• Journal of Korean Society for Quality Management
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• v.44 no.2
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• pp.389-408
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• 2016

Purpose: This study was designed to analyze the behavioral change of knowledge structures and the trends of research topics in the quality management field. Methods: The network structure and knowledge structure of the words were visualized in map form using co-word analysis, cluster analysis and strategic diagram. Results: Summarizing the research results obtained in this study are as follows. First, the word network derived from co-occurrence matrix had 106 nodes and 5,314 links and its density was analyzed to 0.95. Average betweenness centrality of word network was 2.37. In addition, average closeness centrality and average eigenvector centrality of word network were 0.01. Second, by applying optimal criteria of cluster decision and K-means algorithm to word co-occurrence matrix, 106 words were grouped into seven clusters such as standard & efficiency, product design, reliability, control chart, quality model, 6 sigma, and service quality. Conclusion: According to the results of strategic diagram analysis over time, the traditional research topics of quality management field related to reliability, 6 sigma, control chart topics in the third quadrant were revealed to be declined for their study importance. Research topics related to product design and customer satisfaction were found to be an important research topic over analysis periods. Research topic related to management innovation was emerging state and the scope of research topics related to process model was extended to research topics with system performance. Research topic related to service quality located in the first quadrant was analyzed as the key research topic.

• International Journal of Control, Automation, and Systems
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• v.1 no.2
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• pp.194-202
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• 2003

In this paper, we introduce a category of Multi-FNN (Fuzzy-Neural Networks) models, analyze the underlying architectures and propose a comprehensive identification framework. The proposed Multi-FNNs dwell on a concept of fuzzy rule-based FNNs based on HCM clustering and evolutionary fuzzy granulation, and exploit linear inference being treated as a generic inference mechanism. By this nature, this FNN model is geared toward capturing relationships between information granules known as fuzzy sets. The form of the information granules themselves (in particular their distribution and a type of membership function) becomes an important design feature of the FNN model contributing to its structural as well as parametric optimization. The identification environment uses clustering techniques (Hard C - Means, HCM) and exploits genetic optimization as a vehicle of global optimization. The global optimization is augmented by more refined gradient-based learning mechanisms such as standard back-propagation. The HCM algorithm, whose role is to carry out preprocessing of the process data for system modeling, is utilized to determine the structure of Multi-FNNs. The detailed parameters of the Multi-FNN (such as apexes of membership functions, learning rates and momentum coefficients) are adjusted using genetic algorithms. An aggregate performance index with a weighting factor is proposed in order to achieve a sound balance between approximation and generalization (predictive) abilities of the model. To evaluate the performance of the proposed model, two numeric data sets are experimented with. One is the numerical data coming from a description of a certain nonlinear function and the other is NOx emission process data from a gas turbine power plant.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.2
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• pp.181-189
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• 2013

In this paper, we introduce the fuzzy neural network based on the individual input space to design the pattern recognizer. The proposed networks configure the network by individually dividing each input space. The premise part of the networks is independently composed of the fuzzy partition of individual input spaces and the consequence part of the networks is represented by polynomial functions. The learning of fuzzy neural networks is realized by adjusting connection weights of the neurons in the consequent part of the fuzzy rules and it follows a back-propagation algorithm. In addition, in order to optimize the parameters of the proposed network, we use real-coded genetic algorithms. Finally, we design the optimized pattern recognizer using the experimental data for pattern recognition.

• Proceedings of the KIEE Conference
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• 2002.11c
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• pp.19-22
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• 2002

In this paper, we aims to develop a microcontroll er-based ECG monitoring system and portable pulse oximeter using Compact Flash Interface. First, portable pulse oximeter system is designed to record 2 channel of biosignals simultaneously, including 1 channel of $SpO_2$ and 1 channel of pulse rate. It is very small and portable. Besides, the system makes it possible to measure a patient's condition without an additional medical equipment. We tried to solve the problems generated by a patient's motion. That is, we added an analog circuit to a traditional pulse oximeter in order to eliminate the change of the base line. And we used 2D sector algorithm. As present, SpO2 modules are completed. But there are still many further development needed in order to enhance the function. Especially, compact falsh interface remains the most to complete. Second, ECG monitoring system uses almost same as present 3-lead ECG system. But we focus on the analog part, especially in filter. The proposed filter is composed of two parts. One is a filter to remove the power-line interface. The other is a filter to remove the baseline drift. A filter to remove the power-line and the baseline drift is necessarily used in the ECG system. The implemented filter have three features; minimizing the distortion in DC component, removing the harmonic component of power-line frequency. Using compact flash interface, we can easily transfer a patient's personal information and the measured signal data to a network based server environment. That means, it is possible to implement a patient's monitoring system with low cost.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.4
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• pp.1976-1981
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• 2013

In this paper, we propose a frequency-domain interference cancellation algorithm for direct-sequence spread spectrum systems. In the previously proposed frequency-domain interference cancellation algorithms that protocol defines the rules concerning the collection of means of Transmission Control Protocol (TCP: Transmission Control Protocol) is the most widely used in the transport layer. Two-way traffic through the network path to the same end-to-end transfer of data in the opposite direction between pairs of nodes are infused with two or more TCP connection using the network traffic patterns from the exchanger and routers share results of approval. Per-flow input/output structure of matter using the LTS online reaction when evaluated as this is the most important factor. TCP-MT when the connection duration is one of the largest performance gains.

• Geotechnical Engineering
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• v.13 no.4
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• pp.95-108
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• 1997

For normally consolidated clay, several researchers have developed a number of theoretical time factors to determine the coefficient of consolidation However, depending on the assumptions and analytical techniques, it could considerably vary even for a specific degree of consolidation. In this paper, a method is proposed to determine a consistent coefficient of consolidation over all ranges of degree of consolidation by applying the concept of the Optimum Design Technique. The initial excess pore pressure distribution is assumed to be obtainable by the successive spherical cavity expansion theory. The dissipation of pore pressure is simulated by means of two dimensional linear-uncoupled axisymmetric consolidation analysis. The minimization of the differences between the measured and the predicted excess pore pressures was carried by BFGS unconstrained optimum design algorithm with one dimensional golden section search technique. By analyzing numerical and real field examples, it can be found that the adopted optimum technique gives a consistent and convergent results.

• Clean Technology
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• v.8 no.1
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• pp.27-37
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• 2002

To verify the performance and effectiveness of bilinear model for the development of ozone prediction system, the simulation experiments of the model identification for ozone formation were performed by using bilinear and linear models. And the prediction results of the ozone formation by bilinear model were compared to those of linear model and the measured data of Seoul. ARMA(Autoregressive Moving Average) model was used in the model identification. A recursive parameter estimation algorithm based on an equation error method was used to estimate parameters of model. From the results of model identification experiment, the ozone formation by bilinear model showed good agreement with the ozone formation from the simulator. From the comparison of the prediction results and the measured data, it appears that the method proposed in this work is a reasonable means of developing real-time short-term prediction of ozone formation for an ozone forecast system.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.26 no.3
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• pp.667-678
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• 2016

Due to a development of the cable/wireless network infra, the traffic as big as unable to compare with the past is being served through the internet, the traffic is increasing every year following the change of the network paradigm such as the object internet, especially the traffic of about 1.6 zettabyte is expected to be distributed through the network in 2018. As the network traffic increases, the performance of the security infra is developing together to deal with the bulk terabyte traffic in the security equipment, and is generating hundreds of thousands of security events every day such as hacking attempt and the malignant code. Efficiently analyzing and responding to an event on the attack attempt detected by various kinds of security equipment of company is one of very important assignments for providing a stable internet service. This study attempts to overcome the limit of study such as the detection of Tor network traffic using the existing low-latency by classifying the anonymous network by means of the suggested algorithm about the event detected in the security infra.

• The Journal of Korean Association of Computer Education
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• v.23 no.1
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• pp.53-61
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• 2020

In the information society, the ability of learners to use computers to conduct self-directed learning is important. Indeed, the higher the computer's ability to use computers, the more the academic achievement needs to be analyzed. The purpose of this study was to identify longitudinal trajectories of student awareness of ICT literacy and frequency of computer use. We also examined the effects of the longitudinal patterns on academic achievement and college major choice. A non-parametric approach, K-means for longitudinal data(KML) algorithm, was conducted using 9-year longitudinal data from Seoul Education Longitudinal Study (2010-2018). Findings indicated that a pattern presenting a higher awareness of ICT literacy and frequency of computer use showed better academic achievements and was likely to prefer to choose engineering-related majors.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.9
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• pp.1020-1025
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• 2016

In the recent, the communication market increased every year. Because of the user's demands and exhaustion of wireless resource, we needs a new technology of the communication system. The femtocell is one of the new technology of the communication system. 'Femto' means very small. By using the femtocell that made up the very small cell, the frequency efficiency increase. The femtocell has different cell environments. The Power Control is important for femtocell to avoid interference and unnecessary handover. In this paper, we propose a new femtocell power control that is improvement of handover probability and throughput. And we simulate and check the result.