• Journal of KIISE
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• v.45 no.3
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• pp.234-241
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• 2018

The study of classifying gamer types or analyzing the characteristics of gamers is a field of interest for data analysis researchers. From the past to the present, much research has been done on gamer categorization and gamer analysis. However, most studies use surveys or bio-signals, which is not practical because it is difficult to obtain large amounts of data. Even if the game log is used, it is difficult to analyze the psychology of the gamer because the gamer is categorized and analyzed by extracting only statistical values. However, if we can extract the cognitive psychology information of the gamer from the basic game log, we can analyze the gamer more intuitively and easily. In this paper, we extracted eight cognitive psychological features representing the behavior and psychological information of the gamer using Crazy Dragon's game log, which is a mobile Role-Playing-Game (RPG). In addition, we classified gamers based upon cognitive psychological features and analyzed them using eight cognitive psychological features. As a result, most gamers were highly correlated with one or two types.

• Journal of Biomedical Engineering Research
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• v.43 no.4
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• pp.185-192
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• 2022

Early detection of mild cognitive impairment can help prevent the progression of dementia. The purpose of this study was to design and validate a machine learning model that automatically differential diagnosed patients with mild cognitive impairment and identified cognitive decline characteristics compared to a control group with normal cognition using resting-state quantitative electroencephalogram (qEEG) with eyes closed. In the first step, a rectified signal was obtained through a preprocessing process that receives a quantitative EEG signal as an input and removes noise through a filter and independent component analysis (ICA). Frequency analysis and non-linear features were extracted from the rectified signal, and the 3067 extracted features were used as input of a linear support vector machine (SVM), a representative algorithm among machine learning algorithms, and classified into mild cognitive impairment patients and normal cognitive adults. As a result of classification analysis of 58 normal cognitive group and 80 patients in mild cognitive impairment, the accuracy of SVM was 86.2%. In patients with mild cognitive impairment, alpha band power was decreased in the frontal lobe, and high beta band power was increased in the frontal lobe compared to the normal cognitive group. Also, the gamma band power of the occipital-parietal lobe was decreased in mild cognitive impairment. These results represented that quantitative EEG can be used as a meaningful biomarker to discriminate cognitive decline.

• Journal of The Korean Association For Science Education
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• v.28 no.7
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• pp.697-712
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• 2008

The purpose of this study was to seek strengths and weaknesses from analyzing Korea and U.S. science textbooks in terms of general structural features, contents, cognitive levels of questions and the purpose of questions used in science textbooks. This provided insight into improvement of textbooks that can effectively assist teaching and learning. To investigate organization of unit in textbooks in-depth, the evolution unit was selected and scrutinized as one example. The results showed that the number of pages, activities, vocabulary words, and vocabulary lists are considerably different between Korean and the U.S. Commonly, U.S. textbooks were more laden with information and lacking in coherence than those of the Korean textbooks. The findings on the cognitive levels of questions showed that the majority of questions in both nations are concerned with knowledge. However, the difference between the two nations is great in the ratios of analysis, synthesis, and evaluation questions. Questions are concentrated in review section (45% of Korean and 60.6% of U.S.) in textbooks. It suggested that well-planned questions in a review section can provide the basic guidance for strength in a science classroom.

• Journal of the Korean Society for information Management
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• v.18 no.3
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• pp.265-284
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• 2001

The aim of this study was to discover the correlation between users cognitive style and their attitude towards evaluating the system. Postgraduate students cognitive styles were defined as Verbaliser/Imager and Wholist/Analytic, and the functionality and ease of learning features of a Web-based OPAC(Online Public Access Catalogue) system were evaluated using a combined evaluation methods: interviews for the preliminary survey, a questionnaire far the central data collection, and a psychometric approach for the judgement of students cognitive style using Ridings CSA(Cognitive Style Assessment) tool. Forty-four postgraduate student volunteers responded and data was analysed using SPSS(Statistical Package for Social Science) for Windows. The statistical analysis of each feature of the evaluation, the correlation between the variables, and the features were explored using Pearsons correlation coefficients(r). In exploring the effects of the cognitive styles of individuals, this study has failed to reveal a significant (P < 0.05) correlations in the interactive Web-based OPACs evaluation. It could be said that the contribution of cognitive styles to evaluating Web-based OPACs is likely to be weaker than that of non-cognitive (or demographic) variables.

• Journal of the Ergonomics Society of Korea
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• v.14 no.1
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• pp.25-35
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• 1995

For information processing tasks, it is an important cognitive skill to manipulate and store information, which is known as information intake. One of the tasks which greatly involve this skill would be a spreadsheet calculation task. In this study, a spreadsheet calculation task is analyzed by the cognitive task analysis based on the cognitive factors having been usef for a model of human information processing. By the results of the cognitive task analysis, the spreadsheet calculation tasks to be used in the experiments are designed and the testbattery of cognitive abilities assessment (CCAB ; complex cognitive asssessment battery) are selected. Then, the features of cognitive demands and a human performance model of the spreadsheet calculation task are suggested by means of correlation analysis, principal component factor analysis, and regression analysis of the results of the experiments on task performances and the assessment of cognitive abilities. Also, the application of the results of the study to job placement and further research issues are described.

• Journal of The Korean Association For Science Education
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• v.28 no.3
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• pp.227-240
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• 2008

Cognitive conflict is well recognized as an important factor in conceptual change and is widely used in developing constructivism-based curricula. However, cognitive conflicts can also contribute to student anxiety during learning, which, when not properly addressed, can have negative impacts on students' motivation and achievement. Therefore, instructors need to be aware of the impacts of introducing cognitive conflicts in their instruction. We need a practical instrument that can help identify the existence and features of cognitive conflicts introduced by the instruction and the resulting anxiety. Based on the literature on studies of cognitive conflicts and student anxiety, we developed a quantitative instrument, the In-class Conflict and Anxiety Recognition Evaluation (iCARE), and used it to monitor the status of students' cognitive conflicts and anxiety in Physics by Inquiry (PBI) classes. In this paper, we introduce this instrument and present the types of information that can be obtained. Research and pedagogical values of this instrument are also discussed.

• Journal of Gifted/Talented Education
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• v.14 no.4
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• pp.15-45
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• 2004

The purpose of this study is to find out the effect of science journal writings on the cognitive and affective features of the science gifted students. In this research, the tasks of on-line science journal writings were assigned for 6 months and the subjects in this study were 21 students of Chemistry Division of the Center for Science Gifted Education, Seoul National University. Consequently in science journals, science concepts are found in various aspects according to the writing formats, and psychological and behavioral characteristics of the science-gifted are revealed in positive or negative aspects. In cognitive prospect, science journal writing equips students with better understanding about science concepts and scientific research. In affective prospect, science journal writing help students improve observation and attitude toward science as wren as writing skills. Accordingly, science journal writing has positive effect on cognitive and affective characteristics of the science-gifted. In conclusion, acknowledged by most of science-gifted students as both beneficial and appropriate in their education program, science journal writing should be emphasized in education for science-gifted students.

• Korean Journal of Biological Psychiatry
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• v.23 no.2
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• pp.41-47
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• 2016

Dementia with Lewy bodies (DLB) is the second most common causes of dementia. It can exhibit a variety of clinical symptoms including cognitive decline, cognitive fluctuation, visual hallucinations, parkinsonism, REM sleep behavior disorder, hypersensitivity to neuroleptics and autonomic dysfunctions. Despite more well-known criteria for DLB, there are often misdiagnosis and inappropriate treatment. It gives a lot of clinical burden to the clinician as well as to patients and families. When reducing the misdiagnosis, the burden of all will be reduced. The special concern and solicitation are needed in order not to miss the diagnosis when the cardinal features of DLB may not be volunteered by patients and the caregivers. To control the symptoms, clinicians must find and reduce drugs that can have the negative effects on DLB symptoms. There is limited evidence about specific interventions but available data suggest cholinesterase inhibitors improve the cognitive and behavioral symptoms and menmantine slightly improves the global impression.

• 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.

• Molecules and Cells
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• v.43 no.3
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• pp.215-221
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• 2020

The olfactory bulb (OB) has an extremely higher proportion of interneurons innervating excitatory neurons than other brain regions, which is evolutionally conserved across species. Despite the abundance of OB interneurons, little is known about the diversification and physiological functions of OB interneurons compared to cortical interneurons. In this review, an overview of the general developmental process of interneurons from the angles of the spatial and temporal specifications was presented. Then, the distinct features shown exclusively in OB interneurons development and molecular machinery recently identified were discussed. Finally, we proposed an evolutionary meaning for the diversity of OB interneurons.