• Proceedings of the KIEE Conference
• /
• 2015.07a
• /
• pp.1345-1346
• /
• 2015

본 논문에서는 보행자 및 배경 이미지로부터 HOG-PCA 특징을 추출하고 다항식 기반 RBFNNs(Radial Basis Function Neural Network) 패턴분류기과 최적화 알고리즘을 이용하여 보행자를 검출하는 시스템 설계를 제안한다. 입력 영상으로부터 보행자를 검출하기 위해 전처리 과정에서 HOG(Histogram of oriented gradient) 알고리즘을 통해 특징을 추출한다. 추출된 특징은 고차원이므로 패턴분류기 분류 시 많은 연산과 처리속도가 따른다. 이를 개선하고자 PCA (Principal Components Analysis)을 사용하여 저차원으로의 차원 축소한다. 본 논문에서 제안하는 분류기는 pRBFNNs 패턴분류기의 효율적인 학습을 위해 최적화 알고리즘인 PSO(Particle Swarm Optimization)을 사용하여 구조 및 파라미터를 최적화시켜 모델의 성능을 향상시킨다. 사용된 데이터로는 보행자 검출에 널리 사용되는 INRIA2005_person data set에서 보행자와 배경 영상을 각각 1200장을 학습 데이터, 검증 데이터로 구성하여 분류기를 설계하고 테스트 이미지를 설계된 최적의 분류기를 이용하여 보행자를 검출하고 검출률을 확인한다.

• Preventive Nutrition and Food Science
• /
• v.21 no.2
• /
• pp.138-146
• /
• 2016

In this study, we report the optimal extraction conditions for obtaining organosulfur compounds, such as cycloalliin, from garlic by using principal component analysis (PCA). Extraction variables including temperature ($40{\sim}80^{\circ}C$), time (0.5~12 h), and pH (4~12) were investigated for the highest cycloalliin yields. The cycloalliin yield (5.5 mmol/mL) at pH 10 was enhanced by ~40% relative to those (~3.9 mmol/mL) at pH 4 and pH 6. The cycloalliin level at $80^{\circ}C$ showed the highest yield among the tested temperatures (5.05 mmol/mL). Prolonged extraction times also increased cycloalliin yield; the yield after 12 h was enhanced ~2-fold (4 mmol/mL) compared to the control. Isoalliin and cycloalliin levels were inversely correlated, whereas a direct correlation between polyphenol and cycloalliin levels was observed. In storage for 30 days, garlic stored at $60^{\circ}C$ (11 mmol/mL) showed higher levels of cycloalliin and polyphenols than those at $40^{\circ}C$, with the maximum cycloalliin level (13 mmol/mL) on day 15. Based on the PCA analysis, the isoalliin level depended on the extraction time, while cycloalliin amounts were influenced not only by extraction time, but also by pH and temperature. Taken together, extraction of garlic at $80^{\circ}C$, with an incubation time of 12 h, at pH 10 afforded the maximum yield of cycloalliin.

• Journal of Korean Society for Atmospheric Environment
• /
• v.18 no.4
• /
• pp.317-325
• /
• 2002

An air pollution monitoring station has been operated at Tokchok Island since April 1999 to characterize the background atmosphere in the vicinity of the Yellow Sea. In this study, eight chemical species in PM$_{2.5}$ and three gaseous species were analyzed. A total of 53 samples were collected for the analysis of PM$_{2.5}$ and gaseous species from April, 1999 to April, 2001. The overall mean mass concentration of PM$_{2.5}$ was 20.8 $\mu\textrm{g}$/㎥ and the eight soluble ionic species accounted for about 46.8% of PM$_{2.5}$ mass. Approximately 80% of samples appeared to experience the chloride loss effect. Air pollutant sources of PM$_{2.5}$ measured at Tokchok Island were qualitatively identified by the principal component analysis. It was found that five principal components are secondary aerosol, soil, incineration, phase change of nitrate, and ocean.and ocean.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.10 no.8
• /
• pp.3865-3883
• /
• 2016

Infrastructure as a Service (IaaS) encapsulates computer hardware into a large amount of virtual and manageable instances mainly in the form of virtual machine (VM), and provides rental service for users. Currently, VM anomaly incidents occasionally occur, which leads to performance issues and even downtime. This paper aims at detecting anomalous VMs based on performance metrics data of VMs. Due to the dynamic nature and increasing scale of IaaS, detecting anomalous VMs from voluminous correlated and non-Gaussian monitored performance data is a challenging task. This paper designs an anomaly detection framework to solve this challenge. First, it collects 53 performance metrics to reflect the running state of each VM. The collected performance metrics are testified not to follow the Gaussian distribution. Then, it employs independent components analysis (ICA) instead of principal component analysis (PCA) to extract independent components from collected non-Gaussian performance metric data. For anomaly detection, it employs multi-class Bayesian classification to determine the current state of each VM. To evaluate the performance of the designed detection framework, four types of anomalies are separately or jointly injected into randomly selected VMs in a campus-wide testbed. The experimental results show that ICA-based detection mechanism outperforms PCA-based and LDA-based detection mechanisms in terms of sensitivity and specificity.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2007.11a
• /
• pp.1430-1436
• /
• 2007

A principal components analysis (PCA) of the median head-related impulse responses (HRIRs) in the CIPIC HRTF database reveals that the individual HRIRs can be adequately reconstructed by a linear combination of 12 orthonormal basis functions. These basis functions can be used generally to model arbitrary HRIRs, which are not included in the process to obtain the basis functions. To clarify whether these basis functions can be used to model other set of arbitrary HRIRs, an numerical error analysis for modeling and a series of subjective listening tests were carried out using the measured and modeled HRIRs. The results showed that the set of individual HRIRs, which were measured in our lab using different measurement conditions, techniques, and source positions, can be well modeled with reasonable accuracy. Furthermore, all subjects reported not only the accurate vertical perception but also the front-back discrimination with the modeled HRIRs based on 12 basis functions. However, as less basis functions were used for HRIR modeling, the modeling accuracy and localization performance deteriorated.

• Transactions of the Korean Society for Noise and Vibration Engineering
• /
• v.18 no.4
• /
• pp.448-457
• /
• 2008

A principal components analysis (PCA) of the median-plane head-related impulse responses (HRIRs) in the CIPIC HRTF database reveals that the individual HRIRs in the median plane can be adequately reconstructed by a linear combination of 12 orthonormal basis functions. These basis functions can be used to model arbitrary median-plane HRIRs, which are not included in the process to obtain the basis functions. Memory size can be reduced up to 5-fold depending on the number of HRIRs to be modeled. To clarify whether these basis functions can be used to model other set of arbitrary median plane HRIRs, a numerical error analysis for modeling and a series of subjective listening tests were carried out using the measured and modeled HRIRs. The results showed that the set of individual HRIRs in the median plane, which were measured in our lab using different measurement conditions, techniques, and source positions, can be modeled with reasonable accuracy. All subjects, involved in the subjective listening test, reported not only the accurate vertical perception but also the front-back discrimination with the modeled HRIRs based on 12 basis functions.

• Korean Journal of Environment and Ecology
• /
• v.29 no.2
• /
• pp.145-161
• /
• 2015

This research was conducted in order to understand the hybridization between Quercus aliena Blume and Q. serrata Murray in Korea which show wide range of morphological variations within species and interspecific variations of diverse overlapping characteristics caused by hybridization. Morphological analysis (principal components analysis; PCA) of 116 individuals representing two species and their intermediates were performed. As a result, two species were clearly distinguished in terms of morphology, and intermediate morpho-types assumed to be hybrids between the two species were mostly located in the middle of each parent species in the plot of the principal components analysis. There was a clear distinction between two species in trichome distribution pattern which is an important diagnostic character in taxonomy of genus Quercus, whereas intermediate morpho-types showed intermediate state between two species' trichome distributions. Forty-two individuals representing two species and their intermediates were examined for leaf flavonoid constituents. Twenty-three flavonoid compounds were isolated and identified: They were glycosylated derivatives of flavonols, kaempferol, quercetin, isorhamnetin and myricetin. The flavonoid constituents of Q. aliena were five glycosylated derivatives: kaempferol 3-O-galactoside, kaempferol 3-O-glucoside, quercetin 3-O-galactoside, quercetin 3-O-glucoside, and Isorhamnetin 3-O-glucoside. The flavonoid constituents of Q. serrata had 20 diverse flavonol compounds including five flavonoid compounds found in Q. aliena. It was found that there is a clear difference in flavonoid constituents of Q. aliena and Q. serrata. Flavonoid chemistry is very useful in recognizing each species and putative hybrids. The flavonoid constituents of intermediates were a mixture of the two species' constituents and they generally showed similar characteristics to morpho-types. The hybrids between Q. aliena and Q. serrata showed morphologically and chemically diverse characteristics and it is assumed that there are frequent interspecific hybridization and introgression.

• The Journal of the Acoustical Society of Korea
• /
• v.22 no.7
• /
• pp.539-544
• /
• 2003

This paper describes how to reduce the effect of an occupation threshold by that the transform of mixture components of HMM parameters is controlled in hierarchical tree structure to prevent from over-adaptation. To reduce correlations between data elements and to remove elements with less variance, we employ PCA (Principal component analysis) and ICA (independent component analysis) that would give as good a representation as possible, and decline the effect of over-adaptation. When we set lower occupation threshold and increase the number of transformation function, ordinary MLLR adaptation algorithm represents lower recognition rate than SI models, whereas the proposed MLLR adaptation algorithm represents the improvement of over 2% for the word recognition rate as compared to performance of SI models.

• Journal of Korea Multimedia Society
• /
• v.14 no.8
• /
• pp.1010-1019
• /
• 2011

This was a preliminary research for the goal of understanding between internal structure of Osteogenesis Imperfecta Murine (OIM) bone and its fragility. 54 hyperspectral bone data sets were captured by using JASCO 2000 Raman spectrometer at UMKC-CRISP (University of Missouri-Kansas City Center for Research on Interfacial Structure and Properties). Each data set consists of 1,091 data points from 9 OIM bones. The original captured hyperspectral data sets were noisy and base-lined ones. We removed the noise and corrected the base-lined data for the final efficient classification. High dimensional Raman hyperspectral data on OIM bones was reduced by Principal Components Analysis (PCA) and Linear Discriminant Analysis (LDA) and efficiently classified for the first time. We confirmed OIM bones could be classified such as strong, middle and weak one by using the coefficients of their PCA or LDA. Through experiment, we investigated the efficiency of classification on the reduced OIM bone data by the Bayesian classifier and K -Nearest Neighbor (K-NN) classifier. As the experimental result, the case of LDA reduction showed higher classification performance than that of PCA reduction in the two classifiers. K-NN classifier represented better classification rate, compared with Bayesian classifier. The classification performance of K-NN was about 92.6% in case of LDA.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.11 no.6
• /
• pp.491-499
• /
• 2001

In this paper, the scheme of an efficient fuzzy rule generation and fuzzy system construction using GA(genetic algorithm) and FCM(fuzzy c-means) clustering algorithm is proposed for TSK(Takagi-Sugeno-Kang) type fuzzy system. In the structure identification, input data is transformed by PCA(Principal Component Analysis) to reduce the correlation among input data components. And then, a set fuzzy rules are generated for a given criterion by FCM clustering algorithm . In the parameter identification premise parameters are optimally searched by GA. On the other hand, the consequent parameters are estimated by RLSE(Recursive Least Square Estimate) to reduce the search space. From this one can systematically obtain the valid number of fuzzy rules which shows satisfying performance for the given problem. Finally, we applied the proposed method to the Box-Jenkins data and rice taste data modeling problems and obtained a better performance than previous works.