• Journal of The Korean Society of Agricultural Engineers
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• v.55 no.1
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• pp.31-38
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• 2013

The purpose of this study was to evaluate climate change vulnerability over the agricultural infrastructure in terms of flood and drought using principal component analysis. Vulnerability was assessed using vulnerability resilience index (VRI) which combines climate exposure, sensitivity, and adaptive capacity. Ten flood proxy variables and six drought proxy variables for the vulnerability assessment were selected by opinions of researchers and experts. The statistical data on 16 proxy variables for the local governments (Si, Do) were collected. To identify major variables and to explain the trend in whole data set, principal component analysis (PCA) was conducted. The result of PCA showed that the first 3 principal components explained approximately 83 % and 89 % of the total variance for the flood and drought, respectively. VRI assessment for the local governments based on the PCA results indicated that provinces where having the relatively large cultivation areas were categorized as vulnerable to climate change.

• The KIPS Transactions:PartB
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• v.15B no.4
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• pp.285-292
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• 2008

Color histograms have been used as feature vectors to characterize the color features of given images, but they have a limitation in efficiency by generating high-dimensional feature vectors. In this paper, we present a method to reduce the dimension of the feature vectors by applying PCA (principal components analysis) to the color histogram of a given vehicle image. With SVM (support vector machine) method, the dimension-reduced feature vectors are used to recognize the colors of vehicles. After reducing the dimension of the feature vector by a factor of 32, the successful recognition rate is reduced only 1.42% compared to the case when we use original feature vectors. Moreover, the computation time for the color recognition is reduced by a factor of 31, so we could recognize the colors efficiently.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.8 no.1
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• pp.11-17
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• 2008

Typical wireless sensor networks used in structural monitoring are continuous types wherein data transmission is progressive at all time that may include irrelevant and insignificant data and information. Continuous types of wireless monitoring systems often pose problems of handling large-sized data that may deteriorate the performance of the system. The proposed method is to suggest an event-triggered monitoring system that captures and transmits relevant data only. An error signal generated by the Principal Components Analysis (PCA) is utilized as an index for event detection and selective data transmission. With this new monitoring scheme, the remote server is relieved of unwanted data by receiving only relevant information from the wireless sensor networks. The performance of the proposed scheme was verified with simulation studies.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.17 no.7 s.124
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• pp.638-648
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• 2007

A principal components analysis of the entire median HRIRs in the CIPIC HRTF database reveals that the individual HRIRs can be adequately reconstructed by a linear combination of several orthonormal basis functions. The basis functions represent the inter-individual and inter-elevation variations in median HRIRs. There exist elevation-dependent tendencies in the weights of basis functions, and the basis functions can be ordered according to the magnitude of standard deviation of the weights at each elevation. We propose a HRIR customization method via tuning of the weights of 3 dominant basis functions corresponding to the 3 largest standard deviations at each elevation. Subjective listening test results show that both front-back reversal and vertical perception can be improved with the customized HRIRs.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2006.04a
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• pp.1001-1008
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• 2006

The main objective of this paper is to compare economical effectiveness of typical methods for checking stability in principal components of steel cable-stayed bridges. Elastic and inelastic buckling analyses are carried out for frame-like numerical models of cable-stayed bridges. The axial-flexural interaction equations prescribed in AASHTO Allowable Stress Design (ASD) and AASHTO Load and Resistance Factor Design (LRFD) are used in order to check the stability of principal components. Parametric studies are performed for numerical models which have the center span length of 300m, 600m, 900m and l200m with different girder depths. Peak values of the interaction equations are calculated at the intersection point between girders and towers. These peak values are considered as a major factor to design of principal components of cable-stayed bridges. As a result, more economical design for girders and towers can be feasible using the inelastic buckling analysis. In addition, LRFD codes are more economical about 20% on the average than ASD codes for all numerical models of cable-stayed bridges.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.8
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• pp.3946-3965
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• 2018

Network anomaly detection in Software Defined Networking, especially the detection of DDoS attack, has been given great attention in recent years. It is convenient to build the Traffic Matrix from a global view in SDN. However, the monitoring and management of high-volume feature-rich traffic in large networks brings significant challenges. In this paper, we propose a moving window Principal Components Analysis based anomaly detection and mitigation approach to map data onto a low-dimensional subspace and keep monitoring the network state in real-time. Once the anomaly is detected, the controller will install the defense flow table rules onto the corresponding data plane switches to mitigate the attack. Furthermore, we evaluate our approach with experiments. The Receiver Operating Characteristic curves show that our approach performs well in both detection probability and false alarm probability compared with the entropy-based approach. In addition, the mitigation effect is impressive that our approach can prevent most of the attacking traffic. At last, we evaluate the overhead of the system, including the detection delay and utilization of CPU, which is not excessive. Our anomaly detection approach is lightweight and effective.

• Korean Institute of Interior Design Journal
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• v.21 no.5
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• pp.280-288
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• 2012

The objective of this study was to analyze the characteristics of traditionality expressions at modernized Chinese restaurant in Hong Kong. As a case study, the study examined 12 modernized Chinese restaurants in Hong Kong. The gathered data were categorized and examined according to the ways of traditionality expressions, which included reproduction, transformation, and reinterpretation of traditional components. Each of the components was measured for the amount of traditional or modernity expression on a five-point scale. The five-point scoring system put an emphasis on tradition; 1 point was given to principal modernity(modernity: 90-100% + tradition: 0-10%), 2 points were given to principal modernity + auxiliary tradition(modernity: 70-90% + tradition: 10-30%), 3 points were given to the same ratio between tradition and modernity(modernity: 40-60% + tradition: 40-60%), 4 points were given to principal tradition + auxiliary modernity(modernity: 10-30% + tradition: 70-90%), and 5 points were given to principal tradition(modernity: 0-10% + tradition: 90-100%). The analysis performed according to those criteria and methodologies led to the following findings and conclusions: TM style, in which modernity was principal, usually did transformation and reinterpretation of traditionality. As for the design attributes of the styles, the TM style, they processed a majority of the spatial components as modern or reinterpretation of traditionality, which would be easily considered to be modern without careful observation, and applied a small amount of direct reproduction or transformation, which gives out a direct hint at traditionality, to attract more attention. Many of the spatial components did not express traditionality directly, expressing it indirectly or metaphorically. Traditionality was expressed in a small number of the spatial components, thus serving as a focus or impact point in the given space.

• Journal of the Institute of Convergence Signal Processing
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• v.11 no.4
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• pp.320-325
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• 2010

This paper is about the method and procedure to register the candidate sequentially in the face recognition system using the PCA(Principal Components Analysis). We use the method to update the principal components sequentially with the SKL algorithm which is improved R-SVD algorithm. This algorithm enable us to solve the re-training problem of the increase the candidates number sequentially in the face recognition using the PCA. Also this algorithm can use in robust tracking system with the bright change based to the principal components. This paper proposes the procedure in the face recognition system which sequentially updates the principal components using the SKL algorithm. Then we compared the face recognition performance with the batch procedure for calculating the principal components using the standard KL algorithm and confirms the effects of the forgetting factor in the SKL algorithm experimentally.

• The Journal of the Acoustical Society of Korea
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• v.22 no.8
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• pp.711-716
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• 2003

This paper proposes the method to select the number of optimal mixtures in each state in Continuous Density HMM (Hidden Markov Models), Previously, researchers used the same number of mixture components in each state of HMM regardless spectral characteristic of speaker, To model each speaker as accurately as possible, we propose to use a different number of mixture components for each state, Selection of mixture components considered the probability value of mixture by each state that affects much parameter estimation of continuous density HMM, Also, we use PCA (principal component analysis) to reduce the correlation and obtain the system' stability when it is reduced the number of mixture components, We experiment it when the proposed method used average 10% small mixture components than the conventional HMM, When experiment result is only applied selection of mixture components, the proposed method could get the similar performance, When we used principal component analysis, the feature vector of the 16 order could get the performance decrease of average 0,35% and the 25 order performance improvement of average 0.65%.

• Journal of Navigation and Port Research
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• v.27 no.2
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• pp.163-170
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• 2003

This empirical study takes the activation approach for the competitive power of Korean shipping companies in the Korea-China liner routes. Data for this study were collected from Korea/ China/ 3rd flag shipping companies through the 500 questionnaires. The data of 250 respondents were analyzed statistically to verify the hypotheses and to induce Regression Equation which could predicts the influencing level of the determinants to competitive advantage for Korean shipping companies on Korea-China Liner Shipping Routes. Factor Analysis/ Cronbach's Alpha/ Principal Analysis/ Multiple Regression Analysis were used in order to test the hypotheses for the empirical study.