• Korean journal of communication and information
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• v.70
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• pp.132-164
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• 2015

The formation of knowledge of the people of Korean society is the social practices of collective subjectivity. Subjectivity is the truth of the self, which is incessantly created, questioned and modified in the milieu of self-reflection. In an attempt to examine the hermeneutics of the subject of Korean society, a conceptual framework is proposed, which, with the notion of life embedded, consists of a historical sequence of the popular, minjung, multitude, people and community. The period of 1960s saw the ambiguous mass of lifes floating, the individual with his/her own interior world of consciousness emerge. The ideological solidarity is formed in the the next two decades, in contestation with immediate and physical threatening such as poverty and dictatorship. The democratization of Korean society and the global expansion of neoliberal regime gave a re-birth of multitude and people which is characterized with their pursuit of the co-existence and co-realization of singularity and universality on the ethical principle of the open and communicative radicality.

• Journal of the Korea Society of Computer and Information
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• v.3 no.2
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• pp.189-199
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• 1998

This study presents a FZOGP(fuzzified zero-one goal programming) model and a DHP (Delphic Hierarchy Process) that can be used to help information systems(IS) managers decides which IS projects should be selected. Delphic method is conducted prior to AHP so that not only can the objectives to be considered in analysis be determined, but the opinions of all decision makers can also be incorporated in problem formulation. While the DHP provides an ideal ranking process for the selection of IS Projects, it does not consider real constraints that exists in decision making process. Then this study intends to show how the DHP can be used to establish a priority structure for use within a FZOGP model. The advantages of FZOGP model are as follows: the imprecise aspiration level for each objective can be considered in FZOGP model. And, the common features between the new FZOGP and the GP models are that the objective functions in both models are minimized and the structure of their formulations are the same.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.2
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• pp.166-172
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• 2014

Image classification is an important problem in computer vision. However, it is a very challenging problem due to the variability, ambiguity and scale change that exists in images. In this paper, we propose a method of a hypergraph based modeling can consider the higher-order relationships of semantic attributes of a scene image and apply it to a scene image classification. In order to generate the hypergraph optimized for specific scene category, we propose a novel search method based on a probabilistic subspace method and also propose a method to aggregate the expression values of the member semantic attributes that belongs to the searched subsets based on a linear transformation method via likelihood based estimation. To verify the superiority of the proposed method, we showed that the discrimination power of the feature vector generated by the proposed method is better than existing methods through experiments. And also, in a scene classification experiment, the proposed method shows a competitive classification performance compared with the conventional methods.

• Journal of Internet Computing and Services
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• v.9 no.4
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• pp.115-131
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• 2008

Small mobile devices have become commonplace in our everyday life, from cellular phones to PDAs. Discovering dense regions for the mobile devices is one of the problems of grate practical importance. It can be used in monitoring movement of vehicles, concentration of troops, etc. In this paper, we propose a novel algorithm on continuously clustering a large set of mobile objects. We assume that a mobile object reports its position only if it is too far away from the expected position and thus the location data received may be imprecise. To compute the location of each individual object could be costly especially when the number of objects is large. To reduce the complexity of the computation, we want to first cluster objects that are in proximity into a group and treat the members in a group indistinguishable. Each individual object will be examined only when the inaccuracy causes ambiguity in the final results. We conduct extensive experiments on various data sets and analyze the sensitivity and scalability of our algorithms.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.6
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• pp.661-666
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• 2003

In this paper, the conventional k-modes and fuzzy k-modes algorithms for clustering categorical data is extended by representing the clusters of categorical data with fuzzy centroids instead of the hard-type centroids used in the original algorithm. The hard-type centroids of the traditional algorithms had difficulties in dealing with ambiguous boundary data, which might be misclassified and lead to thelocal optima. Use of fuzzy centroids makes it possible to fully exploit the power of fuzzy sets in representing the uncertainty in the classification of categorical data. The distance measure between data and fuzzy centroids is more precise and effective than those of the k-modes and fuzzy k-modes. To test the proposed approach, the proposed algorithm and two conventional algorithms were used to cluster three categorical data sets. The proposed method was found to give markedly better clustering results.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.9
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• pp.777-781
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• 2001

This paper presents an image contrast enhancement technique for improving the low contrast images using the improved IAFC(Integrated Adaptive Fuzzy Clustering) model. The low pictorial information of a low contrast image is due to the vagueness or fuzziness of the multivalued levels of brightness rather than randomness. Fuzzy image processing has three main stages, namely, image fuzzification, modification of membership values, and image defuzzification. Using a new model of automatic crossover point selection, optimal crossover point is selected automatically. The problem of crossover point selection can be considered as the two-category classification problem. The improved IAFC model is used to classify the image into two classes. The proposed method is applied to several experimental images with 256 gray levels and the results are compared with those of the histogram equalization technique. We utilized the index of fuzziness as a measure of image quality. The results show that the proposed method is better than the histogram equalization technique.

• Journal of KIISE:Databases
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• v.32 no.2
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• pp.161-176
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• 2005

oping and applying XML techniques. One key aspect of our taxonomy is the support of the credibility of the result by evaluating which XML document types can be processed by a method. Another key aspect is to provide a basis for determining which is the best for target XML document types. Application with preparations for XML document mining shows that our taxonomy may present XML document types to be able to consider during the preparation process and target XML document types to be used for experiments.

• Journal of Navigation and Port Research
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• v.31 no.6
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• pp.537-543
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• 2007

It's an important part to calculate the weights between criterions and to aggregate the decision inputs in a MCDM(Multi criterion decision making) This paper presents a method for aggregation cf decision inputs and application to the MCDM. We incorporate the fuzzy set theory and the basic nature of subjectivity due to ambiguity to achieve a flexible decision approach suitable for uncertain and fuzzy environments. To obtain the scoring that corresponds to the best alternative or the ranking of the alternatives, we need to use a total order for the fuzzy numbers involved in the problem. In this article, we consider a definition of such a total order, which is based on two subjective aspects: the degree of optimism/pessimism reflected with the ordered weighted averaging(OWA) oprators. A numerical example, expecially location analysis for anchorage area, is given to illustrate the approach.

• Journal of the Korean Institute of Landscape Architecture
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• v.38 no.1
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• pp.107-118
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• 2010

Palaces of a country can be representative aggregate of the culture and arts of the country. Palaces were used not only as a living place to protect kings and royal families and to live cultural lives, but also a political place to govern the country. Kings in Choseon founded the country on the Sung Confucianism, their philosophical background. They built Bangji and Wondo as constant reminders of their philosophy. Bangji is the most apparent characteristic in the palace gardens of the Choseon Dynasty. Finding out the original form of Jidang, restoring the original and passing it on to future generations can be passing on the spiritual culture of our ancestors. This study is done to find out or locate well preserved Jidang, transformed Jidang and lost Jidang in Changdeokgung, which is the best conserved palace of Choseon. This study is composed of Jidang which has been kept in its original state, transformed Jidang, locating lost Jidang and Jidnang which has been unearthed. The total number of Donggwoldo's Jidangs is 17; those that are kept in their original state, 4; transformed Jidangs, 5; Jidangs that were lost and have been located, 8; and newly appeared Jidangs, 2. From the results, opinions on restoration are presented. This study can be a small drop in the thin stream of tradition passing onto future generations in this world where knowledge and information are transported momentarily and the classification of culture and border is mixed, yielding vagueness.

• Journal of Broadcast Engineering
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• v.17 no.1
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• pp.73-80
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• 2012

Recently, medical equipments are developed and used for diagnosis or studies. In addition, demand of techniques which automatically deal with three dimensional medical images obtained from the medical equipments is growing. One of the techniques is automatic bone segmentation which is expected to enhance the diagnosis efficiency of osteoporosis, fracture, and other bone diseases. Although various researches have been proposed to solve it, they are unable to be used in practice since a size of the medical data is large and there are many low contrast boundaries with other tissues. In this paper, we present a fast and accurate automatic framework for bone segmentation based on multi-resolutions. On a low resolution step, a position of the bone is roughly detected using constrained branch and mincut which find the optimal template from the training set. Then, the segmentation and the registration are iteratively conducted on the multiple resolutions. To evaluate the performance of the proposed method, we make an experiment with femur and tibia from 50 test knee magnetic resonance images using 100 training set. The proposed method outperformed the constrained branch and mincut in aspect of segmentation accuracy and implementation time.