• Journal of the Korean Data and Information Science Society
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• v.18 no.4
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• pp.879-890
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• 2007

Statistical matching is a method of data integration for data sources that do not share the same units. It could produce rapidly lots of new information at low cost and decrease the response burden affecting the quality of data. This paper proposes a statistical matching technique combining k-NN (k-nearest neighborhood) and regression methods. We select k records in a donor file that have similarity in value with a specific observation of the common variable in a recipient file and estimate an imputation value for the recipient file, using regression modeling in the donor file. An empirical comparison study is conducted to show the properties of the proposed method.

• Journal of Korean Society for Geospatial Information Science
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• v.14 no.4 s.38
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• pp.71-77
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• 2006

Support Vector Machine (SVM) which has roots in a statistical learning theory is a training algorithm based on structural risk minimization. Generally, SVM algorithm uses the kernel for determining a linearly non-separable boundary and classifying the data. But, classical kernels can not apply to effectively the hyperspectral image classification because it measures similarity using vector's dot-product or euclidian distance. So, This paper proposes the spectral similarity kernel to solve this problem. The spectral similariy kernel that calculate both vector's euclidian and angle distance is a local kernel, it can effectively consider a reflectance property of hyperspectral image. For validating our algorithm, SVM which used polynomial kernel, RBF kernel and proposed kernel was applied to land cover classification in Hyperion image. It appears that SVM classifier using spectral similarity kernel has the most outstanding result in qualitative and spatial estimation.

• Journal of the Korean Society of Clothing and Textiles
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• v.26 no.3_4
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• pp.431-442
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• 2002

The purpose of this study was to identify the importance of salesperson selling behavior such as salesperson's orientation, similarity with customers and expertise as well as the relationship benefits of salesperson. A total of 400 questionnaires were distributed to adults in Daegu-Kyongbuk area and 335 questionnaires were collected(84%) and 314 samples were used for the statistical analysis. The primary methods of the statistical analysis were factor analysis, confirmatory factor analysis, correlation and path analysis using LISREL 8. The results are as follows: First, clothings salesperson's customer-orientation(p < .10), expertise, similarity (p< .10) and salesperson's functional, social benefits showed positive relation with customer satisfaction. And salesperson's selling-orientation influenced customer satisfaction of salesperson negatively. In addition customer satisfaction of salesperson showed positive relation with salesperson loyalty and satisfaction of the stores. Second, the salesperson loyalty showed positive relation with store loyalty and word-of-mouth but showed negative relation with post-purchase information search. Customer satisfaction of stores showed negative relation with post-purchase information search but no meaningful relation with store loyalty and word-of-mouth.

• Journal of the Society of Naval Architects of Korea
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• v.59 no.2
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• pp.72-79
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• 2022

Deep-learning-based Super-Resolution (SR) methods were evaluated to reconstruct pressure fields with a high resolution from low-resolution images taken from a coarse grid simulation. In addition to a canonical SRCNN(super-resolution convolutional neural network) model, two modified models from SRCNN, adding an activation function (ReLU or Sigmoid function) to the output layer, were considered in the present study. High resolution images obtained by three models were more vivid and reliable qualitatively, compared with a conventional super-resolution method of bicubic interpolation. A quantitative comparison of statistical similarity showed that SRCNN model with Sigmoid function achieved best performance with less dependency on original resolution of input images.

• Journal of the Korea Safety Management & Science
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• v.26 no.1
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• pp.63-74
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• 2024

The objectives of this study is to classify evacuation types, derive the characteristics of 4 types, develop and discover evacuation routes within the performance hall space, and present the statistical classification results of the evacuation classification model by classification type. To achieve this purpose, the characteristics of each evacuation type's four types are applied through a network reliability analysis method and utilized for institutional improvement and policy. This study applies for the building law, evacuation and relief safety standards when establishing a performance hall safety management plan, and reflects it in safety-related laws, safety standards, and policy systems. Statistical data by evacuation type were analyzed, and measurement characteristics were compared and analyzed by evacuation types. Evaluate the morphological similarity and reliability of evacuation types according to door width and passage length and propose the install position of evacuation guidance sign boards. The results of this study are expected to be used as basic data to provide operation strategies for safety facility evacuation information sign boards according to evacuation route classification types when taking a safety management plan. The operation strategy for the evacuation sign boards installation that integrates employee guidance and safety training is applied to the performance hall safety management plan. It will contribute to establishing an operational strategy for performance space safety when constructing performance facilities in the future.

• Economic and Environmental Geology
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• v.28 no.3
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• pp.271-277
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• 1995

The geological information analysis based on spatial statistical techniques have been studied in relation to mineral exploration. The applicability of outlier detection using moving-window statistics and directional cross-variography analysis have been verified by using geochemical data sets surveyed in the Taebaek area for mineral exploration. The directional variogram analysis has been basically known as a geostatistical method for spatial continuity measures. In this study, the application of this proposed method was extended to measure spatial correlation or similarity problems between two geochemical elements. For the appraisal of the usefulness of this scheme, five kinds of variogram functions were computed for original data and revised data, obtained by removing outliers detected by moving-window statistics and the results were compared. It is concluded that these advanced spatial statistical methods at the interpretation stage of spatial similarity provide us with valuable quantitative results as decision-supporting information for regional mineral exploration task.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.5
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• pp.701-709
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• 2010

This paper presents an efficient signature recognition method by using the hybrid similarity criterion, which is in inverse proportion to distance and in proportion to correlation between the images. The distance is applied to express the spacial property of image, and the correlation is also applied to express the statistical property. The proposed criterion provides the robust recognition to both the geometrical variations such as position, size, and rotation and the shape variation. The normalized cross-correlation(NCC), which is calculated by considering 4 directions based on the histogram of binary image, is applied to express rapidly and accurately the similarity between the images. The proposed method has been applied to the problem for recognizing the 20 truck images of 288*288 pixels and the 105(3 persons * 35 images) signature images of 256*256 pixels, respectively. The experimental results show that the proposed method has a superior recognition performance that appears the image characters well. Especially, the hybrid criterion of NCC and ordinal distance has a superior recognition performance to the hybrid criterion using city-block or Euclidean distance.

• Communications for Statistical Applications and Methods
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• v.22 no.6
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• pp.605-613
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• 2015

A three-arm parallel design has been proposed to assess the biosimilarity between a biological product and a reference product using relative distance (Kang and Chow, 2013). The three-arm parallel design consists of two arms for the reference product and one arm for the biosimilar product. This paper extended the three-arm parallel design to a (k + 1)-arm parallel design composed of k (${\geq}3$) arms for the reference product and one arm for the biosimilar product. A new relative distance was defined based on Euclidean distance; consequently, a corresponding test procedure was developed based on asymptotic distribution. Type I error rates and powers were investigated both theoretically and empirically.

• Journal of The Korean Astronomical Society
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• v.37 no.5
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• pp.399-404
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• 2004

Cosmic rays are ubiquitous in space, and are apparently present wherever the matter density is small enough that they are not removed by collisions with ambient particles. The essential similarity of their energy spectra in many different regions places significant general constraints on the mechanisms for their acceleration and confinement. Diffusive shock acceleration is at present the most successful acceleration mechanism proposed, and, together with transport in Kolmogorov turbulence, can account for the universal specta. In comparison to shock acceleration, statistical acceleration, invoked in many situations, has significant disadvantages. The basic physics of acceleration and transport are discussed, and examples shown where it apparently works very well. However, there are now well-established situations where diffusive shock acceleration cannot be the accelerator. This problem will be discussed and possible acceleration mechanism evaluated. Statistical acceleration in these places is possible. In addition, a new mechanism, called diffusive compression acceleration, will be discussed and shown to be an attractive candidate. It has similarities with both statistical acceleration and shock acceleration.

• International Journal of Internet, Broadcasting and Communication
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• v.7 no.1
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• pp.36-41
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• 2015

This paper is proposed a wavelet-based MCDT(Mask Coefficient Differential and Threshold) method of image registration of Multi-images contaminated with visible image and infrared image. The method for ensure reliability of the image registration is to the increase statistical corelation as getting the common feature points between two images. The method of threshold the wavelet coefficients using derivatives of the wavelet coefficients of the detail subbands was proposed to effectively registration images with distortion. And it can define that the edge map. Particularly, in order to increase statistical corelation the method of the normalized mutual information. as similarity measure common feature between two images was selected. The proposed method is totally verified by comparing with the several other multi-image and the proposed image registration.