Ssanghee Seo

The Relation between Affective Style of Stressor on EEG Asymmetry and Stress Scale during Multimodal Task

In previous paper, we founded that the affective style of subjects according to an auditory stressor existed. Subjects in the stress group compared to other groups reported a higher level of stress on physiological stress scale. The aim of the current study was to investigate the relation between affective style and stress scale under various stress conditions. This experiment consisted of three sessions such as auditory, movie, and unknot task. We used woman scream, horror movie, and unknot stimuli to evoke stress. We classified the affective style according to task based on EEG asymmetry. The stress scale in stress group was greater than that of other groups for all tasks. Also, a subject who in stress group for specific stimulus was not always in stress group for other stimuli. These results demonstrate that the subjects with the propensity to negative affective style are apt to be stressed.

Brain Response to Good and Bad Design

This paper is about the decision of whether good or bad design is the result of the human brain process. Our research team has used the technique of functional MRI and Electroencephalogram (EEG) to address the question of how the brain answers while subjects viewed different designs. Classifying the good or bad designs, subjects chose a mouse button to decide their perception of good or bad design and we analyzed their patterns of EEG rhythms and fMRI. The results of fMRI showed that the perceptions of different feelings of designs are associated with the frontal lobe and the occipital lobe. After analyzing the EEG by the Event-related brain potentials (ERP) method, we also found that the amplitude of ERP components in perception of bad design is greater and latency is shorter than that of good design. Therefore, the human brain responds sooner and stronger in perception of bad feeling.

EEG Analysis of Frontal Lobe Activities by Decision Stimuli

The brain is processing various acts and thoughts of humans. Among the functions of the brain, decision making, reasoning and complex calculation are governed by the frontal lobe. If the FLA (Frontal Lobe Activity) is kept low for a long period of time, human reasoning and decision making are interrupted and anti-social behaviors can emerge which are hardly understandable in view of common people and it can result in serious problems. EEG (Electroencephalogram) was measured by using decision making stimuli which help determine the FLA and, with the index of the measured EEG data, the evoked conditions of subjects were compared and analyzed by utilizing EP (Evoked Potential) and Power Spectrum Analyzing. In the end, by the result of both methods, subjects with apparently low FLA index appeared, and, with the help of the obtained FLA index, critical values determining whether the FLA is in the normal range or not could be presented.

A performance analysis model of PC-based software router supporting IPv6-IPv4 translation for residential gateway

This paper presents a queuing analysis model of a PC-based software router supporting IPv6-IPv4 translation for residential gateway. The propose models are M/G/1/K or MMPP-2/G/1/K by arrival process of PC-based software router. In M/G/1/K, the arrival process is assumed to be Poisson process which is independent, identically distributed. In MMPP-2/G/1/K, The arrival process is assumed to be two-state Markov modulated Poisson process (MMPP). MMPP-2/G/1/K model is used to represent self-similar traffic. The service time distribution is arbitrary. The service discipline of server is processor sharing. The total number of packets that can be processed at one time is limited to K. We obtain PC-based software router performance metrics such as system sojourn time, blocking probability and throughput. The parameters are estimated by maximizing the log-like hood function of the measured average response time. The model has been validated through measurements. The performance metrics predicted by the model fit well to the experimental outcome.

The Effect of an Auditory Stressor, with Respect to Affective Style, on Frontal EEG Asymmetry and ERP Analysis

The aim of the current study was to investigate the effect of an auditory stressor, with respect to affective style, on frontal EEG asymmetry, ERP, and psychological stress. Twenty subjects were tested during the sound of a womans scream and the sound of birds. A greater negative N200 and positive P300 amplitude was exhibited for a womans scream compared with the sound of birds. A shorter N200 and P300 latency was exhibited. Also, a greater right frontal activity was found during a womans scream. Furthermore, the affective style of subjects according to an auditory stressor was found. Subjects in the stress group compared to other groups reported a higher level of stress on Cohens Perceived Stress Scale. These results demonstrate that a womans scream results in relatively greater right frontal activity and psychological stress and serves as an auditory stressor.

A Performance Analysis Model of PC-based Software Router Supporting IPv6-IPv4 Translation for Residential Gateway

This paper presents a queuing analysis model of a PC-based software router supporting IPv6-IPv4 translation for residential gateway. The propose models are M/G/1/K or MMPP-2/G/1/K by arrival process of PC-based software router. In M/G/1/K, the arrival process is assumed to be Poisson process which is independent, identically distributed. In MMPP-2/G/1/K, The arrival process is assumed to be two-state Markov modulated Poisson process (MMPP). MMPP-2/G/1/K model is used to represent self-similar traffic. The service time distribution is arbitrary. The service discipline of server is processor sharing. The total number of packets that can be processed at one time is limited to K. We obtain PC-based software router performance metrics such as system sojourn time, blocking probability and throughput. The parameters are estimated by maximizing the log-like hood function of the measured average response time. The model has been validated through measurements. The performance metrics predicted by the model fit well to the experimental outcome.