• Journal of Korean Elementary Science Education
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• v.33 no.1
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• pp.140-161
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• 2014

The purpose of this study was to analyze 181 papers about brain-based learning appeared in domestic scientific journals from 1989 to May of 2012 and suggest application conditions in elementary science education. The results of this study summarizes as follows; First, learning activity suggested by brain-based learning study is mainly explained by working of brain function. Learning activity explained by brain-based learning study are divided into 'learning according to specialized brain function, learning according to brain function integration and learning beyond specialization and integration of hemispheres'. Second, it searched how increased knowledge of brain structure and function affects learning. Analysis from this point of view suggests that brain-based learning study affects learning in many ways especially emotion, creativity and learning motivation. Third, brain-based learning study suggests various possibilities of learning activity reflecting brain plasticity. Plasticity which is one of most important characteristics of brain supports the validity of learning activity as learning disorder treatment and explains the possibility of selective increment of brain function by leaning activity and the need of whole-brain approach to learning activity. Fourth, brain-based learning brought paradigm shifts in education field. It supports learning sophistication on the understanding of student's learning activity, guides learning method that reflects the characteristics of subject and demands reconstruction of curriculum. Fifth, there are many conditions to apply brain-based learning in elementary science education field, learning environment that fits brain-based learning, change of perspectives on teaching and learning of science educators and development of brain-based learning curriculum are needed.

• Journal of the Korea Society of Computer and Information
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• v.25 no.8
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• pp.47-54
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• 2020

Developmental disorders are impairments of brain and/or central nervous system and refer to a disorder of brain function that affects languages, communication skills, perception, sociality and so on. In diagnosis of developmental disorders, behavioral response such as expressing emotions in proper situation is one of observable indicators that tells whether or not individual has the disorders. However, diagnosis by observation can allow subjective evaluation that leads erroneous conclusion. This research presents the technological environment and data acquisition system for AI based screening of autism disorder. The environment was built considering activities for two screening protocols, namely Autism Diagnostic Observation Schedule (ADOS) and Behavior Development Screening for Toddler (BeDevel). The activities between therapist and baby during the screening are fully recorded. The proposed software in this research was designed to support recording, monitoring and data tagging for learning AI algorithms.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.12
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• pp.1729-1738
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• 2021

Machine learning has a close relationship with cognitive psychology and brain science and is developing together. This paper analyzes the OASIS-3 dataset using machine learning techniques and proposes a model for predicting dementia. Dimensional reduction through PCA (Principal Component Analysis) is performed on the data quantifying the volume of each area among OASIS-3 data, and only important elements (features) are extracted and then various machine learning including gradient boosting and stacking Apply the models and compare the performance of each. Unlike previous studies, the proposed technique has a great differentiation because it uses not only the brain biometric data, but also basic information data such as the participant's gender and medical information data of the participant. In addition, it was shown that the proposed technique through various performance evaluations is a model that can better predict dementia by finding features that are more related to dementia among various numerical data.

• Korean Journal of Culture and Social Issue
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• v.18 no.1
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• pp.27-51
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• 2012

The current paper examines the effect of collectivism on perceived youth unemployment anxiety as well as mental health and the mediating effects of employment self-efficacy; self-esteem; and the frequency of upward and downward social comparisons. In Study 1, data were gathered from 179 university students in upper-ranking schools and middle-ranking schools in Seoul, Korea. Our results indicated that (a) collectivism was positively correlated to, and also an significant predictor of perceived youth unemployment anxiety and mental health and (b) employment self-efficacy and self-esteem had mediating effects on the relationship between collectivism and perceived youth unemployment anxiety and mental health. In Study 2, data were gathered from 118 students in upper-ranking schools in Seoul, Korea. Our results indicated that (c) upward social comparison had mediating effects on the relationship between collectivism and perceived youth unemployment anxiety and mental health, while downward social comparison did not. The findings are discussed in terms of their general implications for understanding the importance of culture in employment seeking settings.

• Journal of Dairy Science and Biotechnology
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• v.33 no.3
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• pp.179-196
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• 2015

Because of our aging population, there is increasing concern about the impact of dementia and age-related cognitive decline. Intense research efforts on effective dietary interventions for the prevention or amelioration of dementia and age-related cognitive decline have indicated that dairy products affect physiological health and potentially healthy brain function during aging. Milk is a rich source of proteins and peptides with nutritional and immunotropic activities. The preparation of biologically active proteins and peptides generally requires enzymatic degradation, chemical modification, or the addition of specific co-factors. Milk-derived preparations are widely available in the food industry in the form of hygiene products and infant formulas. However, milk-derived products could also be applied as preventive or therapeutic measures for a wide-range of pathological conditions not only in neonates and infants but also in adults, including the elderly. Because they have no adverse side effects, milk-derived proteins and peptides could be used as a supplementary treatment for dementia and age-related cognitive decline.

• Korean Journal of Psychosomatic Medicine
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• v.29 no.1
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• pp.67-76
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• 2021

Objectives : The aim of this study was to compare activities of daily living (ADLs) according to degenerative changes in brain [i.e., medial temporal lobe atrophy (MTA), white matter hyperintensities] and to examine the association between neurocognitive functions and ADLs in Korean patients with dementia due to Alzheimer's disease (AD) and mild cognitive impairment (MCI). Methods : Participants were 111 elderly subjects diagnosed with AD or MCI in this cross-sectional study. MTA in brain MRI was rated with standardized visual rating scales (Scheltens scale) and the subjects were divided into two groups according to Scheltens scale. ADLs was evaluated with the Korean version of Blessed Dementia Scale-Activity of daily living (BDS-ADL). Neurocognitive function was evaluated with the Korean version of the Consortium to Establish a Registry for Alzheimer's Disease assessment packet (CERAD-K). Independent t-test was performed to compare ADLs with the degree of MTA. Pearson correlation and hierarchical multiple regression analyses were performed to analyze the relationship between ADLs and neurocognitive functions. Results : The group with high severity of the MTA showed significantly higher BDS-ADL scores (p<0.05). The BDS-ADL score showed the strongest correlation with the word list recognition test among sub-items of the CERAD-K test (r=-0.568). Findings from the hierarchical multiple regression analysis revealed that the scores of MMSE-K and word list recognition test were factors that predict ADLs (F=44.611, p<0.001). Conclusions : ADLs of AD and MCI patients had significant association with MTA. Our study, which identifies factors correlated with ADLs can provide useful information in clinical settings. Further evaluation is needed to confirm the association between certain brain structures and ADLs.

• The KIPS Transactions:PartA
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• v.11A no.7 s.91
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• pp.555-562
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• 2004

Both global volume reduction and local shape changes of hippocampus within the brain indicate their abnormal neurological states. Hippocampal shape analysis consists of two main steps. First, construct a hippocampal shape representation model ; second, compute a shape similarity from this representation. This paper proposes a novel method for the analysis of hippocampal shape using integrated Octree-based representation, containing meshes, voxels, and skeletons. First of all, we create multi-level meshes by applying the Marching Cube algorithm to the hippocampal region segmented from MR images. This model is converted to intermediate binary voxel representation. And we extract the 3D skeleton from these voxels using the slice-based skeletonization method. Then, in order to acquire multiresolutional shape representation, we store hierarchically the meshes, voxels, skeletons comprised in nodes of the Octree, and we extract the sample meshes using the ray-tracing based mesh sampling technique. Finally, as a similarity measure between the shapes, we compute $L_2$ Norm and Hausdorff distance for each sam-pled mesh pair by shooting the rays fired from the extracted skeleton. As we use a mouse picking interface for analyzing a local shape inter-actively, we provide an interaction and multiresolution based analysis for the local shape changes. In this paper, our experiment shows that our approach is robust to the rotation and the scale, especially effective to discriminate the changes between local shapes of hippocampus and more-over to increase the speed of analysis without degrading accuracy by using a hierarchical level-of-detail approach.

• The Journal of Korean society of community based occupational therapy
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• v.1 no.1
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• pp.79-89
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• 2011

The number of the disabled person had been increased for the industrial accident and the environmental pollution. Especially, developmental disability has the high prevalence rate between 5% and 10% of the whole children. The children with a developmental disability can be treated by the physical therapy, the occupational therapy, the psychology therapy, speech therapy, and art therapy. Visual preception which is function to recognize the external environment through the optic organ could be related to most behaviors on the everyday life. But because the children with disability could not develop the visual-preception enough, they came to have difficulties in executing daily life project. For this reason, it is most important to understand the estimation and the cure on the visual-preception in the pediatric occupational therapy. To improve the visual-preception power, we have many kind of methods including sensory integration, training program for the visual-perception and art-craft program. Particularly, the art-craft which is the representative activity for making something by hands, can be applied to anyone. As the study on the brain has been activated, it was proved that handicraft actives could have an good effect on the brain function and using brain. When the fine motor exercise and more delicate and accurate motion were carried, these motions need the essential help of the visual-perception. So it could be expected that using the repetitive hand function by art-craft makes the brain function improve, when a activity that needs a fine motor exercise and more delicate, accurate motion was carried, It also indicates that the art-craft program has a clear treatment value. Though the intervention between visual-perception development and visual-perception disability have a majority in the field of occupational therapy, there is a few study yet. Therefore, this study tried to look back on the necessity of applying the art-craft program to the children with disability as the prestudy for preliminary validity of the master's thesis.

• Journal of Educational Research in Mathematics
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• v.26 no.2
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• pp.205-224
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• 2016

Nowadays technological instruments are advanced to measure brain waves called EEG. Also, it is important to find some facts that cause students to have mathematic anxiety (MA) and to provide remedy programs to lessen their MA in order to help students cure MA that could contribute to negative self-efficacy toward mathematics and mathematical learning. To find how they change the MA level, a small group of 11 high school students in Suwon city participated for ten weeks at the remedy program based on students' levels of MA diagnosed by MASS instrument (Ko, & Yi, 2011) and proofread by 8 advisors who worked in related research areas. The results showed that the remedy program was effective to lessen students' MA and it should provide a long term period since some negative experiences were accumulated for a long time of his or her past schooling by others such as teachers, peers, and parents. EEG showed that students got better scores on a percent of correct answers and a reaction time and some student' EEG from a group HMA became smaller heights and width in comparison of the other groups.

• Journal of KIISE
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• v.44 no.6
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• pp.587-594
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• 2017

Recently, motor imagery electroencephalogram(EEG) based Brain-Computer Interface(BCI) systems have received a significant amount of attention in various fields, including medicine and engineering. The Common Spatial Pattern(CSP) algorithm is the most commonly-used method to extract the features from motor imagery EEG. However, the CSP algorithm has limited applicability in Small-Sample Setting(SSS) situations because these situations rely on a covariance matrix. In addition, large differences in performance depend on the frequency bands that are being used. To address these problems, 4-40Hz band EEG signals are divided using nine filter-banks and Regularized CSP(R-CSP) is applied to individual frequency bands. Then, the Mutual Information-Based Individual Feature(MIBIF) algorithm is applied to the features of R-CSP for selecting discriminative features. Thereafter, selected features are used as inputs of the classifier Least Square Support Vector Machine(LS-SVM). The proposed method yielded a classification accuracy of 87.5%, 100%, 63.78%, 82.14%, and 86.11% in five subjects("aa", "al", "av", "aw", and "ay", respectively) for BCI competition III dataset IVa by using 18 channels in the vicinity of the motor area of the cerebral cortex. The proposed method improved the mean classification accuracy by 16.21%, 10.77% and 3.32% compared to the CSP, R-CSP and FBCSP, respectively The proposed method shows a particularly excellent performance in the SSS situation.