• Journal of Korean Society of Rural Planning
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• 제10권3호
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• pp.41-51
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• 2004

This study aims to develop a potential evaluation method for urban spatial expansion using remote sensing (RS) and geographic information system (GIS). A multi-criteria evaluation method with several criteria and their weighting values was introduced to evaluate the score and quantification of the potential surface around the existing cities. The six criteria with one geographic factor, slope, and five accessibility factors, time distance from center of the city, national road, interchange of expressway, a big city, and station, were defined for the potential. RS techniques were applied for classification of the actual urban expansion maps between two periods, and GIS functions were used for score of accessibility criteria with a distance decay function from geographic, road and several point maps, which was developed in this study. The new methodology was applied to a test area, Suwon, between 1986 and 1996. In order to optimize the six weighting values, this study made new findings to search the optimal combination of the weighting values from new methodology, weighted scenario method for intensity order (WSM), combined with intensity order and AHP method, including a trial and error method for sensitivity analysis to make the intensity order. The optimal combination of the weighting values by the new method generated the optimal potential surface, considering spatial trend of urban expansion in the test area.

• Communications for Statistical Applications and Methods
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• 제20권6호
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• pp.455-466
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• 2013

In nested case-control studies, the most common way to make inference under a proportional hazards model is the conditional logistic approach of Thomas (1977). Inclusion probability methods are more efficient than the conditional logistic approach of Thomas; however, the epidemiology research community has not accepted the methods as a replacement of the Thomas' method. This paper promotes the inverse probability weighting method originally proposed by Samuelsen (1997) in combination with an approximate jackknife standard error that can be easily computed using existing software. Simulation studies demonstrate that this approach yields valid type 1 errors and greater powers than the conditional logistic approach in nested case-control designs across various sample sizes and magnitudes of the hazard ratios. A generalization of the method is also made to incorporate additional matching and the stratified Cox model. The proposed method is illustrated with data from a cohort of children with Wilm's tumor to study the association between histological signatures and relapses.

• Journal of Advanced Marine Engineering and Technology
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• 제39권1호
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• pp.58-62
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• 2015

Most blog sites provide predefined classes based on contents or topics, but few bloggers choose classes for their posts because of its cumbersome manual process. This paper proposes an automatic blog post classification method that variously combines term frequency, document frequency and class frequency from each classes to find appropriate weighting scheme. In experiment, combination of term frequency, category term frequency and inversed (excepted category's) document frequency shows 77.02% classification precisions.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• 제14권7호
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• pp.677-684
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• 2003

This paper addresses the subblock phase weighting(SPW) method to reduce the PAPR in OFDM system. This method divides the input block of OFDM signal into many subblocks and lower the peak power by weighting the phase of each subblocks properly. SPW method can be realized by only one IFFT. PAPR reduction performance is novelly examined when the adjacent, interleaved and random subblock partitioning schemes are used in the SPW system. The random subblock partition scheme has the most effective. More subblocks can effectively reduce the PAPR, but there is a problem that the processing time of iteration is increased. We propose a new weighting factor combination of the complementary sequence characteristic with threshold technique. OFDM data can be recovered by the inserted side information of weighting factor in the feed forward type. Also, BER performance of this SPW system is analyzed when error happens in the side information.

• Journal of Information Processing Systems
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• 제20권3호
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• pp.296-306
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• 2024

Traditional ecological driving (Eco-Driving) evaluations often rely on mathematical models that predominantly offer subjective insights, which limits their application in real-world scenarios. This study develops a robust, data-driven Eco-Driving evaluation model by integrating dynamic and distributed multi-source data, including vehicle performance, road conditions, and the driving environment. The model employs a combination weighting method alongside K-means clustering to facilitate a nuanced comparative analysis of Eco-Driving behaviors across vehicles with identical energy consumption profiles. Extensive data validation confirms that the proposed model is capable of assessing Eco-Driving practices across diverse vehicles, roads, and environmental conditions, thereby ensuring more objective, comprehensive, and equitable results.

• Journal of Information Processing Systems
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• 제15권6호
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• pp.1489-1502
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• 2019

This work introduces a novel unweighted combination method (UCSS) for business failure perdition (BFP). With considering features of BFP in the age of big data, UCSS integrates the quantitative and qualitative analysis by utilizing soft set theory (SS). We adopt the conventional expert system (ES) as the basic qualitative classifier, the logistic regression model (LR) and the support vector machine (SVM) as basic quantitative classifiers. Unlike other traditional combination methods, we employ soft set theory to integrate the results of each basic classifier without weighting. In this way, UCSS inherits the advantages of ES, LR, SVM, and SS. To verify the performance of UCSS, it is applied to real datasets. We adopt ES, LR, SVM, combination models utilizing the equal weight approach (CMEW), neural network algorithm (CMNN), rough set and D-S evidence theory (CMRD), and the receiver operating characteristic curve (ROC) and SS (CFBSS) as benchmarks. The superior performance of UCSS has been verified by the empirical experiments.

• Korean Journal of Remote Sensing
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• 제22권6호
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• pp.485-493
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• 2006

This study is to combine precipitation data with different spatial-temporal characteristics using an optimal weighting method. This optimal weighting method is designed for combination of AWS rain gage data and S-band RADAR-estimated rain data with weighting function in inverse proportion to own mean square error for the previous time step. To decide the optimal weight coefficient for optimized precipitation according to different training time, the method has been performed on Changma case with a long spell of rainy hour for the training time from 1 hour to 10 hours. Horizontal field of optimized precipitation tends to be smoothed after 2 hours training time, and then optimized precipitation has a good agreement with synoptic station rainfall assumed as true value. This result suggests that this optimal weighting method can be used for production of high-resolution quantitative precipitation rate using various data sets.

• Smart Media Journal
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• 제2권1호
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• pp.31-36
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• 2013

A robust and efficient text extraction is very important for an accuracy of Optical Character Recognition (OCR) systems. Natural scene images with degradations such as uneven illumination, perspective distortion, complex background and multi color text give many challenges to computer vision task, especially in text extraction. In this paper, we propose a method for extraction of the text in signboard images based on a combination of mean shift algorithm and weighting scheme of hue and saturation in HSI color space for clustering algorithm. The number of clusters is determined automatically by mean shift-based density estimation, in which local clusters are estimated by repeatedly searching for higher density points in feature vector space. Weighting scheme of hue and saturation is used for formulation a new distance measure in cylindrical coordinate for text extraction. The obtained experimental results through various natural scene images are presented to demonstrate the effectiveness of our approach.

• Journal of Korea Multimedia Society
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• 제9권2호
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• pp.255-263
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• 2006

It is common that a junk mail has an inconsistency of mail addresses between those of the mail headers and the mail recipients. In addition, users easily know that an email is a junk or legitimate mail only by looking for the title of the email. In this paper, we tried to apply the filtering classifiers of mail address validation check and the combination method of title-content weighting to improve the performance of junk mail filtering system. In order to verify the effectiveness of the proposed method, we performed an experiment by applying them to Naive Bayesian classifier. The experiment includes the unit testing and the combination of the filtering techniques. As a result, we found that our method improved 11.6% of recall and 2.1% of precision that it contributed the enhancement of the junk mail filtering system.

• 유체기계공업학회:학술대회논문집
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• 유체기계공업학회 2003년도 유체기계 연구개발 발표회 논문집
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• pp.627-630
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• 2003

This work presents a numerical procedure to optimize the shape of three-dimensional channel with angled ribs mounted on one of the walls to enhance turbulent heat transfer. The response surface method is used as an optimization technique with Reynolds-averaged Navier-Stokes analysis of flow and heat transfer. SST turbulence model is used as a turbulence closure. The width-to-height ratio of the rib, rib height-to-channel height ratio, pitch-to-rib height ratio and attack angle of the rib are chosen as design variables. The objective function is defined as a linear combination of heat-transfer and friction-loss related terms with weighting factor. D-optimal experimental design method is used to determine the data points. Optimum shapes of the channel have been obtained for the weighting factors in the range from 0.0 to 1.0.