• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.4
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• pp.203-210
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• 2017

Data clustering is one of the most difficult and challenging problems and can be formally considered as a particular kind of NP-hard grouping problems. The K-means algorithm is one of the most popular and widely used clustering method because it is easy to implement and very efficient. However, it has high possibility to trap in local optimum and high variation of solutions with different initials for the large data set. Therefore, we need study efficient computational intelligence method to find the global optimal solution in data clustering problem within limited computational time. The objective of this paper is to propose a combined artificial bee colony (CABC) with K-means for initialization and finalization to find optimal solution that is effective on data clustering optimization problem. The artificial bee colony (ABC) is an algorithm motivated by the intelligent behavior exhibited by honeybees when searching for food. The performance of ABC is better than or similar to other population-based algorithms with the added advantage of employing fewer control parameters. Our proposed CABC method is able to provide near optimal solution within reasonable time to balance the converged and diversified searches. In this paper, the experiment and analysis of clustering problems demonstrate that CABC is a competitive approach comparing to previous partitioning approaches in satisfactory results with respect to solution quality. We validate the performance of CABC using Iris, Wine, Glass, Vowel, and Cloud UCI machine learning repository datasets comparing to previous studies by experiment and analysis. Our proposed KABCK (K-means+ABC+K-means) is better than ABCK (ABC+K-means), KABC (K-means+ABC), ABC, and K-means in our simulations.

• Journal of Korean Society on Water Environment
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• v.23 no.4
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• pp.490-497
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• 2007

A Combined sewer overflows (CSOs) are themselves a significant source of water pollution. Therefore, the control of urban drainage for CSOs reduction and receiving water quality protection is needed. Examples in combined sewer systems include downstream storage facilities that detain runoff during periods of high flow and allow the detained water to be conveyed by an interceptor sewer to a centralized treatment plant during periods of low flow. The design of such facilities as stormwater detention storage is highly dependant on the temporal variability of storage capacity available (which is influenced by the duration of interevent dry periods) as well as the infiltration capacity of soil and recovery of depression storage. As a result, a continuous approach is required to adequately size such facilities. This study for the continuous long-term analysis of urban drainage system used analytical probabilistic model based on derived probability distribution theory. As an alternative to the modeling of urban drainage system for planning or screening level analysis of runoff control alternatives, this model have evolved that offer much ease and flexibility in terms of computation while considering long-term meteorology. This study presented rainfall and runoff characteristics of the subject area using analytical probabilistic model. This study presented the average annual COSs and number of COSs when the interceptor capacity is in the range $3{\times}DWF$ (dry weather flow). Also, calculated the average annual mass of pollutant lost in CSOs using Event Mean Concentration. Finally, this study presented a decision of storage volume for CSOs reduction and water quality protection.

• Proceedings of the KSME Conference
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• 2007.05b
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• pp.1986-1991
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• 2007

KEPRI has studied anode-supported planar SOFCs and kW class stacks operated at intermediate temperature for development of a combined heat and power unit. A single cell composed of Ni-YSZ/FL/ScSZ/LSCF showed the maximum power density of 0.55 W/$cm^2$ at $650^{\circ}C$ and 1.8 W/$cm^2$ at $750^{\circ}C$. With 37 cells of 10${\times}10cm^2$ and stainless steel interconnects, a 1kW class SOFC stack was manufactured. When a 1kW class SOFC system was operated at $750^{\circ}C$ with city gas, it showed the power output of 1.3 kWe at 50 A. It also recuperated heat of 0.57-1.2 kWth according to the loaded current through combustion of unreacted anode off-gas. Recently, KEPRI is developing a new kW class SOFC stack and system to increase efficiency and durability at intermediate temperature.

• Transactions of The Korea Fluid Power Systems Society
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• v.2 no.4
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• pp.14-22
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• 2005

The safety factor of hydraulic piston pumps & motors due to high pressurization, high speedization and low weight/volume realization to enhance the output density shows a tendency to decrease. Therefore more effective test methods are necessary to predict the exact life. The failure of hydraulic pumps & motors operating in high pressure and high speed mainly occurs in piston-shoe assemblies, and the major failure mode is wearout of the shoe surface. The sensitive parameters in the endurance life test are speed, pressure and temperature, and the failure production increases in proportion to the operating time. In this research, the authors propose the combined accelerated life test model using the analysis method of the combined accelerated life test results of piston-shoe assemblies by applying simultaneously high speed, high pressure and high temperature in accordance with variation of speed, pressure and temperature to reduce the life test time.

• Journal of computational fluids engineering
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• v.16 no.2
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• pp.1-10
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• 2011

A new computational program, which is based on the CIP/CCUP(Constraint Interpolation Profile/CIP Combined Unified Procedure) method, has been developed to numerically analyse sloshing phenomena dealt as multiphase-flow problems. For the convection terms of Navier-Stokes equations, the RCIP(Rational function CIP) method was adopted and the THINC-WLIC(Tangent of Hyperbola for Interface Capturing-Weighted Line Interface Calculation) method was used to capture the air/water interface. To validate the present numerical method, two-dimensional dam-breaking and sloshing problems in a rectangular tank were solved by the developed method in a stationary Cartesian grid system. In the case of sloshing problems, simulations by using a improved MPS(Moving Particle Simulation) method, which is named as PNU-MPS(Pusan National University-MPS), were also carried out. The computational results are compared with those of experiments and most of the comparisons are reasonably good.

• Journal of Positioning, Navigation, and Timing
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• v.4 no.4
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• pp.205-211
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• 2015

The Global Navigation Satellite System (GNSS) is undergoing dramatic changes. Nowadays, much more satellites are transmitting navigation data at more frequencies. A multi-GNSS analysis is performed to improve the positioning accuracy by processing combined observations from different GNSS. The multi-GNSS technique can improve significantly the positioning accuracy. In this paper, we present a combined Global Positioning System (GPS), the GLObal NAvigation Satellite System (GLONASS), the China Satellite Navigation System (BeiDou), and the Quasi-Zenith Satellite System (QZSS) standard point positioning (SPP) method to exploit all currently available GNSS observations at Mokpo (MKPO) station in South Korea. We also investigate the multi-GNSS data recorded at MKPO reference station. The positioning accuracy is compared with several combinations of the satellite systems. Because of the different frequencies and signal structure of the different GNSS, intersystem biases (ISB) parameters for code observations have to be estimated together with receiver clocks in multi-GNSS SPP. We also present GPS/GLONASS and GPS/BeiDou ISB values estimated by the daily average.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.2
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• pp.687-701
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• 2020

In the production of industrial fabric, it needs automatic real-time system to detect defects on the fabric for assuring the defect-free products flow to the market. At present, many visual-based methods are designed for detecting the fabric defects, but they usually lead to high false alarm. Base on this reason, we propose a Sobel operator combined with patch statistics (SOPS) algorithm for defects detection. First, we describe the defect detection model. mean filter is applied to preprocess the acquired image. Then, Sobel operator (SO) is applied to deal with the defect image, and we can get a coarse binary image. Finally, the binary image can be divided into many patches. For a given patch, a threshold is used to decide whether the patch is defect-free or not. Finally, a new image will be reconstructed, and we did a loop for the reconstructed image to suppress defects noise. Experiments show that the proposed SOPS algorithm is effective.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.4
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• pp.1760-1778
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• 2018

For image segmentation with intensity inhomogeneity, many region-based level set methods have been proposed. Some of them however can't get the relatively ideal segmentation results under the severe intensity inhomogeneity and weak edges, and without use of the image gradient information. To improve that, we propose a new level set method combined with local direction gradient in this paper. Firstly, based on two assumptions on intensity inhomogeneity to images, the relationships between segmentation objects and image gradients to local minimum and maximum around a pixel are presented, from which a new pixel classification method based on weight of Euclidian distance is introduced. Secondly, to implement the model, variational level set method combined with image spatial neighborhood information is used, which enhances the anti-noise capacity of the proposed gradient information based model. Thirdly, a new diffusion process with an edge indicator function is incorporated into the level set function to classify the pixels in homogeneous regions of the same segmentation object, and also to make the proposed method more insensitive to initial contours and stable numerical implementation. To verify our proposed method, different testing images including synthetic images, magnetic resonance imaging (MRI) and real-world images are introduced. The image segmentation results demonstrate that our method can deal with the relatively severe intensity inhomogeneity and obtain the comparatively ideal segmentation results efficiently.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.6
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• pp.2870-2888
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• 2017

Recent studies have shown that the flow table size of hardware SDN switch cannot match the number of concurrent flows. Combined SDN Forwarding Element (CFE), which comprises several software switches and a hardware switch, becomes an alternative approach to tackle this problem. Due to the limited capacity of software switch, the way to route concurrent flows in CFE can largely affect the maximum delay that a flow suffers at CFE. As delay-guarantee is a nontrivial task for network providers with the increasing number of delay-sensitive applications, we propose an analytical model of CFE to evaluate a rules placement solution first. Next, we formulate the problem of Rules Placement with delay guarantee in CFE (RPCFE), and present the genetic-based rules placement (GARP) algorithm to solve the RPCFE problem. Further, we validate the analytical model of CFE through simulations in NS-3 and compare the performance of GARP with three benchmark algorithms.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.28 no.2
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• pp.18-26
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• 2005

The balanced scorecard(BSC) overcomes the limit of traditional financial statement that focuses on only financial performance. BSC is widely used in government and industry because of the clear representation of the relationship and logic between the key performance indicators(KPI) of 4 perspectives - financial, customer, internal process, and loaming and growth. However, traditional BSC does not consider evaluating the difference between the results measured by BSC. By using relatively small number of inputs and outputs In comparing decision-making units, data envelopment analysis(DEA) can aggregate multiple performance measures. In this research, we propose a methodology named CDB(Combined DEA and BSC) to evaluate the performance of organization considering financial and non-financial perspectives. CDB uses KPI of cause-and-effect relationship on BSC as inputs and outputs of DEA method. In addition, this research proposes a method of converting the KPI of BSC to the input and output variables of DEA, and enhancing discrimination power using the limit number of variables. We illustrate the methodology by giving an example of evaluating aquisition-unit efficiency in a supply chain.