• The Journal of the Acoustical Society of Korea
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• 제26권2E호
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• pp.63-68
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• 2007

Using the neural network model for oriented principal component analysis (OPCA), we propose a solution to the data least squares (DLS) problem, in which the error is assumed to lie in the data matrix only. In this paper, we applied this neural network model to channel equalization. Simulations show that the neural network based DLS outperforms ordinary least squares in channel equalization problems.

• ETRI Journal
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• 제33권3호
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• pp.443-453
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• 2011

This paper evaluates the efficiency of mobile content firms through a hybrid approach combining data envelopment analysis (DEA) to analyze the relative efficiency and performance of firms and principal component analysis (PCA) to analyze data structures. We performed a DEA using the total amount of assets, operating costs, employees, and years in business as inputs, and revenue as output. We calculated fifteen combinations of DEA efficiency in the mobile content firms. We performed a PCA on the results of the fifteen DEA models, dividing the mobile content firms into those having either 'asset-oriented' or 'manpower and experience-oriented' efficiency. Discriminant analysis was used to validate the relationship between the efficiency models and mobile content types. This paper contributes toward the construction of a framework that combines the DEA and PCA approaches in mobile content firms for use in comprehensive measurements. Such a framework has the potential to present major factors of efficiency for sustainable management in mobile content firms and to aid in planning mobile content industry policies.

• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2003년도 가을 학술발표논문집 Vol.30 No.2 (2)
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• pp.739-741
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• 2003

Electroencephalogram (EEG)-based brain computer interface (BCI) provides a new communication channel between human brain and computer. EEG is very noisy data and contains artifacts, thus the extraction of features that are robust to noise and artifacts is important. In this paper we present a method with employ both independent component analysis (ICA) and oriented principal component analysis (OPCA) for artifact-robust feature extraction.

• 한국항공운항학회지
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• 제17권1호
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• pp.39-45
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• 2009

An Analysis of wind is essential for planning runway direction. As a general rule, the principal traffic runway at an airport should be oriented as closely as practicable in the direction of the prevailing wind. Aircraft are able to maneuver on a runway as long as the wind component at right angles to the direction of landing and taking-off, the cross wind component, is not excessive. ICAO recommends that runway be oriented so that aircraft may be landed at least 95% of the time with allowable cross wind components not exceeding specified limits based upon the airport reference field length. Based on the recommendation, the direction of the runway or runways at an airport can be determined through graphical vector analysis on wind rose. This study is to develop the wind-rose software for planning the optimum runway direction at an airport with the raw wind data based on reliable wind distribution statistics that extend over as long as a period as possible, preferably of not less than 5 years.

• 한국콘텐츠학회논문지
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• 제17권7호
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• pp.371-383
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• 2017

본 연구는 사회주의와 시장경제가 혼합된 경제체제를 운영하고 있는 중국경제에서 성장과 분배의 상충관계의 조정과정을 분석하기 위한 시도이다. 연구방법으로는 주성분분석을 활용하고 사회후생 지표의 가중치를 분석하여 중국의 도농 간 사회후생 수준의 변화과정과 그 특성을 분석하였다. 분석결과에 의하면 전국과 도시지역과는 달리 농촌지역에서의 소득변화가 사회후생 수준을 증가시키지만 사회후생 지표의 개선에는 미흡한 것으로 나타났다. 즉, 중국은 경제성장 과정에서 농촌지역의 사회후생 지표에 대한 개선이 필요하며 경제성장이 농촌지역의 사회후생을 증가시킬 수 있는 잠재력은 상존한다고 할 수 있다. 성장과 분배를 동시에 추구하는 중국의 경제체제에서 경제성장에 의한 후생수준의 향상은 실현되고 있다. 그러나 소득의 분배 과정에 의한 사회후생 지표의 개선은 제한적이기 때문에 중국경제에서 분배과정이 시장기능보다 취약하다고 볼 수 있다. 결과적으로 중국의 경우 사회후생 수준을 향상시키기 위해서는 분배기능을 강화해야 할 것이다.

• 대한원격탐사학회지
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• 제31권4호
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• pp.303-319
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• 2015

The objectives of this paper are to measure surface imperviousness using three different classification methods: per-pixel, sub-pixel, and object-oriented classification. They are tested on high-spatial resolution QuickBird data at 2.4 meters (four spectral bands and three principal component bands) as well as a medium-spatial resolution Landsat TM image at 30 meters. To measure impervious surfaces, we selected 30 sample sites with different land uses and residential densities across image representing the city of Phoenix, Arizona, USA. For per-pixel an unsupervised classification is first conducted to provide prior knowledge on the possible candidate spectral classes, and then a supervised classification is performed using the maximum-likelihood rule. For sub-pixel classification, a Linear Spectral Mixture Analysis (LSMA) is used to disentangle land cover information from mixed pixels. For object-oriented classification several different sets of scale parameters and expert decision rules are implemented, including a nearest neighbor classifier. The results from these three methods show that the object-oriented approach (accuracy of 91%) provides more accurate results than those achieved by per-pixel algorithm (accuracy of 67% and 83% using Landsat TM and QuickBird, respectively). It is also clear that sub-pixel algorithm gives more accurate results (accuracy of 87%) in case of intensive and dense urban areas using medium-resolution imagery.

• 성인간호학회지
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• 제17권2호
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• pp.259-267
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• 2005

Purpose: The purpose of the study was to investigate change of life in middle-aged men. Method: The research method employed Q-methodology. twenty-five participants rated 39 selected Q-statements on a scale of 1~9. The collected data were analyzed using pc-QUNAL software. Result: Principal component analysis identified 3 types of change of life in middle-aged men. The categories were labeled 'Mature-oriented', 'Effeminate-oriented', 'Juvenescence-oriented'. Conclusion: We have found change of life in middle-aged men through this research. To setup and apply differences based on this result is needed.

• International Journal of Computer Science & Network Security
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• 제22권2호
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• pp.232-240
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• 2022

To fulfill user expectations, the rapid evolution of software techniques and approaches has necessitated reliable and flawless software operations. Aging prediction in the software under operation is becoming a basic and unavoidable requirement for ensuring the systems' availability, reliability, and operations. In this paper, an improved evolutionary computing-driven extreme learning scheme (ECD-ELM) has been suggested for object-oriented software aging prediction. To perform aging prediction, we employed a variety of metrics, including program size, McCube complexity metrics, Halstead metrics, runtime failure event metrics, and some unique aging-related metrics (ARM). In our suggested paradigm, extracting OOP software metrics is done after pre-processing, which includes outlier detection and normalization. This technique improved our proposed system's ability to deal with instances with unbalanced biases and metrics. Further, different dimensional reduction and feature selection algorithms such as principal component analysis (PCA), linear discriminant analysis (LDA), and T-Test analysis have been applied. We have suggested a single hidden layer multi-feed forward neural network (SL-MFNN) based ELM, where an adaptive genetic algorithm (AGA) has been applied to estimate the weight and bias parameters for ELM learning. Unlike the traditional neural networks model, the implementation of GA-based ELM with LDA feature selection has outperformed other aging prediction approaches in terms of prediction accuracy, precision, recall, and F-measure. The results affirm that the implementation of outlier detection, normalization of imbalanced metrics, LDA-based feature selection, and GA-based ELM can be the reliable solution for object-oriented software aging prediction.

• 전기학회논문지
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• 제66권2호
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• pp.416-424
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• 2017

In this study, we propose a design of digits recognition system based on RBFNNs through a comparative study of pre-processing algorithms in order to recognize digits in handwritten. Histogram of Oriented Gradient(HOG) is used to get the features of digits in the proposed digits recognition system. In the pre-processing part, a dimensional reduction is executed by using Principal Component Analysis(PCA) and (2D)2PCA which are widely adopted methods in order to minimize a loss of the information during the reduction process of feature space. Also, The architecture of radial basis function neural networks consists of three functional modules such as condition, conclusion, and inference part. In the condition part, the input space is partitioned with the use of fuzzy clustering realized by means of the Fuzzy C-Means algorithm. Also, it is used instead of gaussian function to consider the characteristic of input data. In the conclusion part, the connection weights are used as the extended type of polynomial expression such as constant, linear, quadratic and modified quadratic. By using MNIST handwritten digit benchmarking database, experimental results show the effectiveness and efficiency of proposed digit recognition system when compared with other studies.

• 한국실내디자인학회논문집
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• 제19권5호
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• pp.182-189
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• 2010

An exhibition administrator, one who works in the exhibition space of museums and exhibition halls, has carried on various tasks in order to improve the exhibition standard and viewer's satisfaction. Although exhibition administrators have a variety of direct perceptions regarding an exhibition in the actual on-site space, a study on their consciousness was absent. Thus, this study was to comprehend the awareness of how the consciousness of exhibition administrators, who directly understand the various matters regarding the exhibition on-site, was structured and to investigate the difference between the consciousness of exhibition viewers and designers. For the study, Q-Methodology, which can scientifically manage the consciousness such as awareness and the acquired attitudes through individual experiences from a specific group, was applied. The classification of 33 Q-methodology research questions was carried out with 18 exhibition administrators, who are working at either national or public museums and exhibition halls in Korea, and the Principal Component Analysis (PCA) using the QUANL PC program was performed. The results of the analysis provided the following 4 types: 'viewer attraction and exhibition method oriented', 'exhibition standard oriented', 'public relations oriented' and 'the public and government's interest oriented'. Each type showed significant characteristics. Additionally, n showed that 'exhibition standard oriented' was the common type after comparing the type of consciousness among the 3 groups of people, such as an exhibition administrator, an exhibition designer, and a viewer. It indicated that the types of 'public relations oriented' and 'the public and government's interest oriented' from the consciousness category for the exhibition administrator were the most independent type, not being found in any of the other groups. And the Significant correlation between the exhibition viewers and designers was identified after examining the Pearson's correlation among the 3 groups.