• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.295-297
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• 2003

The coastal provinces of South China have been uniquely shaped by various tectonic events. During the midlate Mesozoic tectono-thermal event, the oblique subduction of the Paleo Kula-Pacific plate beneath the Eurasian plate has created a complicated tectonic setting for the whole region. However, the mechanism of this event is not completely understood. In this paper, we discuss the advantages of using LANDSAT TM satellite imagery over a small part of the region - the Mirs Bay Basin which is largely covered by dense vegetation and where limited outcrops is seen. The use of satellite imagery complements field mapping and the result shows a prominent sinistral offset along the eastern margin of the Mirs Bay Basin, which was not previously recognized on the ground.

• (The) Research of the performance art and culture
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• no.37
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• pp.365-389
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• 2018

This research aims to study Michael Chekhov's acting techniques scientifically, because his techniques has been studied only theoretically or empirically. Especially, this study focuses on 'imagination' and 'Psychological Gesture' from the perspective of cognitive psychology. Chekhov thought 'imagination' as the basis and core of all the works of acting. In cognitive psychology, it is called as 'imagery' and means 'a representation of the mind of the object not communicated by the sensory organs currently'. This study starts with defining imagery and takes a brief look at the features and kinds of imagery. Then the researcher will prove scientifically the possibility of training acting using imagery as Chekhov's assertion. For the proof of the validity of imagery, we'll look for the theoretical evidences-functional equivalence hypothesis, psychoneuromuscular theory, symbolic learning theory, psychophygiological information processing-and experimental ones-measurements of cerebral blood flow or event-related potential, experiments with fMRI(functional magnetic resonance imaging) or PET(positron emission tomography). As a result, we can see that imagery is functionally identical to perception and improves fulfillment of cognitive and physical tasks. As proving physical changes can draw out psychological changes(feeling) on the medium of imagery, we can also see the validity of Psychological Gesture. From the above research, even if Chekhov developed the acting techniques only on the basis of his experience, his techniques can be thought as having scientific validity. Though insufficient, this study can be a help for actors or students as they using Chekhov's techniques.

• Journal of Biomedical Engineering Research
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• v.43 no.6
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• pp.375-381
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• 2022

Brain-computer interface (BCI) is a technology that allows users with motor disturbance to control machines by brainwaves without a physical controller. Motor imagery (MI)-BCI is one of the popular BCI techniques, but it needs a long calibration time for users to perform a mental task that causes high fatigue to the users. MI is reported as showing a similar neural mechanism as motor execution (ME) and motor observation (MO). However, integrative investigations of these three tasks are rarely conducted. In this study, we propose a new paradigm that incorporates three tasks (MI, ME, and MO) and conducted a comparative analysis. For this study, we collected Electroencephalograms (EEG) of motor imagery/execution/observation from 28 healthy subjects and investigated alpha event-related (de)synchronization (ERD/ERS) and classification accuracy (left vs. right motor tasks). As result, we observed ERD and ERS in MI, MO and ME although the timing is different across tasks. In addition, the MI showed strong ERD on the contralateral hemisphere, while the MO showed strong ERD on the ipsilateral side. In the classification analysis using a Riemannian geometry-based classifier, we obtained classification accuracies as MO (66.34%), MI (60.06%) and ME (58.57%). We conclude that there are similarities and differences in fundamental neural mechanisms across the three motor tasks and that these results could be used to advance the current MI-BCI further by incorporating data from ME and MO.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.10a
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• pp.373-376
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• 2004

최근에 뇌파를 이용하여 컴퓨터와 통신하거나 기기를 제어할 수 있는 이른바 뇌-컴퓨터 인터페이스BCI(Brain-Computer Interface)에 대한 연구가 대두되고 있다. 이러한 BCI 연구의 궁극적 목표는 다양한 정신상태에 따른 뇌파의 특성을 파악하여 컴퓨터나 기기 등을 제어하는 것이다. 본 논문에서는 움직임과 관련 있는 10～12Hz의 mu파 영역에서의 ERD/ERS를 계산하였고, 그 결과 왼쪽과 오른쪽 손의 움직임을 상상할 때에 운동과 관련된 기능이 집중되어 있는 일차운동영역(primary motor area)의 mu파에서 ERD/ERS의 차이가 나타남을 발견하였다 또한, RLS방법을 사용한 Adaptive Autoregressive Model 계수의 특징을 추출을 하였으며, 이를 신경망으로 학습시켜 인식률을 비교하였다.

• Science of Emotion and Sensibility
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• v.17 no.2
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• pp.3-12
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• 2014

A way to increase effectiveness of charitable donation ads is to activate or magnify emotional experiences (e.g., sympathy, empathy, psychological distress) among target audience. Past studies suggest that mental imagery and attention, which activate or magnify emotional experiences, can be influenced by verbal message attributes (i.e., message concreteness and valence) of charitable donation advertisements. Based on the previous research, the study built a conceptual framework for processing of charitable donation advertising: message concreteness and valence ${\rightarrow}$ mental imagery and attention ${\rightarrow}$ emotional experiences ${\rightarrow}$ donation intention. To verify the framework, the study investigated on the influence of message concreteness and valence on mental imagery and attention through assessing ERP responses. It also examined how message concreteness and valence have an effect on the intent to donate through measuring the amount of donation. The study revealed that concrete message activated mental imagery more than abstract message whereas negative message enhanced attentional level more than positive message. Compared to the other conditions, when the message was concrete and negative, the amount of donation was significantly large.

• Sleep Medicine and Psychophysiology
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• v.8 no.1
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• pp.45-51
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• 2001

Objectives: The experience of traffic accident is a kind of the psychosocial stressors to person. The traffic accident-related patients may show the psychophysiologic hyperarousal. So we examined the differences of psychophysiologic response between patients with and without the memory of experienceing a traffic accident. Methods: Twenty-four traffic accident-related patients were divided into two groups according to ther memory of a traffic accident. In psychological assessment, levels of anxiety and depression were evaluated by State-Trait Anxiety Inventory, Beck's Depression Inventory, and Hamilton Rating Scales For Anxiety and Depression. Heart rate, electrodermal response (EDR), and electromyographic activity (EMG) were measured by biofeedback system, and systolic and diastolic blood pressure by automated vital sign monitor during baseline, task, and rest periods. We utilized script-driven imagery technique as a stressful task. The patients listened to the script describing their own traffic accident experience and were instructed to imagine the event during the task period. Statistically analytic data were obtained from the differences of psychological and psychophysiologic data between two groups. Results: The memory group did not show significantly higher EDR than the none memory group, but showed higher tendency during baseline, imagery, and rest periods. The memory group showed significantly lower EMG than the none memory group during rest period. However, there were no differences in other psychophysiologic reponses between the two groups. Conclusion: Our results showed that the memory group had higher tendency in autonomic arousal level such as electrodermal response than the none memory group. We suggest that physicians need to minimize repetitive imagery of traffic accident (reexperience), and decrease the autonomic hyperarousal in the treatment of traffic accident-related patients.

• The Journal of the Korea Contents Association
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• v.11 no.7
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• pp.100-109
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• 2011

This thesis is a content analysis on whether the proportion of structural element and theme association of television news imagery is different, depending on the historical background, and on what it means, which can be the index of scene-based and realistic report. Most researches of television news are horizontal studies of the same period, making light of vertical studies reflecting the change of age. Therefore, This study analyzed 729 items composed of 11,945 shots extracted from MBC Newsdesk from 1987, to 2007, the samples of which were extracted by systematic random sampling with five years' interval. This content analysis found out that there was high proportion of scene-based and realistic report such as 'sound-bite', 'event footage', 'direct matching' in the year 1987, 2007, and high proportion of 'corroboration shot', 'file footage', 'indirect reference', 'literal matching only' in the year 1997, which revealed the fact that reality-based report had not been faithfully accomplished in 1997.

• Korean Journal of Cognitive Science
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• v.21 no.2
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• pp.309-338
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• 2010

In this paper, we studied the brain-computer interface (BCI). BCIs help severely disabled people to control external devices by analyzing their brain signals evoked from motor imageries. The findings in the field of neurophysiology revealed that the power of $\beta$(14-26 Hz) and $\mu$(8-12 Hz) rhythms decreases or increases in synchrony of the underlying neuronal populations in the sensorymotor cortex when people imagine the movement of their body parts. These are called Event-Related Desynchronization / Synchronization (ERD/ERS), respectively. We implemented a BCI-based mouse interface system which enabled subjects to control a computer mouse cursor into four different directions (e.g., up, down, left, and right) by analyzing brain signal patterns online. Tongue, foot, left-hand, and right-hand motor imageries were utilized to stimulate a human brain. We used a non-invasive EEG which records brain's spontaneous electrical activity over a short period of time by placing electrodes on the scalp. Because of the nature of the EEG signals, i.e., low amplitude and vulnerability to artifacts and noise, it is hard to analyze and classify brain signals measured by EEG directly. In order to overcome these obstacles, we applied statistical machine-learning techniques. We could achieve high performance in the classification of four motor imageries by employing Common Spatial Pattern (CSP) and Linear Discriminant Analysis (LDA) which transformed input EEG signals into a new coordinate system making the variances among different motor imagery signals maximized for easy classification. From the inspection of the topographies of the results, we could also confirm ERD/ERS appeared at different brain areas for different motor imageries showing the correspondence with the anatomical and neurophysiological knowledge.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.5
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• pp.197-206
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• 2014

Motor imagery based Brain-computer Interface(BCI), which has recently attracted attention, is the technique for decoding the user's voluntary motor intention using Electroencephalography(EEG). For classifying the motor imagery, event-related desynchronization(ERD), which is the phenomenon of EEG voltage drop at sensorimotor area in ${\mu}$-band(8-13Hz), has been generally used but this method are not free from the performance degradation of the BCI system because EEG has low spatial resolution and shows different ERD-appearing band according to users. Common spatial pattern(CSP) was proposed to solve the low spatial resolution problem but it has a disadvantage of being very sensitive to frequency-band selection. Discriminative filter bank common spatial pattern(DFBCSP) tried to solve the frequency-band selection problem by using the Fisher ratio of the averaged EEG signal power and establishing discriminative filter bank(DFB) which only includes the feature frequency-band. However, we found that DFB might not include the proper filters showing the spatial pattern of ERD. To solve this problem, we apply a band-selection process using CSP feature vectors and linear discriminant analysis to DFBCSP instead of the averaged EEG signal power. The filter selection results and the classification accuracies of the existing and the proposed methods show that the CSP feature is more effective than signal power feature.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.11
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• pp.1115-1121
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• 2009

For HRI (Human-Robot Interaction) in daily life, robots need to recognize non-rigid objects such as clothes and blankets. However, the recognition of non-rigid objects is challenging because of the variation of the shapes according to the places and laying manners. In this paper, the cognition of non-rigid object based on a cognitive system is presented. The characteristics of non-rigid objects are analysed in the view of HRI and referred to design a framework for the cognition of them. We adopt a linguistic cognitive system for describing all of the events happened to robots. When an event related to the non-rigid objects is occurred, the cognitive system describes the event into a sentential form and stores it at a sentential memory, and depicts the objects with a spatial model for being used as references. The cognitive system parses each sentence syntactically and semantically, in which the nouns meaning objects are connected to their models. For answering the questions of humans, sentences are retrieved by searching temporal information in the sentential memory and by spatial reasoning in a schematic imagery. Experiments show the feasibility of the cognitive system for cognizing non-rigid objects in HRI.