• Journal of the Korea Society for Simulation
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• v.9 no.3
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• pp.77-89
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• 2000

This paper suggests a multi-attribute dispatching rule for an automated guided vehicle(AGV). The attributes to be considered are the number of queues in outgoing buffers of workstations, distance between an idle AGV and a workstation with a job waiting for the service of vehicle, and the number of queues in input buffers of the destination workstation of a job. The suggested rule is based on the simple additive weighting method using a normalized score for each attribute. A neural network approach is applied to obtain an appropriate weight vector of attributes based on the current status of the manufacturing system. Backpropagation algorithm is used to train the neural network model. The proposed dispatching rules and some single attribute rules are compared and analyzed by simulation technique. A number of simulation runs are executed under different experimental conditions to compare the several performance measures of the suggested rules and some existing single attribute dispatching rules each other.

• Journal of Korean Society of Transportation
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• v.4 no.1
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• pp.12-27
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• 1986

This study examined user preferences toward transportation modes in Seoul. Two multidimensional scaling models, the ideal point and vector models, were applied to data on mode preferences of 114 adults in the metropolitan area. While both models produced fairly similar results, the vector model performed slightly better than the other in terms of interpretability of the results. The transport attributes elicited are comfort, flexibility, travel cost, travel time, privacy, and safety; among which comfort is salient most. The comfort variable is a multi-faceted attribute in nature. The variations of attribute preferences are most significant between the gender groups as well as worker/nonworker groups. In particular, male workers, female workers and female nonworkers form three distinctive market segments. An unidimensional scaling of the preference data reveals that subway, auto-driver, and subscription bus modes are preferred most, whereas motorcycle and bicycle least. The other modes of express bus, taxt, auto-passenger, bus and walk rank intermediately. An examination of how preference orders vary among modal groups hints that users align their stated attitudes to their choice in order to reduce cognitive dissonance.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.703-708
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• 2009

The present paper describes the application of an improved impression transfer vector method (Sakurai et al., 2007) to transform the three basic dimensions (Evaluation, Activity, and Potency) of higher-order impression. First, a set of shapes and surface textures of faces was represented by multi-dimensional vectors. Second, the variation among faces was coded in reduced parameters derived by applying principal component analysis. Third, a facial attribute along a given impression dimension was analyzed to select discriminative parameters from among principal components with higher sensitivity to impressions, and obtain an impression transfer vector. Finally, the parametric coordinates were changed by adding or subtracting the impression transfer vector and the image was manipulated so that its facial appearance clearly exhibits the transformed impression. A psychological rating experiment confirmed that the impression transfer vector modulated three dimensions of higher-order impression. We discussed the versatility of the impression transfer vector method.

• Journal of the Korean Society of Clothing and Textiles
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• v.19 no.5
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• pp.699-712
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• 1995

The purpose of this study was 1) to identify the constructing factors of jeans brand image 2) to analyze the domestic jeans market using perceptual maps of three benefit segments based on stdy(I). The questionnaire consisted of brand preference, attribute of brand image and wearer image was selected from the previous studies or developed for this study. The subjects were 350 male and female university students who have purchased at least one of the nine jeans wear brand selected for the study. For statistical analysis, reliability test, factor analysis, MANOVA, and multiple regression were used. The results of this study were as follows: 1. Symbolism, quality, and economy were found out as constricting factors of brand image in the attribute dimensions, while innovative and active image were found out in the wearer image dimensions. 2. 9 Perceptual maps of attribute dimensions and 3 perceptual maps of wearer image dimensions were constructed and each ideal vector was drawn.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.48 no.5
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• pp.88-98
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• 2011

Recently, according as the importance of GIS(geography information system) database security is embossed, much researches had been achieved about GIS network security. But most such researches are weak against sourceful illegal reproductions and distributions of GIS vector data map. In this paper, we proposed an efficient layer unit contents based partial encryption technique in the vector map compression domain to prevent illegal distributions and unauthorized accesses. This method achieves a partial encryption about each central coordinate and directional parameters of a MCA(minimum coding attribute) that is created at the vector map compression processing in the vector space. First, the position encryption is applied as permutating randomly the center coordinate of each record that is minimum unit of vector map shape. And second, the direction encryption that changing shapes of vector map topography is applied as encrypting the direction of vertices's coordinates of each record. In experimental results, we confirmed that our proposed method can encipher the large volumed vector map data effectively in low computational complexity. Also, we could minimize the decline of compression efficiency that occurred by conventional contents based encryption schemes using AES or DES algorithms.

• Journal of the Korea Society of Computer and Information
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• v.26 no.4
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• pp.1-9
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• 2021

In this paper, we propose a training algorithm of support vector machine (SVM) with a sensitive variable. Although machine learning models enable automatic decision making in the real world applications, regulations prohibit sensitive information from being used to protect privacy. In particular, the privacy protection of the legally protected attributes such as race, gender, and disability is compulsory. We present an efficient least square SVM (LSSVM) training algorithm using a fully homomorphic encryption (FHE) to protect a partial sensitive attribute. Our framework posits that data owner has both non-sensitive attributes and a sensitive attribute while machine learning service provider (MLSP) can get non-sensitive attributes and an encrypted sensitive attribute. As a result, data owner can obtain the encrypted model parameters without exposing their sensitive information to MLSP. In the inference phase, both non-sensitive attributes and a sensitive attribute are encrypted, and all computations should be conducted on encrypted domain. Through the experiments on real data, we identify that our proposed method enables to implement privacy-preserving sensitive LSSVM with FHE that has comparable performance with the original LSSVM algorithm. In addition, we demonstrate that the efficient sensitive LSSVM with FHE significantly improves the computational cost with a small degradation of performance.

• Journal of Korea Society of Industrial Information Systems
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• v.4 no.4
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• pp.143-148
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• 1999

This paper presents a method which enables raster maps to be used like vector maps in the wed environment and develops a raster map viewer which can be executed in the wed browser. Through the preprocessing process the coordinates attached to each object in the raster map can be used as vector information. The raster map viewer makes the spatial analysis possible using the attribute database connected to the coordinates of each object, This map viewer makes the Web GIS can be constructed at the lower cost because the viewer uses the characteristics of raster map. And the map viewer has merit point of easily developing a component for spatial analysis.

• Journal of the Korean Home Economics Association
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• v.39 no.10
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• pp.55-67
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• 2001

The purpose of this study were 1) to find out the benefits sought factors and segment the customers of internet shopping mall, 2) to find out the store image factors of internet shopping mall, and 3) to analyze the internet shopping mall market using perceptual map of segmented groups. The questionnaires dealing with attribute dimension of internet shopping mall image, benefits sought, and demographic variables were selected from the previous studies or were developed for this study. The data from 319 respondents which were collected through the internet survey site was analyzed by factor analysis, cluster analysis, one-way ANOVA, and $X^2$-test. The results of this study were as follows: 1. Benefit sought by consumer in internet shopping malls was found to include six different factors: assortments of products, search efficiency, brand/fashionability, delivery convenience, promotion service and informativeness. 2. As a result of subdividing the consumers, four distinctive groups were formed on the basis of benefit factors: multi-benefit oriented group, convenience oriented group, brand oriented group and low-benefit oriented group. Demographic traits such as education and income level were proven to significantly differentiate the benefit segments. 3. In the structural components of internet shopping-malls image, product/information, service/convenience and economy were drawn from attribute dimensions. 4. 12 perceptual maps of internet shopping mall image were constructed and each ideal vector were drawn.

• Journal of the Korea Institute of Building Construction
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• v.14 no.6
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• pp.605-613
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• 2014

Recently proposed intelligent images are generating, storing and managing along with existing image information and 5W1H information. Therefore, these vector images can be useful in searching and managing photos taking during building construction and maintenance processes. In addition, when the vector photos, a key to the intelligent image, is linked with BIM, it is possible to find BIM objects by utilizing information included in vector photos. And if the taken vector photo is saved as attributes of the extracted object, the vector photo can be managed as the historical data. Furthermore, this new technology will contribute to make the management of construction information more efficiently. This study is about the development of the technology of extracting BIM objects from vector photo information and managing the attributes of the extracted objects. Also the prototype modules was developed and tested to evaluate the processes of setting reference points, converting coordinate system, calculating positions, and so on. Through these processes, it was confirmed that the possibility of extracting BIM objects from vector photos and of managing attribute data of objects.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.18 no.3
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• pp.92-98
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• 2010

The AHP methodology compares criteria, or alternatives with respect to a criterion, in a natural, pairwise mode. AHP has been applied in a wide variety of applications multi objective decision making being just one. If a group of expert with different aspect, they need some way to revise expert group. We proposed the concatenation of expert to survey the AHP pairwise question for multi-attribute decision making. In this paper, we suggest a way to revise the expert's priorities in hierarch using concept of different group opinion.