• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.6
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• pp.77-86
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• 2008

Traditional cluster-based routing method is a representative method for increasing the energy efficiencies. In these cluster-based routing methods, the selected cluster head collect/aggregate the information and send the aggregated information to the base station. But they have to solve the unnecessary energy dissipation of frequent information exchange between the cluster head and whole member nodes in cluster. In this paper, we minimize the frequency of the information exchange for reducing the unnecessary transmit/receive frequencies as calculate the overlapped area or number of overlapped member nodes between the selected cluster head and previous cluster head in the setup phase. And besides, we consider the direction of super cluster head for optimal cluster formation. So, we propose the modified cluster selection scheme that optimizes the energy dissipation in the setup phase and reuses the saved energy in the steady phase efficiently that prolongs the whole wireless sensor network lifetime by uniformly selecting the cluster head.

• The Journal of the Acoustical Society of Korea
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• v.24 no.1
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• pp.29-37
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• 2005

This paper proposes an automatic genre classification system for Korean traditional music. The Proposed system accepts and classifies queried input music as one of the six musical genres such as Royal Shrine Music, Classcal Chamber Music, Folk Song, Folk Music, Buddhist Music, Shamanist Music based on music contents. In general, content-based music genre classification consists of two stages - music feature vector extraction and Pattern classification. For feature extraction. the system extracts 58 dimensional feature vectors including spectral centroid, spectral rolloff and spectral flux based on STFT and also the coefficient domain features such as LPC, MFCC, and then these features are further optimized using SFS method. For Pattern or genre classification, k-NN, Gaussian, GMM and SVM algorithms are considered. In addition, the proposed system adopts MFC method to settle down the uncertainty problem of the system performance due to the different query Patterns (or portions). From the experimental results. we verify the successful genre classification performance over $97{\%}$ for both the k-NN and SVM classifier, however SVM classifier provides almost three times faster classification performance than the k-NN.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.34 no.11
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• pp.1757-1763
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• 2010

Flywheel energy storage system (FESS) is defined as a high speed rotating flywheel system that can save surplus electric power. The FESS is proposed as an efficient energy storage system because it can accumulate a large amount of energy when it is operated at a high rotating speed and no mechanical problems are encountered. The FESS consists of a shaft, flywheel, motor/generator, bearings, and case. It is difficult to simulate rotor dynamics using common structure simulation programs because these programs are based on the 3D model and complex input rotating conditions. Therefore, in this paper, a program for the FESS based on the 2D FEM was developed. The 2D FEM can model easier than 3D, and it can present the multi-layer rotor with different material each other. Stiffness changing of the shaft caused by shrink fitting of the hub can be inputted to get clear solving results. The results obtained using the program were compared with those obtained using the common programs to determine any errors.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.6
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• pp.89-98
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• 2005

Fingerprint segmentation and ridge orientation estimation algorithms with images from a mobile camera are proposed. The fingerprint images from a mobile camera are quite different from those from conventional sensor, called touch based sensor such as optical, capacitive, and thermal. For example, the images from a mobile camera are colored and the backgrounds or non-finger regions are very erratic depending on how the image capture time and place. Also the contrast between ridge and valley of a mobile camera image are lower than that of touch based sensor image. To segment fingerprint region, we first detect the initial region using color information and texture information. The LUT (Look Up Table) is used to model the color distribution of fingerprint images using manually segmented images and frequency information is extracted to discriminate between in focused fingerprint regions and out of focused background regions. With the detected initial region, the region growing algerian is executed to segment final fingerprint region. In fingerprint orientation estimation, the problem of gradient based method is very sensitive to outlier that occurred by scar and camera noise. To solve this problem, we propose a robust regression method that removes the outlier iteratively and effectively. In the experiments, we evaluated the result of the proposed fingerprint segmentation algerian using 600 manually segmented images and compared the orientation algorithms in terms of recognition accuracy.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.2
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• pp.165-172
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• 2010

In clinical data minig, choosing the optimal subset of features is such important, not only to reduce the computational complexity but also to improve the usefulness of the model constructed from the given data. Moreover the threshold values (i.e., cut-off points) of selected features are used in a clinical decision criteria of experts for differential diagnosis of diseases. In this paper, we propose a fuzzy discretization approach, which is evaluated by measuring the degree of separation of redundant attribute values in overlapping region, based on spatial distribution of data with continuous attributes. The weighted average of the redundant attribute values is then used to determine the threshold value for each feature and rough set theory is utilized to select a subset of relevant features from the overall features. To verify the validity of the proposed method, we compared experimental results, which applied to classification problem using 668 patients with a chief complaint of dyspnea, based on three discretization methods (i.e., equal-width, equal-frequency, and entropy-based) and proposed discretization method. From the experimental results, we confirm that the discretization methods with fuzzy partition give better results in two evaluation measures, average classification accuracy and G-mean, than those with hard partition.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.1
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• pp.140-145
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• 2010

In this work, to theoretically analyze the nonlinear charging characteristic, a Radial Basis Function Neural Network (RBFNN) is adopted. Based on the RBFNN, an charging characteristic tendency of a Linear Type Magnetic Flux Pump (LTMFP) is analyzed. In the paper, we developed the LTMFP that generates stable and controllable charging current and also experimentally investigated its charging characteristic in the cryogenic system. From these experimental results, the charging current of the LTMFP was also found to be frequency dependent with nonlinear quality due to the nonlinear magnetic behaviour of superconducting Nb foil. On the whole, in the case of essentially cryogenic experiment, since cooling costs loomed large in the cryogenic environment, it is difficult to carry out various experiments. Consequentially, in this paper, we estimated the nonlinear characteristic of charging current as well as realized the intelligent model via the design of RBFNN based on the experimental data. In this paper, we view RBF neural networks as predominantly data driven constructs whose processing is based upon an effective usage of experimental data through a prudent process of Fuzzy C-Means clustering method. Also, the receptive fields of the proposed RBF neural network are formed by the FCM clustering.

• Journal of Korea Water Resources Association
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• v.55 no.4
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• pp.279-289
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• 2022

Since the frequency of heavy rainfall is increasing due to climate change, water levels in the river exceed past historical records. The rating-curve is to convert water level into flow dicscharge from the regression analysis of the water level and corresponding flow discharges. However, the rating-curve involves many uncertainties because of the limited data especially when observed water level exceed past historical water levels. In order to compensate for insufficient data and increase the accuracy of flow discharge data, this study estimates the flow discharge in the river computed mathematically using Monte Carlo simulation based on a 1D hydrodynamic numerical model. Based on the existing rating curve, a random combination of coefficients constituting the rating-curve creates a number of virtual rating curve. From the computed results of the hydrodynamic model, it is possible to estimate flow discharge which reproduces best fit to the observed water level. Based on the statistical evaluation of these samples, a method for mathematically estimating the water level and flow discharge of all cross sections is porposed. The proposed methodology is applied to the junction of Yochoen Stream in the Seomjin River. As a result, it is confirmed that the water level reproducibility was greatly improved. Also, the water level and flow discharge can be calculated mathematically when the proposed method is applied.

• Korean Journal of Community Nutrition
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• v.28 no.3
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• pp.235-244
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• 2023

Objectives: Based on the results from the Korean Total Diet Study (KTDS), the sodium (Na) and potassium (K) intake of Koreans were estimated and compared with intake estimates from the Food & Nutrient Database (FNDB), as in the Korea National Health and Nutrition Examination Survey (KNHANES) to verify the validity of these estimates. Methods: One hundred and thirty-four representative foods (RFs) covering 92.5% of the total food intake of Koreans were selected, and 228 pairs of corresponding 'RF x representative cooking method' were derived by reflecting the methods used mainly in terms of frequency and quantity in their cooking. RF samples were collected from three cities with a larger population size in three regions (nine cities) nationwide, and six composite samples were made for each RF, considering its regional and/or seasonal characteristics. One thousand three hundred and sixty-eight 'RF x representative cooking method' pair samples were prepared, and the Na and K contents were assessed using inductively coupled plasma atomic emission spectrometry (ICP-MS). The Na and K intake of the Korean population was estimated by linking the content with the food intake data from the 7th KNHANES. Results: The mean Na and K intake of Koreans were 2,807.4 mg and 2,335.0 mg per person per day, respectively. A comparison with the Na and K intake from KNHANES, including only RFs of KTDS, showed comparable results with less than 5% variation. While the contribution and ranking of food items to Na intake were similar between KNHANES and KTDS, there were differences in K intake. This was attributed to the large discrepancies in the K content of rice and coffee between KTDS results and the values in the 9th Revision of the National Food Composition Table used in KNHANES. Conclusions: The Na and K intake of Koreans estimated based on the KTDS, which performed nutrient analysis on samples prepared to a 'table-ready' state using foods of the representative collection, was similar and comparable with that of KNHANES. This supports the validity and usefulness of FNDB-based nutrient intake estimation at the population level. The list of nutrients studied in KTDS is expected to be expanded, allowing for intake estimation of nutrients with currently insufficient or absent information in the FNDBs in use.

• Journal of Korea Entertainment Industry Association
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• v.13 no.6
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• pp.187-202
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• 2019

The main goal of this study is to investigate influence of trust in physical education (PE) teachers and immersion experience in PE classes on attitude and satisfaction during PE classes. Total 863 middle school students in Gwang-ju metropolitan area were recruited by utilizing a convenience sampling method. All data were analyzed by using SPSS statistic program ver. 25.0 (frequency analysis, exploratory factor analysis, reliability analysis, correlation analysis, multiple regression analysis). Alpha was set at 0.05. The results of this study is summarized as in the following. First, all sub-factors of trust in the PE teachers partially positively or negatively influence sub-factors of attitude during PE classes. Second, sub-factors of satisfaction during PE classes were partially positively affected to trust in the PE teachers. Third, Attitude during PE Classes were found to have partial positive influence on immersion experience in PE classes. Fourth, sub-factors of immersion experience in PE classes have partial positive effect on the sub-factors of satisfaction during PE classes. Thus, in order to the positive attitude and greater satisfaction during PE classes, it is important to establish the trust of PE teachers through maintaining interaction with students, constructing better systemic class, and creating the class conditions based on considering students' ability. In addition, in order to enhance immersion experiences of students during PE classes, it is necessary to set up learning goals and tasks based on ability of students, to study various teaching method, and to make only focusing on the performance based PE classes without grading.

• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.195-211
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• 2014

Cloud computing services provide IT resources as services on demand. This is considered a key concept, which will lead a shift from an ownership-based paradigm to a new pay-for-use paradigm, which can reduce the fixed cost for IT resources, and improve flexibility and scalability. As IT services, cloud services have evolved from early similar computing concepts such as network computing, utility computing, server-based computing, and grid computing. So research into cloud computing is highly related to and combined with various relevant computing research areas. To seek promising research issues and topics in cloud computing, it is necessary to understand the research trends in cloud computing more comprehensively. In this study, we collect bibliographic information and citation information for cloud computing related research papers published in major international journals from 1994 to 2012, and analyzes macroscopic trends and network changes to citation relationships among papers and the co-occurrence relationships of key words by utilizing social network analysis measures. Through the analysis, we can identify the relationships and connections among research topics in cloud computing related areas, and highlight new potential research topics. In addition, we visualize dynamic changes of research topics relating to cloud computing using a proposed cloud computing "research trend map." A research trend map visualizes positions of research topics in two-dimensional space. Frequencies of key words (X-axis) and the rates of increase in the degree centrality of key words (Y-axis) are used as the two dimensions of the research trend map. Based on the values of the two dimensions, the two dimensional space of a research map is divided into four areas: maturation, growth, promising, and decline. An area with high keyword frequency, but low rates of increase of degree centrality is defined as a mature technology area; the area where both keyword frequency and the increase rate of degree centrality are high is defined as a growth technology area; the area where the keyword frequency is low, but the rate of increase in the degree centrality is high is defined as a promising technology area; and the area where both keyword frequency and the rate of degree centrality are low is defined as a declining technology area. Based on this method, cloud computing research trend maps make it possible to easily grasp the main research trends in cloud computing, and to explain the evolution of research topics. According to the results of an analysis of citation relationships, research papers on security, distributed processing, and optical networking for cloud computing are on the top based on the page-rank measure. From the analysis of key words in research papers, cloud computing and grid computing showed high centrality in 2009, and key words dealing with main elemental technologies such as data outsourcing, error detection methods, and infrastructure construction showed high centrality in 2010~2011. In 2012, security, virtualization, and resource management showed high centrality. Moreover, it was found that the interest in the technical issues of cloud computing increases gradually. From annual cloud computing research trend maps, it was verified that security is located in the promising area, virtualization has moved from the promising area to the growth area, and grid computing and distributed system has moved to the declining area. The study results indicate that distributed systems and grid computing received a lot of attention as similar computing paradigms in the early stage of cloud computing research. The early stage of cloud computing was a period focused on understanding and investigating cloud computing as an emergent technology, linking to relevant established computing concepts. After the early stage, security and virtualization technologies became main issues in cloud computing, which is reflected in the movement of security and virtualization technologies from the promising area to the growth area in the cloud computing research trend maps. Moreover, this study revealed that current research in cloud computing has rapidly transferred from a focus on technical issues to for a focus on application issues, such as SLAs (Service Level Agreements).