• ETRI Journal
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• v.40 no.2
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• pp.167-179
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• 2018

This paper proposes an IEEE 802.15.4m compliant TV white-space orthogonal frequency-division multiplexing (TVWS)-(OFDM) radio frequency (RF) transceiver that can be adopted in advanced metering infrastructures, universal remote controllers, smart factories, consumer electronics, and other areas. The proposed TVWS-OFDM RF transceiver consists of a receiver, a transmitter, a 25% duty-cycle local oscillator generator, and a delta-sigma fractional-N phase-locked loop. In the TV band from 470 MHz to 698 MHz, the highly linear RF transmitter protects the occupied TV signals, and the high-Q filtering RF receiver is tolerable to in-band interferers as strong as -20 dBm at a 3-MHz offset. The proposed TVWS-OFDM RF transceiver is fabricated using a $0.13-{\mu}m$ CMOS process, and consumes 47 mA in the Tx mode and 35 mA in the Rx mode. The fabricated chip shows a Tx average power of 0 dBm with an error-vector-magnitude of < 3%, and a sensitivity level of -103 dBm with a packet-error-rate of < 3%. Using the implemented TVWS-OFDM modules, a public demonstration of electricity metering was successfully carried out.

• The Journal of Korean Association of Computer Education
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• v.4 no.1
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• pp.175-181
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• 2001

WBI provides new opportunities to realize the flexible learning environment based on hypermedia and to support distance learning with a diverse interaction. The instructors or learners in WBI claim to be able to resolve reluctant fluctuations such as disorientation and cognitive overload. To overcome these phenomena, a supplementary tool able to manage a learning space organized by the instructor's or learner's own way and offer effective navigation techniques is presented in this paper. A learning space management and navigation tool called HyperMap dynamically represents the learning space in the form of a two-dimensional labeled graph. This HyperMap also can be used for an instruction design tool, learners portfolio for the exchange of learning experiences, and the assessment of WBI.

• Bulletin of the Korean Mathematical Society
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• v.37 no.1
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• pp.171-179
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• 2000

We prove the following: (1) For a Hausdorff space X, the hyperspace K(X) of compact subsets of X is hemicompact if and only if X is hemicompact. (2) For a regular space X, the hyperspace $C_K(X)$ of subcontinua of X is hemicompact (hemiconnected) if and only if X is hemicompact (hemiconnected). (3) For a locally compact Hausdorff space X, each open set in X is hemicompact if and only if each basic open set in the hyperspace K(X) is hemicompact. (4) For a connected, locally connected, locally compact Hausdorff space X, K(X) is hemiconnected if and only if X is hemiconnected.

• ETRI Journal
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• v.36 no.3
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• pp.333-342
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• 2014

Most hyper-ellipsoidal clustering (HEC) approaches use the Mahalanobis distance as a distance metric. It has been proven that HEC, under this condition, cannot be realized since the cost function of partitional clustering is a constant. We demonstrate that HEC with a modified Gaussian kernel metric can be interpreted as a problem of finding condensed ellipsoidal clusters (with respect to the volumes and densities of the clusters) and propose a practical HEC algorithm that is able to efficiently handle clusters that are ellipsoidal in shape and that are of different size and density. We then try to refine the HEC algorithm by utilizing ellipsoids defined on the kernel feature space to deal with more complex-shaped clusters. The proposed methods lead to a significant improvement in the clustering results over K-means algorithm, fuzzy C-means algorithm, GMM-EM algorithm, and HEC algorithm based on minimum-volume ellipsoids using Mahalanobis distance.

• Asia Marketing Journal
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• v.26 no.1
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• pp.45-59
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• 2024

Extended Reality (XR) technology, the umbrella term covering hyper-realistic technologies, is known to enhance consumer experience and is therefore developing rapidly and being utilized across various industries. Growing studies have examined XR technology and consumer experience; however, the literature has failed to fully explore hyper-realistic technology through a holistic perspective. To fill this gap, we analyzed 720 Korean and international articles through semantic network analysis and topic modeling and identified the literature on XR research in consumer experience. As a result, we extracted six main topics: "Tourism," "Buying Behavior," "XR Technology Acceptance," "Virtual Space," "Game," and "XR Environment." The results provide comprehensive insight on XR technology in consumer experience, whereas the literature is bounded on the production side as revealing a lack of academic discourse on consumer rights and responsibilities. Research reflecting the consumer welfare perspective is, therefore, recommended for future studies.

• The Journal of the Korea Contents Association
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• v.1 no.1
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• pp.15-23
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• 2001

It is difficult to figure out the specific contents of the buildings in the internet spatial area, since those data on the internet present only the location of buildings and the outlines of lands on which buildings are located, An experimental study for the view management of building information at internet urban spatial area was conducted on the Web-GIS based map using hyper map. With the building information on the 2-D map, modified from the previous numerical map and the regional building information and additional information, a new form of building through 3-D icons was shown on the internet spatial area. This study shows the Web-based building management system, which is designed to manage attribute data about hyper-linked buildings of 2.5-D icons and to reproduce visual building information by putting a variety of information into hyper-linked icons on the hyper map. This system not only complements the lack of consistency between real buildings and those on the map, but also provides users with more familiar urban space, so that everybody can utilize the building information as long as he has access to the internet.

• The KIPS Transactions:PartD
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• v.11D no.4
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• pp.823-834
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• 2004

In this research, the similarity search algorithms are provided for large video data streams. A video stream that consists of a number of frames can be expressed by a sequence in the multidimensional data space, by representing each frame with a multidimensional vector By analyzing various characteristics of the sequence, it is partitioned into multiple video segments and clusters which are represented by hyper-rectangles. Using the hyper-rectangles of video segments and clusters, similarity functions between two video streams are defined, and two similarity search algorithms are proposed based on the similarity functions algorithms by hyper-rectangles and by representative frames. The former is an algorithm that guarantees the correctness while the latter focuses on the efficiency with a slight sacrifice of the correctness Experiments on different types of video streams and synthetically generated stream data show the strength of our proposed algorithms.

• The Bulletin of The Korean Astronomical Society
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• v.42 no.2
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• pp.60.1-60.1
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• 2017

In this study we apply Convolution Neural Network(CNN) to solar flare occurrence prediction with various parameter options using the 00:00 UT MDI images from 1996 to 2010 (total 4962 images). We assume that only X, M and C class flares correspond to "flare occurrence" and the others to "non-flare". We have attempted to look for the best options for the models with two CNN pre-trained models (AlexNet and GoogLeNet), by modifying training images and changing hyper parameters. Our major results from this study are as follows. First, the flare occurrence predictions are relatively good with about 80 % accuracies. Second, both flare prediction models based on AlexNet and GoogLeNet have similar results but AlexNet is faster than GoogLeNet. Third, modifying the training images to reduce the projection effect is not effective. Fourth, skill scores of our flare occurrence model are mostly better than those of the previous models.

• Journal of KIISE:Software and Applications
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• v.36 no.11
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• pp.936-946
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• 2009

A graph cuts method has recently attracted a lot of attentions for image segmentation, as it can globally minimize energy functions composed of data term that reflects how each pixel fits into prior information for each class and smoothness term that penalizes discontinuities between neighboring pixels. In previous approaches to graph cuts-based automatic image segmentation, GMM(Gaussian mixture models) is generally used, and means and covariance matrixes calculated by EM algorithm were used as prior information for each cluster. However, it is practicable only for clusters with a hyper-spherical or hyper-ellipsoidal shape, as the cluster was represented based on the covariance matrix centered on the mean. For arbitrary-shaped clusters, this paper proposes graph cuts-based image segmentation using mean shift analysis. As a prior information to estimate the data term, we use the set of mean trajectories toward each mode from initial means randomly selected in $L^*u^*{\upsilon}^*$ color space. Since the mean shift procedure requires many computational times, we transform features in continuous feature space into 3D discrete grid, and use 3D kernel based on the first moment in the grid, which are needed to move the means to modes. In the experiments, we investigate the problems of mean shift-based and normalized cuts-based image segmentation methods that are recently popular methods, and the proposed method showed better performance than previous two methods and graph cuts-based automatic image segmentation using GMM on Berkeley segmentation dataset.

• Korean Institute of Interior Design Journal
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• v.15 no.3 s.56
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• pp.75-82
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• 2006

Discussions on transparency have been being analyzed as variedly as the diversity itself in contemporary architecture. Though it is inappropriate to summarize the discussions into several specific viewpoints, as the notional classifications on transparency are varied according to the points of individual researchers, it can be said that, by approaching with the standpoint of the designers who may have various difficulties in the course of design, the meaning of this thesis lies largely in the fact that it attempted to study the architectural application techniques of transparency notion both through surface aspect which could be said to decide on the appearance of the architecture shape and through, in physical aspects as a combination of space components comprising the inner space, spatial aspect to which architectural techniques of transparency notion are applied. Through these, we conclude as follows. 1. Representation Techniques of Transparency in Surface : Transparency from surface viewpoint could be categorized into 1) emphasis on property-of-matter, 2) lightness of Literal material itself, 3) visual ambivalence, and 4) dematerialized hyper-surface. 2. Representation Techniques of Transparency in Space : In spatial viewpoint, transparency is summarized into sub-viewpoints as 1) straightforward space 2) ambiguous spacer 3) expanded space