• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2006년도 Proceedings of ISRS 2006 PORSEC Volume II
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• pp.555-558
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• 2006

In recent years, urban development has expanded rapidly in Nawabshah City of Pakistan. A major effect associated with this population trend is transformation of the landscape from natural cover types to increasingly impervious urban land. The core objective of this study are to provide time-series information to define and measure the urban land cover changes of Nawabshah, Pakistan between the years 1992 and 2002, and to examine related urbanization impacts on air quality of the study area. Two multi-temporal Landsat images acquired in 1992 and 2002 together with standard topographical maps to measure land cover changes were used in this study. The image processing and data manipulation were conducted using algorithms supplied with the ERDAS Imagine software. An unsupervised classification approach, which uses a minimum spectral distance to assign pixels to clusters, was used with the overall accuracy ranging from 84 percent to 92 percent. Land cover statistics demonstrate that during the study period (1992-2002) extensive transformation of barren and vegetated lands into urban land have taken place in Nawabshah City. Results revealed that land cover changes due to urbanization has not only contaminated the air quality of the study area but also raised the health concerns for the local residents.

• 환경영향평가
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• 제13권3호
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• pp.137-151
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• 2004

Many of today's environmental problems are regional in scope and their effects overlap and interact. The purpose of this paper is to developed a simple method for an integrated assessment of environmental conditions across the Mid-Nakdong River Region, by combining data on land use, impervious cover, roads, streams, riparian areas, forest patches, population, pollutant loadings, soil erosion and topography. A cluster analysis was used to identify groups of sub-watersheds with similar environmental characteristics. The mean value for each group was used to find watershed that may be more vulnerable to future environmental degradation. Watersheds in cluster I and II had high amount of forest, but the amount of riparian vegetation was low. Watersheds in cluster III, which located in the middle Geumho River and the main course of Nakdong River, had a greater proportion of their agriculture, a greater proportion of agriculture on steep slopes, and less forest adjacent to streams. Watersheds in cluster IV and V were in the most urbanized areas of the region. The principal adverse impacts for watersheds in this group were high scores for urban area, impervious cover, pollutant loadings, population density, forest fragmentation, and low amounts of forest and riparian forest cover. Notwithstanding the exploratory nature of cluster analysis, it appears to be a useful tool for grouping watersheds with similar environmental characteristics.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제4권3호
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• pp.322-326
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• 2004

This paper describes a new iris recognition method based on a shift-invariant wavelet sub-images. For the feature representation, we first preprocess an iris image for the compensation of the variation of the iris and for the easy implementation of the wavelet transform. Then, we decompose the preprocessed iris image into multiple subband images using a shift-invariant wavelet transform. For feature representation, we select a set of subband images, which have rich information for the classification of various iris patterns and robust to noises. In order to reduce the size of the feature vector, we quantize. each pixel of subband images using the Lloyd-Max quantization method Each feature element is represented by one of quantization levels, and a set of these feature element is the feature vector. When the quantization is very coarse, the quantized level does not have much information about the image pixel value. Therefore, we define a new similarity measure based on mutual information between two features. With this similarity measure, the size of the feature vector can be reduced without much degradation of performance. Experimentally, we show that the proposed method produced superb performance in iris recognition.

• Molecules and Cells
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• 제37권5호
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• pp.399-405
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• 2014

Autophagy targets cytoplasmic cargo to a lytic compartment for degradation. Autophagy-related (Atg) proteins, including the transmembrane protein Atg9, are involved in different steps of autophagy in yeast and mammalian cells. Functional classification of core Atg proteins in plants has not been clearly confirmed, partly because of the limited availability of reliable assays for monitoring autophagic flux. By using proUBQ10-GFP-ATG8a as an autophagic marker, we showed that autophagic flux is reduced but not completely compromised in Arabidopsis thaliana atg9 mutants. In contrast, we confirmed full inhibition of auto-phagic flux in atg7 and that the difference in autophagy was consistent with the differences in mutant phenotypes such as hypersensitivity to nutrient stress and selective autophagy. Autophagic flux is also reduced by an inhibitor of phosphatidylinositol kinase. Our data indicated that atg9 is phenotypically distinct from atg7 and atg2 in Arabidopsis, and we proposed that ATG9 and phosphatidylinositol kinase activity contribute to efficient autophagy in Arabidopsis.

• 한국전자통신학회논문지
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• 제8권9호
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• pp.1299-1305
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• 2013

이 논문에서 우리는 MFCC 특징벡터의 차원 저감을 통해 음성 인식에서의 계산량을 줄이는 방법을 조사한다. 특징벡터의 특성분해는 벡터의 성분을 분산의 크기에 따라 배치되도록 선형 변환 시켜준다. 첫 번째 성분은 가장 큰 분산을 가져서 패턴 분류에서 가장 중요한 역할을 한다. 따라서, 분산이 작은 성분들을 제외시키는 차원 저감을 통하여, 계산량을 줄이면서 동시에 음성 인식 성능을 저하시키지 않는 방법을 생각할 수 있다. 실험 결과, MFCC 특징벡터의 성분을 절반 정도로 줄여도 음성인식 오류율에 큰 악영향이 없음이 확인되었다.

• 대한원격탐사학회지
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• 제25권3호
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• pp.263-270
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• 2009

Noise band removal is a crucial step before spectral matching since the noise bands can distort the typical shape of spectral reflectance, leading to degradation on the matching results. This paper proposes a statistical noise band removal method for hyperspectral data using the correlation coefficient between two bands. The correlation coefficient measures the strength and direction of a linear relationship between two random variables. Considering each band of the hyperspectral data as a random variable, the correlation between two signal bands is high; existence of a noisy band will produce a low correlation due to ill-correlativeness and undirected ness. The unsupervised k-nearest neighbor clustering method is implemented in accordance with three well-accepted spectral matching measures, namely ED, SAM and SID in order to evaluate the validation of the proposed method. This paper also proposes a hierarchical scheme of combining those measures. Finally, a separability assessment based on the between-class and the within-class scatter matrices is followed to evaluate the applicability of the proposed noise band removal method. Also, the paper brings out a comparison for spectral matching measures. The experimental results conducted on a 228-band hyperspectral data show that while the SAM measure is rather resistant, the performance of SID measure is more sensitive to noise.

• Structural Monitoring and Maintenance
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• 제2권3호
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• pp.181-197
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• 2015

Assessing the condition of paint on civil structures is an important but challenging and costly task, in particular when it comes to large and complex structures. Current practices of visual inspection are labour-intensive and time-consuming to perform. In addition, this task usually relies on the experience and subjective judgment of individual inspectors. In this study, hyperspectral imaging and classification techniques are proposed as a method to objectively assess the state of the paint on a civil or other structure. The ultimate objective of the work is to develop a technology that can provide precise and automatic grading of paint condition and assessment of degradation due to age or environmental factors. Towards this goal, we acquired hyperspectral images of steel surfaces located at long (mid-range) and short distances on the Sydney Harbour Bridge with an Acousto-Optics Tunable filter (AOTF) hyperspectral camera (consisting of 21 bands in the visible spectrum). We trained a multi-class Support Vector Machines (SVM) classifier to automatically assess the grading of the paint from hyperspectral signatures. Our results demonstrate that the classifier generates highly accurate assessment of the paint condition in comparison to the judgement of human experts.

• Smart Structures and Systems
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• 제24권2호
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• pp.173-182
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• 2019

Due to the degradation of beamforming properties at angles close to $0^{\circ}$ to $180^{\circ}$, linear array does not have a complete $180^{\circ}$ inspection range but a smaller one. This paper develops a improved sensor array with two additional sensors above and below the linear sensor array, and presents time difference and two dimensional multiple signal classification (2D-MUSIC) based impact localization for omni-directional localization on composite structures. Firstly, the arrival times of impact signal observed by two additional sensors are determined using the wavelet transform and compared, and the direction range of impact source can be decided in general, $0^{\circ}$ to $180^{\circ}$ or $180^{\circ}$ to $360^{\circ}$. And then, 2D-MUSIC based spatial spectrum formula using uniform linear array is applied for locate accurate position of impact source. When the arrival time of impact signal observed by two additional sensors is equal, the direction of impact source can be located at $0^{\circ}$ or $180^{\circ}$ by comparing the first and last sensor of linear array. And then the distance is estimated by time difference algorithm. To verify the proposed approach, it is applied to a quasi-isotropic epoxy laminate plate and a stiffened composite panel. The results are in good agreement with the actual impact occurring position.

• International Journal of Naval Architecture and Ocean Engineering
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• 제13권1호
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• pp.659-673
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• 2021

This study aims to investigate the impact of the High Pressure Selective Catalytic Reduction system (SCR-HP) on a large marine two-stroke engine performance parameters by employing thermodynamic modelling. A coupled model of the zero-dimensional type is extended to incorporate the modelling of the SCR-HP components and the Control Bypass Valve (CBV) block. This model is employed to simulate several scenarios representing the engine operation at both healthy and degraded conditions considering the compressor fouling and the SCR reactor clogging. The derived results are analysed to quantify the impact of the SCR-HP on the investigated engine performance. The SCR system pressure drop and the cylinder bypass valve flow cause an increase of the engine Specific Fuel Oil Consumption (SFOC) in the range 0.3-2.77 g/kWh. The thermal inertia of the SCR-HP is mainly attributed to the SCR reactor, which causes a delayed turbocharger response. These effects are more pronounced at low engine loads. This study supports the better understanding of the operating characteristics of marine two-stroke diesel engines equipped with the SCR-HP and quantification of the impact of the components degradation on the engine performance.

• 방송공학회논문지
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• 제26권7호
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• pp.844-854
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• 2021

Semi-supervised learning (SSL) and few-shot learning (FSL) have shown impressive performance even then the volume of labeled data is very limited. However, SSL and FSL can encounter a significant performance degradation if the diversity gap between the labeled and unlabeled data is high. To reduce this diversity gap, we propose a novel scheme that relies on an autoencoder for generating pseudo examples. Specifically, the autoencoder is trained on a specific class using the available labeled data and the decoder of the trained autoencoder is then used to generate N samples of that specific class based on N random noise, sampled from a standard normal distribution. The above process is repeated for all the classes. Consequently, the generated data reduces the diversity gap and enhances the model performance. Extensive experiments on MNIST and FashionMNIST datasets for SSL and FSL verify the effectiveness of the proposed approach in terms of classification accuracy and robustness against adversarial attacks.