• 한국지역사회생활과학회지
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• 제27권3호
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• pp.387-403
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• 2016

This study explored the relationships between unmarried adult children and their coresident parents with a focus on the role of intergenerational exchanges and family values affecting parent-child relations. A total of 767 unmarried adult children who lived with their parents were selected from the data of the third National Korean Family Survey in 2015. The main findings were that coresident adult children exchange diverse resources with their parents and that exchange patterns whether receiving more or giving more differed depending on the helping dimensions. 'Receiving' type was more prominent in the dimension of practical help, while, 'receiving and giving' type was more noticeable in the dimension of emotional help. Findings also suggest that intergenerational exchange and family values contribute to parent-child relationship quality. While being an active provider of practical help is positively associated with relationship quality, being a recipient of emotional help is related to a higher level of relationship quality compared to being indifferent. In addition, a stronger value of family responsibility was associated with a higher level of relationship quality. These findings indicate that the importance of the practical and emotional component in the relationships between unmarried adult children and their co-resident parents and reciprocal intergenerational exchange and strong family values may be contributory factors to better parent-child relationships.

• 한국식생활문화학회지
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• 제23권3호
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• pp.388-396
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• 2008

This study examined the effects of Web ad components on customer attitude and purchasing decisions in 300 individuals who visited family restaurant Websites. The results are summarized as follows: First, Web ad components such as content, design, and interactivity had effects on the cognitive attitudes of the customers. And design, accessibility, and Web functionality had significant effects on the customers' emotional attitudes. In addition, content, navigation, and Web functionality had significant effects on the customers' behavioral attitudes. Lastly, the cognitive, emotional, and behavioral attitudes of the customers had significant effects on their purchases. From these results, design elements such as content, color, and menus, along with user interactivity for information are considered helpful components of a food service Web ad for customer cognition of the restaurant's information. In addition, aspects of Web functionality such as the food service's Web ad set-up, or the protection of personal information, the color design and menu, as well as accessibility for easy use, are all helpful in terms of gaining a customer attitude that is friendly and preferential towards a restaurant's menu items.

• Clinical and Experimental Pediatrics
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• 제48권5호
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• pp.469-475
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• 2005

Mother-infant interaction is a crucial component of an infant's cognitive, emotional and behavioral development. Most people are preoccupied with fetal education, the physical conditions of the postpartum mother and baby, and emphasizing an early start in the child's education. However, the effects of a mother's postnatal emotional state on the development of the infant are often overlooked. Postpartum depression is a significant health problem affecting 10-20 percent of new mothers. Recent research findings indicate that the suffering caused by postpartum depression is not limited to these mothers alone; their babies and close family members are vulnerable to short-term and long-term effects as well. This review summarizes the findings of recent research works, in the light of publications within the last seven years.

• International Journal of Contents
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• 제17권4호
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• pp.52-61
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• 2021

The 2020 US Presidential Election was a highly-anticipated moment for our global society. During the election period, the most intriguing issue was who would be the winner-Trump or Biden? Among the possible main themes of the 2020 election, from the COVID-19 pandemic to racism, this study focused on feminism ('women') as a main component of Biden's victory. To explore the character of Biden's supporters, this paper focused on internet spaces as a source of public opinion. To guide the data analysis, this study employed four indices from empirical studies on Big Data analytics: issue salience, attention diversity, emotional mentioning, and semantic cohesion. The main finding of this study was that the representative keyword 'women' appeared more prevalently within content related to Biden than Trump, and the keyword pairs indicated that female voters were the main reason for Trump's failure but the root cause of Biden's victory. The results of this study indicated the role of the internet as a forum for public opinion and a fountain of political knowledge, which requires more rigorous investigation by researchers.

• 제어로봇시스템학회논문지
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• 제12권3호
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• pp.284-288
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• 2006

In this paper, we apply several pattern recognition algorithms to emotion recognition system with speech signal and compare the results. Firstly, we need emotional speech databases. Also, speech features for emotion recognition is determined on the database analysis step. Secondly, recognition algorithms are applied to these speech features. The algorithms we try are artificial neural network, Bayesian learning, Principal Component Analysis, LBG algorithm. Thereafter, the performance gap of these methods is presented on the experiment result section. Truly, emotion recognition technique is not mature. That is, the emotion feature selection, relevant classification method selection, all these problems are disputable. So, we wish this paper to be a reference for the disputes.

• 한국기계가공학회지
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• 제17권3호
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• pp.141-147
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• 2018

Recently, interest in customers has shifted to the emotional quality of customers as the driving, handling, and collision stability of automobiles have been greatly improved. The NVH performance of a vehicle is quantified and evaluated from the DPDS. To improve the DPDS, we need to optimize the shape without considering the increases in thickness of the parts or additions to the parts. And at the same time, we need to establish design and analysis processes to satisfy the requirements of the DPDS.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2006년도 춘계학술대회 학술발표 논문집 제16권 제1호
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• pp.347-350
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• 2006

In this paper, we apply several pattern recognition algorithms to emotion recognition system with speech signal and compare the results. Firstly, we need emotional speech databases. Also, speech features for emotion recognition is determined on the database analysis step. Secondly, recognition algorithms are applied to these speech features. The algorithms we try are artificial neural network, Bayesian learning, Principal Component Analysis, LBG algorithm. Thereafter, the performance gap of these methods is presented on the experiment result section. Truly, emotion recognition technique is not mature. That is, the emotion feature selection, relevant classification method selection, all these problems are disputable. So, we wish this paper to be a reference for the disputes.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제6권2호
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• pp.150-154
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• 2006

In this paper, we apply several pattern recognition algorithms to emotion recognition system with speech signal and compare the results. Firstly, we need emotional speech databases. Also, speech features for emotion recognition are determined on the database analysis step. Secondly, recognition algorithms are applied to these speech features. The algorithms we try are artificial neural network, Bayesian learning, Principal Component Analysis, LBG algorithm. Thereafter, the performance gap of these methods is presented on the experiment result section.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2002년도 ICCAS
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• pp.52.5-52
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• 2002

In this paper, we develop analysis models for classification of temporal data from human subjects. The study focuses on the analysis of electroencephalogram (EEG) signals obtained during various emotional states. We demonstrate a generally applicable method of removing EOG and EMG artifacts from EEGs based on independent component analysis (ICA). All EEG channel maps were interpolated from 10 EEG subbands. ICA methods are based on the assumptions that the signals recorded on the scalp are mixtures of signals from independent cerebral and artifactual sources, that potentials arising from different parts of the brain, scalp and body are summed linearly at the electrodes and that prop...

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2014년도 추계학술대회 논문집
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• pp.481-482
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• 2014