• Journal of the Korean Geographical Society
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• v.30 no.3
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• pp.296-310
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• 1995

Classification of spatial units into meaningful sets is an important procedure in spatial analysis. It is crucial in characterizing and identifying spatial structures. But traditional classification methods such as cluster analysis require an exact database and impose a clear-cut boundary between classes. Scrutiny of realistic classification problems, however, reveals that available infermation may be vague and that the boundary may be ambiguous. The weakness of conventional methods is that they fail to capture the fuzzy data and the transition between classes. Fuzzy subsets theory is useful for solving these problems. This paper aims to come to the understanding of theoretical foundations of fuzzy spatial analysis, and to find the characteristics of fuzzy classification methods. It attempts to do so through the literature review and the case study of urban classification of the Cities and Eups of Kyung-Nam Province. The main findings are summarized as follows: 1. Following Dubois and Prade, fuzzy information has an imprecise and/or uncertain evaluation. In geography, fuzzy informations about spatial organization, geographical space perception and human behavior are frequent. But the researcher limits his work to numerical data processing and he does not consider spatial fringe. Fuzzy spatial analysis makes it possible to include the interface of groups in classification. 2. Fuzzy numerical taxonomic method is settled by Deloche, Tranquis, Ponsard and Leung. Depending on the data and the method employed, groups derived may be mutually exclusive or they may overlap to a certain degree. Classification pattern can be derived for each degree of similarity/distance $\alpha$. By takina the values of $\alpha$ in ascending or descending order, the hierarchical classification is obtained. 3. Kyung-Nam Cities and Eups were classified by fuzzy discrete classification, fuzzy conjoint classification and cluster analysis according to the ratio of number of persons employed in industries. As a result, they were divided into several groups which had homogeneous characteristies. Fuzzy discrete classification and cluste-analysis give clear-cut boundary, but fuzzy conjoint classification delimit the edges and cores of urban classification. 4. The results of different methods are varied. But each method contributes to the revealing the transparence of spatial structure. Through the result of three kinds of classification, Chung-mu city which has special characteristics and the group of Industrial cities composed by Changwon, Ulsan, Masan, Chinhai, Kimhai, Yangsan, Ungsang, Changsungpo and Shinhyun are evident in common. Even though the appraisal of the fuzzy classification methods, this framework appears to be more realistic and flexible in preserving information pertinent to urban classification.

• Journal of the Korean Association of Geographic Information Studies
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• v.12 no.3
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• pp.164-178
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• 2009

This study was aimed to make GIS oiling thematic maps and analyze temporal oiling variation patterns for two months after 'Hebei Spirit' oil spill accident in December 7, 2007 using GIS and oiling status surveyed data. As a basic work for making of oiling thematic maps, geometric corrections were performed with IKONOS images using ground control points data. These corrected images were used to make detailed coastline from digital charts, and then spatial unit of coastline were defined using classified coastline types. And to know the representative parameters which reflect oiling situation, relationship between oiling status parameters extracted from four times oiling assessment reports and total petroleum hydrocarbons (TPHs) data (December 2007 and January 2008) monitored by Korea Ocean Research and Development Institute (KORDI). Using these representative oiling status parameters pollution value were calculated, and they were keyed into spatial unit of coastline as attributive value. GIS oiling status thematic maps made with coastline containing pollution value showed the initial two month's situations somewhat well. Also, to analyze temporal variation pattern of coastline types, about 13.4km length coastline around Malripo beach was defined as detailed study area where is the common spatial zone surveyed oiling status by each organizations. Based on this study results, it could be possible to provide oiling status maps quickly and to support decision making for oiling control action and scientific pollution monitoring.

• Journal of Science of Art and Design
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• v.1
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• pp.189-226
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• 1999

The purpose of this paper is to examine the common characteristics of late 20th century interior design style and the post-modern thinking system. A period has its own predominant spirit which determine the tendency of art, and the ubiquitous power in the spirit decides the period's pattern of art. Therefore the interior design style belongs to general art sphere that has its own individual character derived from the dominant power of the controlling system. Paying special attention to this understanding, the auther has processed this paper by combining the post-modem thinking with special characteristics of each of the 20th century interior design style. Until now, researches have been focused on the individual style of post-modern design; however, a general research comprising the whole characteristics of expression has not been made. Accordingly, the rationale of emphasizing the general point of view is establshed. Also, this study suggests a model applicable to studies concerning other art area. This type of methodology is receving more attention as an approach investigating new art ideology for researching post-modern thinking and late 20th century art styles. The conclusions are as follows: First, the distinctive expressions of postmodernism appear to be characteristic of illusion, metaphor, pluralism, decoration, and symmetry, Those of late modernism appear to be the characteristic of complicated simplicity and symplified complexity, passiveness of symbolism and harmony, indeterminacy of form and space, and unintentional decorativeness. And the characteristics of deconstructionism are spatial difference and temporal defferal, and un-reductive and non formal abstractiveness of the space, unfinishness, chance, and secretiveness of individual style. Second, the disinctive expression seems to share common characteristics with postmodern thinking. The best examples are pluralism, non-formalism, populism, and historicism, originating from the deconstruction of 'meta-narrative'. Third, based on the second conclusion, general distinctive expression could be simplified as chacteristics of plurality, hybridity, and indeterminacy. These expressive chacteristics appear to be automatically connected with general postmodern thinking. Last, in consideration of the above conclusion, the extreme generality could be distinctively clarified as 'textural co-exsistence'. Accordingly, the author might confirm that 'textural co-existence' originated from the text that comes from postmodern thinking. In conclusion, design expression of late 20th century interior design accepts the ?universal theme of ubiquitous postmodern thinking. And universal expressions and supreme generality can be common analysis tools for understanding and studying complicated late 20th century interior design.

• Journal of KIISE
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• v.44 no.9
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• pp.887-892
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• 2017

Brain-computer interface (BCI) is a technology that controls computer and transmits intention by measuring and analyzing electroencephalogram (EEG) signals generated in multi-channel during mental work. At this time, optimal EEG channel selection is necessary not only for convenience and speed of BCI but also for improvement in accuracy. The optimal channel is obtained by removing duplicate(redundant) channels or noisy channels. This paper propose a dual filter-based channel selection method to select the optimal EEG channel. The proposed method first removes duplicate channels using Spearman's rank correlation to eliminate redundancy between channels. Then, using F score, the relevance between channels and class labels is obtained, and only the top m channels are then selected. The proposed method can provide good classification accuracy by using features obtained from channels that are associated with class labels and have no duplicates. The proposed channel selection method greatly reduces the number of channels required while improving the average classification accuracy.

• The KIPS Transactions:PartB
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• v.11B no.4
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• pp.509-516
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• 2004

Semantic interpretation of image is incomplete without some mechanism for understanding semantic content that is not directly visible. For this reason, human assisted content-annotation through natural language is an attachment of textual description to image. However, keyword-based retrieval is in the level of syntactic pattern matching. In other words, dissimilarity computation among terms is usually done by using string matching not concept matching. In this paper, we propose a method for computerized semantic similarity calculation In WordNet space. We consider the edge, depth, link type and density as well as existence of common ancestors. Also, we have introduced method that applied similarity measurement on semantic image retrieval. To combine wi#h the low level features, we use the spatial color distribution model. When tested on a image set of Microsoft's 'Design Gallery Line', proposed method outperforms other approach.

• Korean Journal of Optics and Photonics
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• v.23 no.4
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• pp.135-142
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• 2012

We have developed a measurement method of the refractive index profile of an optical fiber by using diffraction phase microscopy. In the microscope system, the reference light was extracted directly from the probe light that passed through the sample by means of pinhole filtering with a diffraction grating. The spatial interference pattern produced by the probe light and the reference light was processed to generate the phase image of the sample fiber. The index profile was obtained by the inverse Abel transform of the phase profile. In order to remove the background phase that originated from the index difference between the cladding and the surrounding medium, the background phase was calculated from the phase data of the cladding to make a core phase profile that can be directly transformed to the index profile of the core without the full phase image that includes the entire cladding part.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.3
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• pp.199-203
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• 2016

A brain-computer interface or BCI provides an alternative method for acting on the world. Brain signals can be recorded from the electrical activity along the scalp using an electrode cap. By analyzing the EEG, it is possible to determine whether a person is thinking about his/her hand or foot movement and this information can be transferred to a machine and then translated into commands. However, we do not know which information relates to motor imagery and which channel is good for extracting features. A general approach is to use all electronic channels to analyze the EEG signals, but this causes many problems, such as overfitting and problems removing noisy and artificial signals. To overcome these problems, in this paper we used a new optimization method called the Fruit Fly optimization algorithm (FOA) to select the best channels and then combine them with CSP method to extract features to improve the classification accuracy by linear discriminant analysis. We also used particle swarm optimization (PSO) and a genetic algorithm (GA) to select the optimal EEG channel and compared the performance with that of the FOA algorithm. The results show that for some subjects, the FOA algorithm is a better method for selecting the optimal EEG channel in a short time.

• ETRI Journal
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• v.36 no.1
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• pp.134-140
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• 2014

Many reports have shown that the access pattern for geospatial tiles follows Zipf's law and that its parameter ${\alpha}$ represents the access characteristics. However, visits to geospatial tiles have temporal and spatial popularities, and the ${\alpha}$-value changes as they change. We construct a mathematical model to simulate the user's access behavior by studying the attributes of frequently visited tile objects to determine parameter estimation algorithms. Because the least squares (LS) method in common use cannot obtain an exact ${\alpha}$-value and does not provide a suitable fit to data for frequently visited tiles, we present a new approach, which uses a moment method of estimation to obtain the value of ${\alpha}$ when ${\alpha}$ is close to 1. When ${\alpha}$ is further away from 1, the method uses the associated cache hit ratio for tile access and uses an LS method based on a critical cache size to estimate the value of ${\alpha}$. The decrease in the estimation error is presented and discussed in the section on experiment results. This new method, which provides a more accurate estimate of ${\alpha}$ than earlier methods, promises more effective prediction of requests for frequently accessed tiles for better caching and load balancing.

• Journal of Internet Computing and Services
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• v.5 no.3
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• pp.73-86
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• 2004

This paper presents a hybrid digital watermarking scheme for color images, We insert two watermarks in the DWT domain using spread-spectrum correlation-based watermarking in luminance component of the color image and in spatial domain using pixel-value substitution of blue channel of color image. The objectives of this paper are to have the watermark robust to common signal processing and to detect any changes on the watermarked image for tamper detection at the same time. This watermark scheme will have the robustness characteristic as typical in frequency domain watermark, and also ability to detect any changes on the image (tamper detection).

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.6
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• pp.527-533
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• 2013

BCI (Brain-Computer Interface) is a system that transforms a subject's brain signal related to their intention into a control signal by classifying EEG (electroencephalograph) signals obtained during the imagination of movement of a subject's limbs. The BCI system allows us to control machines such as robot arms or wheelchairs only by imaging limbs. With the exact same experiment environment, activated brain regions of each subjects are totally different. In that case, a simple approach is to use as many channels as possible when measuring brain signals. However the problem is that using many channels also causes other problems. When applying a CSP (Common Spatial Pattern), which is an EEG extraction method, many channels cause an overfitting problem, and in addition there is difficulty using this technique for medical analysis. To overcome these problems, we suggest an optimal channel selection method using a BPSO (Binary Particle Swarm Optimization), BPSO with channel impact factor, and GA. This paper examined optimal selected channels among all channels using three optimization methods and compared the classification accuracy and the number of selected channels between BPSO, BPSO with channel impact factor, and GA by SVM (Support Vector Machine). The result showed that BPSO with channel impact factor selected 2 fewer channels and even improved accuracy by 10.17~11.34% compared with BPSO and GA.