• Journal of The Korean Society of Agricultural Engineers
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• v.50 no.3
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• pp.91-104
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• 2008

This study developed the WSM (weighted scenario method)-AHP method that can optimize the weighting value for multi-criteria to make GIS grid-based potential surface. The potential surface has been used to simulate urban expansion using distributed cellular automata model and to generate land-use planning as basic data. This study formulated the WSM-AHP method in mathematically and applied to test region, Suwon city, which located on south area from Seoul. WSM-AHP method generates potential map for each pair of weighting value for all criteria, which one criterion is weighted with high weighting value and the others use low weighting value, considering that the summation for all criteria weighting values should be "1". The potential change rate to the step of weighted scenario for weighting value of criteria is standardized like AHP intensity matrix in this study. From the standard potential change rate, WSM-AHP intensity matrix is completed, and then the optimal weighting value is calculated from the maximum eigenvector of the WSM-AHP matrix, according to the new WSM-AHP method developed in this study. The applied results of new method showed that the optimal weighting value from WSM-AHP is more resonable than the general AHP specialists' evaluation for weighting value. The another new finding of this study is to suggest the deterministic approach to optimize the weighting value for the distributed CA model, which is used to find new city area and to generate rational land-use planning.

• Journal of KIISE:Databases
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• v.37 no.6
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• pp.285-291
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• 2010

In this paper, we propose a new paradigm of weighting methods for naive Bayesian learning. We propose more fine-grained weighting methods, called value weighting method, in the context of naive Bayesian learning. While the current weighting methods assign a weight to an attribute, we assign a weight to an attribute value. We develop new methods, using Kullback-Leibler function, for both value weighting and feature weighting in the context of naive Bayesian. The performance of the proposed methods has been compared with the attribute weighting method and general naive bayesian. The proposed method shows better performance in most of the cases.

• Proceedings of the KIEE Conference
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• 1998.11b
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• pp.481-483
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• 1998

In general, spatial filtering method was proposed to simplify measurement system through parallel Processing hardware. Spatial filtering is a method of detection that we can get a spatial pattern information, as we process a special space pattern, to say, as we process spatial parallel process by using the spatial weighting function. The important processing characteristics will be depended in according to how ire design a spatial weighting function, a spatial sensitive distribution. The form of the weighting function which is realized from the generally used spatial filtering is fixed and the weighting value was already became a binary-value. In this paper, we propose a new method in order to construct adaptive measurement systems. This method is a weighting function design to make multi-valued and variable.

• The KIPS Transactions:PartB
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• v.17B no.5
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• pp.381-388
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• 2010

Naive Bayesian learning has been widely used in many data mining applications, and it performs surprisingly well on many applications. However, due to the assumption that all attributes are equally important in naive Bayesian learning, the posterior probabilities estimated by naive Bayesian are sometimes poor. In this paper, we propose more fine-grained weighting methods, called value weighting, in the context of naive Bayesian learning. While the current weighting methods assign a weight to each attribute, we assign a weight to each attribute value. We investigate how the proposed value weighting effects the performance of naive Bayesian learning. We develop new methods, using gradient descent method, for both value weighting and feature weighting in the context of naive Bayesian. The performance of the proposed methods has been compared with the attribute weighting method and general Naive bayesian, and the value weighting method showed better in most cases.

• Journal of Environmental Impact Assessment
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• v.10 no.1
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• pp.59-71
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• 2001

This study aims to propose a determinant model to select a method on calculating weight of each indicator for environmental evaluation. According to analyzing and comparing with three types of methods for calculating weights which are usually used to evaluate environment with indicators, the weights which were obtained by each type were all different from each other. This means that a differential weighting method must be applied to each of environmental evaluation studies. Therefore, a determinant model is required to determine weight-calculating methods. Three types of weighting methods, such as weighting by importance degree, weighting by eigen-value and weighting by analytic hierarchy process, were compared. Under the necessity, a determinant model was drawn for selecting a compatible method to calculate weights of indicators in environmental evaluation.

• Proceedings of the IEEK Conference
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• 2000.06d
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• pp.123-126
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• 2000

In this paper, we propose new watermarking technique using weighting factor decision method in the watermark embedding step and adaptive threshold decision method in the watermark extracting step. In our method, we are determined weighting factor in simple by calculating distance between pixel coefficient and neighborhood pixel coefficients and threshold is adaptively determined by searching the minimized extract error value using histogram of difference value.

• Journal of computational fluids engineering
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• v.15 no.2
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• pp.55-61
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• 2010

A dependence of weighting parameter in preconditioning method for solving low Mach number flow with incompressible flow nature is investigated. The present preconditioning method employs a finite-difference method applied Roe‘s flux difference splitting approximation with the MUSCL-TVD scheme and 4th-order Runge-Kutta method in curvilinear coordinates. From the computational results of benchmark flows through a 2-D backward-facing step duct it is confirmed that there exists a suitable value of the weighting parameter for accurate and stable computation. A useful method to determine the weighting parameter is introduced. With this method, high accuracy and stable computational results were obtained for the flow with low Mach number in the range of Mach number less than 0.3.

• 제어로봇시스템학회:학술대회논문집
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• 1999.10a
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• pp.266-269
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• 1999

An electronically Scannable microphone system is in the Planning stage. For this Purpose, a multiple microphone array with controllable delay is available. To achieve effective point-listening characteristics, we proposed an enclosed microphone array system with a complex weighting method. In this system, both the microphone arrangement and the value of the complex weighting are important. In this report, the construction of microphone array system and the signal-processing method are explained, and the calculation method for optimal complex weighting is also presented. A prototype experimental setup is designed and fabricated to verify the expected characteristics.

• Journal of the Korea Institute of Military Science and Technology
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• v.11 no.4
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• pp.68-75
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• 2008

This paper proposes a new data hiding method for binary images using the weighting value of pixel-value differencing. The binary cover image is partitioned into non-overlapping sub-blocks and find the most suitable position to embed a secret bit for each sub-block. The proposed method calculates the weighted value for a sub-block to pivot a pixel to be changed. This improves the image quality of the stego-image. The experimental results show that the proposed method achieves a good visual quality and high capacity.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.4 no.5
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• pp.910-924
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• 2010

As Internet usage has increased, the risk of adolescents being exposed to adult content and harmful information on the Internet has also risen. To help prevent adolescents accessing this content, a novel detection method for adult images is proposed. The proposed method involves three steps. First, the Image Of Interest (IOI) is extracted from the image background. Second, the IOI is distinguished from the segmented image using a novel weighting mask, and it is determined to be acceptable or unacceptable. Finally, the features (color and texture) of the IOI or original image are compared to a critical value; if they exceed that value then the image is deemed to be an adult image. A Receiver Operating Characteristic (ROC) curve analysis was performed to define this optimal critical value. And, the textural features are identified using a gray level co-occurrence matrix. The proposed method increased the precision level of detection by applying a novel weighting mask and a receiver operating characteristic curve. To demonstrate the effectiveness of the proposed method, 2850 adult and non-adult images were used for experimentation.