• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.9
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• pp.1392-1401
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• 2017

In this study, the design methodology of pattern classification is introduced for avoiding faults through partial discharge occurring in the power facilities and local sites. In order to classify some partial discharge types according to the characteristics of each feature, the model is constructed by using the Radial Basis Function Neural Networks(RBFNNs) and Particle Swarm Optimization(PSO). In the input layer of the RBFNNs, the feature vector is searched and the dimension is reduced through Principal Component Analysis(PCA) and PSO. In the hidden layer, the fuzzy coefficients of the fuzzy clustering method(FCM) are tuned using PSO. Raw datasets for partial discharge are obtained through the Motor Insulation Monitoring System(MIMS) instrument using an Epoxy Mica Coupling(EMC) sensor. The preprocessed datasets for partial discharge are acquired through the Phase Resolved Partial Discharge Analysis(PRPDA) preprocessing algorithm to obtain partial discharge types such as void, corona, surface, and slot discharges. Also, when the amplitude size is considered as two types of both the maximum value and the average value in the process for extracting the preprocessed datasets, two different kinds of feature datasets are produced. In this study, the classification ratio between the proposed RBFNNs model and other classifiers is shown by using the two different kinds of feature datasets, and also we demonstrate the proposed model shows superiority from the viewpoint of classification performance.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.39 no.9
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• pp.823-831
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• 2011

According to the development of loading equipments, it is usual to change or replace the existing stores. It has been known that pylon-mounted under stores strongly affect aircraft dynamics characteristics due to the change of aerodynamics. To predict the aerodynamics and aero-elasticity is essentially requested with considering the configuration and shape of external stores during the development of aircraft and/or external stores. In this paper, computational fluid dynamics and computational structure dynamics interaction methodology are applied for prediction of aerodynamic characteristics for F-5 aircraft's horizontal tail with various shape of external stores. FLUENT and ABAQUS were used to calculate fluid and structural dynamics. Code-bridge was made base on the globally supported radial basis function to execute interpolation and mapping. As a result, even though the aeroelasticity of the horizontal tail slightly changes according to the shape of external store, the flutter was not occurred at the considered flight conditions in this study.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.5
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• pp.744-752
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• 2012

In this study, the Polynomial-based Radial Basis Function Neural Networks is proposed as an one of the recognition part of overall face recognition system that consists of two parts such as the preprocessing part and recognition part. The design methodology and procedure of the proposed pRBFNNs are presented to obtain the solution to high-dimensional pattern recognition problems. In data preprocessing part, Principal Component Analysis(PCA) which is generally used in face recognition, which is useful to express some classes using reduction, since it is effective to maintain the rate of recognition and to reduce the amount of data at the same time. However, because of there of the whole face image, it can not guarantee the detection rate about the change of viewpoint and whole image. Thus, to compensate for the defects, Linear Discriminant Analysis(LDA) is used to enhance the separation of different classes. In this paper, we combine the PCA&LDA algorithm and design the optimized pRBFNNs for recognition module. The proposed pRBFNNs architecture consists of three functional modules such as the condition part, the conclusion part, and the inference part as fuzzy rules formed in 'If-then' format. In the condition part of fuzzy rules, input space is partitioned with Fuzzy C-Means clustering. In the conclusion part of rules, the connection weight of pRBFNNs is represented as two kinds of polynomials such as constant, and linear. The coefficients of connection weight identified with back-propagation using gradient descent method. The output of the pRBFNNs model is obtained by fuzzy inference method in the inference part of fuzzy rules. The essential design parameters (including learning rate, momentum coefficient and fuzzification coefficient) of the networks are optimized by means of Differential Evolution. The proposed pRBFNNs are applied to face image(ex Yale, AT&T) datasets and then demonstrated from the viewpoint of the output performance and recognition rate.

• Journal of the Korean School Mathematics Society
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• v.16 no.1
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• pp.265-287
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• 2013

The purpose of this study was to analyze the trends of domestic research on teacher knowledge in mathematics in terms of its conceptualizations of teacher knowledge, topics, methods, subjects, and content domains. For this purpose, the papers published in 9 professional journals during the recent 14 years (1999-2012) were analyzed by 5 criteria. The results of this study showed that the concept of PCK was the most frequent, whereas its subcategories appeared in different forms. The most frequent research topic was survey of teacher knowledge. The qualitative research methodology was more frequently used than the quantitative methodology, whereas mixed one was hardly used. The subjects for research included a little more elementary school teachers than secondary counterparts, but did similarly both pre-service and in-service teachers. Whereas both the research on number and operations in elementary mathematics education and the research on function in secondary were active, the rest of content domains were not. On the basis of these results, this paper provides several implications for future research direction in teacher knowledge in mathematics.

• The Korean Journal of Archival Studies
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• no.44
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• pp.5-49
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• 2015

Although a study on documentation strategy has been steadily releasing recently in the archival study field, it is rare that the cases or studies applying the institutional functional analysis methodology that Helen Samuels had suggested. The institutional functional analysis is a methodology to provide a comprehensive understanding of the record by defining the essential features of the institution at a macro level. The documentation area derived from the institutional functional analysis functions as a priori framework for an archivist to select and keep the records of the institution. In other words, by analyzing the function of the institution through the institutional functional analysis methodology, it makes possible to identify the functions not covered under the current records retention schedule at a macro level ensuring accountability of the organization's business activities. The documentation project of the United States is a prime example to comply with this background. In this study, by analyzing the case of the United States Congress, it is proposed the derived implications for applying the institutional functional analysis to the National Assembly of the Republic of Korea, where is the similar national institution to the U.S. Congress. For this purpose, firstly, the theoretical debate on the institutional functional analysis as the previous studies. Secondly, the documentation project of the United States Congress has been case analyzed by each function according to the institutional functional analysis. Thirdly, on the basis of the case study results, the implications are derived and it is suggested that the documentation areas applicable to the National Assembly of the Republic of Korea.

• Korean Journal of Remote Sensing
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• v.39 no.5_1
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• pp.577-587
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• 2023

The utilization of crowdsourced spatial data has been actively researched; however, issues stemming from the uncertainty of data quality have been raised. In particular, when low-quality data is mixed into drone imagery datasets, it can degrade the quality of spatial information output. In order to address these problems, the study presents a methodology for automatically validating the geometric quality of crowdsourced imagery. Key quality factors such as spatial resolution, resolution variation, matching point reprojection error, and bundle adjustment results are utilized. To classify imagery suitable for spatial information generation, training and validation datasets are constructed, and machine learning is conducted using a radial basis function (RBF)-based support vector machine (SVM) model. The trained SVM model achieved a classification accuracy of 99.1%. To evaluate the effectiveness of the quality validation model, imagery sets before and after applying the model to drone imagery not used in training and validation are compared by generating orthoimages. The results confirm that the application of the quality validation model reduces various distortions that can be included in orthoimages and enhances object identifiability. The proposed quality validation methodology is expected to increase the utility of crowdsourced data in spatial information generation by automatically selecting high-quality data from the multitude of crowdsourced data with varying qualities.

• Journal of Sasang Constitutional Medicine
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• v.4 no.1
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• pp.5-29
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• 1992

In this study, the author researched the process in which the philosophical basis of 'Sa Sang Medicine (四象醫學)' and its methodology build up the principles of Sa Sang Medicine, and then, examined how the principles were applied to the theoretical system of Sa Sang Medicine. The conclusion would be summarized as follows. 1. 'Nae Kyung Medicine (內經醫學)' was developed under the concept that the cosmos's order and its moving rule could be directly applied to that of human body, which corresponded to the 'Theory of Hwang-No (黃老之學)'. On the contrary, Sa Sang Medicine is a thoroughly human-oriented theory formed in the Confucianism system. 2. Lee Jae-Ma's Substantialism can be briefed into 'Mind 心' (Tae Keuk 太極), 'Mind-Body 心身' (Yang Eui 兩儀) and 'Activity-Mind-Body-Matter 事心身物' (Sa Sang 四象), which respectively represents one-elemented substance, two-elemented substance and four-elemented substance. Especially, Sa Sang was used as a basic framework in which he recognized all the objects and phenomena. So, most critical significance of his substantialism consists in the intention of Sa Sang type classifying. 3. By the method of Sa Sang type classifying, Lee Jae-Ma not only redefined the main concepts of confucianism and developed a unique philosophy of his own, but also, in the field of medical science, resystemized and re-explained the structure and function of human body. 4. From the recognition that Activity-Mind-body-Matter (Sa Sang) are four different existence forms of energy 氣 (or four variation types of energy), Yi Jae-Ma thinks that the viscera of human body have a vertical structure of 'four parts 四焦' (upper, mid-upper, mid-lower and lower parts) and its physiological function is operated by the rising and falling action of four energy presentations (sorrow 哀, anger 怒, joy 喜 and pleasure 樂). 5. In "Gyuk Chi Go 格致藁", Lee Jae-Ma understood the concept of joy, anger, sorrow and pleasure on the basis of nature-emotion theory 性情論 from the philosophical viewpoint. But, from the medical viewpoint of "Dong Eui Su Se Bo Won 東醫壽世保元", he understood them on the basis of vital energy theory. That is, sorrow, anger, joy and pleasure are expression of advance or reverse of nature vital-energy 性氣 and emotion vital-energy 情氣. 6. The rising and falling action principle of four energy presentations (sorrow, anger, joy and pleasure) which produces and helps each other is an identical principles of Sa Sang Medicine, distinguished from the Oh-Haeng 五行 circulating principle in Nae Kyung Medicine. Through this principle, Lee Jae-Ma explained the viscera physiology of human body, pathology & diagnosis and pharmacology.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.9 no.6
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• pp.94-104
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• 2010

The capacity of highway is restricted and traffic congestion is caused by increasing traffic demand. Also, greenhouse gases are increased by traffic congestion. CDM (Clean Development Mechanism) is an idea of interest to reduce greenhouse gases. However, CDM's cases applied in traffic field are rare. Thus, it is necessary that methodology to reduce greenhouse gas should be developed and applied to CDM. A methodology for identifying greenhouse gas emissions was developed in this paper. This methodology was developed on the basis of baseline methodology registered at UN. Travel time and speed in the conventional traffic condition and in the automated traffic condition are compared by BPR function. The calculated speed applied to emission factor equation and then $CO_2$ emissions was calculated. A simulation was executed to evaluate the validity of the developed methodology. In the result, advanced vehicle's $CO_2$ emissions are more than conventional vehicle's $CO_2$ emissions in the stable flow condition. However, advanced vehicle's $CO_2$ emissions are less than conventional vehicle's $CO_2$ emissions in the unstable flow condition. It is assure that capacity of highway is enhanced and efficiency of highway is improved by adopting advanced safety vehicle in the smart road.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.4
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• pp.682-691
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• 2017

In this paper, we propose the fusion design methodology of both pedestrian detection and object tracking system realized with the aid of HOG-PCA based RBFNN pattern classifier. The proposed system includes detection and tracking parts. In the detection part, HOG features are extracted from input images for pedestrian detection. Dimension reduction is also dealt with in order to improve detection performance as well as processing speed by using PCA which is known as a typical dimension reduction method. The reduced features can be used as the input of the FCM-based RBFNNs pattern classifier to carry out the pedestrian detection. FCM-based RBFNNs pattern classifier consists of condition, conclusion, and inference parts. FCM clustering algorithm is used as the activation function of hidden layer. In the conclusion part of network, polynomial functions such as constant, linear, quadratic and modified quadratic are regarded as connection weights and their coefficients of polynomial function are estimated by LSE-based learning. In the tracking part, object tracking algorithms such as mean shift(MS) and cam shift(CS) leads to trace one of the pedestrian candidates nominated in the detection part. Finally, INRIA person database is used in order to evaluate the performance of the pedestrian detection of the proposed system while MIT pedestrian video as well as indoor and outdoor videos obtained from IC&CI laboratory in Suwon University are exploited to evaluate the performance of tracking.

• Convergence Security Journal
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• v.12 no.4
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• pp.25-31
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• 2012

The SSE-CMM model is how to verify the level of information protection as a process-centric information security products, systems and services to develop the ability to assess the organization's development. The CMM is a model for software developers the ability to assess the development of the entire organization, improving the model's maturity level measuring. However, this method of security engineering process improvement and the ability to asses s the individual rather than organizational level to evaluate the ability of the processes are stopped. In this research project based on their existing research information from the technical point of view is to define the maturity level of protection. How to diagnose an information security vulnerabilities, technical security system, verification, and implementation of technical security shall consist of diagnostic status. The proposed methodology, the scope of the work place and the current state of information systems at the level of vulnerability, status, information protection are implemented to assess the level of satisfaction and function. It is possible that measures to improve information security evaluation based on established reference model as a basis for improving information security by utilizing leverage.