• Journal of Korean Society for Atmospheric Environment
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• 제10권E호
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• pp.343-356
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• 1994

In this study, a statistical investigation was carried out for the evaluation of any relationship between polycyclic aromatic hydrocarbons (PAHss) associated with ambient aerosols and other air quality parameters under varying meteorological conditions. Daily measurements for PAHs and air quality/meteorological parameters were selected from a data-base constructed by a comprehensive air monitoring in London during 1985-1987. Correlation coefficients were calculated to examine any significant relationship between the PAHs and other individual variables. Statistical analysis was further Performed for the air quality/meteorological data set using a principal component analysis to derive important factors inherent in the interactions among the variables. A total of six components were identified, representing vehicle emission, photochemical activity/volatilization, space heating, atmospheric humidity, atmospheric stability, and wet deposition. It was found from a stepwise multiple regression analysis that the vehicle emission component is overall the most important factor contributing to the variability of PAHs concentrations at the monitoring site. The photochemical activity/volatilzation component appeared to be also an important factor particularly for the lower molecular weight PAHs. In general, the space heating component was found to be next important factor, while the contributions of other three components to the variance of each PAHs did not appear to be as much important as the first three components in most cases. However, a consistency for these components in their negative correlations with PAHs data was found, indicating their roles in the depletion of PAHs concentrations in the urban atmosphere.

• The Plant Pathology Journal
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• 제32권2호
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• pp.123-135
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• 2016

U.S. cotton production is suffering from the yield loss caused by the reniform nematode (RN), Rotylenchulus reniformis. Management of this devastating pest is of utmost importance because, no upland cotton cultivar exhibits adequate resistance to RN. Nine populations of RN from distinct regions in Alabama and one population from Mississippi were studied and thirteen morphometric features were measured on 20 male and 20 female nematodes from each population. Highly correlated variables (positive) in female and male RN morphometric parameters were observed for body length (L) and distance of vulva from the lip region (V) (r = 0.7) and tail length (TL) and c' (r = 0.8), respectively. The first and second principal components for the female and male populations showed distinct clustering into three groups. These results show pattern of sub-groups within the RN populations in Alabama. A one-way ANOVA on female and male RN populations showed significant differences ($p{\leq}0.05$) among the variables. Multiple sequence alignment (MSA) of 18S rRNA sequences (421) showed lengths of 653 bp. Sites within the aligned sequences were conserved (53%), parsimony-informative (17%), singletons (28%), and indels (2%), respectively. Neighbor-Joining analysis showed intra and inter-nematodal variations within the populations as clone sequences from different nematodes irrespective of the sex of nematode isolate clustered together. Morphologically, the three groups (I, II and III) could not be distinctly associated with the molecular data from the 18S rRNA sequences. The three groups may be identified as being non-geographically contiguous.

• Journal of Biosystems Engineering
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• 제39권4호
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• pp.377-388
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• 2014

Purpose: Determining the spatial structure of data is important in understanding within-field variability for site-specific crop management. An understanding of the spatial structures present in the data may help illuminate interrelationships that are important in subsequent explanatory analyses, especially when site variables are correlated or are a combined response to multiple causative factors. Methods: In this study, correlation, principal component analysis, and single and nested variogram models were applied to soil electrical conductivity and chemical property data of two fields in central Missouri, USA. Results: Some variables that were highly correlated, or were strongly expressed in the same principal component, exhibited similar spatial ranges when fitted with a single variogram model. However, single variogram results were dependent on the active lag distance used, with short distances (30 m) required to fit short-range variability. Longer active lag distances only revealed long-range spatial components. Nested models generally yielded a better fit than single models for sensor-based conductivity data, where multiple scales of spatial structure were apparent. Gaussian-spherical nested models fit well to the data at both short (30 m) and long (300 m) active lag distances, generally capturing both short-range and long-range spatial components. As soil conductivity relates strongly to profile texture, we hypothesize that the short-range components may relate to the scale of erosion processes, while the long-range components are indicative of the scale of landscape morphology. Conclusion: In this study, we investigated the effect of changing active lag distance on the calculation of the range parameter. Future work investigating scale effects on other variogram parameters, including nugget and sill variances, may lead to better model selection and interpretation. Once this is achieved, separation of nested spatial components by factorial kriging may help to better define the correlations existing between spatial datasets.

• 제어로봇시스템학회논문지
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• 제9권2호
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• pp.159-167
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• 2003

This study suggests the hybrid fault diagnosis method of signed digraph (SDG) and partial least squares (PLS). SDG offers a simple and graphical representation for the causal relationships between process variables. The proposed method is based on SDG to utilize the advantage that the model building needs less information than other methods and can be performed automatically. PLS model is built on local cause-effect relationships of each variable in SDG. In addition to the current values of cause variables, the past values of cause and effect variables are inputted to PLS model to represent the Process armies. The measured value and predicted one by dynamic PLS are compared to diagnose the fault. The diagnosis example of CSTR shows the proposed method improves diagnosis resolution and facilitates diagnosis of masked multiple-fault.

• 대한화학회지
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• 제31권6호
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• pp.567-575
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• 1987

한국산 고대유리 시료 45종을 입수하여 그속에 함유된 19종의 원소(Ag, As, Br, Ce, Co, Cr, Eu, Fe, Hf, K, La, Lu, Na, Ru, Sb, Sc, Sm, Th, Zn)는 중성자방사화분석에 의하고, Pb는 원자흡수분광분석법에 의해 각각 정량하였다. 이들 20종 원소의 분석데이타를 사용하여 원소 상호간의 상관관계를 상관메트릭스법으로 검토하였다. 그리고 주성분분석법으로 각 시료의 농도분포를 평면에 나타내었으며, 측정된 제조년대 및 발굴위치가 같은 시료가 모이면 이들 시료를 SIMCA를 위한 참조시료로 삼았다. 이들 참조시료 및 시험시료를 SIMCA에 의해 분류하였더니 참조시료 전부와 시험시료중 3종이 주성분분석법에 의한 분류결과와 일치하였다.

• 한국항해항만학회지
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• 제30권1호
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• pp.35-43
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• 2006

본 연구는 교통안전공단과 사단법인 녹색교통운동이 공동으로 개발한 교통문화지수와 관련한 2002년과 2003년의 전국 81개 도시 자료를 토대로 통계적 분석을 행하여 이들 대상도시들을 유형화하고, 집단별 영향요인에 근거하여 교통사고 예방대책들을 제시하고자 하였다. 먼저 교통문화지수와 영향요인들에 대한 주성분분석 결과로는 4개의 주성분으로 구분 지울 수 있었으며, 도시 특성별 최적 집단 수는 4개가 적합한 것으로 나타났다. 또한 이들 유형화된 집단별 교통문화지수에의 영향요인을 단계별 다중 회귀분석법을 이용하여 분석한 결과, 4개 집단 모두 높은 설명력을 갖는 회귀모형을 구축할 수 있었다. 이에 따라 각 집단별 교통사고 예방대책들을 구체적으로 제시할 수 있었으며, 아울러 투자된 시설이 얼마나 교통사고 예방에 효과적이었는가를 분석할 필요성이 있음을 향후의 연구 과제로 제시하였다.

• 대한원격탐사학회지
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• 제15권2호
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• pp.91-105
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• 1999

최근 다중 지질정보의 통합적 해석은 GIS의 중요한 응용 분야중 하나로 인식되고 있다. 공간통합을 위하여 지구통계학적 방법들이 개발되어 있지만, 통합결과와 입력 주제도들 사이의 관계에 대한 통계적, 정량적 분석방법론의 개발은 아직까지 체계적으로 정립되어 있지 못한 상황이다. 본 연구에서는 지질도, 지화학자료, 항공지구물리자료, 지형자료 및 원격탐사 영상등 다양한 지질정보등이 보고된 옥동지역을 대상으로 하여 광물 부존 예상도 작성 사례연구를 수행하여 기존에 이용되고 있는 여러 공간 통합 방법중 확실인자 (Certainty Factor: CF) 추정방법과 다변량 통계 분석방법중 하나인 주성분분석을 시험적인 통합방법으로 우선적으로 적용한 뒤, 입력 자료와 통합결과에 대한 정량적인 통계량 정보를 추출하고자 하였다. 입력 주제도와 통합 결과사이의 관계 규명에는 통계 분할표를 이용한 통계처리를 편의 분석에는 잭나이프 방법을 적용하였다. 통합정보에 대한 통계량 분석을 통하여, 통합 결과와 입력자료 사이의 정량적 관계를 추출할 수 있었으며, 부가적으로 입력자료의 상태수준에 대한 판단정보를 얻을 수 있었다. 이러한 결과는 GIS 관점에서 통합결과 해석에 중요한 결정보조자료로 활용될 수 있으며, 복잡한 다중정보를 다루는데 공간 통합문제에서도 입력정보 검증을 위한 일반적일 처리과정으로도 발전할 수 있을 것으로 생각된다.

• 한국정보통신학회논문지
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• 제19권12호
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• pp.2792-2799
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• 2015

본 논문에서는 화자 인식의 성능을 개선하기 위해서 glottal flow로부터 source mel-frequency cepstral coefficient (SMFCC), 왜도, 첨도를 추출하여 활용하였다. 일반적으로 glottal flow의 고주파 대역은 응답의 크기가 평탄하므로 미리 정한 차단주파수 미만에 대해서만 SMFCC를 추출한다. 추출된 SMFCC, 왜도, 첨도는 종래의 특징 파라미터와 결합된 후 종래의 화자인식 시스템과 동등한 조건에서의 성능 비교를 위하여 principal component analysis (PCA) 및 linear discriminiat analysis (LDA)를 통한 차원축소가 행해진다. 대용량의 화자인식 실험결과를 통해서 제안된 인식 시스템이 종래의 화자인식 시스템 보다 더 좋은 성능을 나타냄을 확인할 수 있었으며, 특히 가우시안 혼합이 낮을 때 더 높은 성능향상을 나타내었다.

• Journal of Electrical Engineering and Technology
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• 제13권4호
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• pp.1614-1622
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• 2018

The research related to fault diagnosis in permanent magnet synchronous motors (PMSMs) has attracted considerable attention in recent years because various faults such as permanent magnet demagnetization and short-circuited turns can occur and result in unexpected failure of motor related system. Several conventional current and back electromotive force (BEMF) analysis techniques were proposed to detect certain faults in PMSMs; however, they generally deal with a single fault only. On the contrary, cases of multiple faults are common in PMSMs. We propose a fault diagnosis method for PMSMs with single and multiple combined faults. Our method uses three phase BEMF voltages based on the fast Fourier transform (FFT), support vector machine(SVM), and visualization tools for identifying fault types and severities in PMSMs. Principal component analysis (PCA) and t-distributed stochastic neighbor embedding (t-SNE) are used to visualize the high-dimensional data into two-dimensional space. Experimental results show good visualization performance and high classification accuracy to identify fault types and severities for single and multiple faults in PMSMs.

• 농촌계획
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• 제15권3호
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• pp.23-32
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• 2009

The purpose of this research was to evaluate rural housing environment through evaluation of the two parties, public officials, the interest group and residents, the beneficiaries surveying general understanding and measuring difference in understanding between public officials and residents. Through the difference in understanding, this study was to propose effective promotion method and desirable direction of rural housing environment. For progress hereafter, by seeking active involvement of residents, this study proposed possible renewal plan of residential environment. Process of this study was first, research documents to examine several rural housing environment related promotions, and several analysis techniques like principal component analysis, multiple regression analysis used to understand different ideas Opinion of Public Officials and Inhabitants. Then take surveys of residents living in renewal zone, and surveys of public officials of borough, which already performed renewal projects to evaluate comprehensively as either residents' or administrators' view.