• ETRI Journal
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• v.27 no.6
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• pp.759-767
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• 2005

This research is to substantially analyze the economic value of portable Internet (WiBro), WCDMA High Speed Downlink Packet Access (HSDPA), WiBro+VoIP, and WiBro+DMB regarded as the next generation of broadcasting. Based on the empirical analysis of economic values, we provide the optimal paths of converged communications and broadcasting services related to WiBro. 1,000 Internet users in the Seoul and Gyeonggi areas were surveyed in their homes. The collected survey was calculated as an accurate economic value distribution for relevant services, and the average and mean were taken using a parametric logit model, semi-parametric Spike model, and nonparametric Turnbull and Kernel estimations in order to analyze the contingent economic value of the amount offered to the subjects of the analysis. The contingent value analysis results varied slightly according to the different methodologies; however, all showed the following common features. The economic value of WiBro, Internet-based WCDMA, VoIP, and DMB with WiBro appeared to be similar. Therefore, if WiBro and WCDMA (HSDPA) form a competitive relationship, the types of bundled services offered as portable Internet service and the supply point of such bundled services are expected to emerge in a strategic plan for stimulating service markets and the prior occupation of the market.

• JSTS:Journal of Semiconductor Technology and Science
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• v.16 no.4
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• pp.436-442
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• 2016

An electroencephalogram (EEG)-connectome processor to monitor and diagnose mental health is proposed. From 19-channel EEG signals, the proposed processor determines whether the mental state is healthy or unhealthy by extracting significant features from EEG signals and classifying them. Connectome approach is adopted for the best diagnosis accuracy, and synchronization likelihood (SL) is chosen as the connectome feature. Before computing SL, reconstruction optimizer (ReOpt) block compensates some parameters, resulting in improved accuracy. During SL calculation, a sparse matrix inscription (SMI) scheme is proposed to reduce the memory size to 1/24. From the calculated SL information, a small world feature extractor (SWFE) reduces the memory size to 1/29. Finally, using SLs or small word features, radial basis function (RBF) kernel-based support vector machine (SVM) diagnoses user's mental health condition. For RBF kernels, look-up-tables (LUTs) are used to replace the floating-point operations, decreasing the required operation by 54%. Consequently, The EEG-connectome processor improves the diagnosis accuracy from 89% to 95% in Alzheimer's disease case. The proposed processor occupies $3.8mm^2$ and consumes 1.71 mW with $0.18{\mu}m$ CMOS technology.

• ETRI Journal
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• v.42 no.2
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• pp.258-271
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• 2020

A correlation exists between luminance samples and chrominance samples of a color image. It is beneficial to exploit such interchannel redundancy for color image compression. We propose an algorithm that predicts chrominance components Cb and Cr from the luminance component Y. The prediction model is trained by supervised learning with Laplacian-regularized least squares to minimize the total prediction error. Kernel principal component analysis mapping, which reduces computational complexity, is implemented on the same point set at both the encoder and decoder to ensure that predictions are identical at both the ends without signaling extra location information. In addition, chrominance subsampling and entropy coding for model parameters are adopted to further reduce the bit rate. Finally, luminance information and model parameters are stored for image reconstruction. Experimental results show the performance superiority of the proposed algorithm over its predecessor and JPEG, and even over JPEG-XR. The compensation version with the chrominance difference of the proposed algorithm performs close to and even better than JPEG2000 in some cases.

• Korean Journal of Optics and Photonics
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• v.14 no.2
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• pp.194-199
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• 2003

The analysis of operation characteristics of a miniaturized electrostatic electron lens system called an Einzel lens was performed using a simulation tool of FCM method. The potential distributions of Einzel lenses operated both in retarding and accelerating modes show similar features. But the electric fields determined from the potential distributions show opposite directions, which results in different features in the electron beam trajectory in each mode of operation. For the same working distance, focusing voltage in the accelerating mode is higher than that in the retarding mode.

• Cross-Cultural Studies
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• v.35
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• pp.35-58
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• 2014

This article aims to explain the 'people-image' of Bakhtin's works in the light of "Transgredience" and "Transition." According to Bakhtin, the real core of every culture is the people. But he did try to answer the question "what is the people?" I think, the secret of Bakhtinian thought is located in the people-image, because it is the one of the territories that have not been explained. For this purpose, we have to examine four images represented by Bakhtin, - rogue, clown, fool, thief. These images are the concrete and individualized images of people, who can characterize the power of transgredience and transition. They commonly act for changing ordinary borders of identities formulated with nationality, property, status, classes, sex and so forth. In this sense, Bakhtin thinks that the masks are the real nature which can show the mutational power of Being. That is the kernel of Bakhtin's people-image that makes and changes every cultural world. When we accept and practise this perspective positively, we will realize that Bakhtin's position is close to the cultural politics, because a practical power of thought cannot help but being political. That's why we have to investigate Bakhtin's people-image from a vantage point of "Transgredience" and "Transition."

• Korean Journal of Remote Sensing
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• v.22 no.4
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• pp.265-274
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• 2006

Extracting ground points is the kernel of DTM generation being considered as one of the most popular LIDAR applications. The previous extraction approaches can be mostly characterized as a point based approach, which sequentially examines every individual point to determine whether it is measured from ground surfaces. The number of examinations to be performed is then equivalent to the number of points. Particularly in a large set, the heavy computational requirement associated with the examinations is obviously an obstacle to employing more sophisticated criteria for the examination. To reduce the number of entities to be examined and produce more robust results, we developed an approach based on features rather than points, where a feature indicates an entity constructed by grouping some points. In the proposed approach, we first generate a set of features by organizing points into surface patches and grouping the patches into surface clusters. Among these features, we then attempt to identify the ground features with the criteria based on the attributes of the features. The points grouped into these identified features are labeled ground points, being used for DTM generation afterward. The Proposed approach was applied to many real airborne LIDAR data sets. The analysis on the results strongly supports the prominent performance of the proposed approach in terms of not only the computational requirement but also the quality of the DTM.

• Korean Journal of Environment and Ecology
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• v.26 no.3
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• pp.322-332
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• 2012

The objectives of this paper were to investigate home range, habitat selection, and threat factors of leopard cats (Prionailurus bengalensis) living in rural area of Korea. The results based on radio tracking of three leopard cats (two males and one female) can be summarized as follows. First, the average home range of leopard cats were $2.64{\pm}1.99km^2$ (Kernel 95) and $3.69{\pm}1.34km^2$ (MCP 100), and the average size of core areas was $0.64{\pm}0.47km^2$ (Kernel 50). The home range of a male leopard cat that radio-tracked in winter was the largest ($5.19km^2$, MCP 100). Second, the Johnson's habitat selection model based on the Jacobs index showed that leopard cats preferred meadows and paddy fields avoiding forest covers at the second level, whereas they preferred meadows adjacent to streams and avoided paddy fields at the third level. Finally, roadkill could be prime threat factor for the cat population. Therefore, habitats dominated by paddy fields, stream corridors with paved roads, and human settlements with insufficient forest patches could threaten the long-term viability of leopard cat populations. Thus the habitat managements for the leopard cat conservation should focus on the prevention of road-kill and the installation of wildlife passages in rural highways adjacent to stream corridors.

• The Korean Journal of Quaternary Research
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• v.17 no.2
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• pp.85-99
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• 2003

Since the experience of major landscape change during last half of the century due to war and rapid urbanization, the traditional character has been weakened, and it is necessary for a reconsideration to improve the landscape for the future. To review these relationships, the importance of a comprehensive understanding of nature has been suggested. Therefore identification of a new concept based on the 'socio-cultural influence of landscape' and 'sense of place' which are related to peoples' previous experience, is required. Furthermore more practical definitions and criteria to reveal the relationship are necessary. Among the terms suggested to describe sense of place such as 'home', 'place identity', 'place-based meaning' and 'settlement identity' etc., the 'home' is selected to represent our surrounding landscape. For more practical classification of home landscape, additional terms are suggested and defined based on both the relationships between human beings and nature, and between memory derived from previous experience and shared values with in the community. The additional terms which are the most important in the role of landscape character related to humans' are; ⅰ) Personal Landscape: Landscape of an individual human, which derives from previous personal experience; involves distinguishable character for a given person, and it is emotional and flexible depending on circumstances. ⅱ) Ordinary Landscape： Landscape of the 'common interest' between members of a community, which is acceptable as a surrounding for everyday daily life, it produces the richness and variety of landscape. ⅲ) Kernel Landscape： Landscape of the 'common ground' which is acceptable to the majority members of the community, and it provides variety and stability for periods of time, and it could strongly represent community attitudes toward nature. ⅳ) Prototype Landscape: Landscape as the 'common denominator' of overall community from past to present and towards the future, which encompasses all the kernel landscape throughout history. It provides a sense of place, balances the homogeneity of character throughout overall communities. Some part of this can be shared throughout history to shape an overall sense of place. It can also represent short terms fashions. For a prototype landscape to reveal sense of place, there are a couple of points which we should underline the commencing point. Firstly, understanding the relationship between humans and nature should be based on a given character of surroundings. Secondly, reoccurring landscape elements which have sustained in history can lead to sense of place, and should be reviewed the influences between nature and humans.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.4
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• pp.387-394
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• 2016

A stereo matching method is one of the ways to obtain a depth value from two dimensional images. This method estimates the depth value of target images using stereo images which have two different viewpoints. In the result of stereo matching, the depth value is represented by a disparity value. The disparity means a distance difference between a current pixel in one side of stereo images and its corresponding point in the other side of stereo images. The stereo matching in a homogeneous region is always difficult to find corresponding points because there are no textures in that region. In this paper, we propose a novel matching equation using the distance transform to estimate accurate disparity values in the homogeneous region. The distance transform calculates pixel distances from the edge region. For this reason, pixels in the homogeneous region have specific values when we apply this transform to pixels in that region. Therefore, the stereo matching method using the distance transform improves the matching accuracy in the homogeneous regions. In addition, we also propose an adaptive matching cost computation using a kernel of one dimensional array depending on the characteristic of regions in the image. In order to aggregate the matching cost, we apply a cross-scale cost aggregation method to our proposed method. As a result, the proposed method has a lower average error rate than that of the conventional method in all regions.

• Journal of Korean Society for Geospatial Information Science
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• v.18 no.2
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• pp.29-33
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• 2010

The purpose of LiDAR ground classification is to archive both goals which are acquiring confident ground points with high precision and describing ground shape in detail. In spite of many studies about developing optimized algorithms to kick out this, it is very difficult to classify ground points and describing ground shape by airborne LiDAR data. Especially it is more difficult in a dense forested area like Korea. Principle misclassification was mainly caused by complex forest canopy hierarchy in Korea and relatively coarse LiDAR points density for ground classification. Unfortunately, a lot of LiDAR surveying performed in summer in South Korea. And by that reason, schematic LiDAR points distribution is very different from those of Europe. So, this study propose enhanced ground classification method considering Korean land cover characteristics. Firstly, this study designate highly confident candidated LiDAR points as a first ground points which is acquired by using big roller classification algorithm. Secondly, this study applied weighted gradient kernel(WGK) algorithm to find and include highly expected ground points from the remained candidate points. This study methods is very useful for reconstruct deformed terrain due to misclassification results by detecting and include important terrain model key points for describing ground shape at site. Especially in the case of deformed bank side of river area, this study showed highly enhanced classification and reconstruction results by using WGK algorithm.