• Journal of architectural history
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• v.14 no.2 s.42
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• pp.41-55
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• 2005

Temple with Multi-Buddha's Pavilions is a temple consisting of more than 2 Buddha's Pavilions. Individual Buddha's Pavilions tend to form distinguished area, or to keep independent axis from other Buddha's Pavilions. This study is to understand the philosophy of layout of individual Buddha's Pavilions located in the Temple with Multi-Buddha's Pavilions. To investigate a relationship to layout of individual Buddha's Pavilions on the basis of Buddhism doctrine makes us to understand philosophies about temple layout which temple constructors had. Bulkooksa, a temple having several pavilions placed in parallel, integrates diverse philosophies such as Vairocana Buddha-Ksetra from Vairocana Buddha's Pavilion, Sakyamuni Buddha-Ksetra from both Sakyamuni Buddha's Pavilion and two stupa, and Amitayus Buddha-Ksetra (Sukhavati) from Amitayus Buddha-Ksetra Pavilion. Sakyamuni Buddha's Pavilion and Amitayus Buddha's Pavilion are placed east to west in parallel, and Vairocana Buddha's Pavilion is placed behind them. Beobjusa, a temple having several pavilions placed cross axis, combines three axes such as the first, main axis linking Kumkang Gate - Chunwang Gate - Palsang Pavilion - Amitayus Buddha's Pavilion - Sakyamuni Buddha's Pavilion, the second axis linking Palsang Pavilion -Maitreya Pavilion, and the third axis linking Amitayus Buddha's Pavilion - Avalokiteshvara Pavilion. Relationship among each Buddha's land is clearly expressed by means of this cross axis layout of Buddha's Pavilions, reflecting a philosophy of rebirth in Nirvana that Wonhyo and Eusang propagated. Buseoksa, a temple having several pavilions placed the before and the behind, combines three Buddha's lands such as Maitreya Buddha-Ksetra, Amitayus Buddha-Ksetra and Vairocana Buddha-Ksetra, by means of arrangement of Maitreya Pavilion, Anyang Pavilion and Amitayus Buddha's Pavilion at bended axis, and east facing Amitayus Buddha. By investigating the philosophy of Temple layout with Multi-Buddha's Pavilions in this study, Buddha's Land conception, for people, that ancient Korean temples have, is understood.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.4
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• pp.355-359
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• 2014

In this paper, we proposed the new fuzzy pattern classifier which combines several fuzzy models with simple consequent parts hierarchically. The basic component of the proposed fuzzy pattern classifier with hierarchical structure is a fuzzy model with simple consequent part so that the complexity of the proposed fuzzy pattern classifier is not high. In order to analyze and divide the input space, we use Fuzzy C-Means clustering algorithm. In addition, we exploit Conditional Fuzzy C-Means clustering algorithm to analyze the sub space which is divided by Fuzzy C-Means clustering algorithm. At each clustered region, we apply a fuzzy model with simple consequent part and build the fuzzy pattern classifier with hierarchical structure. Because of the hierarchical structure of the proposed pattern classifier, the data distribution of the input space can be analyzed in the macroscopic point of view and the microscopic point of view. Finally, in order to evaluate the classification ability of the proposed pattern classifier, the machine learning data sets are used.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 1999.12a
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• pp.315-323
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• 1999

The measuring systems of auto-parts are most of greater part very expensive. This paper tries to study to make a low-cost measuring equipment. There's several kinds of parts in automobile. In this study, we take aircon-switch called magnet coil-housing as the object of measurements. The measurements of this product is currently in difficult situations at factory. In the case of the mesuring objects being big sizes and camera sensor having under 410000 pixels, the key point is the number of pixels not to be changed whenever the same object is measured under the same position. We modified and used fuzzy c-means algorithm to get mostly without the change of the numbers of pixels exactly. Also, the standardized ruler is necessary to measure the length of the object but it is not easy to get the precised ruler. Therefore, the standard length has been taken as the mean value of the pixels in the previous passed objects manually obtained at factory. The results are displayed on monitor and transferred these signals to the microprocessor through RSC-232 port to determine a good or bad of products.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.2
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• pp.24-31
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• 2011

This paper proposes spatio-temporal denoising algorithm based on nonlocal means. Though the conventional denoising algorithms based on nonlocal means have good performance in noise removal, it is difficult to implement them into the hardware system due to much computational load and the need for several frame buffers. Therefore we adopted infinite impulse response temporal noise reduction algorithm in the proposed algorithm. Proposed algorithm shows less artificial denoised result in the motionless region. In the motion region, spatial filter based on efficiently improved nonlocal means algorithm conduct noise removal with less motion blur. Experimental results including comparisons with conventional algorithms for various noise levels and test images show the proposed algorithm has a good performance in both visual and quantitative criteria.

• Journal of KIISE
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• v.45 no.3
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• pp.288-293
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• 2018

There have recently been several studies investigating how to apply a privacy preserving technique to publish data. Differential privacy can protect personal information regardless of an attacker's background knowledge by adding probabilistic noise to the original data. To perform differentially private k-means clustering, the existing algorithm builds a differentially private histogram and performs the k-means clustering. Since it constructs an equi-width histogram without considering the distribution of data, there are many buckets to which noise should be added. We propose a k-means clustering algorithm using a quad-tree that captures the distribution of data by using a small number of buckets. Our experiments show that the proposed algorithm shows better performance than the existing algorithm.

• International Journal of Knowledge Content Development & Technology
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• v.7 no.1
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• pp.57-78
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• 2017

There are several statistical classification algorithms available for land use/land cover classification. However, each has a certain bias or compromise. Some methods like the parallel piped approach in supervised classification, cannot classify continuous regions within a feature. On the other hand, while unsupervised classification method takes maximum advantage of spectral variability in an image, the maximally separable clusters in spectral space may not do much for our perception of important classes in a given study area. In this research, the output of an ANN algorithm was compared with the Possibilistic c-Means an improvement of the fuzzy c-Means on both moderate resolutions Landsat8 and a high resolution Formosat 2 images. The Formosat 2 image comes with an 8m spectral resolution on the multispectral data. This multispectral image data was resampled to 10m in order to maintain a uniform ratio of 1:3 against Landsat 8 image. Six classes were chosen for analysis including: Dense forest, eucalyptus, water, grassland, wheat and riverine sand. Using a standard false color composite (FCC), the six features reflected differently in the infrared region with wheat producing the brightest pixel values. Signature collection per class was therefore easily obtained for all classifications. The output of both ANN and FCM, were analyzed separately for accuracy and an error matrix generated to assess the quality and accuracy of the classification algorithms. When you compare the results of the two methods on a per-class-basis, ANN had a crisper output compared to PCM which yielded clusters with pixels especially on the moderate resolution Landsat 8 imagery.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.28 no.6
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• pp.1401-1414
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• 2018

The k-means clustering algorithm groups input data with the number of groups represented by variable k. In fact, this algorithm is particularly useful in market segmentation and medical research, suggesting its wide applicability. In this paper, we propose a privacy-preserving clustering algorithm that is appropriate for outsourced encrypted data, while exposing no information about the input data itself. Notably, our proposed model facilitates encryption of all data, which is a large advantage over existing privacy-preserving clustering algorithms which rely on multi-party computation over plaintext data stored on several servers. Our approach compares homomorphically encrypted ciphertexts to measure the distance between input data. Finally, we theoretically prove that our scheme guarantees the security of input data during computation, and also evaluate our communication and computation complexity in detail.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.16 no.4
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• pp.246-253
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• 2016

Infrared (IR) imaging has been researched for various applications such as surveillance. IR radiation has the capability to detect thermal characteristics of objects under low-light conditions. However, automatic segmentation for finding the object of interest would be challenging since the IR detector often provides the low spatial and contrast resolution image without color and texture information. Another hindrance is that the image can be degraded by noise and clutters. This paper proposes multi-level segmentation for extracting regions of interest (ROIs) and objects of interest (OOIs) in the IR scene. Each level of the multi-level segmentation is composed of a k-means clustering algorithm, an expectation-maximization (EM) algorithm, and a decision process. The k-means clustering initializes the parameters of the Gaussian mixture model (GMM), and the EM algorithm estimates those parameters iteratively. During the multi-level segmentation, the area extracted at one level becomes the input to the next level segmentation. Thus, the segmentation is consecutively performed narrowing the area to be processed. The foreground objects are individually extracted from the final ROI windows. In the experiments, the effectiveness of the proposed method is demonstrated using several IR images, in which human subjects are captured at a long distance. The average probability of error is shown to be lower than that obtained from other conventional methods such as Gonzalez, Otsu, k-means, and EM methods.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.11
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• pp.5692-5716
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• 2019

One of the best means to safeguard the confidentiality, security, and privacy of an image within the IoT-Cloud is through encryption. However, looking through encrypted data is a difficult process. Several techniques for searching encrypted data have been devised, but certain security solutions may not be used in IoT-Cloud because such solutions are not lightweight. We propose a lightweight scheme that can perform a content-based search of encrypted images, namely EEIRI. In this scheme, the images are represented using local features. We develop and validate a secure scheme for measuring the Euclidean distance between two descriptor sets. To improve the search efficiency, we employ the k-means clustering technique to construct a searchable tree-based index. Our index construction process ensures the privacy of the stored data and search requests. When compared with more familiar techniques of searching images over plaintexts, EEIRI is considered to be more efficient, demonstrating a higher search cost of 7% and a decrease in search accuracy of 1.7%. Numerous empirical investigations are carried out in relation to real image collections so as to evidence our work.

• KIEAE Journal
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• v.16 no.6
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• pp.77-82
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• 2016

Purpose: Almost every research carried out in our country against the natural disaster is focused on the temporary facilities such as temporary housing, emergency shelter and as a result, it is very hard to find out researches on the ordinary houses which installed integrated systems of hazard-resistant against the natural disaster. Method: To conduct this research, categorizing process for design, structural, environmental and installation elements found in the Hazard-Resistant and Reduction House built for sale in Japan was performed. Result: In this study, several design concepts and subordinate items are recommended for hazard-resistant housing. First, design concept of 'Preparedness' which means security and access to the storage storing goods especially food & beverage for the emergencies is needed. The subordinate items consist of security of stocking space, diversified and circular storage system, and safety storage system. Second, design concept of 'Security' which means security of physical safety space and rapid recovery to returning to daily life against natural disaster is needed. The subordinate items consist of many items including not only structure and facilities but also architectural design method. And finally, design concept of 'Maintenance, Support and Return' which means minimizing the physical and psychological damages and support safety and physical conditions of the victims from the impact of the disaster to returning to daily life is needed. The subordinate items consist of high efficiency insulation/airtightness design, microclimate design, combination of photovoltaic system and storage battery, non-power appliance system against the power failure, storing system for drinking water, rainwater storing and utilization system.