• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.45 no.11
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• pp.932-938
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• 2017

Particle-in-cell method which blends Eulerian grids and Lagrangian particle is utilized to solve simplified hall-effect thruster. Since this study individually tracks not only neutrons and ions but also electrons, message passing interface(mpi) scheme is adopted for parallel computer cluster. Helical movement of an electron cloud in constant magnetic field is validated comparing with an exact solution. A plasma in radial magnetic field and axial electric field in a reaction cylinder is established. Electrons do double helix movement and are well anchored in a cylinder. Ionization of neutrons by impact with high-speed electrons generates ion particles. They are accelerated by axial electric field, which forms a plume of a plasma-effect thruster.

• Archives of design research
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• v.18 no.1 s.59
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• pp.205-214
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• 2005

A development proposal that maximizes the trend of travel souvenir and articles toward tourism and natural resources through utilization of the Limited Production method was the focus of the present research. First, the flaws of travel souvenir and articles, currently produced in Inje, Kangwon-Do, were identified, as were the regional uniqueness of the area. The comparative advantages of developmental conditions of the above-specified region to various other Si/Kun regions were demonstrated to ascertain the optimal production method of travel souvenir and articles. The results are as follows. Superior supply of,7aw materials necessary for production of wood-worked travel souvenir and articles are abundantly available and the dose proximity of 17 existing workshops self-contain the production capacity to sustain the Limited Production method. Furthermore, the regional governing council conveyed positive attitudes towards the prospect of creating a regional production complex of wood-worked travel souvenir and articles. The results demonstrate that the optimal method of maximizing the trend of travel souvenir and articles toward tourism and natural resources is achieved through systematic collaboration of industry, education, and tourism that promote development, production, and merchandising of Inje's regional travel souvenir and articles.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.5 s.311
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• pp.37-44
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• 2006

In this paper, a new version of the ICM method(MICM, modified ICM) in which the contextual information is modelled by Markov random fields (MRF) is introduced. To extract the feature, a new local MRF model with a fitting block neighbourhood is proposed. This model selects contextual information not only from the relative intensity levels but also from the geometrically directional position of neighbouring cliques. Feature extraction depends on each block's contribution to the local variance. They discriminates it into several regions, for example context and background. Boundaries between these regions are also distinctive. The proposed algerian performs segmentation using directional block fitting procedure which confines merging to spatially adjacent elements and generates a partition such that pixels in unified cluster have a homogeneous intensity level. From experiment with ink rubbed copy images(Takbon, 拓本), this method is determined to be quite effective for feature identification. In particular, the new algorithm preserves the details of the images well without over- and under-smoothing problem occurring in general iterated conditional modes (ICM). And also, it may be noted that this method is applicable to the handwriting recognition.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.14 no.2
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• pp.1-13
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• 2015

Traffic volume data is basic information that is used in a wide variety of fields. Existing missing traffic volume data imputation method did not take the effect on the rainfall. This research analyzed considering of the rainfall effect in missing traffic volume data imputation method. In order to consider the effect of rainfall, established the following assumption. When missing of traffic volume data generated in rainy days it would be more accurate to use only the traffic volume data of the past rainy days. To confirm this assumption, compared for accuracy of imputed results at three kinds of imputation method(Unconditional Mean, Auto Regression, Expectation-Maximization Algorithm). The analysis results, the case on consideration of the rainfall effect was more low error occurred.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.42 no.1
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• pp.75-80
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• 2005

A new antenna shuffling scheme for double space time transmit diversity is proposed. The proposed method obtains the shuffling pattern directly from the estimated channel by maximizing minimum post-processing signal to noise ratio(SNR), while the conventional method minimizes channel correlation. Since the minimum post-processing SNR is directly related with error performance, the proposed method shows better bit error rate performance than the conventional method. Monte Carlo simulations showed that the proposed scheme has more 3 dB SNR gain than the conventional scheme for 10/sup -3/ bit error rate in spatially correlated fadingcaused by a single cluster model.

• The Journal of the Acoustical Society of Korea
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• v.23 no.5
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• pp.400-409
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• 2004

In this paper. a voice personality transformation method is proposed. which makes one person's voice sound like another person's voice. To transform the voice personality. vocal tract transfer function is used as a transformation parameter. Comparing with previous methods. the proposed method makes transformed speech closer to target speaker's voice in both subjective and objective points of view. Conversion between vocal tract transfer functions is implemented by classification of entire vector space followed by linear transformation for each cluster. LPC cepstrum is used as a feature parameter. A joint classification and transformation method is proposed, where optimum clusters and transformation matrices are simultaneously estimated in the sense of a minimum mean square error criterion. To evaluate the performance of the proposed method. transformation rules are generated from 150 sentences uttered by three male and on female speakers. These rules are then applied to another 150 sentences uttered by the same speakers. and objective evaluation and subjective listening tests are performed.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.11 no.2
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• pp.10-20
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• 2012

This study shows how to estimate AADT(Annual Average Daily Traffic) on temporary count data using new grouping method. This study deals with clustering permanent traffic counts using monthly adjustment factor, daily adjustment factor and a percentage of hourly volume. This study uses a percentage of hourly volume comparing with other studies. Cluster analysis is used and 5 groups is suitable. First, make average of monthly adjustment factor, average of daily adjustment factor, a percentage of hourly volume for each group. Next estimate AADT using 24 hour volume(not holiday) and two adjustment factors. Goodness of fit test is used to find what groups are applicable. MAPE(Mean Absolute Percentage Error) is 8.7% in this method. It is under 1.5% comparing with other method(using adjustment factors in same section). This method is better than other studies because it can apply all temporary counts data.

• Korean Institute of Interior Design Journal
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• v.17 no.5
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• pp.157-165
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• 2008

This study confirm the value and the importance of the human sensibility study to add up the new meaning, and to suggest a new value of Korean sensibility study through the understanding of current statusand trend of the sensibility study in the space. The method of the study was to collect date related to the sensibility study and to analyze it focusing on its details. The date was collected from researches published on the website since the establishment of Korean Institute of Interior Design and Architectural Institute of Korea and selected at the keyword search comer. The data was extracted under keywords of research object, research purpose, research method, and analysis method. And then it was quantified with HAYASH lll program and used for analyses according to its pattern and feature. The study shows that nowadays categories representing the current status and trend of the sensibility studies in space consist of the environment, the human, and the space. The contemporary study for sensibility puts the importance on a object and a subject of the study like the environment harmonized with human and space, the humans the subject that essentially uses the spate, and the space for the architecture and the interior that puts human in. Accordingly, the study for human sensibility should develop into the study for the design focused on the intangible relationship such as 'information', 'elements for space design', 'sensibility' beyond the existing tangible categories of environment, human, and space. In addition, in the method ways of study and analysis, those studies for the sensible relationship are required to develop into new types of study applying research methods of various studies beyond the traditional border between human studies, social science, and natural science.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.2
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• pp.171-177
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• 2011

Accuracy and computing time are considerable issues in machine learning. In general, the computing time for data analysis is increased in proportion to the size of given data. So, we need a sampling approach to reduce the size of training data. But, the accuracy of constructed model is decreased by going down the data size simultaneously. To solve this problem, we propose a new statistical sampling method having similar performance to the total data. We suggest a rule to select optimal sampling techniques according to given data structure. This paper shows a sampling method for reducing computing time with keeping the most of accuracy using cluster sampling, stratified sampling, and systematic sampling. We verify improved performance of proposed method by accuracy and computing time between sample data and total data using objective machine learning data sets.

• The Journal of the Korea Contents Association
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• v.7 no.6
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• pp.1-8
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• 2007

In electronic commerce, it is important for users to recommend the proper item among large item sets with saving time and effort. Therefore, if the recommendation system can be recommended the suitable item, we will gain a good satisfaction to the user. In this paper, we proposed the associative relation clustering split method in the collaborative filtering in order to perform the accuracy and the scalability. We produce the lift between associative items using the ratings data. and then split the node group that consists of the item to improve an efficiency of the associative relation cluster. This method differs the association about the items of groups. If the association of groups is filled, the reminding items combine. To estimate the performance, the suggested method is compared with the K-means and EM in the MovieLens data set.