• 대한교통학회지
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• 제23권8호
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• pp.101-111
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• 2005

대중교통의 서비스 개선은 접근성이 개선되어 대중교통 이용자의 수요를 늘리는 중요한 역할로 작용한다. 본 연구는 서울시가 최근 2004년 7월 대대적으로 실시한 대중교통체계 개편 후 지하철이용자의 접근성 변화를 설명하기 위한 것이다. 첫번째 연구목적은 공간상호작용 개념을 포함하는 한센형 접근성 지표를 지하철-버스간 환승할인 전후의 자료로부터 추정하고 비교 설명한다. 두번째 연구목적은 개편 전 후의 접근성 지표가 단기의 교통과 토지이용간의 관계를 설명하는 통행배분모형에 어떠한 역할을 하는지를 해석하는 것이다. 분석에 사용한 비접촉식 카드승차권과 접촉식 승차권 자료는 2004년 5월의 하루 평균 지하철 기종점자료와 서비스 변화가 발생한 2004년 8-9월의 하루 평균 지하철 기종점자료이다. 결론적으로 비접촉식 카드 이용자의 접근성이 향상되어 대중교통개편의 수혜자가 된 것으로 나타났으며, 그 효과는 서울지역에 넓게 분포된 것으로 나타났다. 통행배분모형연구에서 접근성 지표의 역할은 중요한 것으로 나타났으며, 기존 모형에서 접근성 지표의 변수가 생략되면, 추정된 모형의 파라메터 들이 편기(bias)된다는 것을 발견하였다. 그리고, 접근성 지표의 생략으로 인한 통행배정모형의 예측력 저하 원인을 규명하는 노력이 시도되었다.

• 한국환경복원기술학회지
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• 제6권3호
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• pp.46-55
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• 2003

This study aims to evaluate the Ulsan city residents' perception and satisfaction with open spaces and cityscape after consideration in the side of getting primary data for the city open spaces policy and Green Plan for Ulsan city. In this study, low data was gathered by questionnaires survey with stratified random sampling method. Questionnaires were designed by several sets of variables such as behavioral patterns, satisfactions for open spaces and user's demographic variables. Data were analyzed by descriptive statistics, cross-tabulation and regression analysis. The main results of this study can be summarized as follows : 1. In overage the residents were slightly satisfied with park open spaces. There were good and poor park open spaces. in the perceptions of citizens as follows : 'nearby mountain and open spaces', 'rail side green area' were high satisfactory, and 'riverside', 'green qualities' were low in satisfaction. 2. In overage the residents were slightly satisfied with cityscape. There were good and poor cityscape in the perceptions of citizens as follows : 'nearby forest in and open spaces', 'night scape of an urban center' were high satisfactory, and 'streetscape', 'appearances of high-rise buildings' were low in satisfaction. 3. As a results of regression analysis predictable variables for satisfaction with Park and Open spaces were : 'open spaces by the public', 'open spaces by neighbor', 'grande open spaces', 'open spaces of residence'. 4. As a results of regression analysis predictable variables for satisfaction with cityscape were : 'Central Business District(C.B.D) and nearby mountain and open spaces', 'residence and streetscape', 'riverside and park green open spaces'.

• 생물정신의학
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• 제12권1호
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• pp.68-72
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• 2005

Object:Nicotine dependence is the most common substance abuse disorder. One of the characteristics of nicotine dependence is craving. Regional activation of the brain induced by craving for nicotine was evaluated by using functional magnetic resonance imaging to investigate neuroanatomical site of smoking craving. Method:A smoker who satisfied DSM-IV criteria for nicotine dependence and a non smoker was studied. MRI data were acquired on a 1.5T Magnetom Vision Plus with a head volume coil. Two sets of visual stimuli were presented to subjects in a random manner. One was the film scenes of inducing smoking craving and the other was neutral stimuli not related to smoking. There were two fMRI sessions before and after smoking or sham smoking. Data were analyzed using SPM99. Results:fMRI showed significant activated area in anterior cingulate and medial frontal lobes in the smoker during smoking craving. Right dorsolateral prefrontal cortex and parietal lobes were activated in the control during visual stimulation before smoking. After smoking, there was no brain activation during visual stimulation in both of smoker and non smoker. Conclusion:Metabolic activity of the anterior cingulate and medial frontal lobes increased during craving for smoking. This result suggests that fMRI may be a valuable tool in the identification of neurobiological process of craving.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2005년도 Proceedings of ISRS 2005
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• pp.403-406
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• 2005

In order to evaluate the Capability of ETM+ remotely- sensed data to provide 'Forest-shrub land-Rangeland' cover type map in areas near the timberline of northern forests of Iran, the data were analyzed in a portion of nearly 790 ha located in Neka-Zalemroud region. First, ortho-rectification process was used to correct the geometric errors of the image, yielding 0/68 and 0/69 pixels of RMS. error in X and Y axis, respectively. The original and panchromatic bands were fused using PANSHARP Statistical module. The ground truth map was made using 1 ha field plots in a systematic-random sampling grid, and vegetative form of trees, shrubs and rangelands was recorded as a criteria to name the plots. A set of channels including original bands, NDVI and IR/R indices and first components of PCI from visible and infrared bands, was used for classification procedure. Pair-wise divergence through CHNSEL command was used, In order to evaluate the separability of classes and selection of optimal channels. Classification was performed using ML classifier, on both original and fused data sets. Showing the best results of $67\%$ of overall accuracy, and 0/43 of Kappa coefficient in original data set. Due to the results represented above, it's concluded that ETM+ data has an intermediate capability to fulfill the spectral variations of three form- based classes over the study area.

• 지질공학
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• 제21권3호
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• pp.247-257
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• 2011

본 연구는 사면재해 취약성 평가를 위해 사면모델 중 하나인 무한사면 해석모델을 적용하였다. 그러나 무한사면 해석모델은 광역적인 연구지역에 적용하는데 있어서 데이터획득 및 처리과정에 어려움이 있고 데이터 획득과정에서 불가피하게 불확실성이 개입되는 문제가 있다. 이러한 불확실성을 최소화하기 위해 확률론적 해석기법인 몬테카를로 시뮬레이션을 적용하였으며, 광역적인 연구지역에 무한사면 해석모델을 적용하기 위하여 GIS를 활용한 무한사면 안정해석법으로 파괴확률을 획득하였다. 연구지역으로는 사면재해가 집중적으로 발생한 보은지역을 선정하였고 사면의 기하학적인 특성과 점착력 및 내부마찰각 등의 강도정수를 획득하였다. 또한 불확실성의 효과를 평가하기 위해 강도정수의 변동계수를 10%에서 30%로 고려하였고 이러한 과정을 통하여 확률론적 해석기법은 자료의 불확실성을 감쇠시킬 수 있다는 결과를 도출하였다.

• International Journal of Contents
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• 제9권4호
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• pp.1-10
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• 2013

The electroencephalogram (EEG) time series is a measure of electrical activity received from multiple electrodes placed on the scalp of a human brain. It provides a direct measurement for characterizing the dynamic aspects of brain activities. These EEG signals are formed from a series of spatial and temporal data with multiple dimensions. Missing data could occur due to fault electrodes. These missing data can cause distortion, repudiation, and further, reduce the effectiveness of analyzing algorithms. Current methodologies for EEG analysis require a complete set of EEG data matrix as input. Therefore, an accurate and reliable imputation approach for missing values is necessary to avoid incomplete data sets for analyses and further improve the usage of performance techniques. This research proposes a new method to automatically recover random consecutive missing data from real world EEG data based on Linear Dynamical System. The proposed method aims to capture the optimal patterns based on two main characteristics in the coevolving EEG time series: namely, (i) dynamics via discovering temporal evolving behaviors, and (ii) correlations by identifying the relationships between multiple brain signals. From these exploits, the proposed method successfully identifies a few hidden variables and discovers their dynamics to impute missing values. The proposed method offers a robust and scalable approach with linear computation time over the size of sequences. A comparative study has been performed to assess the effectiveness of the proposed method against interpolation and missing values via Singular Value Decomposition (MSVD). The experimental simulations demonstrate that the proposed method provides better reconstruction performance up to 49% and 67% improvements over MSVD and interpolation approaches, respectively.

• Journal of Microbiology and Biotechnology
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• 제18권2호
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• pp.219-227
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• 2008

The free-living photoheterotrophic Gram-negative bacterium Rhodobacter sphaeroides possesses a quorum-sensing (QS) regulatory system mediated by CerR-CerI, a member of the LuxR-LuxI family. To identify the genes affected by the regulatory system, random lacZ fusions were generated in the genome of R. sphaeroides strain 2.4.1 using a promoter-trapping vector, pSG2. About 20,000 clones were screened and 23 showed a significantly different level of ${\beta}$-gal activities upon the addition of synthetic 7,8-cis-N-tetradecenoyl-homoserine lactone (RAI). Among these 23 clones, the clone showing the highest level of induction was selected for further study, where about a ten-fold increase of ${\beta}$-gal activity was exhibited in the presence of RAI and induction was shown to be required for cerR. In this clone, the lacZ reporter was inserted in a putative gene that exhibited a low homology with catD. A genetic analysis showed that the expression of the catD homolog was initiated from a promoter of another gene present upstream of the catD. This upstream gene showed a strong homology with luxR and hence was named qsrR (quorum-sensing regulation regulator). A comparison of the total protein expression profiles for the wild-type cells and qsrR-null mutant cells using two-dimensional gel electrophoresis and a MALDI-TOF analysis allowed the identification of sets of genes modulated by the luxR homolog.

• 산업경영시스템학회지
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• 제40권1호
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• pp.57-64
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• 2017

In order to reduce damages to major railroad components, which have the potential to cause interruptions to railroad services and safety accidents and to generate unnecessary maintenance costs, the development of rolling stock maintenance technology is switching from preventive maintenance based on the inspection period to predictive maintenance technology, led by advanced countries. Furthermore, to enhance trust in accordance with the speedup of system and reduce maintenances cost simultaneously, the demand for fault diagnosis and prognostic health management technology is increasing. The objective of this paper is to propose a highly reliable learning model using various machine learning algorithms that can be applied to critical rolling stock components. This paper presents a model for railway rolling stock component fault diagnosis and conducts a mechanical failure diagnosis of motor components by applying the machine learning technique in order to ensure efficient maintenance support along with a data preprocessing plan for component fault diagnosis. This paper first defines a failure diagnosis model for rolling stock components. Function-based algorithms ANFIS and SMO were used as machine learning techniques for generating the failure diagnosis model. Two tree-based algorithms, RadomForest and CART, were also employed. In order to evaluate the performance of the algorithms to be used for diagnosing failures in motors as a critical railroad component, an experiment was carried out on 2 data sets with different classes (includes 6 classes and 3 class levels). According to the results of the experiment, the random forest algorithm, a tree-based machine learning technique, showed the best performance.

• Spatial Information Research
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• 제21권5호
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• pp.15-22
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• 2013

본 연구는 동북아시아 지역의 이산화탄소 분포와 식생지수의 상관성 규명을 목적으로 한다. 이를 위해 지리가중치 분석기법을 활용하여 GOSAT 이산화탄소 측정자료와 MODIS 식생지수에 대해 다중공간회귀 분석을 시행하였다. 그 결과 이산화탄소와 식생지수 사이에는 전체적인 (-)의 상관관계가 나타나고 있음을 확인할 수 있었다. 공간적 자기상관성 측정을 위한 Global Morans'I지수와 Anselin Local Morans'I 통계 분석 결과에서는 이산화탄소는 일정한 군집성을 보이며 분포하고 있는 것으로 나타나났다. 이러한 결과는 산림파괴와 같은 개발 활동이 이산화탄소의 배출에 영향을 미쳐 일정한 군집을 형성하게 된 것으로 추정된다. 그러나 이산화탄소의 분포는 인위적 배출원과 식생의 호흡, 해양의 배출과 흡수 등의 다양한 요인과 결부되어 달라지기 때문에 이산화탄소 분포에 개입되는 다양한 변수와 상관성을 평가하는 후속연구가 필요할 것으로 사료된다.

• 천문학회지
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• 제29권spc1호
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• pp.151-154
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• 1996

We examine the observations of large-scale magnetic fields in the Universe. We begin at the largest scale with clusters of galaxies and work our way down through galaxies and finally to the Milky Way. on which we concentrate in detail. We examine the observations of the Galactic magnetic field, and their interpretation, under the philosophy that the Galactic magnetic field is like that in other spiral galaxies. We use pulsar data. diffuse Galactic synchrotron emission, and starlight polarization data to discuss the Galaxy's global magnetic configuration and the uniform ($B_u$), random ($B_r$), and total ($B_t$) components of the field strength. We find disagreement among conclusions derived from the various data sets and argue that the pulsar data are not the best indicator for large-scale Galactic field. Near the Solar circle, we find that the azimuthal average of $B_t$ is 4.2$\mu$G and we adopt $B_u\~$2.2 and $B_r\~3.6{\mu}G$. $B_t$ is higher in spiral arms, reaching $\~5.9{\mu}G$. $B_t$ is higher for smaller $R_{Gal}$, reaching $\~8.0{\mu}G$ for $R_{Gal}$ = 4.0 kpc. The pattern of field lines is not concentric circles but spirals. The inclination of the magnetic spiral may be smaller than that of the Galaxy's spiral arms if our sample, which refers primarily to the interarm region near the Sun, is representative. However, it is not inconceivable that the local field lines follow the Galaxy's spiral pattern, as is observed in external galaxies.