• Journal of the Korean Data and Information Science Society
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• 제18권2호
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• pp.481-488
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• 2007

The k-means algorithm is well known for its efficiency in clustering large data sets. However, working only on numeric values prohibits it from being used to cluster real world data containing categorical values. The k-modes algorithm is to extend the k-means paradigm to categorical domains. The algorithm requires a pre-setting or random selection of initial points (modes) of the clusters. This paper improved the problem of k-modes algorithm, using the Max-Min method that is a kind of methods to decide initial values in k-means algorithm. we introduce new similarity measures to deal with using the categorical data for clustering. We show that the mushroom data sets and soybean data sets tested with the proposed algorithm has shown a good performance for the two aspects(accuracy, run time).

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2008년도 하계종합학술대회
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• pp.387-388
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• 2008

In this paper, we have designed and fabricated hyperabrupt varactor diodes. Capacitance variations of hyperabrupt-doped varactor diodes are larger than those of uniform-doped varactor diodes. The measured reverse breakdown voltage of the fabricated varactor diodes was about 20 V. For the anode contact diameter of $50\;{\mu}m$, the maximum capacitance of the fabricated varactor diode was 2.1 pF and the minimum capacitance 0.44 pF. Therefore, the $C_{max}/C_{min}$ ratio was 4.77. Also, for the anode contact diameter of $60\;{\mu}m$, the maximum and minimum capacitances were 2.9 and 0.62 pF, respectively. And, thus, the $C_{max}/C_{min}$ ratio was 4.64.

• Journal of applied mathematics & informatics
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• 제20권1_2호
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• pp.209-224
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• 2006

This paper presents an optimization model with performance constraints for two kinds of graph elements layout problem. The layout problem is partitioned into finite subproblems by using graph theory and group theory, such that each subproblem overcomes its on-off nature about optimal variable. Furthermore each subproblem is relaxed and the continuity about optimal variable doesn't change. We construct a min-max problem which is locally equivalent to the relaxed subproblem and develop the first order necessary and sufficient conditions for the relaxed subproblem by virtue of the min-max problem and the theories of convex analysis and nonsmooth optimization. The global optimal solution can be obtained through the first order optimality conditions.

• Asian Pacific Journal of Cancer Prevention
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• 제17권3호
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• pp.1197-1199
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• 2016

Background: This study aimed to facilitate decision-making in cases of breast cancer radiotherapy shifts by simulating millimetric shifts and analyzing their effects on dose distribution. Methods: The study included 30 patients with left side breast cancer who were treated with three dimensional conformal radiotherapy (3D-CRT) in the Radiation Oncology Department in Hatay Public Hospital, between January 2013 and April 2015. A treatment plan shifting at three axes with six different measures was simulated. Results: The biggest difference in values was (+3mm shift) 476cGy, with a 7.7 % change for heart and 25.6% for spinal cord. The shifts in values respectively for CTV min, mean, max were -4.8%, 2.5%, 4%. The differences for lymphatic min, mean, max were 21.3%, 20.3%, -12.2%. Conclusion: The most important thing is not the treatment plan quality, but its practicality. The treatment plan must be practical and its practice must be controlled rigidly.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2007년도 심포지엄 논문집 정보 및 제어부문
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• pp.92-94
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• 2007

This paper considers an optimal control problem for a remote control to an electrical drive system with a DC motor. Since it is a linear control system with time-delay subject to unknown but bounded disturbance, we construct a worst-case feedback control policy. This policy can guarantee that, for all admissible uncertain disturbances, the real system state should be in a prescribed neighborhood of a desired value, and the cost functional takes the best guarantee value. The worst-case feedback control policy is allowed to be corrected at one correction point between the initial to the final time, which is equivalent to solving a 1-level min-max problem. Since the min-max problem at the stage does not yield a simple analytical solution, we consider an approximate control policy, which is equivalent and can be solved explicitly m the numerical experiments.

• 정보통신설비학회논문지
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• 제10권2호
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• pp.80-85
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• 2011

In this paper, I propose flexible base point used for a BTC(Block Truncation Coding). Halftoning images are used for printer by reducing the number of pixel depth. During over 20 years, many researches have been studied to apply this techniques to image compression. BTC algorithms are the compression methods using digital halftoning technique about images. In the BTC algorithm, an image block is divided into higher and lower domain compared with the mean of block. then the MAX and MIN representative values are evaluated by calculating the mean of higher and lower domain respectively. At a result, an image block(for example 88 size) is compressed into 64bits pixel representation and 16 bits of the MAX and MIN. And they also have been tried to sustain the image quality high after compression. In this paper, I found that there is some marginal possibility to enhance the image quality by adjusting the base point(generally mean of block) of existing algorithms.

• Structural Engineering and Mechanics
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• 제75권2호
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• pp.239-246
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• 2020

In this paper, a novel analytical method, Max-Min Approach (MMA), has been presented and applied to consider the nonlinear vibration of dry cask storage systems. The nonlinear governing equation of the structure has been developed using the shell theory. The MMA results are compared with numerical solutions derived by Runge-Kutta's Method (RKM). The results indicate a satisfying agreement between MMA and numerical solutions. Parametric studies have been conducted on the nonlinear frequency of dry casks. The phase-plan of the problem is also presented and discussed. The proposed approach can potentially ca be extended to highly nonlinear problems.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2011년도 학술발표회
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• pp.473-473
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• 2011

Group method of data handling neural networks model (GMDH-NNM) is used to estimate daily reference evapotranspiration (ETo) using limited climatic variables such as max temperature ($T_{max}$), min temperature ($T_{min}$), mean wind speed ($W_{mean}$), mean relative humidity ($RH_{mean}$) and sunshine duration (SD). And, for the performances of GMDH-NNM, it consists of training and test performances, respectively. The training and test performances are carried out using daily time series data, respectively. From this research, we evaluate the impact of GMDH-NNM for the modeling of the nonlinear time series data. We should, thus, construct the credible data of the daily ETo data using GMDH-NNM, and can suggest the methodology for the irrigation and drainage networks system. Furthermore, this research represents that the strong nonlinear relationship such as ETo modeling can be generalized using GMDH-NNM.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제7권12호
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• pp.3149-3165
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• 2013

Content based image retrieval is increasingly gaining popularity among image repository systems as images are a big source of digital communication and information sharing. Identification of image content is done through feature extraction which is the key operation for a successful content based image retrieval system. In this paper content based image retrieval system has been developed by adopting a strategy of combining multiple features of shape, color and relevance feedback. Shape is served as a primary operation to identify images whereas color and relevance feedback have been used as supporting features to make the system more efficient and accurate. Shape features are estimated through second derivative, least square polynomial and shapes coding methods. Color is estimated through max-min mean of neighborhood intensities. A new technique has been introduced for relevance feedback without bothering the user.

• 전기의세계
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• 제49권9호
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• pp.9-16
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• 2000

A receding horizon $H_{\infty}$ predictive control method is derived by solving a min-max problem in non-recursive forms. The min-max cost index is converted to a quadratic form which for systems with input saturation can be minimized using QP. Through the use of closed-loop prediction the prediction of states the use of closed-loop prediction the prediction of states in the presence of disturbances are made non-conservative and it become possible to get a tighter $H_{\infty}$ norm bound. Stability conditions and $H_{\infty}$ norm bounds on disturbance rejection are obtained in infinite horizon sence. Polyhedral types of feasible sets for sets and disturbances are adopted to deal with the input constraints. The weight selection procedures are given in terms of LMIs and the algorithm is formulated so that it can be solved via QP. This work is a modified version of an earlier work which was based on ellipsoidal type feasible sets[15].