective in interaction compared to other passive input products. We have developed and researched next generation cognitive TV models in user centered. In this paper we present a result of the experiment that had been taken with Fraunhofer IIS $SHORE^{TM}$ demo software version to measure emotion recognition. This new approach was based on the real time cognitive TV models and through this approach we studied the relationship between humans and cognitive TV. This study follows following steps: 1) Cognitive TV systems can be on automatic ON/OFF mode responding to motions of people 2) Cognitive TV can directly select channels as face changes (ex, Neutral Mode and Happy Mode, Sad Mode, Angry Mode) 3) Cognitive TV can detect emotion recognition from facial expression of people within the fixed time and then if Happy mode is detected the programs of TV would be shifted into funny or interesting shows and if Angry mode is detected it would be changed to moving or touching shows. In addition, we focus on improving the emotion recognition through facial expression. Furthermore, the improvement of cognition TV based on personal characteristics is needed for the different personality of users in human to computer interaction. In this manner, the study on how people feel and how cognitive TV responds accordingly, plus the effects of media as cognitive mechanism will be thoroughly discussed.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.18 no.6
• /
• pp.241-250
• /
• 2019

Road signs are guide facilities for road users, and the Ministry of Land, Infrastructure and Transport has established and operated a system to enhance the convenience of managing these road signs. The role of road signs will decrease in the future autonomous driving, but they will continue to be needed. For the accurate mechanical recognition of texts on road signs, automatic road sign recognition equipment has been developed and it has applied image-based text recognition technology. Yet there are many cases of misrecognition due to irregular specifications and external environmental factors such as manual manufacturing, illumination, light reflection, and rainfall. The purpose of this study is to derive location-based destination names for finding misrecognition errors that cannot be overcome by image analysis, and to improve the automatic recognition of road signs destination names by using Levenshtein similarity verification method based on phoneme separation.

• Journal of the Korea Convergence Society
• /
• v.8 no.5
• /
• pp.13-17
• /
• 2017

Existing Speech feature extracting method in speech Signal, there are incorrect recognition rates due to incorrect speech which is not clear threshold value. In this article, the modeling method for improving speech recognition performance that combines the feature extraction for speech and silence characteristics normalized to the non-speech. The proposed method is minimized the noise affect, and speech recognition model are convergence of speech signal feature extraction to each speech frame and the silence feature normalization. Also, this method create the original speech signal with energy spectrum similar to entropy, therefore speech noise effects are to receive less of the noise. the performance values are improved in signal to noise ration by the silence feature normalization. We fixed speech and non speech classification standard value in cepstrum For th Performance analysis of the method presented in this paper is showed by comparing the results with CHMM HMM, the recognition rate was improved 2.7%p in the speech dependent and advanced 0.7%p in the speech independent.

• The Journal of the Acoustical Society of Korea
• /
• v.11 no.3
• /
• pp.61-66
• /
• 1992

There have been many researches that uses neural network models for automatic speech recognition, but the main trend was finding the neural network models and learning rules appropriate to automatic speech recognition. However, the choice of the input speech parameter for the neural network as well as neural network model itself is a very important factor for the improvement of performance of the automatic speech recognition system using neural network. In this paper we select 6 speech parameters from surveys of the speech recognition papers which uses neural networks, and analyze the performance for the same data and the same neural network model. We use 8 sets of 9 Korean plosives and 18 sets of 8 Korean vowels. We use recurrent neural network and compare the performance of the 6 speech parameters while the number of nodes is constant. The delta cepstrum of linear predictive coefficients showed best result and the recognition rates are 95.1% for the vowels and 100.0% for plosives.