• Asia pacific journal of information systems
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• v.30 no.1
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• pp.167-187
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• 2020

College students experience more cyber bullying than youth and cyber bullying on college students may be more harmful than youth. But many studies of cyber bullying have been conducted in youth, but little has been studied for college students. Therefore, this study investigated the negative effects of college students' cyber bullying experience on cognitive processing ability and emotional states. The social support of friends has a buffering effect that prevents stress and reduces the influence on external damage in stressful situations. But the impact of parental social support is controversial. Traditionally, the social support of parents has been claimed to mitigate the negative effects of external damage. Recently, however, it has been argued that parental social support, without considering the independence and autonomy needs of college students, does not alleviate the negative effects. Therefore, this study examined how the social support of friends and parents moderate the negative impact of cyber bullying. The results show that the more college students experience cyber bullying, the lower their cognitive processing ability and emotional states. And, the higher the social support of friends, the lower the harmful impacts of cyber bullying on cognitive processing ability and emotional states. But, the higher the social support of parents, the higher the harmful impacts of cyber bullying on cognitive processing ability and emotional states.

• Proceedings of the IEEK Conference
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• 2001.06e
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• pp.61-64
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• 2001

This paper describes a basic study for the classification of cognitive mental states as a basic research of a human-computer interface technique. To recognize the mental states, we obtained 22 subjects’brain waves in course of two types of experiments. One of the experiments is to choose an answer among yes, no or reject buttons, to underlying questions and the other is to select an icon displayed in a monitor screen. After acquiring the brain wave signals, we construct a feature set with the percent power increase for a given segment with respect to that of the reference period. The linear discriminative algorithm is used to classify the cognitive yes/no mental states.

• International Journal of Contents
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• v.8 no.4
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• pp.56-63
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• 2012

In recent decades, analyzing the activities of human brain achieved some accomplishments by using the functional Magnetic Resonance Imaging (fMRI) technique. fMRI data provide a sequence of three-dimensional images related to human brain's activity which can be used to detect instantaneous cognitive states by applying machine learning methods. In this paper, we propose a new approach for distinguishing human's cognitive states such as "observing a picture" versus "reading a sentence" and "reading an affirmative sentence" versus "reading a negative sentence". Since fMRI data are high dimensional (about 100,000 features in each sample), extremely sparse and noisy, feature selection is a very important step for increasing classification accuracy and reducing processing time. We used the Fisher Discriminant Ratio to select the most powerful discriminative features from some Regions of Interest (ROIs). The experimental results showed that our approach achieved the best performance compared to other feature extraction methods with the average accuracy approximately 95.83% for the first study and 99.5% for the second study.

• Korean Journal of Adult Nursing
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• v.20 no.4
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• pp.600-612
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• 2008

Purpose: This study was conducted to compare the recovery state of 6 month between s-ICH and s-SAH patients. The patients' recovery state was measured with 2 dimensions: functional and cognitive. Methods: Non-experimental prospective design was adopted by including 108 hemorrhagic stroke patients(s-ICH: 52 vs s-SAH: 56) admitted to Intensive Care Unit of one university hospital. Results: The study results showed that overall functional recovery state of s-SAH patients was better than that of s-ICH patients, and s-SAH patients also showed better recovery states in all of the sub-dimensions of functional recovery, such as feeding, grooming, and toileting, than those of s-ICH in 6 month. On the contrary, the study results showed that overall cognitive recovery states of 6 month between two groups were not significantly different. However, according to the results comparing the sub-dimensions of cognitive recovery, s-SAH patients' recovery states on attention, communication and memory were significantly better than those of s-ICH patients, while recovery states on problem solving, safety behavior, and social behavior between 2 groups were not significantly different. Conclusion: From the study results, it was noted that s-SAH patients showed better recovery states in cognitive dimension as well as in functional dimension compared with s-ICH patients.

• Smart Media Journal
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• v.5 no.1
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• pp.30-37
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• 2016

In recent decades, the study of human brain function has dramatically increased thanks to the advent of Functional Magnetic Resonance Imaging. This is a powerful tool which provides a deep view of the activities of the brain. From fMRI data, the neuroscientists analyze which parts of the brain have responsibility for a particular action and finding the common pattern representing each state involved in these tasks. This is one of the most challenges in neuroscience area because of noisy, sparsity of data as well as the differences of anatomical brain structure of each person. In this paper, we propose the use of appropriate discriminant methods, such as Fisher Discriminant Ratio and hypothesis testing, together with strong boosting ability of Adaboost classifier. We prove that discriminant methods are effective in classifying cognitive states. The experiment results show significant better accuracy than previous works. We also show that it is possible to train a successful classifier without prior anatomical knowledge and use only a small number of features.

• Korean Journal of Adult Nursing
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• v.24 no.5
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• pp.540-545
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• 2012

Purpose: The purpose of the study was to compare level of functional independence and its correlates among community-dwelling older adults in rural areas between South Korea and the United Sates. Methods: The study employed a comparative and correlational design. Data were collected from 198 community-dwelling older adults in rural areas (South Korea=100, & US = 98). Functional independence, cognitive function, obesity and general characteristics were measured. Results: From both countries, approximately fifteen percent of older adults living independently had cognitive problems without any treatments. Among Korean older adults functional independence was associated with a number of chronic diseases and aging while in the United States the participants had a negative correlation with obesity and aging. Conclusion: For Korean older adults in rural areas, nurses should focus on monitoring older adults' abilities to manage chronic illness and designing self-management programs while in the United States the focus should be on healthy lifestyle programs about exercise and diet to increase functional independence.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.63 no.1
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• pp.34-39
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• 2014

In cognitive radios, secondary users can use the spectrum exclusively allocated to a primary wireless system if the secondary users detect the spectrum in idle states. Because the secondary users can utilize the idle state of the spectrum, the utilization rate of the spectrum can be improved. The idle states can be detected by using secondary users' sensing schemes. However, the wireless channel environment where secondary users perform the spectrum sensing is not very friendly to secondary users because the signal-to-noise ratio of the received primary signal is very low. Hence, cooperative sensing scheme where more than one secondary user take part in the spectrum sensing is generally used in cognitive radios. In this paper, we investigate the cooperative sensing performance for machine-to-machine communication devices operated by batteries with limited energy. In general, the energy consumed for the spectrum sensing increases as the length of the sensing period and the number of cooperative sensing nodes. Accordingly, even though the total amount of the consumed energy is the same, an energy allocation methodology how to distribute the energy to the sensing period and sensing nodes can achieve the optimum sensing performance, which is numerically analyzed.

• Journal of Korean Library and Information Science Society
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• v.48 no.3
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• pp.281-302
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• 2017

This study examined the differences in a searcher's mental states of a complex information search and retrieval task during information search process between the two groups: participants who were exposed to mental demand manipulation and those not exposed. Data from the experiments and questionnaires were analyzed. Based on qualitative approach and quantitative analyses, the results indicated that the participants exposed to mental demand required more thoughts; addressed negative emotions more often; reduced a searcher's efforts; and interrupted search performance than those not exposed. These results suggest that mental demand contributed to a searcher's perceived thought, emotion, effort, and performance, although these mental states differed in relative contribution of information search process. Significant differences were found between the two groups with respect to the component of mental demand, performance, and frustration of the NASA-TLX subjective cognitive load. These results have implications for search user interface design and information search systems among others.

• Journal of International Academy of Physical Therapy Research
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• v.5 no.2
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• pp.730-737
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• 2014

The aim of this study is to examine the effects of virtual reality cognitive rehabilitation program on cognitive function, physical function and depression of long-term care insurance nongrading elderly dementia using Daytime protection service. For achieve this purpose, 30 dementia elderly were randomly assigned in to the experimental group(n=15)and control group(n=15). All subjects performed a general therapeutic exercise and 20- 30minutes takes virtual reality cognitive rehabilitation program were conducted with experimental group 2 times a week for 8 weeks. The intervention effects were measured by using cognitive function is mini-mental states examination-Korean version(MMSE-K), visual perception is MVPT(Motor-Free Visual Perception Test), Berg's balance scales(BBS), depression test GDS-K and lower limb strength. The results of study represented that the training group showed significant improvement in MMSEK( p<.05), visual perception(p<.05), balance(p<.05), lower limb strength(p<.05) and depression (p<.05). In conclusion, the virtual reality cognitive rehabilitation training using improves visual perception included cognitive function, physical function included balance, and lower limb strength and depression. These results suggest that virtual reality training using virtual reality cognitive rehabilitation program is feasible and suitable for mild dementia.

• Korean Journal of Cognitive Science
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• v.13 no.3
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• pp.11-21
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• 2002

Parke and Waters' model［1］ of muscle-based face deformation was used to develop a system that can synthesize facial expressions when the pleasure-displeasure and arousal-sleep coordinate values of internal states are specified. Facial expressions sampled from a database developed by Chung, Oh, Lee and Byun ［2］ and its underlying model of internal states were used to find rules for face deformation. The internal - state model included dimensional and categorical values of the sampled facial expressions. To find out deformation rules for each of the expressions, changes in the lengths of 21 facial muscles were measured. Then, a set of multiple regression analyses was performed to find out the relationship between the muscle lengths and internal states. The deformation rules obtained from the process turned out to produce natural-looking expressions when the internal states were specified by the pleasure-displeasure and arousal-sleep coordinate values. Such a result implies that the rules derived from a large scale database and regression analyses capturing the variations of individual muscles can be served as a useful and powerful tool for synthesizing facial expressions.