• 감성과학
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• 제7권4호
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• pp.57-65
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• 2004

본 논문에서는 color, texture, shape의 정보를 통합 이용하여 내용기반 영상검색 시스템의 성능을 향상시키는 기법을 고찰하였다. 먼저 영상에 내재되어 있는 color를 분석 추출하여 몇 개의 대표색으로 요약 표현한 다음, 이를 활용한 근사치 측정도를 고안하였다. Texture정보 분석에 있어서는 영상의 주축 행렬 데이터를 통계적 접근 방법으로 추출하였다. Edge분석의 방법으로는 Edge 막대그래프에서 색상변환, 양자화, 필터링에 관련된 정보를 선행처리 후 Edge 정보를 추출하였다. 마지막으로, 본 연구의 결과인 내용기반 영상검색 시스템의 효율성을 precision-recall 분석과 실험적 결과를 통하여 입증하였다.

• 대한전자공학회논문지TC
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• 제48권4호
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• pp.53-60
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• 2011

OFDM(Orthogonal Frequency Division Multiplexing) 시스템의 Rayleigh fading 에 대한 내구성을 증대시키기 위하여 채용되는 2 종류의 스마트안테나 즉 귀납적인 고유공간법에 기반한 FFT(Fast Fourier Transform) 전단 스마트안테나와 Wiener 해법에 기반한 FFT 후단 스마트안테나의 가중치벡터 갱신의 수학적 모델을 정의한 후 컴퓨터 모의실험에 의거, 그 성능들을 비교 분석하였다. 장치의 복잡성의 대가로 FFT 후단 스마트안테나의 성능이 훨씬 우수함이 보여졌고 특히 다중경로의 시간지연이 OFDM 가드타임을 벗어날 경우와 강한 동일채널 간섭신호가 존재할 경우의 FFT 후단 스마트안테나 성능의 우월성이 입증되었다. FFT 후단 스마트안테나의 복잡성을 줄이기 위하여 제안된 부채널 군집형 가중치벡터 갱신 안테나와 부채널 전력 기반의 MRC(Maximum Ratio Combining) 다이버시티 안테나 기법의 성능이 전형적인 Wiener 해법에 기반한 FFT 후단 스마트안테나와 비교되었다.

• Journal of Plant Biotechnology
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• 제38권1호
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• pp.9-14
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• 2011

To determine whether pattern recognition based on metabolite fingerprinting for whole cell extracts can be used to discriminate cultivars metabolically, leaves of nine commercial Orostachys plants were subjected to Fourier transform infrared spectroscopy (FT-IR). FT-IR spectral data from leaves were analyzed by principal component analysis (PCA) and Partial least square discriminant analysis (PLS-DA). The dendrogram based on hierarchical clustering analysis of these PLS-DA data separated the nine Orostachys species into five major groups. The first group consisted of O. iwarenge 'Yimge', 'Jeju', 'Jeongsun' and O. margaritifolius 'Jinju' whereas in the second group, 'Sacheon' was clustered with 'Busan,' both of which belong to O. malacophylla species. However, 'Samchuk', belong to O. malacophylla was not clustered with the other O. malacophylla species. In addition, O. minuta and O. japonica were separated to the other Orostachys plants. Thus we suggested that the hierarchical dendrogram based on PLS-DA of FT-IR spectral data from leaves represented the most probable chemotaxonomical relationship between commercial Orostachys plants. Furthermore these metabolic discrimination systems could be applied for reestablishment of precise taxonomic classification of commercial Orostachys plants.

• Journal of Microbiology and Biotechnology
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• 제30권9호
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• pp.1355-1366
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• 2020

Sediment bacterial communities are critical to the biogeochemical cycle in river ecosystems, but our understanding of the relationship between sediment bacterial communities and their specific input streams in rivers remains insufficient. In this study, we analyzed the sediment bacterial community structure in a local river receiving discharge of urban domestic sewage by applying Illumina MiSeq high-throughput sequencing. The results showed that the bacterial communities of sediments samples of different pollution types had similar dominant phyla, mainly Proteobacteria, Actinobacteria, Chloroflexi and Firmicutes, but their relative abundances were different. Moreover, there were great differences at the genus level. For example, the genus Bacillus showed statistically significant differences in the hotel site. The clustering of bacterial communities at various sites and the dominant families (i.e., Nocardioidaceae, and Sphingomonadaceae) observed in the residential quarter differed from other sites. This result suggested that environmentally induced species sorting greatly influenced the sediment bacterial community composition. The bacterial co-occurrence patterns showed that the river bacteria had a nonrandom modular structure. Microbial taxonomy from the same module had strong ecological links (such as the nitrogenium cycle and degradation of organic pollutants). Additionally, PICRUSt metabolic inference analysis showed the most important function of river bacterial communities under the influence of different types of domestic sewage was metabolism (e.g., genes related to xenobiotic degradation predominated in residential quarter samples). In general, our results emphasize that the adaptive changes and interactions in the bacterial community structure of river sediment represent responses to different exogenous pollution sources.

• 한국산업정보학회논문지
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• 제27권6호
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• pp.127-140
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• 2022

최근 정보통신기술(ICT)의 발달로 산업혁명은 3차 산업에서 4차 산업으로 옮겨가고 있다. 기업이 미래에 생존하기 위해서는 이러한 기술을 채택해야 한다는 것에는 의심의 여지가 없다. 본 연구의 목적은 제4차 산업혁명을 위한 사물인터넷(IoT) 연구 문헌의 지적 구조를 분석하여 해당 분야에 대한 더 나은 통찰력을 제시하는 것이다. 연구 데이터는 Web of Science 데이터베이스에서 추출되었으며, CiteSpace를 사용하여 총 1,631개의 문서와 72,754개의 참고 문헌을 분석하였다. 저자동시인용분석을 이용하여 제4차 산업혁명을 위한 사물인터넷 연구 분야의 지적 구조를 분석하기 위해 군집분석, 타임라인 분석, 연구전환점 분석을 수행하여 'Supply Chain', 'Digital Twin', 'Smart Manufacturing System' 등 12개의 하위 영역을 식별하였다. 타임라인 분석을 통해 연구가 확대되고 있는 분야와 축소되고 있는 분야를 분석하였으며, 연구의 한계점과 향후 연구방향을 결론과 함께 제시하였다.

• 드라이브 ㆍ 컨트롤
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• 제20권2호
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• pp.15-23
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• 2023

In this study, two-dimensional location of crops for auto weeding was detected using deep learning. To construct a dataset for soybean detection, an image-capturing system was developed using a mono camera and single-board computer and the system was mounted on a weeding robot to collect soybean images. A dataset was constructed by extracting RoI (region of interest) from the raw image and each sample was labeled with soybean and the background for classification learning. The deep learning model consisted of four convolutional layers and was trained with a weakly supervised learning method that can provide object localization only using image-level labeling. Localization of the soybean area can be visualized via CAM and the two-dimensional position of the soybean was estimated by clustering the pixels associated with the soybean area and transforming the pixel coordinates to world coordinates. The actual position, which is determined manually as pixel coordinates in the image was evaluated and performances were 6.6(X-axis), 5.1(Y-axis) and 1.2(X-axis), 2.2(Y-axis) for MSE and RMSE about world coordinates, respectively. From the results, we confirmed that the center position of the soybean area derived through deep learning was sufficient for use in automatic weeding systems.

• 정보관리학회지
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• 제40권2호
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• pp.59-80
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• 2023

기존의 연구자 유형 구분 모델은 대부분 연구성과 지표를 활용해왔다. 이 연구에서는 인용 영향력이 공동연구와 관련이 있다는 점을 감안하여 인용 데이터를 활용하지 않고 공동연구 지표만으로 연구자 유형을 분석하는 새로운 방법을 모색해보았다. 공동연구 패턴과 공동연구 범위를 기준으로 연구자를 Sparse & Wide (SW) 유형, Dense & Wide (DW) 유형, Dense & Narrow (DN) 유형, Sparse & Narrow (SN) 유형의 4가지로 구분하는 모델을 제안하였다. 제안된 모델을 양자계측 분야에 적용해본 결과, 구분된 연구자 유형별로 인용지표와 공저 네트워크 지표에 차이가 있음이 통계적으로 검증되었다. 이 연구에서 제시한 공동연구 특성에 따른 연구자 유형 구분 모델은 인용정보를 필요로 하지 않으므로 연구관리 정책과 연구지원서비스 측면에서 폭넓게 활용할 수 있을 것으로 기대된다.

• 한국자원식물학회:학술대회논문집
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• 한국자원식물학회 2023년도 임시총회 및 춘계학술대회
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• pp.40-40
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• 2023

Atopic dermatitis is a chronic inflammatory skin diseases caused by skin barrier dysfunction. Allium victoralis var. Platyphyllum (AVP) is a perennial plant used as vegetable and herbal medicine. The purpose of this study was to suggest that AVP is a new cosmetic material by examining the effects of AVP on the skin barrier and inflammatory response. A bibliometric network analysis was performed through keyword co-occurrence analysis by extracting author keyword from 69 articles retrieved from SCOPUS. We noted the anti-inflammatory activity shown by the results of clustering and mapping from network visualization analysis using VOSviewer software tool. HPLC-UV analysis showed that AVP contains 0.12 ± 0.02 mg/g of chlorogenic acid and 0.10 ± 0.01 mg/g of gallic acid. AVP at 100 ㎍/mL was shown to increase the mRNA levels of filaggrin and involucrin related to skin barrier function by 1.50-fold and 1.43-fold, respectively. In the scratch assay, AVP at concentrations of 100 ㎍/mL and 200 ㎍/mL significantly increased the cell migration rate and narrowed the scratch area. In addition, AVP suppressed the increase of inflammation-related factors COX-2 and NO and decreased the release of β-hexosaminidase. This study suggests that AVP can be developed as a functional cosmetic material for atopy management through skin barrier protection effects, anti-inflammatory and anti-itch effects.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권8호
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• pp.3806-3825
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• 2016

This paper brings out a neoteric frame of reference for visual semantic based 3d video search and retrieval applications. Newfangled 3D retrieval application spotlight on shape analysis like object matching, classification and retrieval not only sticking up entirely with video retrieval. In this ambit, we delve into 3D-CBVR (Content Based Video Retrieval) concept for the first time. For this purpose we intent to hitch on BOVW and Mapreduce in 3D framework. Here, we tried to coalesce shape, color and texture for feature extraction. For this purpose, we have used combination of geometric & topological features for shape and 3D co-occurrence matrix for color and texture. After thriving extraction of local descriptors, TB-PCT (Threshold Based- Predictive Clustering Tree) algorithm is used to generate visual codebook. Further, matching is performed using soft weighting scheme with L₂ distance function. As a final step, retrieved results are ranked according to the Index value and produce results .In order to handle prodigious amount of data and Efficacious retrieval, we have incorporated HDFS in our Intellection. Using 3D video dataset, we fiture the performance of our proposed system which can pan out that the proposed work gives meticulous result and also reduce the time intricacy.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2005년도 Proceedings of ISRS 2005
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• pp.698-701
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• 2005

This paper examines that is extracted certain information in forest areas within high resolution imagery based on wavelet transformation. First of all, study areas are selected one more species distributed spots refer to forest type map. Next, study area is cut 256 x 256 pixels size because of image processing problem in large volume data. Prior to wavelet transformation, five texture parameters (contrast, dissimilarity, entropy, homogeneity, Angular Second Moment (ASM≫ calculated by using Gray Level Co-occurrence Matrix (GLCM). Five texture images are set that shifting window size is 3x3, distance .is 1 pixel, and angle is 45 degrees used. Wavelet function is selected Daubechies 4 wavelet basis functions. Result is summarized 3 points; First, Wavelet transformation images derived from contrast, dissimilarity (texture parameters) have on effect on edge elements detection and will have probability used forest road detection. Second, Wavelet fusion images derived from texture parameters and original image can apply to forest area classification because of clustering in Homogeneous forest type structure. Third, for grading evaluation in forest fire damaged area, if data fusion of established classification method, GLCM texture extraction concept and wavelet transformation technique effectively applied forest areas (also other areas), will obtain high accuracy result.