• Journal of Convergence for Information Technology
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• v.11 no.10
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• pp.10-19
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• 2021

In this paper, we tried to derive characteristic parameters that reflect mental fatigue through EEG measurement and analysis. For this purpose, mental fatigue was induced through a resting state with eyes closed and performing subtraction operations in mental arithmetic for 30 minutes. Five subjects participated in the experiment, and all subjects were right-handed male students in university, with an average age of 25.5 years. Spectral analysis was performed on the EEG collected at the beginning and the end of the experiment to derive feature parameters reflecting mental fatigue. As a result of the analysis, the absolute power of the alpha band in the occipital lobe and the temporal lobe increased as the mental fatigue increased, while the relative power decreased. Also, the difference in power between resting state and task state showed that the relative power was larger than the absolute power. These results indicate that alpha relative power in the occipital lobe and temporal lobe is a feature parameter reflecting mental fatigue. The results of this study can be utilized as feature parameters for the development of an automated system for mental fatigue determination such as fatigue and drowsiness while driving.

• Journal of Digital Convergence
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• v.19 no.10
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• pp.295-301
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• 2021

Individual mental fatigue not only reduces cognitive ability and work performance, but also becomes a major factor in large and small accidents occurring in daily life. In this paper, a CNN model for EEG-based mental fatigue discrimination was proposed. To this end, EEG in the resting state and task state were collected and applied to the proposed CNN model, and then the model performance was analyzed. All subjects who participated in the experiment were right-handed male students attending university, with and average age of 25.5 years. Spectral analysis was performed on the measured EEG in each state, and the performance of the CNN model was compared and analyzed using the raw EEG, absolute power, and relative power as input data of the CNN model. As a result, the relative power of the occipital lobe position in the alpha band showed the best performance. The model accuracy is 85.6% for training data, 78.5% for validation, and 95.7% for test data. The proposed model can be applied to the development of an automated system for mental fatigue detection.

• Journal of Korean Society of Transportation
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• v.20 no.2
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• pp.17-26
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• 2002

Driver's psychophysiological load is one of the key measures for evaluating the safety of the highway. The purpose of this study is to propose and to test the methodology of evaluating the length limit of tangent section using driver's psychophysiological load. Driver's psychophysiological data is represented by the data acquire by frontal and occipital lobe. In order to compare the differences between tangent segments and the orders, real road driving experiments were performed. We collected psychophysiological data during the operation of vehicles. The experimental data were analyzed using FFT (Fast Fourier Transform) and relative power spectrum tools. These routine produces the beta value which is a major factor in consideration of driver's condition. The results in this study are summarized as follows: (1) A new methodology of evaluating the length limit in tangent section of highway using driver's psychophysiological load was proposed. (2) It was observed that driver's work load at tangent section was three times lower than that at the other section types. The beta value at tangent section is 2.219, while that at general section is 0.821. (3) It was observed that the driver's work load was significantly dropped to 0.428 after the continuous driving of 4.2km tangent section. (4) Based on the experimental subjects(from 27 Years to 31). we suggest that 30 times of design speed(3.0 km) could be acceptable as the length limit of tangent section in highway rather than the Previous limit which is 20 times of design speed(2.0km).

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.4
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• pp.773-778
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• 2020

In this paper, we analyzed the effects of musical stimuli on humans in performing mathematical tasks through EEG measurements. The musical stimuli were divided into preferred music and non-preferred music, and mathematical tasks were divided into memorization task and procedure task. The data measured in the EEG experiments was divided into frequency bands of Theta, SMR, and Mid-beta because of the concentration. In our results, preferred music causes more positive emotional response than no music and non-preferred music regardless of the type of mathematical task.

• Proceedings of the Korean Vacuum Society Conference
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• 2010.02a
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• pp.315-315
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• 2010

결정질 실리콘을 포함하는 태양전지의 광전효율은 표면에 입사되는 태양광의 반사를 제외하면 흡수된 광자에 의해 생성되는 전자-정공쌍의 상대적인 비율인 내부양자효율에 의존하게 된다. 실제 생성된 전자-정공쌍은 기판재료의 결정상태와 전기광학적 물성 등에 의해 일부가 재결합되어 2차적인 광자의 생성이나 열로서 작용하고 최종적으로 전자와 정공이 완전히 분리되고 전극에 포집되어 실질적인 유효전류로 작용한다. 16% 이상의 고효율 결정질 실리콘 태양전지양산이 요구되고 있는 현실에서 광전효율 개선 위해 가장 우선적으로 고려되어야 할 변수는 입력 태양광스펙트럼에 대한 결정질 실리콘 표면반사율을 최소화하여 광흡수를 극대화하는 것이라 할 수 있다. 이의 해결을 위하여 대기와 실리콘표면 사이의 굴절률차이가 크면 클수록 태양광스펙트럼에 대한 결정질 실리콘의 광반사는 증가하기 때문에 상대적으로 낮은 굴절률의 $SiO_x$나 $SiN_x$와 같은 반사방지막을 광입력 실리콘표면에 증착하여 광반사율 저감공정을 적용하고 있다. 이와 더불어 결정질 실리콘표면을 화학적으로 혹은 플라즈마이온으로 50-100nm 직경의 바늘형 피라미드형상으로 texturing 함으로 광자들의 다중반사 등에 기인하는 광흡수율의 증가를 기대할 수 있기 때문에 태양전지효율 개선에 긍정적인 영향을 미치는 것으로 이해된다. 본 실험에서도 고효율 다결정 실리콘 태양전지 양산공정에 적용 가능한 ICP-RIE기반 결정질 실리콘표면에 대한 texturing 공정기술을 연구하였다. Double Langmuir 플라즈마 진단시스템(DLP2000)을 적용하여 사용한 $SF_6$와 $O_2$ 개스유량과 챔버압력, 플라즈마 파워에 따른 이온밀도, 전자온도, 포화이온전류밀도, 플라즈마포텐셜의 공간분포를 모니터링하였고 texturing이 완료된 시료에 대하여 A1.5G 표준태양광스펙트럼의 300-1100nm 파장대역에서 반사율을 측정하여 그 변화를 관찰하였다. 본 연구에서 얻어진 결과를 간략히 정리하면 Si texturing에 가장 적합한 플라즈마파워는 100W, $SF_6/O_2$ 혼합비는 18:22, 챔버압력은 30mtorr 등이고 이에 상응하는 플라즈마의 이온밀도는 $2{\sim}3{\times}10^8\;ions/cm^3$, 전자온도는 14~15eV, 포화전류밀도는 $0.014{\sim}0.015mA/cm^2$, 플라즈마포텐셜은 38~39V 범위 등이었다. 현재까지 얻어진 최소 평균반사율은 14.2% 였으며 최적의 texturing패턴 플라즈마공정 조건은 이온에 의한 Si표면원자들의 스퍼터링과 화학반응에 의한 증착이 교차하는 플라즈마 에너지 및 밀도 상태인 것으로 해석된다.

• Sleep Medicine and Psychophysiology
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• v.10 no.1
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• pp.52-60
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• 2003

Objectives: Stage 1 sleep provides important information regarding interpretation of nocturnal polysomnography, particularly sleep onset. It is a short transition period from wakeful consciousness to sleep. The lack of prominent sleep events characterizing stage 1 sleep is a major obstacle in automatic sleep stage scoring. In this study, utilization of simultaneous EEG and EOG processing and analyses to detect stage 1 sleep automatically were attempted. Methods: Relative powers of the alpha waves and the theta waves were calculated from spectral estimation. A relative power of alpha waves less than 50% or relative power of theta waves more than 23% was regarded as stage 1 sleep. SEM(slow eye movement) was defined as the duration of both-eye movement ranging from 1.5 to 4 seconds, and was also regarded as stage 1 sleep. If one of these three criteria was met, the epoch was regarded as stage 1 sleep. Results were compared to the manual rating results done by two polysomnography experts. Results: A total of 169 epochs were analyzed. The agreement rate for stage 1 sleep between automatic detection and manual scoring was 79.3% and Cohen’s Kappa was 0.586 (p<0.01). A significant portion (32%) of automatically detected stage 1 sleep included SEM. Conclusion: Generally, digitally-scored sleep staging shows accuracy up to 70%. Considering potential difficulty in stage 1 sleep scoring, accuracy of 79.3% in this study seems to be strong enough. Simultaneous analysis of EOG differentiates this study from previous ones which mainly depended on EEG analysis. The issue of close relationship between SEM and stage 1 sleep raised by Kinnari remains a valid one in this study.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.1
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• pp.89-94
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• 2021

In this paper, we presented the results of analysis with data obtained through EEG measurements to confirm the effect of musical stimulus when performing mathematical tasks. While the subject was solving a mathematical task, favorite and unfavorite music classified according to the subject's preference were presented as musical stimulus and the tasks were divided into memorization task and procedure task. The data measured in the EEG experiments was divided into theta waves, SMR waves and mid-beta waves which are the frequency bands related to concentration to compare the relative power spectrum values. In our results, in the case of comparing no music with favorite music and no music with unfavorite music, a significant difference was observed in the several channels, and the average difference was shown in the channels F3 and F4 of the frontal lobe. In that channels, the power was found to be greater when the music was presented than the case where there was no music. Depending on the subject's preference, it was confirmed that favorite music showed greater brain activity than unfavorite music.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.21 no.1
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• pp.83-90
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• 2008

A vibration-based monitoring system is newly proposed to predict the loss of prestress forces in prestressed concrete (PSC) girder bridges. Firstly, a global damage alarming algorithm is newly proposed to monitor the occurrence of prestress-loss by using the change in frequency responses. Secondly, a prestress-loss prediction algorithm is selected to estimate the extent of prestress-loss by using the change in natural frequencies. Finally, the feasibility of the proposed system is experimentally evaluated on a scaled PSC girder model for which acceleration responses were measured for several damage scenarios of prestress-loss.

• The Korean Journal of Petroleum Geology
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• v.13 no.1
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• pp.17-23
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• 2007

Gravity characteristics are investigated in the vicinity of the DASAN scientific station, located at the Svalbard Archipelago, the Arctic using ArcGP data. Boundary effects of free-air gravity anomalies, which appeared generally at the continental margin, are erased after Bouguer correction was applied. Complete Bouguer anomalies produced after terrain correction by GrOPO30 show that gravity anomalies increase from continent to marine. This phenomena seem to be related to the rise of Moho discontinuity. The cut-off frequency of 0.16 was decided after power spectrum analysis and the gravity anomalies were divided into two parts. Residual anomalies in high frequency part show that characteristics of high values along the faults and of low values related to thick sediments in the continent. Characteristic is low values from basement subsidence of continental slope or thick sediments in the marine. The undulation of Moho discontinuity from 3-D inversion modeling show typical characteristics of continental margin that become higher from Svalbard archipelago to Knipovich ridge bordering Eurasian plate.

• 한국지구물리탐사학회:학술대회논문집
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• 2005.05a
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• pp.255-260
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• 2005

A Gravity characteristic of Svalbard archipelago in Arctic was studied by using ArcGP data. There are situated the Dasan science station. After bouguer correction, an edge effect of free-air anomaly, which is similar to topography, are not shown at passive continent margin, and after terrain correction with GTOPO30 data, gravity anomaly increases from continent to marine. that is deep connected with rise of Moho discontinuity. The correlation of topography and free-air anomaly shows that the isostasy of continent attains a little less than marine. After filtering, the residual anomaly are shown high and low anomalies related to fracture zone in continent and base depression or thick sedimentary layer in continental slope, marine.