• 자원환경지질
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• 제54권3호
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• pp.353-364
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• 2021

국내 지질학의 연구 분야는 20세기 중반 이후부터 꾸준하게 발전되어왔다. 학술지 "자원환경지질"은 국내 지질학을 대표하는 역사가 긴 학술지로 지질학을 바탕으로 하는 융복합연구 논문이 게재되고 있다. 본 연구는 학술지 "자원환경지질"에 게재된 논문을 대상으로 문헌 고찰(literature review)을 수행하여 지질학의 역사와 발전에 대해 논의하고자 한다. 1968년부터 2020년까지 총 2,571편의 논문 제목, 주제어, 다국어 초록을 수집하였으며, Latent Dirichlet Allocation (LDA) 기반 토픽모델링을 실시하여 연구 주제를 분류하고 연구 동향과 주제간 연관성을 확인하였다. 학술지 "자원환경지질"은 총 8개의 연구주제('암석학 및 지구화학', '수문학 및 수리지질학', '광상학', '화산학', '토양오염 및 복원학', '기초지질 및 구조지질학', '지구물리 및 물리탐사', '점토광물')로 분류할 수 있었다. 1994년 이전에는 '광상학', '화산학', '기초지질 및 구조지질학'의 연구주제들이 활발하게 연구되었으며, 이후 '수문학 및 수리지질학', '토양오염 및 복원학', '지구물리 및 물리탐사', '점토광물'의 연구주제들이 성행하였다. 연관성분석(network analysis)결과, 학술지 "자원환경지질"은 '광상학'을 기반으로 융복합적 연구 논문들이 게재되었다는 것을 확인하였다. 본 연구의 결과는 지질학을 다루는 연구자들에게 문헌 고찰의 새로운 방법론을 제시하여 지질학의 역사에 대한 이해를 제공했음에 의의가 있다.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제15권4호
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• pp.277-282
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• 2015

Braincomputer interface (BCI) technology is making advances in the field of humancomputer interaction (HCI). To improve the BCI technology, we study the changes in the electroencephalogram (EEG) signals for six levels of grip strength: 10%, 20%, 40%, 50%, 70%, and 80% of the maximum voluntary contraction (MVC). The measured EEG data are categorized into three classes: Weak, Medium, and Strong. Features are then extracted using power spectrum analysis and multiclass-common spatial pattern (multiclass-CSP). Feature datasets are classified using a support vector machine (SVM). The accuracy rate is higher for the Strong class than the other classes.

• 한국멀티미디어학회논문지
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• 제21권2호
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• pp.166-172
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• 2018

The distraction of the driver's attention causes as much traffic accidents as drowsiness driving. Yet though there have been many studies on drowsiness driving, research on distraction driving is insufficient. In this paper, we divide distraction of attention into visual distraction and cognitive distraction and analyze the EEG of subjects while viewing images of distracting situations. The results show that more information is received and processed when distractions occur. It is confirmed that the probability of accident increases when the driver receives overwhelming amount of information that he or she cannot concentrate on driving.

• 한국멀티미디어학회논문지
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• 제22권12호
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• pp.1491-1499
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• 2019

Insufficient sleep time and bad sleep quality causes many illnesses and it's research became more and more important. The most common method for measuring sleep quality is the polysomnography(PSG). The PSG is a test used to diagnose sleep disorders. The most common PSG data is obtained from the examiner, which attaches several sensors on a body and takes sleep overnight. However, most of the sleep stage classification in PSG are low accuracy of the classification. In this paper, we have studied algorithm for sleep level classification based on machine learning which can replace PSG. EEG, EOG, and EMG channel signals are studied and tested by using CNN algorithm. In order to compensate the performance, a mixed model using both CNN and DNN models is designed and tested for performance.

• 한국멀티미디어학회논문지
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• 제20권12호
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• pp.1856-1864
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• 2017

The ultimate goal of multimedia in bio-signal research is to approach multimedia contents through bio-signal. Hence it is important to interpret user's emotions by analyzing his or her bio-signals. In this paper, we construct ERP task of oddball component to analyze EEG signal between normal stimuli and fear stimuli and measure EEG during ERP task. The results from extracted ERP component show that there is a difference in N200 in visual stimuli, P300 in auditory stimuli, and N100 and P300. Moreover, there are larger changes in audiovisual stimuli, indicating that users recognize greater fear of crime when visual and auditory stimuli are simultaneously presented.

• 대한의용생체공학회:학술대회논문집
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• 대한의용생체공학회 1989년도 춘계학술대회
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• pp.45-49
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• 1989

In this paper the feature of background EEG is extracted by LS Prony Method for the analysis of background EEG in the time domain. From the experimential results the alpha band amplitude is the largest among bands and beta band amplitude is larger than that of the delta band and theta band. The sustained time for the alpha band, the beta band, the delta band and the theta band is 2.3461(sec), 1.8980(sec), 0.3120(sec), 0.2930(sec) respectively. Consequently the alpha band and the beta band are maintained in the whole, segment. The delta band, the theta band are existed intermittently in the segment.

• 대한의용생체공학회:학술대회논문집
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• 대한의용생체공학회 1998년도 추계학술대회
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• pp.193-194
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• 1998

This paper describes a multi-functional EEG (electroencephalogram) software. The software manages the patient's EEG data systematically and analyzes the signal and display the parameters on a PC monitor in real-time. Since the software provides various parameters simultaneously, user can observe patients multilaterally. Reference patterns of CSA and DSA can be captured and displayed on top of the monitor. And user can mark events of surgical operation or patient's conditions, so it is possible to jump to the points of events directly, when reviewing the recorded file afterwards. Many convenient functions are equipped and these are operated by mouse clicks.

• 한국감성과학회:학술대회논문집
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• 한국감성과학회 2000년도 추계학술대회 논문집
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• pp.44-47
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• 2000

본 연구에서는 향이 인간에 미치는 영향을 EEG의 시계열 분석을 통해 알아보았다. 피험자는 20대 초반의 후각자애가 없는 30명(남녀 각각 15명)을 대상으로 하여, 국제 기준 전극법을 사용하여 Fz과 Cz에서 뇌파를 기록하였다. 100%의 Rose oil Bulgarian, Lemon oil Mistitano, Jasmine abs, Lavender oil France, Peppermint oil을 실험 시약으로 사용하였다. 각 향 자극에 대하여 1분 동안의 측정을 10초 간격으로 구분하여 $\alpha/(\alpha+\beta)$ 비와 $\beta/(\alpha+\beta)$ 대역의 비를 비교 분석하였다. 30초까지는 안정과 향 자극간의 차이가 증대되는 성향을 보였으나 50초부터는 감소되는 경향을 보였다. 본 연구를 통해 향간의 차이가 자극제시 후 30초 일 때 가장 큰 것으로 나타났다고 이 시간을 기준으로 각 향의 선호도를 분석하였다.

• 대한의용생체공학회:학술대회논문집
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• 대한의용생체공학회 1993년도 추계학술대회
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• pp.156-159
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• 1993

In this paper, computerized BEAM (brain electrical activity map) was implemented for objective and quantitative multichannel EEG analysis. BEAM is calculated by 4 point Interpolation method and number of elements are 5140. Representation methods of BEAH are two. One is dot density method which classify brain electrical potential 9 levels by dot density and the other is color method which classify brain electrical 12 levers by different colors. In this BEAM, instantaneous change and average energy distribution over any arbitrary time interval of brain electrical activity could be observed and analyzed easily.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1993년도 한국자동제어학술회의논문집(국제학술편); Seoul National University, Seoul; 20-22 Oct. 1993
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• pp.257-260
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• 1993

A new method of spindle waveform detection is presented for the automated analysis of sleep EEG. The method is based on the combined application of signal conditioning in the time-domain and local spectrum analyzing in the frequency-domain. The overall detection system is implemented and, tested in real-time with a total of 24 hour data obtained from four subjects. The result shows an average agreement of 86.7% with the visually inspected result.