• 한국노년학
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• v.31 no.2
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• pp.401-417
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• 2011

The life review means a process of appraising life of oneself and it is essential for finding the meaning of life in old age. The memoir writing is a kind of method of life review. The memoir writing program used in this study focused especially on enhancing the cognitive skills by providing priming and retrieval support for memory performance in reminiscing past experiences. All fourteen participants were healthy and normal community dwellers and attended four-month long programof memoir writing classes which are consisted of different themes for each week. The aim of this study was to examine if the memoir writing program would render the positive effect on mental health and cognitive ability of the elderly. The results were that quality of life, life satisfaction, ego integrity of the participants showed positive change and the level of depression was significantly reduced compared to that of the control group. The findings in the present study suggest that the memoir writing can serve as one of the community initiative program to the growing population of the elderly for their emotional and cognitive challenges that they face everyday. To warrant the validity of the program, further study is needed for other sectors of elderly population, such as elderly living alone or those with both physical and/or cognitive disadvantages.

• Science of Emotion and Sensibility
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• v.17 no.3
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• pp.107-116
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• 2014

In the current study, it is suggested that when two emotions are presented through cross-modality, such as auditory and visual, incongruence will influence arousal, recognition, and recall of subjects. The first hypothesis is that incongruent cross-modality does not only increase arousal more than the congruent, but it also increases recall and recognition more than congruent. The second hypothesis is that arousal modulates recall and recognition of subjects. To demonstrate the two hypotheses, our experiment's conditions were manipulated to be congruent and incongruent by presenting positive or negative emotions, visually and acoustically. For dependent variables, we measured recall rate and recognition rates. and arousal was measured by PAD (pleasure-arousal-dominance) scales. After eight days, only recognition was measured repeatedly online. As a result, our behavioral experiment showed that there was a significant difference between arousal before watching a movie clip and after (p<.001), but no difference between the congruent condition and incongruent condition. Also, there was no significant difference between recognition performance in the congruent condition and incongruent condition, but there was a main effect of the clips' emotions. Interestingly after analyzing recognition rates separately depending on clips' emotions, there was a significant difference between congruent and incongruent conditions in the only negative clip (p= .044), not in the positive clip. In a detailed result, recognition in the incongruent condition is more than in the congruent condition. Furthermore, in the case of recall performance, there was a significant interaction between the clips' emotions shown in the clips and congruent conditions (p=.039). Through these results, the effect of incongruence with negative emotion was demonstrated, but an incongruent effect by arousal could not be demonstrated. In conclusion, in our study, we tried to determine the impact of one method to convey a story dramatically and have an effect on memory. These effects are influenced by the subjects' perceived emotions (valence and arousal).

• KIPS Transactions on Software and Data Engineering
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• v.12 no.4
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• pp.179-188
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• 2023

Recently, fake news disguises the form of news content and appears whenever important events occur, causing social confusion. Accordingly, artificial intelligence technology is used as a research to detect fake news. Fake news detection approaches such as automatically recognizing and blocking fake news through natural language processing or detecting social media influencer accounts that spread false information by combining with network causal inference could be implemented through deep learning. However, fake news detection is classified as a difficult problem to solve among many natural language processing fields. Due to the variety of forms and expressions of fake news, the difficulty of feature extraction is high, and there are various limitations, such as that one feature may have different meanings depending on the category to which the news belongs. In this paper, emotional change patterns are presented as an additional identification criterion for detecting fake news. We propose a model with improved performance by applying a convolutional neural network to a fake news data set to perform analysis based on content characteristics and additionally analyze emotional change patterns. Sentimental polarity is calculated for the sentences constituting the news and the result value dependent on the sentence order can be obtained by applying long-term and short-term memory. This is defined as a pattern of emotional change and combined with the content characteristics of news to be used as an independent variable in the proposed model for fake news detection. We train the proposed model and comparison model by deep learning and conduct an experiment using a fake news data set to confirm that emotion change patterns can improve fake news detection performance.

• Journal of the Korea Society of Computer and Information
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• v.28 no.10
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• pp.133-153
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• 2023

In this paper, we propose a novel approach to investigating brain-signal measurement technology using Electroencephalography (EEG). Traditionally, researchers have combined EEG signals with bio-signals (BSs) to enhance the classification performance of emotional states. Our objective was to explore the synergistic effects of coupling EEG and BSs, and determine whether the combination of EEG+BS improves the classification accuracy of emotional states compared to using EEG alone or combining EEG with pseudo-random signals (PS) generated arbitrarily by random generators. Employing four feature extraction methods, we examined four combinations: EEG alone, EG+BS, EEG+BS+PS, and EEG+PS, utilizing data from two widely-used open datasets. Emotional states (task versus rest states) were classified using Support Vector Machine (SVM) and Long Short-Term Memory (LSTM) classifiers. Our results revealed that when using the highest accuracy SVM-FFT, the average error rates of EEG+BS were 4.7% and 6.5% higher than those of EEG+PS and EEG alone, respectively. We also conducted a thorough analysis of EEG+BS by combining numerous PSs. The error rate of EEG+BS+PS displayed a V-shaped curve, initially decreasing due to the deep double descent phenomenon, followed by an increase attributed to the curse of dimensionality. Consequently, our findings suggest that the combination of EEG+BS may not always yield promising classification performance.

• Korean Journal of Cognitive Science
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• v.29 no.1
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• pp.39-59
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• 2018

To elucidate the effect of working memory (WM) load on negative facial emotion processing, we examined ERP components (P1 and N170) elicited by fearful and neutral expressions each of which was presented during 0-back (low-WM load) or 2-back (high-WM load) tasks. During N-back tasks, visual objects were presented one by one as targets and each of facial expressions was presented as a passively observed stimulus during intervals between targets. Behavioral results showed more accurate and fast responses at low-WM load condition compared to high-WM load condition. Analysis of mean amplitudes of P1 on the occipital region showed significant WM load effect (high-WM load > low-WM load) but showed nonsignificant facial emotion effect. Analysis of mean amplitudes of N170 on the posterior occipito-temporal region showed significant overall facial emotion effect (fearful > neutral), but, in detail, significant facial emotion effect was observed only at low-WM load condition on the left hemisphere, but was observed at high-WM load condition as well as low-WM load condition on the right hemisphere. To summarize, facial emotion effect observed by N170 amplitudes was modulated by WM load only on the left hemisphere. These results show that early emotional processing of negative facial expression could be eliminated or reduced by high load of WM on the left hemisphere, but could not be eliminated by high load on the right hemisphere, and suggest right hemispheric lateralization of negative facial emotion processing.

• The Korean Journal of Quaternary Research
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• v.17 no.2
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• pp.85-99
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• 2003

Since the experience of major landscape change during last half of the century due to war and rapid urbanization, the traditional character has been weakened, and it is necessary for a reconsideration to improve the landscape for the future. To review these relationships, the importance of a comprehensive understanding of nature has been suggested. Therefore identification of a new concept based on the 'socio-cultural influence of landscape' and 'sense of place' which are related to peoples' previous experience, is required. Furthermore more practical definitions and criteria to reveal the relationship are necessary. Among the terms suggested to describe sense of place such as 'home', 'place identity', 'place-based meaning' and 'settlement identity' etc., the 'home' is selected to represent our surrounding landscape. For more practical classification of home landscape, additional terms are suggested and defined based on both the relationships between human beings and nature, and between memory derived from previous experience and shared values with in the community. The additional terms which are the most important in the role of landscape character related to humans' are; ⅰ) Personal Landscape: Landscape of an individual human, which derives from previous personal experience; involves distinguishable character for a given person, and it is emotional and flexible depending on circumstances. ⅱ) Ordinary Landscape： Landscape of the 'common interest' between members of a community, which is acceptable as a surrounding for everyday daily life, it produces the richness and variety of landscape. ⅲ) Kernel Landscape： Landscape of the 'common ground' which is acceptable to the majority members of the community, and it provides variety and stability for periods of time, and it could strongly represent community attitudes toward nature. ⅳ) Prototype Landscape: Landscape as the 'common denominator' of overall community from past to present and towards the future, which encompasses all the kernel landscape throughout history. It provides a sense of place, balances the homogeneity of character throughout overall communities. Some part of this can be shared throughout history to shape an overall sense of place. It can also represent short terms fashions. For a prototype landscape to reveal sense of place, there are a couple of points which we should underline the commencing point. Firstly, understanding the relationship between humans and nature should be based on a given character of surroundings. Secondly, reoccurring landscape elements which have sustained in history can lead to sense of place, and should be reviewed the influences between nature and humans.

• Journal of the Korean School Mathematics Society
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• v.10 no.2
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• pp.173-185
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• 2007

It is the importance of Lifelong Education that is gradually more and more increased and publicly mentioned as the population of current society is aging even very rapidly. Especially the vivid activity of human being's brain is emphasized rather than before for the protection of senile dementia as people consider the sound life worth. This paper suggests mathematical education that is applicable and suitable for the emotional and cognitive level of the aged as the way of new method. I suggest the 'silver math' that may strengthen memory, thinking power and logical power of the aged, further cause the interest through games with mathematics, finally uplift the self-perception and pride. Thus, several basic elements are proposed here in this paper, that can be the foundation for the systematic and specific research of 'silver math'.

• Fashion & Textile Research Journal
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• v.20 no.5
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• pp.509-519
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• 2018

This study is to examine the effects of salespeople' attributes (i.e., empathy, availability, professional appearance) on consumer cognition, emotion, and behavior. A conceptual model was developed based on stimulus-organism-response (S-O-R) theory and cognition-emotion theory. A total of 542 questionnaires were collected online and some incompletely written questionnaires were excluded. Because of the high possibility of memory distortion, only the questionnaires (n=220) written by those who visited fashion stores within one week were used for the final analysis. The results of PLS analyses demonstrated that 1) salespeople's empathy directly affected consumers' shopping emotion; 2) salespeople's availability and professional appearance indirectly affected consumer's shopping emotion through store image; 3) consumers' shopping emotion positively affected purchase intention. Theoretical and practical implications of the results are discussed in conclusion. As a result of this research, the main characteristics of the salespeople were identified in order to allow the consumers visiting the fashion store to buy the fashion products naturally and the basic directions of sales manuals for the salespeople in the fashion store were presented. It is also hoped that academic researchers will be able to use the characteristics of salespeople as the main data to understand how they affect consumers' cognitive and emotional responses and how they are connected to purchase behavior.

• Journal of the Korea society of information convergence
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• v.7 no.2
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• pp.49-57
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• 2014

Recently, opinion mining is introduced to extract useful information from SNS data and to evaluate the true intention of users. Opinion mining are required several efficient techniques to collect and analyze a large amount of SNS data and extract meaningful data from them. Therefore in this paper, we propose a parallel HDFS(Hadoop Distributed File System) and emotion functions based on Mapreduce to extract some emotional information of users from various unstructured big data on social networks. The experiment results have verified that the proposed system and functions perform faster than O(n) for data gathering time and loading time, and maintain stable load balancing for memory and CPU resources.

• The Journal of Pediatrics of Korean Medicine
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• v.31 no.4
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• pp.49-60
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• 2017

Objectives The purpose of this study is to report the effectiveness of Korean medicine on treating autism spectrum disorder (ASD) in childhood. Methods We treated an 8-years-old patient who was diagnosed with autism (grade II) with herbal medicine, acupuncture and electric moxibustion. Every 11 months, Korean-Childhood Autism Rating Scale (K-CARS) was used to assess the patient's symptom progression. Results After 21 months of Korean medicine treatment, the child's overall health was improved. Moreover, language ability, emotional control, memory and cognitive abilities got better, as well as anxiety, agitation, and aggressive behavior related to ASD were also decreased. K-CARS score at the initial stage of the treatment was 39.5 points, which can be considered as severe autism. After 11 months of the treatment, the K-CARS score was 34.5 points which is mild-moderate autism. Conclusions Korean medicine treatment can be effective in improving symptoms of ASD. However, further studies are needed to demonstrate the treatment benefits to ASD.